CN114424930A - Ultra-wideband UWB (ultra-wideband) vital signal data processing method and device based on singular value decomposition - Google Patents
Ultra-wideband UWB (ultra-wideband) vital signal data processing method and device based on singular value decomposition Download PDFInfo
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Abstract
The present disclosure provides a method and a device for processing Ultra Wide Band (UWB) vital signal data based on singular value decomposition, the method comprising: the method comprises the steps that an ultra-wideband radar life detector is used for emitting continuous pulse sequences to detect, so that multiple groups of continuous echo signals containing vital sign signals are obtained, and an echo signal matrix is preprocessed; singular value decomposition is carried out on the preprocessed echo signal matrix to obtain multi-order singular values and singular matrix components; extracting a space eigenvector and a time eigenvector corresponding to each order of singular value from the singular matrix component; the singular values, the spatial feature vectors and the time feature vectors of all orders are compressed and stored, the problems of a large amount of noise waves and noise interference of echo signals of the ultra-wideband radar life detector, space-time feature coupling, overlarge data volume, occupation of a large amount of storage space and the like can be solved, meanwhile, the singular values of the signals are processed, and the timeliness of vital sign signal processing is improved.
Description
Technical Field
The application relates to the technical field of signal processing, in particular to a method and a device for processing ultra-wideband UWB (ultra-wideband UWB) vital signal data based on singular value decomposition.
Background
The Ultra-Wideband Radar (UWB for short) has the advantages of high range resolution, strong penetration capability, low power consumption, strong anti-interference capability and the like, and along with the rapid development of the Ultra-Wideband Radar detection imaging technology, the technology is widely applied in various aspects of life, and has great potential in the aspects of communication, detection, medical treatment, remote sensing and the like. Among them, the use of ultra wideband radar for life detection is an important application in this field at present. Human body vital signals including respiration and heartbeat are extremely weak low-speed signals, in the process of vital signal detection, interference is caused by body surface micromotion, environmental noise, linear drifting caused by human activities, detector noise, thermal noise and the like, the interference is caused to the extraction and analysis of the vital signals, and the weak signals mutually influence to form a coupling effect. In the process of using the ultra-wideband radar to detect life, a large amount of data are often required to be collected, processed and stored, effective description on the data is difficult to perform due to the coupling effect among multiple signals, and the data volume is reduced.
In the related art, a method of data processing a vital echo signal includes: median filtering, gaussian filtering, wavelet transformation, empirical mode decomposition, and the like. The method is simple and quick, but is easy to cause discontinuity, and is difficult to remove multi-coupling interference signals. The gaussian filtering is a linear smooth filtering, which is suitable for eliminating gaussian noise, but needs to select a proper gaussian filtering function width and a gaussian filtering template length, and it is difficult to find a proper method to determine optimal parameters in an actual process. The wavelet transformation denoising method is a new mathematical theory and method developed in recent decades, has the characteristic of multi-resolution analysis, can focus on any detail of a signal to perform multi-resolution time-frequency domain analysis, has simple and clear algorithm and high calculation speed, but has not very wide application range, is very effective in the frequency range of known noise under specific conditions and the frequency bands of the signal and the noise are mutually separated, has poor denoising effect on white noise widely existing in practical application, and can cause the problems of signal distortion and the like if the fundamental wave parameter is improperly selected. The empirical mode decomposition method is a linear and steady-state spectrum analysis method based on Fourier transform, can decompose complex signals into a limited number of eigenmode functions, compared with wavelet transform, the method decomposes signals according to the time scale characteristics of data per se without presetting any basis function, however, amplitude modulation and frequency modulation signals obtained by empirical mode decomposition have a mode mixing phenomenon, a terminal effect can also influence the decomposition effect, and the denoising effect is greatly reduced.
In this way, the problems of a large amount of noise and noise interference of echo signals of the ultra-wideband radar life detection instrument, time-space characteristic coupling, overlarge data volume, occupation of a large amount of storage space and the like exist, and meanwhile, the timeliness of the life sign signal processing is not high.
Disclosure of Invention
The present disclosure is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the disclosure aims to provide a method and a device for processing ultra-wideband vital signal data based on singular value decomposition, which can reduce the problems of a large amount of noise and noise interference of echo signals of an ultra-wideband radar vital detector, space-time characteristic coupling, overlarge data volume, large storage space occupation and the like, and simultaneously process singular values of signals and improve the timeliness of vital sign signal processing.
The ultra-wideband vital signal data processing method based on singular value decomposition provided by the embodiment of the first aspect of the disclosure includes: the method comprises the steps that an ultra-wideband radar life detector is used for emitting continuous pulse sequences to detect, so that multiple groups of continuous echo signals containing vital sign signals are obtained, wherein the multiple groups of echo signals containing the vital sign signals form an echo signal matrix; preprocessing an echo signal matrix; singular value decomposition is carried out on the preprocessed echo signal matrix to obtain multi-order singular values and singular matrix components; extracting a space eigenvector and a time eigenvector corresponding to each order of singular value from the singular matrix component; and compressing and storing the singular values, the spatial feature vectors and the time feature vectors of each order.
The ultra-wideband vital signal data processing method based on singular value decomposition provided by the embodiment of the first aspect of the disclosure comprises the steps of transmitting a continuous pulse sequence by using an ultra-wideband radar vital detector for detection to obtain a plurality of continuous groups of echo signals containing vital sign signals, wherein the echo signals containing the vital sign signals form an echo signal matrix, preprocessing the echo signal matrix, performing singular value decomposition on the preprocessed echo signal matrix to obtain a plurality of orders of singular values and singular matrix components, extracting a space eigenvector and a time eigenvector corresponding to each order of singular value from the singular matrix components, compressing and storing each order of the singular value, the space eigenvector and the time eigenvector, and obtaining the space eigenvector and the time eigenvector corresponding to each order of the singular value due to the preprocessing and the singular value decomposition, and the singular values, the spatial feature vectors and the time feature vectors of each order are compressed and stored, so that the problems of a large amount of noise and noise interference of echo signals of the ultra-wideband radar life detector, space-time feature coupling, overlarge data volume, occupation of a large amount of storage space and the like can be solved, and meanwhile, the singular values of the signals are processed, so that the timeliness of the life sign signal processing is improved.
The ultra-wideband vital signal data processing device based on singular value decomposition provided by an embodiment of a second aspect of the disclosure includes: the detection module is used for transmitting a continuous pulse sequence by using the ultra-wideband radar life detector to perform detection so as to obtain a plurality of continuous groups of echo signals containing the vital sign signals, wherein the echo signals containing the vital sign signals form an echo signal matrix; the first processing module is used for preprocessing the echo signal matrix; the decomposition module is used for carrying out singular value decomposition on the preprocessed echo signal matrix so as to obtain multi-order singular values and singular matrix components; the extraction module is used for extracting a space eigenvector and a time eigenvector corresponding to each order of singular value from the singular matrix component; and the second processing module is used for compressing and storing the singular values, the spatial feature vectors and the temporal feature vectors of each order.
The ultra-wideband vital signal data processing device based on singular value decomposition provided by the embodiment of the second aspect of the disclosure obtains a plurality of continuous groups of echo signals containing vital sign signals by using an ultra-wideband radar vital detector to emit a continuous pulse sequence for detection, wherein the groups of echo signals containing the vital sign signals form an echo signal matrix, the echo signal matrix is preprocessed, the preprocessed echo signal matrix is subjected to singular value decomposition to obtain a plurality of orders of singular values and singular matrix components, a spatial eigenvector and a temporal eigenvector corresponding to each order of singular value are extracted from the singular matrix components, each order of singular value, the spatial eigenvector and the temporal eigenvector are compressed and stored, and the spatial eigenvector and the temporal eigenvector corresponding to each order of singular value are obtained by using preprocessing and singular value decomposition, and the singular values, the spatial feature vectors and the time feature vectors of each order are compressed and stored, so that the problems of a large amount of noise and noise interference of echo signals of the ultra-wideband radar life detector, space-time feature coupling, overlarge data volume, occupation of a large amount of storage space and the like can be solved, and meanwhile, the singular values of the signals are processed, so that the timeliness of the life sign signal processing is improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
Fig. 1 is a schematic flowchart of a method for processing ultra-wideband vital signal data based on singular value decomposition according to an embodiment of the present disclosure;
fig. 2 is an echo signal matrix X according to an embodiment of the disclosuremxnA time domain information map;
FIG. 3 is a time domain information diagram of a preprocessed echo signal matrix according to an embodiment of the disclosure;
FIG. 4 is a flow chart of singular value decomposition according to an embodiment of the present disclosure;
fig. 5 is a comparison graph of data volumes before and after processing of an echo signal matrix according to an embodiment of the present disclosure;
fig. 6 is a flow chart of a method for processing ultra-wideband vital signal data based on singular value decomposition according to another embodiment of the disclosure;
FIG. 7 is a factorial lithotripsy graph of a principal component lithotripsy testing method according to another embodiment of the present disclosure;
FIG. 8 is a flow chart of principal component screening proposed by another embodiment of the present disclosure;
fig. 9 is a graph of the amplitude components of the spatial eigenvector and the temporal eigenvector corresponding to the 1 st order singular value according to another embodiment of the present disclosure;
fig. 10 is a graph of the magnitude components of the spatial eigenvector and the temporal eigenvector corresponding to the 2 nd order singular value according to another embodiment of the present disclosure;
fig. 11 is a graph of the magnitude components of the spatial eigenvector and the temporal eigenvector corresponding to the 3 rd order singular value according to another embodiment of the present disclosure;
FIG. 12 is a diagram illustrating time domain information of an echo signal processed by the technical solution of the present disclosure;
fig. 13 is a schematic structural diagram of an ultra-wideband vital signal data processing device based on singular value decomposition according to an embodiment of the present disclosure;
fig. 14 is a schematic structural diagram of an ultra-wideband vital signal data processing device based on singular value decomposition according to another embodiment of the present disclosure.
Detailed Description
Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of illustrating the present disclosure and should not be construed as limiting the same. On the contrary, the embodiments of the disclosure include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Fig. 1 is a schematic flowchart of a method for processing ultra-wideband vital signal data based on singular value decomposition according to an embodiment of the present disclosure, where as shown in fig. 1, the method includes:
the present embodiment is exemplified by the ultra-wideband vital signal data processing method based on singular value decomposition being configured as an ultra-wideband vital signal data processing apparatus based on singular value decomposition, in which the ultra-wideband vital signal data processing method based on singular value decomposition in the present embodiment may be configured as an ultra-wideband vital signal data processing apparatus based on singular value decomposition, and the ultra-wideband vital signal data processing apparatus based on singular value decomposition may be disposed in a server or may also be disposed in an electronic device, which is not limited by the embodiments of the present disclosure.
S101: and (2) transmitting a continuous pulse sequence by using the ultra-wideband radar life detector to detect so as to obtain continuous groups of echo signals containing the vital sign signals, wherein the groups of echo signals containing the vital sign signals form an echo signal matrix.
The life-saving equipment developed by using the micropower ultra-wideband radar technology can be called an ultra-wideband radar life detection instrument, through transmitting a continuous pulse sequence, analysis is carried out based on the time domain Doppler effect generated by human body movement on a radar, whether life bodies exist in ruins and the specific position information of the life bodies are judged, and the ultra-wideband radar life detection instrument can be used for emergency rescue tasks such as earthquake disasters and collapse accidents, and the rescue quality and the work efficiency are effectively improved.
The pulse signal returned to the ultra-wideband radar life detection instrument by the vital sign signal through the detection of the continuous pulse sequence can be called as an echo signal, and the echo signal can be returned to the ultra-wideband radar life detection instrument in a signal matrix form, or a matrix array of the echo signal can be generated after the ultra-wideband radar life detection instrument receives the echo signal, so that the method is not limited.
In the embodiment of the disclosure, when the continuous pulse sequence emitted by the ultra-wideband radar life detector detects to obtain the vital signs, the continuous pulse sequence returns the echo signals through the vital signs, and a plurality of groups of echo signals containing the vital sign signals can form an echo signal matrix.
Optionally, in the embodiment of the present disclosure, the ultra-wideband radar life detector is used to transmit a continuous periodic pulse sequence for detection; the echo signals corresponding to each pulse sequence are arranged by using the echo signal matrix, so that the waveform change effect of pulse sequence detection can be enhanced, and the accuracy of the detection result is improved.
In the embodiment of the disclosure, a signal sampling frequency F is setSAnd a continuous pulse train frequency FPRReceiving multiple sets of echo signals containing vital sign signals1，X2，X3，…，XnArranging the received echo signals of each pulse sequence according to rows to form an echo signal matrix Xmxn：
Wherein m and n (m)>1，n>1, and m and n are integers) are respectively a matrix XmxnThe number of rows and columns of (a) may also represent the number of samples of the same pulse wave and the number of pulses in a continuous periodic pulse train, respectively.
In the embodiment of the present disclosure, as shown in fig. 2, fig. 2 is an echo signal matrix X provided in an embodiment of the present disclosuremxnThe time domain information graph and the echo signal matrix received by the ultra-wideband radar life detector have obvious noise, so the echo signal matrix needs to be subjected to denoising processing, and the specific implementation mode refers to the following steps.
S102: and preprocessing the echo signal matrix.
In the embodiment of the present disclosure, the echo signal matrix is preprocessed, and a characteristic waveform in the echo signal matrix may be extracted through waveform transformation, so as to reduce noise influence, or a threshold denoising manner may be used, and a denoising function is realized through filtering of a signal and setting of a threshold, or a corresponding denoising algorithm may be used, which is not limited to this.
Optionally, in the embodiment of the present disclosure, the echo signal matrix may be preprocessed by using a track signal subtraction method and a time-reducing averaging method.
Optionally, in the embodiment of the present disclosure, background wave elimination is performed on the radar echo by using a channel signal subtraction method, so as to eliminate a constant component in the scanning process; and eliminating background clutter caused by static objects in the detected scene by using a time reduction and average method so as to preprocess the echo signal matrix.
Firstly, background wave elimination is carried out on radar echo by using a channel signal subtraction method, and constant components in the scanning process are eliminated. In the present embodiment, forEcho signal matrix XmxnFor any group of pulse echo signalsjJ-1, 2,3, …, n, the result of subtraction of the trace signals X'jComprises the following steps:
X’j＝Xj-Xj-1
and eliminating background clutter caused by detecting static objects of the scene by using a time reduction average method. In the present embodiment, the echo signal matrix XmxnThe background clutter caused by detecting stationary objects in the scene can approximate the dc component, which is estimated by time-reduced averaging:
the result after processing by using a time-reducing average method is as follows:
Rm×n＝Xm×n-S
after the processing, constructing a preprocessed echo signal matrix Rmxn，RmxnFig. 3 is a time domain information diagram of an echo signal matrix preprocessed according to an embodiment of the present disclosure, and compared with fig. 2, the time domain information diagram can be obtained by performing preprocessing on the echo signal matrix through processing methods such as a channel signal subtraction method and a time averaging method, so that the time domain information diagram has an excellent denoising effect, can effectively reduce background clutter, eliminate constant components in a scanning process, and further improve a detection effect of a pulse sequence in an ultra-wideband radar life detector.
S103: and carrying out singular value decomposition on the preprocessed echo signal matrix to obtain multi-order singular values and singular matrix components.
In the embodiment of the present disclosure, the preprocessed echo signal matrix R may be processedmxnSingular value decomposition is performed by the following method:
Um×m＝[u1,u2,u3,…um]
Vn×n＝[v1,v2,v3,…vn]
wherein, UmxmAnd VnxnAre all unit orthogonal arrays, i.e. UUTI and VVT＝I，UmxmCalled left singular matrix, VnxnReferred to as the right singular matrix. Inverted V shapemxnCalled singular value matrix, having singular values only on the main diagonal, all other elements being 0, singular value matrix ^mxnMain diagonal element of (a)1，σ2，σ3，…，σkFor the preprocessed echo signal matrix RmxnK singular values of (a), and satisfies sigma1≥σ2≥σ3≥…≥σk，uiRepresentation matrix UmxmIs called the ith order left singular vector, viRepresentation matrix VnxnIs called the ith order right singular vector, σiRepresenting the ith element of the spectrum of singular values.
In the embodiment of the present disclosure, as shown in fig. 4, fig. 4 is a singular value decomposition flowchart provided in an embodiment of the present disclosure, and is used for a preprocessed echo signal matrix RmxnRespectively construct a matrix RRTAnd RTR, wherein RRTIs a real symmetric matrix of m x m order, where RTR is n × n order real symmetric matrix, and is respectively corresponding to RRTAnd RTAnd (3) decomposing the characteristic value of R according to the following decomposition principle:
RRT＝UΛVT(UΛVT)T＝UΛVTVΛTUT＝U(ΛΛT)UT＝UΣ1UT；
RTR＝(UΛVT)TUΛVT＝VΛTUTUΛVT＝V(ΛTΛ)VT＝VΣ2VT；
wherein, RR is extracted from the result after the characteristic value decompositionTCharacteristic matrices U and R ofTThe characteristic matrix V of R is respectively used as RmxnLeft and right singular matrices of, for sigma1Or sigma2The characteristic value in the process is squared to obtain a singular value matrix lambdamxnAnd completing singular value decomposition.
After singular value decomposition is carried out on the preprocessed echo signal matrix, multistage singular values and singular matrix components can be obtained, singular value matrix components can be subjected to screening processing, or singular matrix components can be subjected to decomposition processing without limitation, spatial eigenvectors and time eigenvectors can be more obvious through processing of the singular matrix components, and extraction efficiency of the spatial eigenvectors and the time eigenvectors is improved.
S104: and extracting the space eigenvector and the time eigenvector corresponding to the singular value of each order from the singular matrix component.
In the embodiment of the present disclosure, the spatial eigenvectors and the time eigenvectors corresponding to the multiple levels of singular values respectively may be extracted according to the components of the singular value matrix, the spatial eigenvectors corresponding to the singular values of different levels may be different from each other, and the time eigenvectors corresponding to the singular values of different levels may also be different from each other.
Optionally, in the embodiment of the present disclosure, singular value decomposition is performed on the preprocessed echo signal matrix by using a principal component lithotripsy inspection method, so as to obtain multiple-order singular values and singular matrix components; the spatial eigenvector and the time eigenvector corresponding to each order of singular value are extracted from the singular matrix component, and the spatial change characteristic and the time change characteristic are calculated according to the signal sampling frequency and the continuous pulse sequence frequency.
In the embodiment of the present disclosure, the principal component may be screened according to a curved shape of a graph in a factor lithograph of the principal component lithotripsy inspection method, or the principal component of the singular value of the echo signal matrix after the preprocessing may also be screened according to a bending point, or the principal component of the singular value of the echo signal matrix after the preprocessing may also be screened according to any other possible implementation manners, which is not limited thereto.
S105: and compressing and storing the singular values, the spatial feature vectors and the time feature vectors of each order.
In the embodiment of the present disclosure, singular values of different orders (for example, 1 order, 2 orders, and 3 orders …), and spatial eigenvectors and temporal eigenvectors corresponding to the singular values of different orders may be respectively compressed and stored, or a singular value of a suitable order, and spatial eigenvectors and temporal eigenvectors corresponding to the singular values of different orders may be selected and respectively compressed and stored, which is not limited herein.
Optionally, in the embodiment of the present disclosure, the singular value, the spatial feature vector corresponding to the singular value, and the temporal feature vector are compressed and stored correspondingly, so that the data compression efficiency can be improved, and the occupation of a large amount of storage space caused by an excessive data amount is reduced.
The singular values that are not subjected to feature decomposition may be referred to as main singular values, and the main singular values are subjected to decomposition of spatial feature vectors and temporal feature vectors, so that feature singular values corresponding to different feature vectors may be generated.
In the embodiment of the disclosure, the pre-screened q-order principal singular value sigma is subjected to1，σ2，σ3，…，σqSpatial feature vector u1，u2，u3，…，uqAnd a temporal feature vector v1，v2，v3，…，vqPerforming one-to-one correspondence storage, i.e. the principal singular value σ of the j-th orderjCorresponding space characteristic vector ujAnd a temporal feature vector vjCreating a container for corresponding storage, and storing q containers in total, wherein each container comprises 3 elements, and the total data of each containerThe quantity is m + n +1, and the original echo signal matrix X is replaced by the quantitymxnRealize data compression, compression ratio ksThe calculation method is as follows:
in the embodiment of the present disclosure, as shown in fig. 5, fig. 5 is a data quantity comparison diagram before and after processing of an echo signal matrix provided in an embodiment of the present disclosure, it can be known that, because the dimension of an echo signal detected by an ultra-wideband radar life detection instrument by transmitting a continuous periodic pulse sequence is large, the value of m and n is often large, and the main singular value screening order q is generally small, data compression can be realized under a low order number, and a good compression effect is achieved.
In the embodiment, a continuous pulse sequence is transmitted by an ultra-wideband radar life detector for detection to obtain a plurality of continuous groups of echo signals containing vital sign signals, wherein the plurality of groups of echo signals containing the vital sign signals form an echo signal matrix, the echo signal matrix is preprocessed, singular value decomposition is carried out on the preprocessed echo signal matrix to obtain a plurality of orders of singular values and singular matrix components, a space eigenvector and a time eigenvector corresponding to each order of singular value are extracted from the singular matrix components, each order of singular value, each space eigenvector and each time eigenvector are compressed and stored, as the preprocessing and the singular value decomposition are used, the space eigenvector and the time eigenvector corresponding to each order of singular value are obtained, and each order of singular value, each space eigenvector and each time eigenvector are compressed and stored, the problems of a large amount of noise and noise interference of echo signals of the ultra-wideband radar life detector, space-time characteristic coupling, overlarge data volume, occupation of a large amount of storage space and the like can be solved, meanwhile, singular values of the signals are processed, and the timeliness of vital sign signal processing is improved.
Fig. 6 is a flowchart of a method for processing ultra-wideband vital signal data based on singular value decomposition according to another embodiment of the disclosure, as shown in fig. 6, the method includes:
s601: and (2) transmitting a continuous pulse sequence by using the ultra-wideband radar life detector to detect so as to obtain continuous groups of echo signals containing the vital sign signals, wherein the groups of echo signals containing the vital sign signals form an echo signal matrix.
S602: and preprocessing the echo signal matrix.
S603: and carrying out singular value decomposition on the preprocessed echo signal matrix to obtain multi-order singular values and singular matrix components.
For description of S601-S603, reference may be made to the above embodiments, which are not described herein again.
S604: and (3) screening principal components of the plurality of singular values of the preprocessed echo signal matrix by adopting a principal component macadam inspection method, and drawing a graph of the characteristic value and the number of the principal components.
In the disclosed embodiment, for the echo signal matrix RmxnK singular values of (a)1，σ2，σ3，…，σkAs shown in fig. 7, fig. 7 is a factor lithograph of a principal component lithotripsy inspection method according to another embodiment of the present disclosure, and as can be seen from fig. 7, the higher the order, the smaller the singular value, and the order interval in which the singular value changes most (i.e., the interval with the highest playing slope) is 2 to 3.
S605: according to the bending condition of the graph, reserving multi-order main singular values of a main component in the graph as multi-order singular values, and determining singular matrix components corresponding to the multi-order singular values.
In the embodiment of the present disclosure, according to the graph change conditions such as the bending point of the graph in the factor lithograph, the interval with the highest slope, and the like, the multi-order main singular value of the principal component meeting the requirement may be selected as the multi-order singular value, or a certain threshold requirement may be set, and the multi-order main singular value of the principal component meeting the threshold requirement may be selected as the multi-order singular value, or a corresponding principal component screening model may be trained, and the multi-order main singular value of the principal component may be determined as the multi-order singular value in a model screening manner, which is not limited.
In the embodiment of the present disclosure, as shown in fig. 8, fig. 8 is a principal component screening flowchart provided in another embodiment of the present disclosure, and comprehensively determines, according to the relative magnitude of the descending gradient of the singular value of each order and the current singular value, the specific steps are as follows:
setting a principal component gradient change threshold T1With a relative size threshold T2From g1(j is 1) starting to calculate the descending gradient g of singular valuejJ is 1,2,3, …, k-1, the calculation method is as follows:
wherein, the judgment gj>T1If yes, if no, let j become j +1 and continue to calculate gj(ii) a If yes, stopping calculation, recording the current order j as p, and calculating the relative size h of the current j as p order singular valuejJ is 1,2,3, …, k, the calculation method is as follows:
wherein, it is judged thatj<T2If yes, if no, let j become j +1 and continue to calculate hj(ii) a If yes, stopping calculation, recording the current order j ═ q, and selecting the main singular value sigma of the previous q order1，σ2，σ3，…，σqAs a result after screening.
In the embodiment of the present disclosure, singular values of an appropriate order may be selected as multiple orders of singular values as needed, and spatial eigenvectors and temporal eigenvectors corresponding to the singular values of each order respectively corresponding to the multiple orders of singular values are determined.
S606: and extracting left singular vectors corresponding to the main singular values of each order from the singular matrix components as space characteristic vectors, and extracting right singular vectors corresponding to the main singular values of each order as time characteristic vectors.
In the embodiment of the disclosure, the q-order major singular value sigma is selected before selection1，σ2，σ3，…，σqAfter the result after screening, the first q-order dominant singular value sigma can be selected according to the result1，σ2，σ3，…，σqExtracting corresponding left singular vectors u of each order1，u2，u3，…，uqFor each order of spatial feature vector, each order of right singular vector v1，v2，v3，…，vqAre the temporal feature vectors of each order.
S607: and determining a distance vector of the space characteristic vector as a space change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
In the embodiment of the present disclosure, the distance vector of the space feature vector may be determined as a space variation characteristic by way of coordinate conversion, coordinate conversion is performed according to the following formula, and the distance vector s corresponding to each order of space feature vector is calculated, where s isiRepresents the ith element in the distance vector s:
s＝[s1,s2,s3,…sm]
wherein c is 3x108m/s is the speed of light, i.e. the pulse detection speed, FSFor the signal sampling frequency, the spatial feature vector u of each orderjIs an m-order vector and the distance vector s is an m-order vector.
S608: and determining a time vector of the time characteristic vector as a time change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
In the embodiment of the present disclosure, the time vector of the time feature vector may be used as a time variation characteristic through coordinate conversion, coordinate conversion is performed according to the following formula, and the time vector t corresponding to each order of time feature vector is calculated, where t isjRepresents the jth element in the time vector t:
t＝[t1,t2,t3,…tn]
wherein, FPRFor successive pulse train frequencies, a time feature vector v of each orderjIs an n-order vector, and the time vector t is an n-order vector.
S609: and compressing and storing the singular values, the spatial feature vectors and the time feature vectors of each order.
For description of S609, reference may be made to the foregoing embodiments specifically, and details are not repeated here.
In the disclosed embodiment, a continuous pulse sequence is transmitted by using an ultra-wideband radar life detector for detection to obtain a plurality of continuous groups of echo signals containing vital sign signals, wherein the plurality of groups of echo signals containing the vital sign signals form an echo signal matrix, the echo signal matrix is preprocessed, singular value decomposition is performed on the preprocessed echo signal matrix to obtain a plurality of levels of singular values and singular matrix components, a plurality of singular values of the preprocessed echo signal matrix are subjected to principal component screening by adopting a principal component rubble inspection method, graphs of characteristic values and principal component numbers are drawn, the plurality of levels of principal singular values of principal components in the graphs are reserved as the plurality of levels of singular values according to the bending condition of the graphs, the singular matrix components corresponding to the plurality of levels of the principal components are determined, left singular vectors corresponding to the principal singular values of each level are extracted from the singular matrix components as space characteristic vectors, the right singular vector corresponding to each order of main singular value is extracted as a time characteristic vector, the distance vector of the space characteristic vector is determined as a space change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency, the time vector of the time characteristic vector is determined as a time change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency, the principle component screening is carried out by adopting a principle component rubble inspection method, the multi-order main singular value of the principle component in the graph is determined according to the bending condition of the graph, the noise interference problem can be effectively processed, part of noise signal interference is filtered, effective signals which are more in line with the requirement are screened out, the efficiency of the principle component screening is improved, the time change characteristic and the space change characteristic which are respectively corresponding to the time characteristic vector and the space characteristic vector are determined according to the signal sampling frequency and the continuous pulse sequence frequency, the extraction and analysis of the vital signals and the establishment of a database are more convenient.
In summary, after the spatio-temporal feature decomposition processing of the present disclosure, amplitude component graphs of the spatial feature vector and the temporal feature vector corresponding to the first 3 orders of singular values are selected, as shown in fig. 9 to 11, fig. 9 is a graph of amplitude components of the spatial feature vector and the temporal feature vector corresponding to the 1 st order of singular values proposed in another embodiment of the present disclosure, fig. 10 is a graph of amplitude components of the spatial feature vector and the temporal feature vector corresponding to the 2 nd order of singular values proposed in another embodiment of the present disclosure, and fig. 11 is a graph of amplitude components of the spatial feature vector and the temporal feature vector corresponding to the 3 rd order of singular values proposed in another embodiment of the present disclosure.
In the embodiment of the present disclosure, as shown in fig. 12, fig. 12 shows a time domain information diagram of an echo signal processed by the technical scheme of the present disclosure, and compared with fig. 2, it can be shown that the technical scheme of the present disclosure can reduce a large amount of interference of noise and noise in the echo signal of the ultra-wideband radar life detector, and can improve the timeliness of the processing of the vital sign signal.
Fig. 13 is a schematic structural diagram of an ultra-wideband vital signal data processing device based on singular value decomposition according to an embodiment of the present disclosure.
As shown in fig. 13, the ultra-wideband vital signal data processing apparatus 130 based on singular value decomposition includes:
the detection module 1301 is configured to use an ultra-wideband radar life detector to transmit a continuous pulse sequence for detection, so as to obtain multiple continuous groups of echo signals including vital sign signals, where the multiple groups of echo signals including the vital sign signals form an echo signal matrix;
a first processing module 1302, configured to pre-process an echo signal matrix;
a decomposition module 1303, configured to perform singular value decomposition on the preprocessed echo signal matrix to obtain multiple-order singular values and singular matrix components;
an extracting module 1304, configured to extract spatial feature vectors and temporal feature vectors corresponding to singular values of each order from the singular matrix component;
the second processing module 1305 is configured to perform compression and storage processing on the singular values, the spatial feature vectors, and the temporal feature vectors of each order.
In some embodiments of the present disclosure, as shown in fig. 14, fig. 14 is a schematic structural diagram of an ultra-wideband vital signal data processing apparatus based on singular value decomposition according to another embodiment of the present disclosure, where the first processing module 1302 is specifically configured to:
and preprocessing the echo signal matrix by using a channel signal subtraction method and a time reduction-averaging method.
In some embodiments of the present disclosure, as shown in fig. 14, the extraction module 1304, includes:
a decomposition submodule 13041, configured to perform singular value decomposition on the preprocessed echo signal matrix by using a principal component lithotripsy inspection method to obtain multiple-order singular values and singular matrix components;
and an extracting submodule 13042, configured to extract a spatial eigenvector and a temporal eigenvector corresponding to each order of singular value from the singular matrix component, and calculate a spatial variation characteristic and a temporal variation characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
In some embodiments of the present disclosure, as shown in fig. 14, the detection module 1301 is specifically configured to:
the ultra-wideband radar life detector is used for emitting a continuous periodic pulse sequence for detection;
and receiving continuous groups of echo signals containing vital sign signals, and arranging the received echo signals of each pulse sequence according to rows to form an echo signal matrix.
In some embodiments of the present disclosure, as shown in fig. 14, the first processing module 1302 is specifically configured to:
background wave elimination is carried out on radar echo by using a channel signal subtraction method so as to eliminate constant components in the scanning process;
and eliminating background clutter caused by static objects in the detected scene by using a time reduction average method so as to preprocess the echo signal matrix.
In some embodiments of the present disclosure, as shown in fig. 14, sub-module 13041 is decomposed, and is specifically configured to:
carrying out principal component screening on a plurality of singular values of the preprocessed echo signal matrix by adopting a principal component macadam inspection method, and drawing a graph of characteristic values and principal component numbers;
according to the bending condition of the graph, reserving multi-order main singular values of a main component in the graph as multi-order singular values, and determining singular matrix components corresponding to the multi-order singular values.
In some embodiments of the present disclosure, as shown in fig. 14, the extraction sub-module 13042 is specifically configured to:
extracting left singular vectors corresponding to main singular values of each order from singular matrix components as space characteristic vectors, and extracting right singular vectors corresponding to the main singular values of each order as time characteristic vectors;
determining a distance vector of a space characteristic vector as a space change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency;
and determining a time vector of the time characteristic vector as a time change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
In some embodiments of the present disclosure, as shown in fig. 14, the second processing module 1305, is specifically configured to;
and carrying out corresponding compression storage processing on the singular value, the space characteristic vector corresponding to the singular value and the time characteristic vector.
Corresponding to the ultra-wideband vital signal data processing method based on singular value decomposition provided in the embodiments of fig. 1 to 12, the present disclosure also provides an ultra-wideband vital signal data processing apparatus based on singular value decomposition, and since the ultra-wideband vital signal data processing apparatus based on singular value decomposition provided in the embodiments of the present disclosure corresponds to the ultra-wideband vital signal data processing method based on singular value decomposition provided in the embodiments of fig. 1 to 12, the implementation manner of the ultra-wideband vital signal data processing method based on singular value decomposition is also applicable to the ultra-wideband vital signal data processing apparatus based on singular value decomposition provided in the embodiments of the present disclosure, and will not be described in detail in the embodiments of the present disclosure.
In the embodiment, a continuous pulse sequence is transmitted by an ultra-wideband radar life detector for detection to obtain a plurality of continuous groups of echo signals containing vital sign signals, wherein the plurality of groups of echo signals containing the vital sign signals form an echo signal matrix, the echo signal matrix is preprocessed, singular value decomposition is carried out on the preprocessed echo signal matrix to obtain a plurality of orders of singular values and singular matrix components, a space eigenvector and a time eigenvector corresponding to each order of singular value are extracted from the singular matrix components, each order of singular value, each space eigenvector and each time eigenvector are compressed and stored, as the preprocessing and the singular value decomposition are used, the space eigenvector and the time eigenvector corresponding to each order of singular value are obtained, and each order of singular value, each space eigenvector and each time eigenvector are compressed and stored, the problems of a large amount of noise and noise interference of echo signals of the ultra-wideband radar life detector, space-time characteristic coupling, overlarge data volume, occupation of a large amount of storage space and the like can be solved, meanwhile, singular values of the signals are processed, and the timeliness of vital sign signal processing is improved.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe various information, the information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information, without departing from the scope of the embodiments of the present application. The words "if" and "if," as used herein, may be interpreted as "at … …" or "when … …" or "in response to a determination," depending on the context.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present disclosure includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.
Claims (10)
1. A method for processing ultra-wideband UWB vital signal data based on singular value decomposition is characterized by comprising the following steps:
the method comprises the steps that an ultra-wideband radar life detector is used for emitting continuous pulse sequences to detect, so that multiple groups of continuous echo signals containing vital sign signals are obtained, wherein the multiple groups of echo signals containing the vital sign signals form an echo signal matrix;
preprocessing the echo signal matrix;
singular value decomposition is carried out on the preprocessed echo signal matrix to obtain multi-order singular values and singular matrix components;
extracting a space eigenvector and a time eigenvector corresponding to the singular value of each order from the singular matrix component;
and compressing and storing the singular values, the spatial feature vectors and the temporal feature vectors of each order.
2. The method of claim 1, wherein the preprocessing the echo signal matrix comprises:
and preprocessing the echo signal matrix by using a channel signal subtraction method and a time reduction-averaging method.
3. The method of claim 1, wherein the extracting spatial eigenvectors and temporal eigenvectors corresponding to the singular values of each order from the singular matrix components comprises:
carrying out singular value decomposition on the preprocessed echo signal matrix by using a principal component gravel inspection method to obtain multi-order singular values and singular matrix components;
and extracting a space eigenvector and a time eigenvector corresponding to the singular value of each order from the singular matrix component, and calculating a space change characteristic and a time change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
4. The method according to claim 1, wherein the detecting with the ultra-wideband radar life detector transmits a continuous pulse sequence to obtain a plurality of continuous sets of echo signals containing vital sign signals, wherein the plurality of sets of echo signals containing vital sign signals form an echo signal matrix, and comprises:
the ultra-wideband radar life detector is used for emitting a continuous periodic pulse sequence for detection;
and receiving the continuous groups of echo signals containing the vital sign signals, and respectively arranging the received echo signals of each pulse sequence according to rows to form the echo signal matrix.
5. The method of claim 2, wherein the preprocessing the echo signal matrix by using a track signal subtraction method and a time-averaging method comprises:
background wave elimination is carried out on radar echo by using a channel signal subtraction method so as to eliminate constant components in the scanning process;
and eliminating background clutter caused by static objects in the detected scene by using a time reduction average method so as to preprocess the echo signal matrix.
6. The method of claim 3, wherein the performing singular value decomposition on the preprocessed echo signal matrix using a principal component lithotripsy inspection method to obtain multiple orders of singular values and singular matrix components comprises:
carrying out principal component screening on a plurality of singular values of the preprocessed echo signal matrix by adopting a principal component macadam inspection method, and drawing a graph of characteristic values and principal component numbers;
and according to the bending condition of the graph, reserving multi-order main singular values of a main component in the graph as the multi-order singular values, and determining singular matrix components corresponding to the multi-order singular values.
7. The method according to claim 3, wherein the extracting spatial eigenvectors and temporal eigenvectors corresponding to the singular values of each order from the singular matrix components and calculating spatial variation characteristics and temporal variation characteristics according to the signal sampling frequency and the continuous pulse sequence frequency comprises:
extracting left singular vectors corresponding to main singular values of each order from the singular matrix components as space characteristic vectors, and extracting right singular vectors corresponding to the main singular values of each order as time characteristic vectors;
determining a distance vector of the space characteristic vector as the space change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency;
and determining a time vector of the time characteristic vector as the time change characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
8. The method according to claim 1, wherein the compressing and storing the singular values, the spatial eigenvectors, and the temporal eigenvectors of the respective orders comprises;
and performing corresponding compression storage processing on the singular value, the spatial feature vector corresponding to the singular value and the temporal feature vector.
9. An ultra-wideband UWB vital signal data processing apparatus based on singular value decomposition, comprising:
the detection module is used for transmitting a continuous pulse sequence by using the ultra-wideband radar life detector to perform detection so as to obtain a plurality of continuous groups of echo signals containing the vital sign signals, wherein the groups of echo signals containing the vital sign signals form an echo signal matrix;
the first processing module is used for preprocessing the echo signal matrix;
the decomposition module is used for carrying out singular value decomposition on the preprocessed echo signal matrix so as to obtain multi-order singular values and singular matrix components;
the extraction module is used for extracting a space eigenvector and a time eigenvector corresponding to the singular value of each order from the singular matrix component;
and the second processing module is used for compressing and storing the singular values, the spatial feature vectors and the temporal feature vectors of each order.
10. The apparatus of claim 9, wherein the extraction module comprises:
the decomposition submodule is used for carrying out singular value decomposition on the preprocessed echo signal matrix by utilizing a principal component rubble detection method so as to obtain multi-order singular values and singular matrix components;
and the extraction submodule is used for extracting the space eigenvector and the time eigenvector corresponding to the singular value of each order from the singular matrix component and calculating the space variation characteristic and the time variation characteristic according to the signal sampling frequency and the continuous pulse sequence frequency.
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| CN114792109A (en) * | 2022-05-16 | 2022-07-26 | 煤炭科学研究总院有限公司 | Vital sign signal extraction method and device, electronic equipment and storage medium |
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| CN116430347B (en) * | 2023-06-13 | 2023-08-22 | 成都实时技术股份有限公司 | Radar data acquisition and storage method |
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