CA1191264A - Broadcast signal recognition system and method - Google Patents
Broadcast signal recognition system and methodInfo
- Publication number
- CA1191264A CA1191264A CA000436517A CA436517A CA1191264A CA 1191264 A CA1191264 A CA 1191264A CA 000436517 A CA000436517 A CA 000436517A CA 436517 A CA436517 A CA 436517A CA 1191264 A CA1191264 A CA 1191264A
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- CA
- Canada
- Prior art keywords
- segments
- signal
- reference signal
- segment
- correlation function
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired
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Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04H—BROADCAST COMMUNICATION
- H04H60/00—Arrangements for broadcast applications with a direct linking to broadcast information or broadcast space-time; Broadcast-related systems
- H04H60/35—Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users
- H04H60/37—Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying segments of broadcast information, e.g. scenes or extracting programme ID
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04H—BROADCAST COMMUNICATION
- H04H60/00—Arrangements for broadcast applications with a direct linking to broadcast information or broadcast space-time; Broadcast-related systems
- H04H60/56—Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups H04H60/29-H04H60/54
- H04H60/58—Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups H04H60/29-H04H60/54 of audio
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
- G06F2218/16—Classification; Matching by matching signal segments
Abstract
ABSTRACT
Broadcast Signal Recognition System and Method The method for the automatic electronic recognition of a program unit broadcast by radio waves includes the formation of a plurality of reference signal segments from the program unit and the processing of such segments to obtain digitized reference signal segments which are then normalized and stored. When the program unit is broadcast, the broadcast signal is processed to generate successive digitized broadcast signal segments which are correlated with the digitized, normalized reference signal segments to obtain correlation function peaks for each resultant correlation segment. The spacing between the correlation function peaks for each correlation segment is then compared to determine whether such spacing is substantially equal to the reference signal segment length. Also, the RMS
value coincident with each correlation function peak is determined and the pattern of such RMS values coincident with the correlation function peaks is compared with the pattern of the RMS values of the normalized reference signal segments.
Broadcast Signal Recognition System and Method The method for the automatic electronic recognition of a program unit broadcast by radio waves includes the formation of a plurality of reference signal segments from the program unit and the processing of such segments to obtain digitized reference signal segments which are then normalized and stored. When the program unit is broadcast, the broadcast signal is processed to generate successive digitized broadcast signal segments which are correlated with the digitized, normalized reference signal segments to obtain correlation function peaks for each resultant correlation segment. The spacing between the correlation function peaks for each correlation segment is then compared to determine whether such spacing is substantially equal to the reference signal segment length. Also, the RMS
value coincident with each correlation function peak is determined and the pattern of such RMS values coincident with the correlation function peaks is compared with the pattern of the RMS values of the normalized reference signal segments.
Description
Description Broadcast Signal Reco~ni-tion System and ~iethod ~echnical Field . ~
The present invention relates to signal recognition systems and methods yenerally, and more particularly to a system and method for matching a broadcast signal to stored reference signal segments by pattern rnatc}l;ny correlat~on siynal peaks and power pa-tterrls at sa;d p~ak poinl:s.
Backyround Art _ _ _ . . .. _ Television and radio stations throuyhout the country have long been monitored by commercial surveying entities to determine the popularity of certain stations and programs and to verify for advertisers that commercial sale messages are presented at the -times prearranged with the broadcast station. Initially, most broadcast surveys were manuaily conducted and tabulated, thereby requiring the use of a large number of persons to monitor individual broadcast statiorls and loy survey information reyarding the proy~-arruniny of the station monitored. The cost of conductiny these surveys on a larye scale for an extended period proved to be prohibitively hiyh due to the labor intensive nature of the survey.
When volunteer surveyors were employed to cut costs, the validity of the data collected often was suspect due to the hiyh probability of error as well as omission resultiny from lack of interest on the part of some volunteers.
In recent years, techniques have been developed for electronically monitoriny broadcast siynals and '~i provi~ing information relative to the content of the progra~ning monitored Initially, these elec-tronie systems elnployed a coded signal technique wherein special coded identification segments were inserted in eaeh prQgram to be monitored, and these segrrlents were then broadcas-t with the audio and/or video program signals. Receiving equipment was -then provided which inclu~ed decoding units designed to decode the broa~cast co~ed segments so that program recogni-tion could be accomplished. Although broadeast eoding teehniques work effectively for some applieations, they do require -the a]location of portions of the broadcast si~nal band for identi[ic:a-tion purposes, and spee;al pLocessin~3 is recl~l;red to eode and decode the bl-oaclcast signal.
To a11evi.lte some o~ the disadvclll-tages involvecl wilh the use of cocled signal techniques, eomplete]y auto-matie broadcast signal identification sys-tems have been developed whieh require no speeial eoding of the broad-east signal. These identifieation systems employ a eomparison teehnique wherein a single, digital]y sampled referenee signal segment derived from a por-tion of the original program eontent to be identified is eompared with sueeessive digitally sampled segmen-ts of the eorresponding broadeast signal ;n a eorrelation proeess to produee a eorrelation funetion signal. The referenee signal seyment and broadeast signal segments are processed in the same manner before correlation, and during correlation, and if the referenee and broadeast signal se~nents are not the same, a eorrelation funetion .
signal having a relatively small amplitude results.
On the other hand, if the segments are the same, a relatively large eorrelation funetion signal is produeed. The amplitude of the eorrelation funetion signal is sensed to provide a recognition signal when the amplitude of the correlation -uncLion signal exceeds a selected -threshold level. U S. P~tent No. 3,919,979 to Warren D. ~oon et al discloses a broadcast signal identification system of this type w]-ich requires no special coding of the broadcast sisnal.
The known, single reference segrnent signal iden-tification systems operate effectively in instances where ideal conditions prevail, bu-t for many appli-cations and prevailing operational conditions, thesesystems are no-t effective. For example, ul-lder ;ntermitterlt signal clropout, a single sec3rllent corr~1cl-t;oll Tncly ~ s~v~r~ly cl~3~d~ , c~ el)y -result in railure to ;ndicaLe corrcsE)ondence of the broadcas-t and reference signals when correspondence does in fact exist.
Finally, with hroadcast music programs, -the speed variations be-tween the same music selections played by different broadcast stationsmay be so extreme that even the use of subaudio techniques known to the prior art in a single reference segment sys-tem in an attemptto compensate for -the efec-ts of such varia-tions are ina(lequate. The ;nabi]ity of known broadcast signal identification systems to cope effectively with substantial music speed variations is a consequential limitation upon the use of such systems, for a need exists in the music production and distribution industry to monitor the rate of play on radio stations of various recordings to aid in the projection of sales.
Since the popularity of a particular recordiny may be quite different in different parts of the country, it is nec~ssary to perform surveys ;n many geographical areas. It has been found that clisc jockeys, in order to create desired effects, are qui-te liXely to vary recording playback speeds, and this practice is quite prevalent. Disc jockey induced speed variations are likely to cause recoynition error in the prior art single reference segment signal recognition sys-tems. Performance of these systems is limited by the fac-t that requirement for tolerance of speed variations limits the length of single segment reference patterns~ This, in turn, limits the ~mount of information which may be used to :recogni.ze a record-ing and thus degracles recocJn:it;.oll per:rol:r~ ce.
isc],osure oE the Inve,nt_on It is a primary object of the present invention to provide a novel broadcast signal recognition system and method whexein signal correlation is provided for a substantial period during a broadcast interval by ~se of a plurality of reference and broadcast signal se~nents.
This compensates for such disturbances as noise bursts or si~nal dropout, for with multiple segments, the detection process may be designed to indicate recognition when coincidence occurs between a number of reference and broadcast signal segments which is less than the total number processed. ;
~ nother;object of the present invention i.s to provide a novel bro~dcast signal recognition system and a method wherein signal recognition is obtained with a nonlinear correlation process which provides a plurality of correlation peaks. The pattern of these peaks is then matched as well as the pattern produced by the RMS
~ 3~,~
power of a signal seginent coincident with the correlation peak of such segment. If matching of -the correlation peaks and the power pat-tern occur within a predeteLmined ti.me window, thell a rna-tch has occl~rred between the broadcast signal and reference segJnents employed or t,he recognition pxocess A further object of the prese:nt i.nvention is -to provide a novel broadcast signal recogni.tion system and method wherein more than one sampling rate may occur in -the reference signal segments employed in -the recogni.tion process. A fast and slow sarnp]e rnay be stored Eor each reference signal segment so -that broadcast signals from faster rate stations will correlate with the faster rate reference segments and signals from slower rate stations will correlate with the slower rate reference segments .
A sti,ll further objec-t of the present invention is to provide a novel broadcast signal recoynition system and method wherein one or more reference signal segments are taken from a program to be broadcast and are pre-normalized before storage. These reference signal segments are processed by normalizing them in accordance with the power in the respective segment and then by Fourier transformation and the performance of a complex conjugate to provide frequency domain complex spectra for storage. The received broadcast signal is prefiltered to select a frequency portion of the audio spectrum that has stable-characteristics for discrimination.
After further fi.ltering and conversion to a digital signal, the broadcast signal is Fourier transformed and subjected to a cornplex multiplication process with the reference signal segments to obtain a vector product. ~he results of the complex multiplication pxocess are then subjected to an inverse Fourier transform step to obtain a correlation functi.on which has been transformed frorn the freq~ency to the time domai.n. This correlation function is now normalized, and the correlation peak for each segment is selected and the peak spacing is compared with segment length. Simultaneous-ly the RMS power of the segment coincident wi-th the segment correlation peak is sensed to determine the segment power point pattern.
These and o-ther ob.iects of the preserlt inventi.on wi.ll become apparent from a consideratio:n of -the fo].low-ing speci:f.i.cat:;.on and cl.aims taken i.n conjullcti.on wi.th the accompanying d:rawing.
Brief Descri.ption of the Drawings Figure 1 is a diagram illustrating the processing of a re~erence and broadcast siynal seyment in accordance with the present invention;
Figure 2 is a block diagram of a system illustrating the steps of -the present invention;
Figure 3 is a block diagram oE the envelope ~
forrning section oE the systern of Figure 2 showiny -the waveforms present at each pOillt i.n the section;
Figure 4 is a diagram showing the reference signal segmen-ts created by the normalizing and zero fill sections of-Figure 2;
Figure 5 is a block diagram of a second embodiment of the envelope forming section of the system of Figure
The present invention relates to signal recognition systems and methods yenerally, and more particularly to a system and method for matching a broadcast signal to stored reference signal segments by pattern rnatc}l;ny correlat~on siynal peaks and power pa-tterrls at sa;d p~ak poinl:s.
Backyround Art _ _ _ . . .. _ Television and radio stations throuyhout the country have long been monitored by commercial surveying entities to determine the popularity of certain stations and programs and to verify for advertisers that commercial sale messages are presented at the -times prearranged with the broadcast station. Initially, most broadcast surveys were manuaily conducted and tabulated, thereby requiring the use of a large number of persons to monitor individual broadcast statiorls and loy survey information reyarding the proy~-arruniny of the station monitored. The cost of conductiny these surveys on a larye scale for an extended period proved to be prohibitively hiyh due to the labor intensive nature of the survey.
When volunteer surveyors were employed to cut costs, the validity of the data collected often was suspect due to the hiyh probability of error as well as omission resultiny from lack of interest on the part of some volunteers.
In recent years, techniques have been developed for electronically monitoriny broadcast siynals and '~i provi~ing information relative to the content of the progra~ning monitored Initially, these elec-tronie systems elnployed a coded signal technique wherein special coded identification segments were inserted in eaeh prQgram to be monitored, and these segrrlents were then broadcas-t with the audio and/or video program signals. Receiving equipment was -then provided which inclu~ed decoding units designed to decode the broa~cast co~ed segments so that program recogni-tion could be accomplished. Although broadeast eoding teehniques work effectively for some applieations, they do require -the a]location of portions of the broadcast si~nal band for identi[ic:a-tion purposes, and spee;al pLocessin~3 is recl~l;red to eode and decode the bl-oaclcast signal.
To a11evi.lte some o~ the disadvclll-tages involvecl wilh the use of cocled signal techniques, eomplete]y auto-matie broadcast signal identification sys-tems have been developed whieh require no speeial eoding of the broad-east signal. These identifieation systems employ a eomparison teehnique wherein a single, digital]y sampled referenee signal segment derived from a por-tion of the original program eontent to be identified is eompared with sueeessive digitally sampled segmen-ts of the eorresponding broadeast signal ;n a eorrelation proeess to produee a eorrelation funetion signal. The referenee signal seyment and broadeast signal segments are processed in the same manner before correlation, and during correlation, and if the referenee and broadeast signal se~nents are not the same, a eorrelation funetion .
signal having a relatively small amplitude results.
On the other hand, if the segments are the same, a relatively large eorrelation funetion signal is produeed. The amplitude of the eorrelation funetion signal is sensed to provide a recognition signal when the amplitude of the correlation -uncLion signal exceeds a selected -threshold level. U S. P~tent No. 3,919,979 to Warren D. ~oon et al discloses a broadcast signal identification system of this type w]-ich requires no special coding of the broadcast sisnal.
The known, single reference segrnent signal iden-tification systems operate effectively in instances where ideal conditions prevail, bu-t for many appli-cations and prevailing operational conditions, thesesystems are no-t effective. For example, ul-lder ;ntermitterlt signal clropout, a single sec3rllent corr~1cl-t;oll Tncly ~ s~v~r~ly cl~3~d~ , c~ el)y -result in railure to ;ndicaLe corrcsE)ondence of the broadcas-t and reference signals when correspondence does in fact exist.
Finally, with hroadcast music programs, -the speed variations be-tween the same music selections played by different broadcast stationsmay be so extreme that even the use of subaudio techniques known to the prior art in a single reference segment sys-tem in an attemptto compensate for -the efec-ts of such varia-tions are ina(lequate. The ;nabi]ity of known broadcast signal identification systems to cope effectively with substantial music speed variations is a consequential limitation upon the use of such systems, for a need exists in the music production and distribution industry to monitor the rate of play on radio stations of various recordings to aid in the projection of sales.
Since the popularity of a particular recordiny may be quite different in different parts of the country, it is nec~ssary to perform surveys ;n many geographical areas. It has been found that clisc jockeys, in order to create desired effects, are qui-te liXely to vary recording playback speeds, and this practice is quite prevalent. Disc jockey induced speed variations are likely to cause recoynition error in the prior art single reference segment signal recognition sys-tems. Performance of these systems is limited by the fac-t that requirement for tolerance of speed variations limits the length of single segment reference patterns~ This, in turn, limits the ~mount of information which may be used to :recogni.ze a record-ing and thus degracles recocJn:it;.oll per:rol:r~ ce.
isc],osure oE the Inve,nt_on It is a primary object of the present invention to provide a novel broadcast signal recognition system and method whexein signal correlation is provided for a substantial period during a broadcast interval by ~se of a plurality of reference and broadcast signal se~nents.
This compensates for such disturbances as noise bursts or si~nal dropout, for with multiple segments, the detection process may be designed to indicate recognition when coincidence occurs between a number of reference and broadcast signal segments which is less than the total number processed. ;
~ nother;object of the present invention i.s to provide a novel bro~dcast signal recognition system and a method wherein signal recognition is obtained with a nonlinear correlation process which provides a plurality of correlation peaks. The pattern of these peaks is then matched as well as the pattern produced by the RMS
~ 3~,~
power of a signal seginent coincident with the correlation peak of such segment. If matching of -the correlation peaks and the power pat-tern occur within a predeteLmined ti.me window, thell a rna-tch has occl~rred between the broadcast signal and reference segJnents employed or t,he recognition pxocess A further object of the prese:nt i.nvention is -to provide a novel broadcast signal recogni.tion system and method wherein more than one sampling rate may occur in -the reference signal segments employed in -the recogni.tion process. A fast and slow sarnp]e rnay be stored Eor each reference signal segment so -that broadcast signals from faster rate stations will correlate with the faster rate reference segments and signals from slower rate stations will correlate with the slower rate reference segments .
A sti,ll further objec-t of the present invention is to provide a novel broadcast signal recoynition system and method wherein one or more reference signal segments are taken from a program to be broadcast and are pre-normalized before storage. These reference signal segments are processed by normalizing them in accordance with the power in the respective segment and then by Fourier transformation and the performance of a complex conjugate to provide frequency domain complex spectra for storage. The received broadcast signal is prefiltered to select a frequency portion of the audio spectrum that has stable-characteristics for discrimination.
After further fi.ltering and conversion to a digital signal, the broadcast signal is Fourier transformed and subjected to a cornplex multiplication process with the reference signal segments to obtain a vector product. ~he results of the complex multiplication pxocess are then subjected to an inverse Fourier transform step to obtain a correlation functi.on which has been transformed frorn the freq~ency to the time domai.n. This correlation function is now normalized, and the correlation peak for each segment is selected and the peak spacing is compared with segment length. Simultaneous-ly the RMS power of the segment coincident wi-th the segment correlation peak is sensed to determine the segment power point pattern.
These and o-ther ob.iects of the preserlt inventi.on wi.ll become apparent from a consideratio:n of -the fo].low-ing speci:f.i.cat:;.on and cl.aims taken i.n conjullcti.on wi.th the accompanying d:rawing.
Brief Descri.ption of the Drawings Figure 1 is a diagram illustrating the processing of a re~erence and broadcast siynal seyment in accordance with the present invention;
Figure 2 is a block diagram of a system illustrating the steps of -the present invention;
Figure 3 is a block diagram oE the envelope ~
forrning section oE the systern of Figure 2 showiny -the waveforms present at each pOillt i.n the section;
Figure 4 is a diagram showing the reference signal segmen-ts created by the normalizing and zero fill sections of-Figure 2;
Figure 5 is a block diagram of a second embodiment of the envelope forming section of the system of Figure
2 showing the waveforms present at each point in the section;
Figure 6 is a diagram showing the broadcast signal segments output from the buffer section of Figure 2;
Figure 7 is a diagram illustra-ting the operation of the normalizing and sliding RMS section of Figure 2; and Figure 8 is a flow diagram illustrating the operation of the decision loyic of Figure 2.
Best Mode For Carrying Out The Invention Effective broadcast signal recognition is extremely difficult to ac}l;.eve, even unde:r ideal broadcast condi-t;ons. The same recordecl p:rogram bro.ldccls-t by cl p].urclli-ty of c~:i..leJel-lt geog:l.clphi.cal:ly separatecl stations .i~5 s~lbjecl to the broadcast conditions peculiar to each individual stat:ion as well as to speed variations which may be inherent or purposely induced. Additional~Ly, each broadcast signal may be subject to varying conditions of noise, signal dropout, fre~uency equalizaiton, dynamic range compression, and other conditions which cause random perturbations in each broadcast signal. Thus, when the recogniti.on process involves the matching of a broad-cast signal with a pre-recorded standard reference signal taken E.rom a recorded program be:Eore it is broadcast, it will be apparent that the broadcast signal Erorn one station may match diEferently with the standard reference signal than will the broadcast signal from another station.
Consequently, classical correlation comparison techniques employing only a single reference signal segment and a single segment taken from a broadcast signal may not provi~e accurate data.
The broadcast signal recognition method of the present invention pref-erably emp:loys a plurality of reference segments taken from a recorded program to be broadcast and a plurali.ty of seglnerlts taken from the signal actually broadcast~ These .reference seglnents may be taken from separa-te time periods of a recording or from the same time period but based upon different frequency bands of the same recording. The decisi.on process for recognition of a recordi.ng is based upon time del.ay coinci.dence of the multiple reference pattern correlation peaks, rather than a single peak of a singl.e correlati.on function exceeding an amplitude threshold. Because a tolerance for slight tirne delay shifts between distinct time periods can be built into the coincidence detection, this multiple segment method can be made less vulnerable to playback speed variations than sing].e segment methods which employ the same total recording time period for recognition.
Turning now in detail to the broadcast signal recognition method:of the present invention, a plurality of signal segments of equal :Lenyth are taken frorn the recorded program to be broadcast, and after being filtered and digitized, these signal segments are pre-normalized to provide normalized refere~ce segments 25 for storage. This prenormalization step involves --first scaling each xeference segment pattern so that it will have a fixed total power for the segment, and this is accomplished by taking the square root of the total power to obtain the root mean square (RMS) amplitude for the segment. This RMS value is then divided into each point P in the segment to obtain a fixed scale factor K where K2 will be the variance of each segment. Then each normali.zed re.erence seyment is zero filled to provide a total reference segment having a data section D and a zero filled section z of equal ]ength (Figure 1).
This normalized zero filled reference segment R is then Fourier transformed and the result stored so that the stored reference segments are preprocessed segments which have been normalized in accorclance with the power in the segment, transformed into a frequency domain and then transformed by the performance of a complex conjugate to prov;de f:requency domain complex spectra.
rllo colnptl:re l:he stored reEe:r-c?rlce seynle~ s w~ h a broaclcast sicJrlal, the brc)adcast si.~,~nc~ is first: rl?ce:i.ved and prefiltered to select a Erequency portion of the audio spectrum that has stable characteristics. Since the high and low frequency portions of the audio spectrum are normally unstable, this prefiltering step generally results in providi~g an envelope in an intermediate stable freq,uency_region. _Qnce the envelope is formed, -~
it is again filtered to obtain a good stable narrow bandwidth signal which is then di.gitized and Fourier transformed to obtain a Erequency domain, complex spectrum.
Sequential subsegrnents of this signal, W}li.C}I are equal in ~.ength to the zero filled reference signal segments R, are then complex multiplied with the reference signal segments to obtain a vector product which is then subjected to an inverse Fourier transform to obtain a time domain correlation function which has not been normalized to the input power of the broadcast signal.
This unnormalized time domain correlation function is then sequentially normalized by a sliding RMS process within a win~ow W having the same length as ~ach da-ta section D. For each point P in the correlation function, the RMS o-f the total digitized broadcast signal within -the win~ow is calculated and divided i~to each point P ;n the correlation func-tion within the ~indow to obtain a normalized segment having a correlation peak CP. The temporal spacing between these correlation peaks is detected and, if such spacing is substantia:lly equal to -the length of the reference segments R, then signal recognition is indi-cated.
Generally, a double dele(tioll p-~ocess -l:o insure pro~3ram :1.ecc)9TIi.t.:lon :i.S cle.si.lahle, ~rid -l:o r3cc(~ pli5h this, power patte?~n recognition may be accolnplisl1ed simultaneously with correlation peak pattern detection.
This involves detecting the RMS power of the segment with-in the window W coincident with the correlation peak and comparing the resultant power pattern resulting from the matched segments. When both the correlation peak spacings and powex patterns match, a recognition signal is generated.
The block diagram system of Figure 2 -taken with the block diagrams and waveforms of Figures 3-8, provides a diagrammatic representation of the basic steps involved in the broadcast signal recoynition method of the present inve-ntion. With reference to Figures 2 thru 8, it willbe noted that a reference signal from a pre-recorded program to be broadcast is first prefiltered by a bandpass filter 10 to select a frequency portion of the audio spectrum having a stable amplitude envelope characteristics. The output from the filter 10 is passed to an envelope forming section 1.2 which provides an enve].ope waveform to a bandpass fi].ter 14. The output from the fi.1.ter 14 is a narrow bandwidth signal which is then digitized in an analog to digital converter 16 and ~ivided intoa plurality of equal length reference segrnents in a segmen-ting section 18. These reference se~nents are then prenormalized seyment by segment in-a normalization section 20 to obtain a ~IS amplitude for each reference segment. This is a conventional normalization process where the square root.of the power of each segment is ob-tained to provide the RMS ampl.i.tucle -Eor -the segment.
The RMS amp].i.tucle for each segment is thell separatc~ly st:o3-ed ;.n a sto:rag~ sect;.orl 22, wh:il.e t?le nc-)rma~ .ed :reference sec3Jrlents are then zero fi.lled in section 2 to form the complete reference segments R (Figure 4).
Each reference segment R is then Fouri.er transformed at 26 and the result transformed by -the performance of a complex conjugate at 28 to provide frequency domain complex spectra for each of -the reference segrnents R
which are separately stored at 30. These stored refer-ence segments can -then be provided at various locations :Eor comparison with a broadcast signal. at tha-t location.
~ he broadcast signal at a loaccltion is received and prefiltered in a bandpass filter 32, Eormed into an envelope by an envelope forming section 34, and ayain filtered by a bandpass filter 36 to provide a narrow bandwidth signal which is digitized by an analog to digital converter 38. The bandpass filter 32, envelope forming section 34, bandpass filter 36 and analog to digital converter 38 are identical in s-tructure and function to the bandpass filter 10, the envelope forming section 12, the bandpass filter 1~ and the analog to digital converter 16 for the reference signal.
It should be noted tha-t -the bandpass filters 10, 14, 32 and 36 and -the envelope formers 12 and 34 may be designed to provide an-: AM signal to be digitized as illustrated in Figure 3 or an FM signal as illustrated in Figure 5. The previously identified Moon patent discloses various filter and envelope formlng units to provide an AM siynal. To similarly opera-te.with an FM signal, the bandpass filters 10 and 32 pass a :Eilte~red FM signal -ko an :L~M erlve]ope forlller l2 or 34. This .Ei'M eJ-ivelope :rorme:r :inc:L~Ides l:wo ch.lJlnels to rece:i.ve the input signal. A first channel includes a high banclpass fi~ter 40 and a rectifier 42 while the second channel includes a low bandpass filter 44 and a rectifi.er 46. The outputs from the rectifiers 42 and 46 are directed to a differencing circuit 48, and the resulting difference signal from these two outputs is then directed to the bandpass filter 14 or 36.
The d.i~gi~-~izea~broàdcast~~signal from tXe analog to digital converter 38 is divided in-to severalbroadcast .
signal segrnents in a seyment former 50. These segments are overlapped in a form overlap buffex section 52 so that although each broadcast signal segment is equal in length to a zero filled reference segment R, the segments taken from the buffer 52 are overlapped for a half segment length as illustrated in Figure 6. Three reference signal segments for comparision with successive grouys of three broadcast signal segments have been shown for .
purposes of illustration in Figures 4 and 6, but other plural numbers of reference signal segrnents may be used.
The broadcast signal segments from the bu~fer 52 are provided from the buffer for use later in a sliding RMS
window section and are also individually converted to a freq~ency-domain, complex spectr;3m in the Fourier transform section 54, but the output from this section, unlike the reference signal segments stored in section 30, is not normalized. This output is subjected to a complex Inultiplicati.on function in -the multiplier section 56 where the stored reference seyments :Erom the storage unit 30 are rnultip:li.ed w;.th the output :Erorn the ~'ourier trallsfo:r]n sect:i.on 54 to ob-tain a vec~o:r E~rc)clllct or cross power spec-tra :Eor each se(3me3lt. 'I`he.ll al:l se~3me3-t:s ar~
inverse ~ourier t:ransEorrned in section 58 t:o obtain a correlation which is then normalized by passing through a sliding RMS window in sect.ion 68.
As previously discussed, the window W provided in section 60 is equal in length to a data section D, and a new RMS is calculated for the signal portion within this window ... each time a new dat;a point enters the window. To achieve this sliding RMS value, the digitized broadcast signal :Erom the form overlap buffer section 52 is employed with a sliding window W having a length equal to the data section R. As illustrated in Figure 7, the ~S value of the broadcast signal within the window Wl is obtained -. and this RMS value is divided into the corresponding -value of the correlation function Pl frorn the Fourier transform section 58 to obtain anormalized.cross correlatio3~vQlue.
Then relative rnovement between the window W and the broaclcast signal occurs for the distance S of one data space whi.ch is equal to rnoving over one po:int in the correlation function as illustrated in Figure 7.
This provi.des the window W2, and the RMS value of the digitized broadoast signal within l:his window is calculated and divided into -the correlation runction P2 to obtain a cross correlation ~alue . ~elative rnotion between the window and the broadcast signal continues in one data space steps with a cross correlation va].ue-. : being obtained during each step until the window reaches the Wx pos:ition. At this point, a corre].atic)n peak will have been establ;shed for segmellt 1 (Fi.gux~e 6), and -the proc:ess ;.s repeated W:i.t.ll ;eyll~ents 2, 3 and X.
The correlation peak in each cross correlation function segment from section 60 is selected in a detection section 62 and -the position (i.e. time of occurrence)of the correlati.on peak in each segment is stored in a storage section 64. Also in section 62, the RMS
.. ..
value coincident with each correlati.on peak is calculated and stored--,in a storage section 66. When the storaye sections 64 and 66 contain in:Forrnation from a plurality of segments equal in number to the number o:E reference segments, a decision loyic sec-tion 68 can deterrnine if a re:Eerence and broadcast signal match exists.
The decision logic section 68 operates in accordance with the flow chart of Figure 8 and as indicated at 70, a plurality of correlation peaks which exceed a predetermined threshold are selected . Eor consideration~ A decision is made at 72 to to determine whether a sufficient number of correlation peaks has been selected for consideration. As previously indicated, the decision log:ic can make a comparison based upon a number of signal and reference segments which is less than the to-tal number of reference segments stored.
For e~ample, if five reference seg~ants were stored initially, section 72 may permit a comparison to continue based upon three or four acceptable correlation peaks.
If the comparison is to continue, section 74 checks the time delay between accepted correlation peaks, and if the time delay or spacing between a succession of peaks is subs-tantially equal to the lengL}l of a reFerel-lce seglnent R, a signal matcll may exixt. This is deLeL~ ed by a delay decisic)ll sectiol~ 7~" whic}
is set to perlllit a ce~rtain amount oE spc3cing erKor, thereby permitting an allowable amount of speed varia-tion in the broadcast signal. Also, the delay decision section may permit more than the allowable spacing variation between a minority of the correlation peaks sensed. For example, where five reference segments R
are employed, the delay decision section may indicate signal recognition when three out of five successive peaks are properly spaced. This will permit the system to operate effectively in the presence of noise bursts, signal dropout, and similar adverse conditions which impair the effectiveness of conventional signal recoynition sys-tems.
Although signal recognition can be indicated at this point, the accuracy of the system is greatly enhanced if an additional comparison of power patterns is ~equired before a recognition signal is provided.
It will be noted in Fiyure 2 that the stored reference segment RMS values are provided by the storage section 22 to the d,ecision logic 68. The power pattern formed by the reference segment RMS values is compared by a decision logic section 78 with the power pattern ~ormed by the ~MS value coincident with each correlation peak which is stored in the storage section 66. For example, if the RMS value of -the ~irst stored reEerence segment is twice that of the second referellce sey1nent and three times that oE the third refe~-eJlce seg1nent, I)1e s~ e relatioJ-]ship shou~d be fol~nd in t}le vallles L~Lovi(iecl by the s-toraye section 66. If these power patterns :L5 are found to be coincident, a decision sec-tion 70 indicates ~thatsignal recognition has occurred.
Industrial App~licabil ty The broadcast signal recogni-tion method may be employed effectiveiy to provide automatic recognition of broadcast recordingst including music and advertisements. ~~
A system ernploying this method can be deployed in a network over a ~arge geographic area to permit surveys to be conducted in real time. This network is capable of operating continuously with a high degree of accuracy, and many channels may be monitored simultaneously for a large number of recordings. The method incorporates techniques which compensate for speed variations, spectral alteration and amplitude cornpression, and these techniques render the identification process relatively insensitive to the character~stics of various broadcast stations. Also, the , .~ 6~
method is highly versatile and readily adaptable for use ~here a variety of variable conditions prevail.
Fcr examp]e: the speed of the reierence signals may be varied to cornpensate for extreme speed varia-tions in the broadcast signal. To accomplish this, a plurality, for example -three, of reference signals may be provided at normal speed, three reference signals may be increased above normal speed and stored, and three reference signals may be decreased in speed below normal and stored. The broadcast signal is then compared against all of these reference signals and a ma-tch will be obtained wi-th the three closes-t -to -the broadcast signal speed.
. .
_ .
Figure 6 is a diagram showing the broadcast signal segments output from the buffer section of Figure 2;
Figure 7 is a diagram illustra-ting the operation of the normalizing and sliding RMS section of Figure 2; and Figure 8 is a flow diagram illustrating the operation of the decision loyic of Figure 2.
Best Mode For Carrying Out The Invention Effective broadcast signal recognition is extremely difficult to ac}l;.eve, even unde:r ideal broadcast condi-t;ons. The same recordecl p:rogram bro.ldccls-t by cl p].urclli-ty of c~:i..leJel-lt geog:l.clphi.cal:ly separatecl stations .i~5 s~lbjecl to the broadcast conditions peculiar to each individual stat:ion as well as to speed variations which may be inherent or purposely induced. Additional~Ly, each broadcast signal may be subject to varying conditions of noise, signal dropout, fre~uency equalizaiton, dynamic range compression, and other conditions which cause random perturbations in each broadcast signal. Thus, when the recogniti.on process involves the matching of a broad-cast signal with a pre-recorded standard reference signal taken E.rom a recorded program be:Eore it is broadcast, it will be apparent that the broadcast signal Erorn one station may match diEferently with the standard reference signal than will the broadcast signal from another station.
Consequently, classical correlation comparison techniques employing only a single reference signal segment and a single segment taken from a broadcast signal may not provi~e accurate data.
The broadcast signal recognition method of the present invention pref-erably emp:loys a plurality of reference segments taken from a recorded program to be broadcast and a plurali.ty of seglnerlts taken from the signal actually broadcast~ These .reference seglnents may be taken from separa-te time periods of a recording or from the same time period but based upon different frequency bands of the same recording. The decisi.on process for recognition of a recordi.ng is based upon time del.ay coinci.dence of the multiple reference pattern correlation peaks, rather than a single peak of a singl.e correlati.on function exceeding an amplitude threshold. Because a tolerance for slight tirne delay shifts between distinct time periods can be built into the coincidence detection, this multiple segment method can be made less vulnerable to playback speed variations than sing].e segment methods which employ the same total recording time period for recognition.
Turning now in detail to the broadcast signal recognition method:of the present invention, a plurality of signal segments of equal :Lenyth are taken frorn the recorded program to be broadcast, and after being filtered and digitized, these signal segments are pre-normalized to provide normalized refere~ce segments 25 for storage. This prenormalization step involves --first scaling each xeference segment pattern so that it will have a fixed total power for the segment, and this is accomplished by taking the square root of the total power to obtain the root mean square (RMS) amplitude for the segment. This RMS value is then divided into each point P in the segment to obtain a fixed scale factor K where K2 will be the variance of each segment. Then each normali.zed re.erence seyment is zero filled to provide a total reference segment having a data section D and a zero filled section z of equal ]ength (Figure 1).
This normalized zero filled reference segment R is then Fourier transformed and the result stored so that the stored reference segments are preprocessed segments which have been normalized in accorclance with the power in the segment, transformed into a frequency domain and then transformed by the performance of a complex conjugate to prov;de f:requency domain complex spectra.
rllo colnptl:re l:he stored reEe:r-c?rlce seynle~ s w~ h a broaclcast sicJrlal, the brc)adcast si.~,~nc~ is first: rl?ce:i.ved and prefiltered to select a Erequency portion of the audio spectrum that has stable characteristics. Since the high and low frequency portions of the audio spectrum are normally unstable, this prefiltering step generally results in providi~g an envelope in an intermediate stable freq,uency_region. _Qnce the envelope is formed, -~
it is again filtered to obtain a good stable narrow bandwidth signal which is then di.gitized and Fourier transformed to obtain a Erequency domain, complex spectrum.
Sequential subsegrnents of this signal, W}li.C}I are equal in ~.ength to the zero filled reference signal segments R, are then complex multiplied with the reference signal segments to obtain a vector product which is then subjected to an inverse Fourier transform to obtain a time domain correlation function which has not been normalized to the input power of the broadcast signal.
This unnormalized time domain correlation function is then sequentially normalized by a sliding RMS process within a win~ow W having the same length as ~ach da-ta section D. For each point P in the correlation function, the RMS o-f the total digitized broadcast signal within -the win~ow is calculated and divided i~to each point P ;n the correlation func-tion within the ~indow to obtain a normalized segment having a correlation peak CP. The temporal spacing between these correlation peaks is detected and, if such spacing is substantia:lly equal to -the length of the reference segments R, then signal recognition is indi-cated.
Generally, a double dele(tioll p-~ocess -l:o insure pro~3ram :1.ecc)9TIi.t.:lon :i.S cle.si.lahle, ~rid -l:o r3cc(~ pli5h this, power patte?~n recognition may be accolnplisl1ed simultaneously with correlation peak pattern detection.
This involves detecting the RMS power of the segment with-in the window W coincident with the correlation peak and comparing the resultant power pattern resulting from the matched segments. When both the correlation peak spacings and powex patterns match, a recognition signal is generated.
The block diagram system of Figure 2 -taken with the block diagrams and waveforms of Figures 3-8, provides a diagrammatic representation of the basic steps involved in the broadcast signal recoynition method of the present inve-ntion. With reference to Figures 2 thru 8, it willbe noted that a reference signal from a pre-recorded program to be broadcast is first prefiltered by a bandpass filter 10 to select a frequency portion of the audio spectrum having a stable amplitude envelope characteristics. The output from the filter 10 is passed to an envelope forming section 1.2 which provides an enve].ope waveform to a bandpass fi].ter 14. The output from the fi.1.ter 14 is a narrow bandwidth signal which is then digitized in an analog to digital converter 16 and ~ivided intoa plurality of equal length reference segrnents in a segmen-ting section 18. These reference se~nents are then prenormalized seyment by segment in-a normalization section 20 to obtain a ~IS amplitude for each reference segment. This is a conventional normalization process where the square root.of the power of each segment is ob-tained to provide the RMS ampl.i.tucle -Eor -the segment.
The RMS amp].i.tucle for each segment is thell separatc~ly st:o3-ed ;.n a sto:rag~ sect;.orl 22, wh:il.e t?le nc-)rma~ .ed :reference sec3Jrlents are then zero fi.lled in section 2 to form the complete reference segments R (Figure 4).
Each reference segment R is then Fouri.er transformed at 26 and the result transformed by -the performance of a complex conjugate at 28 to provide frequency domain complex spectra for each of -the reference segrnents R
which are separately stored at 30. These stored refer-ence segments can -then be provided at various locations :Eor comparison with a broadcast signal. at tha-t location.
~ he broadcast signal at a loaccltion is received and prefiltered in a bandpass filter 32, Eormed into an envelope by an envelope forming section 34, and ayain filtered by a bandpass filter 36 to provide a narrow bandwidth signal which is digitized by an analog to digital converter 38. The bandpass filter 32, envelope forming section 34, bandpass filter 36 and analog to digital converter 38 are identical in s-tructure and function to the bandpass filter 10, the envelope forming section 12, the bandpass filter 1~ and the analog to digital converter 16 for the reference signal.
It should be noted tha-t -the bandpass filters 10, 14, 32 and 36 and -the envelope formers 12 and 34 may be designed to provide an-: AM signal to be digitized as illustrated in Figure 3 or an FM signal as illustrated in Figure 5. The previously identified Moon patent discloses various filter and envelope formlng units to provide an AM siynal. To similarly opera-te.with an FM signal, the bandpass filters 10 and 32 pass a :Eilte~red FM signal -ko an :L~M erlve]ope forlller l2 or 34. This .Ei'M eJ-ivelope :rorme:r :inc:L~Ides l:wo ch.lJlnels to rece:i.ve the input signal. A first channel includes a high banclpass fi~ter 40 and a rectifier 42 while the second channel includes a low bandpass filter 44 and a rectifi.er 46. The outputs from the rectifiers 42 and 46 are directed to a differencing circuit 48, and the resulting difference signal from these two outputs is then directed to the bandpass filter 14 or 36.
The d.i~gi~-~izea~broàdcast~~signal from tXe analog to digital converter 38 is divided in-to severalbroadcast .
signal segrnents in a seyment former 50. These segments are overlapped in a form overlap buffex section 52 so that although each broadcast signal segment is equal in length to a zero filled reference segment R, the segments taken from the buffer 52 are overlapped for a half segment length as illustrated in Figure 6. Three reference signal segments for comparision with successive grouys of three broadcast signal segments have been shown for .
purposes of illustration in Figures 4 and 6, but other plural numbers of reference signal segrnents may be used.
The broadcast signal segments from the bu~fer 52 are provided from the buffer for use later in a sliding RMS
window section and are also individually converted to a freq~ency-domain, complex spectr;3m in the Fourier transform section 54, but the output from this section, unlike the reference signal segments stored in section 30, is not normalized. This output is subjected to a complex Inultiplicati.on function in -the multiplier section 56 where the stored reference seyments :Erom the storage unit 30 are rnultip:li.ed w;.th the output :Erorn the ~'ourier trallsfo:r]n sect:i.on 54 to ob-tain a vec~o:r E~rc)clllct or cross power spec-tra :Eor each se(3me3lt. 'I`he.ll al:l se~3me3-t:s ar~
inverse ~ourier t:ransEorrned in section 58 t:o obtain a correlation which is then normalized by passing through a sliding RMS window in sect.ion 68.
As previously discussed, the window W provided in section 60 is equal in length to a data section D, and a new RMS is calculated for the signal portion within this window ... each time a new dat;a point enters the window. To achieve this sliding RMS value, the digitized broadcast signal :Erom the form overlap buffer section 52 is employed with a sliding window W having a length equal to the data section R. As illustrated in Figure 7, the ~S value of the broadcast signal within the window Wl is obtained -. and this RMS value is divided into the corresponding -value of the correlation function Pl frorn the Fourier transform section 58 to obtain anormalized.cross correlatio3~vQlue.
Then relative rnovement between the window W and the broaclcast signal occurs for the distance S of one data space whi.ch is equal to rnoving over one po:int in the correlation function as illustrated in Figure 7.
This provi.des the window W2, and the RMS value of the digitized broadoast signal within l:his window is calculated and divided into -the correlation runction P2 to obtain a cross correlation ~alue . ~elative rnotion between the window and the broadcast signal continues in one data space steps with a cross correlation va].ue-. : being obtained during each step until the window reaches the Wx pos:ition. At this point, a corre].atic)n peak will have been establ;shed for segmellt 1 (Fi.gux~e 6), and -the proc:ess ;.s repeated W:i.t.ll ;eyll~ents 2, 3 and X.
The correlation peak in each cross correlation function segment from section 60 is selected in a detection section 62 and -the position (i.e. time of occurrence)of the correlati.on peak in each segment is stored in a storage section 64. Also in section 62, the RMS
.. ..
value coincident with each correlati.on peak is calculated and stored--,in a storage section 66. When the storaye sections 64 and 66 contain in:Forrnation from a plurality of segments equal in number to the number o:E reference segments, a decision loyic sec-tion 68 can deterrnine if a re:Eerence and broadcast signal match exists.
The decision logic section 68 operates in accordance with the flow chart of Figure 8 and as indicated at 70, a plurality of correlation peaks which exceed a predetermined threshold are selected . Eor consideration~ A decision is made at 72 to to determine whether a sufficient number of correlation peaks has been selected for consideration. As previously indicated, the decision log:ic can make a comparison based upon a number of signal and reference segments which is less than the to-tal number of reference segments stored.
For e~ample, if five reference seg~ants were stored initially, section 72 may permit a comparison to continue based upon three or four acceptable correlation peaks.
If the comparison is to continue, section 74 checks the time delay between accepted correlation peaks, and if the time delay or spacing between a succession of peaks is subs-tantially equal to the lengL}l of a reFerel-lce seglnent R, a signal matcll may exixt. This is deLeL~ ed by a delay decisic)ll sectiol~ 7~" whic}
is set to perlllit a ce~rtain amount oE spc3cing erKor, thereby permitting an allowable amount of speed varia-tion in the broadcast signal. Also, the delay decision section may permit more than the allowable spacing variation between a minority of the correlation peaks sensed. For example, where five reference segments R
are employed, the delay decision section may indicate signal recognition when three out of five successive peaks are properly spaced. This will permit the system to operate effectively in the presence of noise bursts, signal dropout, and similar adverse conditions which impair the effectiveness of conventional signal recoynition sys-tems.
Although signal recognition can be indicated at this point, the accuracy of the system is greatly enhanced if an additional comparison of power patterns is ~equired before a recognition signal is provided.
It will be noted in Fiyure 2 that the stored reference segment RMS values are provided by the storage section 22 to the d,ecision logic 68. The power pattern formed by the reference segment RMS values is compared by a decision logic section 78 with the power pattern ~ormed by the ~MS value coincident with each correlation peak which is stored in the storage section 66. For example, if the RMS value of -the ~irst stored reEerence segment is twice that of the second referellce sey1nent and three times that oE the third refe~-eJlce seg1nent, I)1e s~ e relatioJ-]ship shou~d be fol~nd in t}le vallles L~Lovi(iecl by the s-toraye section 66. If these power patterns :L5 are found to be coincident, a decision sec-tion 70 indicates ~thatsignal recognition has occurred.
Industrial App~licabil ty The broadcast signal recogni-tion method may be employed effectiveiy to provide automatic recognition of broadcast recordingst including music and advertisements. ~~
A system ernploying this method can be deployed in a network over a ~arge geographic area to permit surveys to be conducted in real time. This network is capable of operating continuously with a high degree of accuracy, and many channels may be monitored simultaneously for a large number of recordings. The method incorporates techniques which compensate for speed variations, spectral alteration and amplitude cornpression, and these techniques render the identification process relatively insensitive to the character~stics of various broadcast stations. Also, the , .~ 6~
method is highly versatile and readily adaptable for use ~here a variety of variable conditions prevail.
Fcr examp]e: the speed of the reierence signals may be varied to cornpensate for extreme speed varia-tions in the broadcast signal. To accomplish this, a plurality, for example -three, of reference signals may be provided at normal speed, three reference signals may be increased above normal speed and stored, and three reference signals may be decreased in speed below normal and stored. The broadcast signal is then compared against all of these reference signals and a ma-tch will be obtained wi-th the three closes-t -to -the broadcast signal speed.
. .
_ .
Claims (19)
1. A method for the automatic electronic recognition of a program unit broadcast by radio waves which includes:
a. processing said program unit to obtain a plurality of digitized reference signal segments;
b. successively processing a broadcast signal to generate successive digitized broadcast signal segments;
c. correlating a plurality of successive broadcast signal segments with an equal number of digitized reference signal segments to obtain correlation function peaks for each resultant correlation segment, and d. comparing the spacing between correlation function peaks for each correlation segment to determine whether such spacing is sub-stantially equal to the reference signal segment length.
a. processing said program unit to obtain a plurality of digitized reference signal segments;
b. successively processing a broadcast signal to generate successive digitized broadcast signal segments;
c. correlating a plurality of successive broadcast signal segments with an equal number of digitized reference signal segments to obtain correlation function peaks for each resultant correlation segment, and d. comparing the spacing between correlation function peaks for each correlation segment to determine whether such spacing is sub-stantially equal to the reference signal segment length.
2. The method of claim 1 which includes obtaining the RMS power value of each reference signal segment, obtaining an RMS power value coincident with each correlation function peak, comparing the pattern of the RMS power values from said reference signal segments with the pattern of the RMS power values coincident with an equal number of said correlation function peaks.
3. The method of claim 1 which includes providing a recognition signal when the spacing between said correlation function peaks is within a predetermined limit.
4. The method of claim 3 which includes providing a recognition signal when the number of spaces between said correlation function peaks which fall within said predetermined limit is more than one half the number of said reference segments.
5. The method of claim 2 which includes providing a recognition signal when the spacing between said correlation peaks is within a predetermined limit and the pattern of the RMS power values coincident with said correlation function peaks matches within predetermined limits the pattern of the RMS power values from said reference signal segments.
6. The method of claim 1 wherein the processing of said program unit includes prefiltering to select a pre-filtered signal in a frequency portion of the audio spectrum with a stable characteristic, forming an envelope from said prefiltered signal to provide an envelope reference signal, filtering the envelope reference signal to obtain a stable, narrow bandwidth reference signal and digitizing said narrow bandwidth reference signal to obtain a digitized reference signal, the processing of said broadcast signal includes pre-filtering to select a prefiltered signal in a frequency portion of the audio spectrum with a stable characteristic, forming an envelope from said prefiltered signal to provide an envelope broadcast signal filtering the envelope reference signal to obtain a stable, narrow bandwidth broadcast signal and digitizing said narrow bandwidth broadcast signal to obtain a digitized broadcast signal.
7. The method of claim 6 which includes normalizing said digitized reference signal to obtain a normalized reference signal before correlation with said broadcast signal segments.
8. The method of claim 7 which includes storing said normalized reference signal and said digitized broadcast signal before correlation.
9. The method of claim 1 which includes dividing said reference signal into a plurality of reference segments of equal length to obtain a plurality of digitized reference segments, normalizing said digitized reference segments to obtain the RMS power value for each reference segment, and storing each such normalized reference segment.
10. The method of claim 9 which includes zero filling each such normalized reference segment to obtain a plurality of zero filled reference segments of equal length, successively subjecting each said zero filled reference segment to a Fourier transformation and the performance of a complex conjugate to obtain a frequency domain complex spectra for each such zero filled reference segment, and storing the resultant frequency domain complex spectra reference signal segments.
11. The method of claim 10 which includes successively dividing said broadcast signal into a plurality of broadcast signal segments equal in length to said zero filled reference segments and storing said digitized broadcast signal segments.
12. The method of claim 11 which includes successively subjecting said stored digitized broadcast signal segments to Fourier transformation to obtain frequency domain, complex spectra broadcast signal segments, multiplying the complex spectra broadcast signal segments with the stored frequency domain complex spectra reference signal segments to obtain cross power spectra segments, subjecting said cross power spectra segments to inverse Fourier transformation to obtain correlation function segments, and obtaining normalized correlation function segments by successively obtaining an RMS power value for each of a plurality of equal length, overlapped sections within each digitized broadcast signal segment each such equal length section being equal in length to one half the length of the broadcast signal segment and the leading and trailing edge of each equal length section within a digitized broadcast signal segment being offset from the leading and trailing edge of the subsequent equal length section by one data space in said correlation function segment, the RMS
value obtained from each equal length section being divided into a corresponding point in said correlation function segment to provide a normalized correlation function segment having a correlation function peak.
value obtained from each equal length section being divided into a corresponding point in said correlation function segment to provide a normalized correlation function segment having a correlation function peak.
13. The method of claim 12 which includes obtaining an RMS power value coincident with each of said correlation function peaks, comparing the pattern of the stored RMS power values from said reference signal segments with the pattern of the RMS power values coincident with an equal number of said correlation function peaks.
14. The method of claim 13 which includes providing a recognition signal when the spacing between said correlation function peaks is within a predetermined limit and the pattern of the RMS power values coincident with said correlation function peaks matches within predetermined limits the pattern of the RMS power values from said digitized reference signal segments.
15. The method of claim 1 which includes pro-cessing said program unit to generate at least two groups of said successive digitized reference signal segments, the speed of one of said groups being varied with relation to the speed of the remaining group.
16. The method of claim 15 which includes correlating said plurality of broadcast signal segments with the groups of reference signal segments.
17. The method of claim 6 wherein the processing of said program unit includes forming an FM envelope from said prefiltered signal which is a function of the frequency content of said prefiltered signal, and the processing of said broadcast signal includes forming an FM envelope from said prefiltered signal which is a function of the frequency content of the prefiltered signal.
18. A method for the automatic, electronic recognition of a program unit broadcast by radio waves which includes:
a. obtaining a plurality of reference signal segments from said program unit;
b. processing said plurality of reference signal segments to obtain digitized reference signal segments;
c. obtaining the RMS power value of each reference signal segment;
d. successively processing a broadcast signal to generate successive digitally sampled broadcast signal segments;
e. correlating a plurality of successive broadcast signal segments with an equal number of digitized reference signal segments to obtain correlation function peaks for each resultant correlation segment;
f. obtaining an RMS power value coincident with each correlation function peak, and g. comparing the pattern of the RMS power values from said reference signal segments with the pattern of the RMS power values coincident with an equal number of said correlation function peaks.
a. obtaining a plurality of reference signal segments from said program unit;
b. processing said plurality of reference signal segments to obtain digitized reference signal segments;
c. obtaining the RMS power value of each reference signal segment;
d. successively processing a broadcast signal to generate successive digitally sampled broadcast signal segments;
e. correlating a plurality of successive broadcast signal segments with an equal number of digitized reference signal segments to obtain correlation function peaks for each resultant correlation segment;
f. obtaining an RMS power value coincident with each correlation function peak, and g. comparing the pattern of the RMS power values from said reference signal segments with the pattern of the RMS power values coincident with an equal number of said correlation function peaks.
19. The method of claim 18 which includes providing a recognition signal when the RMS power value coincident with said correlation function peaks matches within predetermined limits the pattern of RMS power values from said reference signal segments.
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|---|---|---|---|
| US416,664 | 1982-09-10 | ||
| US06/416,664 US4450531A (en) | 1982-09-10 | 1982-09-10 | Broadcast signal recognition system and method |
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|---|---|
| CA1191264A true CA1191264A (en) | 1985-07-30 |
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|---|---|---|---|
| CA000436517A Expired CA1191264A (en) | 1982-09-10 | 1983-09-12 | Broadcast signal recognition system and method |
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| US7831204B1 (en) | 1981-11-03 | 2010-11-09 | Personalized Media Communications, Llc | Signal processing apparatus and methods |
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| GB934918A (en) * | 1961-04-04 | 1963-08-21 | Philips Electrical Ind Ltd | Improvements in or relating to methods for checking record imperfections |
| US3546440A (en) * | 1968-05-24 | 1970-12-08 | Scope Inc | Spectrum analyzer wherein an analog waveform is sampled exponentially in time with two fixed reference sequences |
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| US3919479A (en) * | 1972-09-21 | 1975-11-11 | First National Bank Of Boston | Broadcast signal identification system |
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| US4230990C1 (en) * | 1979-03-16 | 2002-04-09 | John G Lert Jr | Broadcast program identification method and system |
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| US4450531A (en) | 1984-05-22 |
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