CN110378320A - The common cycle of multiple signals determines method, apparatus and readable storage medium storing program for executing - Google Patents
The common cycle of multiple signals determines method, apparatus and readable storage medium storing program for executing Download PDFInfo
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Abstract
The invention discloses a kind of common cycles of multiple signals to determine method, terminal is equipped with the sensor matrices being made of multiple array elements, each array element receives the signal that measured signal source is sent, it include: the output signal to the M array element received K measured signal source of bay, sample when the sky of n times snap, to construct M array element to first signal matrix in K measured signal source；It determines corresponding first covariance matrix of the first signal matrix, and the decomposition of characteristic value is carried out to determine noise vector and signal vector to the first covariance；The solution function of frequency parameter is determined according to noise vector and signal vector；Frequency parameter is scanned for according to function is solved, to obtain the common frequency parameter of the signal of K measured signal source transmitting, wherein common frequency parameter is the common cycle of multiple signals.Invention additionally discloses a kind of common cycle determining device of multiple signals and readable storage medium storing program for executing.The present invention can accurately determine the period of things.
Description
Technical field
The present invention relates to signal processing technology fields more particularly to a kind of common cycle of multiple signals to determine method, dress
It sets and readable storage medium storing program for executing.
Background technique
In the temporal regularity for finding a certain things, namely the period of things is determined, by using the characterization things
Corresponding time series is analyzed, and time series can be indicated by signal, also can determine things by signal processing
Temporal regularity.
For temporal regularity determination there are many method.First, using Fourier analysis method by year-on-year sequence transformation to frequently
On domain；Second, using time variation and the stability being distributed Short Time Fourier Transform method research cycle on a timeline, study things
The variation of period on a timeline when being influenced by external factor；Third selects Gaussian filter extracting cycle signal and closes
At finding out the accurate period to filter out the noise in signal.4th, the location of the period of things is studied with the domain Z figure,
Energy size, and the change in future of Current transaction is judged accordingly.
The above analysis method is individually studied each time series data of things as a signal, but thing
Object is a system entirety, therefore the period of things determined by the above analysis method is inaccurate.
Summary of the invention
The main purpose of the present invention is to provide a kind of common cycles of multiple signals to determine method, apparatus and readable storage
Medium, it is intended to which solve the problems, such as the period of things determines inaccuracy.
To achieve the above object, the present invention provides a kind of common cycles of multiple signals to determine method, the multiple letter
Number common cycle determine method be applied to equipped with aerial array terminal, the aerial array be equipped with M array element, it is each described in
Array element receive measured signal source send signal, the common cycle of the multiple signal determine method the following steps are included:
When carrying out the sky of n times snap to the output signal in the M array element received K measured signal source of the bay
Sampling, to construct the M array elements to first signal matrix in K measured signal source；
It determines corresponding first covariance matrix of the signal matrix, and characteristic value is carried out to first covariance matrix
Decomposition to determine noise vector and signal vector；
The solution function of frequency parameter is determined according to the noise vector and the signal vector；
The frequency parameter is scanned for according to the solution function, to obtain the K measured signal source transmittings
The common frequency parameter of signal, wherein the common frequency parameter is the common cycle of multiple signals.
In one embodiment, it is described to first covariance matrix carry out characteristic value decomposition with determine noise vector with
And the step of signal vector, includes:
First covariance matrix is converted to obtain covariance matrix to be decomposed according to preset noise hypothesis；
The decomposition that characteristic value is carried out to the covariance matrix to be decomposed, obtains the characteristic value of multiple descending sequences；
Signal vector is determined according to each characteristic value and the corresponding sequence serial number of each characteristic value and is made an uproar
Sound vector.
In one embodiment, described true according to each characteristic value and the corresponding sequence serial number of each characteristic value
The step of determining signal vector and noise vector include:
According to the sequence serial number of each characteristic value, K object feature value is determined, wherein the K object feature values
It is all larger than other each characteristic values except the object feature value；
Using the corresponding feature vector of the described object feature value of K as signal vector, and will it is each described in other characteristic values
Corresponding feature vector is as noise vector.
In one embodiment, the solution function that frequency parameter is determined according to the noise vector and the signal vector
The step of include:
Determine corresponding first matrix of each noise vector and corresponding second matrix of each signal vector；
The function that second matrix and first matrix multiple are zero is determined, to find out the solution letter of frequency parameter
Number.
In one embodiment, it is fast to carry out n times for the M array element received K measured signal source to the bay
It is sampled when the sky of bat, includes: the step of first signal matrix of the M array elements to K measured signal source to construct
Determine the optical path difference and phase difference of the adjacent received each signal of array element；
Determine other each array elements to each measured signal source by reference point of the target array element of the aerial array
The corresponding function of inductive signal；
The output signal of the array element sampled when determining n times sky according to the optical path difference, the phase difference and the function
Corresponding objective function；
The corresponding objective function of output signal of the array element sampled when according to n times sky, to construct the M array elements to K
First signal matrix in measured signal source.
In one embodiment, sampling when determining n times sky according to the optical path difference, the phase difference and the function
Array element output signal corresponding objective function the step of include:
The function is rewritten as to the function of plural form according to Euler's formula；
The optical path difference and the phase difference are substituted into the function of plural form, to determine the output sampled when n times sky
The corresponding objective function of signal.
In one embodiment, the common cycle of the multiple signal determines method, further includes:
It is adopted when carrying out the sky of n times snap to the output signal of the received multiple signal sources of M array element of the bay
Sample to determine the second covariance matrix, and carries out Eigenvalues Decomposition to second covariance matrix and obtains multiple feature vectors；
Determine the corresponding weight of each described eigenvector, and according to each described eigenvector and each feature
The corresponding weight of vector constructs second signal matrix；
Space spectral function is determined according to the second signal matrix, and direction of arrival is carried out to the space spectral function and is estimated
The spectral peak quantity is determined as the quantity of signal source to determine spectral peak quantity by meter, wherein the quantity of the signal source is K；
Behind the quantity setting signal source according to determining signal source, the M array element to the bay is executed
The output signal in received K measured signal source sampled when the sky of n times snap, to construct M array elements to K letter
The step of first signal matrix in number source.
In one embodiment, the common cycle of the multiple signal determines method, further includes:
N times snap is carried out to the output signal in received multiple measured signal sources of M array element of the bay
It is sampled when empty, to determine third covariance matrix, and Eigenvalues Decomposition is carried out to the third covariance matrix and obtains multiple spies
Value indicative；
It determines explanation dynamics, and determines object feature value in each characteristic value, wherein each target signature
Value is all larger than other characteristic values in addition to the object feature value；
Judge whether the quantity of the object feature value meets with each object feature value according to the explanation dynamics
Preset condition；
When the quantity of the object feature value meets preset condition, the quantity of the object feature value is determined as signal
The quantity in source, wherein the quantity of the signal source is K；
Behind the quantity setting signal source according to determining signal source, the M array element to the bay is executed
The output signal in received K measured signal source sampled when the sky of n times snap, to construct M array elements to K letter
The step of first signal matrix in number source.
To achieve the above object, the present invention also provides a kind of common cycle determining device of multiple signals, the multiple letters
Number common cycle device be equipped with aerial array and signal acquisition module, the aerial array be equipped with M array element, it is each described in
Array element receives the signal that signal source is sent, and the signal acquisition module is used to acquire the signal of array element received signal source transmission；
The common cycle determining device of the multiple signal further includes memory, processor and is stored in the memory and can be in institute
The determination program of the common cycle run on processor is stated, the signal acquisition module is connected to the processor, described common
The common cycle that multiple signals as described above are executed when the determination program in period is executed by processor determines each step of method
Suddenly.
To achieve the above object, the present invention also provides a kind of readable storage medium storing program for executing, the readable storage medium storing program for executing is stored with altogether
Synperiodic determining program realizes multiple signals as described above when the determination program of the common cycle is executed by processor
Common cycle determines each step of method.
The common cycle of multiple signals provided by the invention determines method, apparatus and readable storage medium storing program for executing, multiple signals
Common cycle determining device is equipped with aerial array, and aerial array includes multiple array elements, and device can receive multiple measured signals simultaneously
The signal of source output.Device carries out n times snap to the output signal in the M array element received K measured signal source of bay
Sky when sample, to construct M array element to the signal matrix in K measured signal source, then determine the corresponding covariance of signal matrix
Matrix, and the decomposition for carrying out characteristic value to covariance matrix obtains signal vector and noise vector, device is according to noise vector
And signal vector determines the solution function of frequency parameter, is finally scanned for according to solution function to frequency parameter, thus
The common frequency parameter of the signal exported to each measured signal source, common frequency parameter is the common cycle of multiple signals.
Since device simultaneously analyzes each signal, the corresponding data of multiple signals are subjected to global analysis, and to each letter
The separation for number carrying out noise vector and signal vector, reduces interference of the noise to common cycle, has accurately determined things
Period.
Detailed description of the invention
Fig. 1 be the present embodiments relate to multiple signals common cycle determining device hardware architecture schematic diagram；
Fig. 2 is the flow diagram of the first embodiment of the determination method of the common cycle of the multiple signals of the present invention；
Fig. 3 is the refinement flow diagram of step S10 in Fig. 2；
Fig. 4 is the refinement flow diagram of step S20 in Fig. 2；
Fig. 5 is the refinement flow diagram of step S30 in Fig. 2；
Fig. 6 is the flow diagram of the second embodiment of the determination method of the common cycle of the multiple signals of the present invention；
Fig. 7 is the refinement flow diagram of step S60 in Fig. 6；
Fig. 8 is the flow diagram of the 3rd embodiment of the determination method of the common cycle of the multiple signals of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The primary solutions of the embodiment of the present invention are: to the received K measured signal of M array element of the bay
The output signal in source sample when the sky of n times snap, to construct the M array elements to first signal in K measured signal source
Matrix；It determines corresponding first covariance matrix of the signal matrix, and characteristic value is carried out to first covariance matrix
It decomposes to determine noise vector and signal vector；Asking for frequency parameter is determined according to the noise vector and the signal vector
Solve function；The frequency parameter is scanned for according to the solution function, to obtain the letter of the K measured signal source transmittings
Number common frequency parameter, wherein the common frequency parameter be multiple signals common cycle.
Since device simultaneously analyzes each signal, the corresponding data of multiple signals are subjected to global analysis, and
The separation that noise vector and signal vector are carried out to each signal, reduces interference of the noise to common cycle, accurately really
The period of things is determined.
As a kind of implementation, the common cycle determining device of multiple signals can be as shown in Figure 1.
What is involved is the common cycle determining device of multiple signals, the common cycles of multiple signals for the embodiment of the present invention
Determining device includes: processor 101, such as CPU, memory 102, communication bus 103, aerial array 104 and signal acquisition
Module 105.Wherein, for communication bus 103 for realizing the connection communication between these components, aerial array 104 includes multiple battle arrays
Member, each array element are used to receive the signal of signal source transmission, and signal acquisition module 105 is used to acquire the letter of each array element output
Number.
Memory 102 can be high speed RAM memory, be also possible to flying wing type memory.As shown in Figure 1, as one kind
It may include the determination program of common cycle in the memory 103 of computer storage medium；And processor 101 can be used for calling
The determination program of the common cycle stored in memory 102, and execute following operation:
When carrying out the sky of n times snap to the output signal in the M array element received K measured signal source of the bay
Sampling, to construct the M array elements to first signal matrix in K measured signal source；
It determines corresponding first covariance matrix of the signal matrix, and characteristic value is carried out to first covariance matrix
Decomposition to determine noise vector and signal vector；
The solution function of frequency parameter is determined according to the noise vector and the signal vector；
The frequency parameter is scanned for according to the solution function, to obtain the K measured signal source transmittings
The common frequency parameter of signal, wherein the common frequency parameter is the common cycle of multiple signals.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
First covariance matrix is converted to obtain covariance matrix to be decomposed according to preset noise hypothesis；
The decomposition that characteristic value is carried out to the covariance matrix to be decomposed, obtains the characteristic value of multiple descending sequences；
Signal vector is determined according to each characteristic value and the corresponding sequence serial number of each characteristic value and is made an uproar
Sound vector.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
According to the sequence serial number of each characteristic value, K object feature value is determined, wherein the K object feature values
It is all larger than other each characteristic values except the object feature value；
Using the corresponding feature vector of the described object feature value of K as signal vector, and will it is each described in other characteristic values
Corresponding feature vector is as noise vector.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
Determine corresponding first matrix of each noise vector and corresponding second matrix of each signal vector；
The function that second matrix and first matrix multiple are zero is determined, to find out the solution letter of frequency parameter
Number.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
Determine the optical path difference and phase difference of the adjacent received each signal of array element；
Determine other each array elements to each measured signal source by reference point of the target array element of the aerial array
The corresponding function of inductive signal；
The output signal of the array element sampled when determining n times sky according to the optical path difference, the phase difference and the function
Corresponding objective function；
The corresponding objective function of output signal of the array element sampled when according to n times sky, to construct the M array elements to K
First signal matrix in measured signal source.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
The function is rewritten as to the function of plural form according to Euler's formula；
The optical path difference and the phase difference are substituted into the function of plural form, to determine the output sampled when n times sky
The corresponding objective function of signal.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
It is adopted when carrying out the sky of n times snap to the output signal of the received multiple signal sources of M array element of the bay
Sample to determine the second covariance matrix, and carries out Eigenvalues Decomposition to second covariance matrix and obtains multiple feature vectors；
Determine the corresponding weight of each described eigenvector, and according to each described eigenvector and each feature
The corresponding weight of vector constructs second signal matrix；
Space spectral function is determined according to the second signal matrix, and direction of arrival is carried out to the space spectral function and is estimated
The spectral peak quantity is determined as the quantity of signal source to determine spectral peak quantity by meter, wherein the quantity of the signal source is K；
Behind the quantity setting signal source according to determining signal source, the M array element to the bay is executed
The output signal in received K measured signal source sampled when the sky of n times snap, to construct M array elements to K letter
The step of first signal matrix in number source.
In one embodiment, processor 101 can be used for calling the determination journey of the common cycle stored in memory 102
Sequence, and execute following operation:
N times snap is carried out to the output signal in received multiple measured signal sources of M array element of the bay
It is sampled when empty, to determine third covariance matrix, and Eigenvalues Decomposition is carried out to the third covariance matrix and obtains multiple spies
Value indicative；
It determines explanation dynamics, and determines object feature value in each characteristic value, wherein each target signature
Value is all larger than other characteristic values in addition to the object feature value；
Judge whether the quantity of the object feature value meets with each object feature value according to the explanation dynamics
Preset condition；
When the quantity of the object feature value meets preset condition, the quantity of the object feature value is determined as signal
The quantity in source, wherein the quantity of the signal source is K；
Behind the quantity setting signal source according to determining signal source, the M array element to the bay is executed
The output signal in received K measured signal source sampled when the sky of n times snap, to construct M array elements to K letter
The step of first signal matrix in number source.
The present embodiment is equipped with aerial array, aerial array according to above scheme, the common cycle determining device of multiple signals
Including multiple array elements, device can receive the signal of multiple measured signal source outputs simultaneously.Device connects M array element of bay
The output signal in K measured signal source of receipts sample when the sky of n times snap, to construct M array element to K measured signal source
Signal matrix, then determine the corresponding covariance matrix of signal matrix, and to covariance matrix carry out characteristic value decomposition obtain
Signal vector and noise vector, device determine the solution function of frequency parameter according to noise vector and signal vector, finally
Frequency parameter is scanned for according to function is solved, to obtain the common frequency ginseng of the signal of each measured signal source output
Number, common frequency parameter is the common cycle of multiple signals.It, will be multiple since device simultaneously analyzes each signal
The corresponding data of signal carry out global analysis, and the separation of noise vector and signal vector is carried out to each signal, reduce
Interference of the noise to common cycle, has accurately determined the period of things.
The hardware architecture of common cycle determining device based on above-mentioned multiple signals proposes the common of the multiple signals of the present invention
The embodiment of cycle determination method.
Referring to Fig. 2, Fig. 2 is that the common cycle of the multiple signals of the present invention determines the first embodiment of method, the multiple letter
Number common cycle determine method the following steps are included:
Step S10 carries out n times snap to the output signal of the received K measured signal of M array element of the bay
Sky when sample, to construct M array elements to first signal matrix in K measured signal source；
In the present embodiment, executing subject is the common cycle determining device of multiple signals, for ease of description, with device
The present embodiment is described in detail in the abbreviation of common cycle determining device as multiple signals.Antenna array is equipped in device
Column, aerial array include multiple array elements, and the quantity of array element is M, and M is integer.M array element forms equidistant line array, Ge Gezhen
First characteristic is identical, and the isotropism of each array element, between adjacent array element between be divided into d, it is received most that d is less than or equal to array element
The half of the wavelength of high-frequency signal, each array element is irrelevant, and each array element and each measured signal source are also uncorrelated.
Aerial array is in the far field in each measured signal source, i.e., antenna array receiver is transmitted from each measured signal source
Signal be plane wave.The characteristic of the receiving branch of each signal for receiving measured signal source is all identical in device.It is each to be measured
Signal source polarity having the same, and each measured signal source is irrelevant, measured signal source can be narrowband, and measured signal source
Quantity be K, and K < M.
Device is additionally provided with signal acquisition module, signal acquisition module carry out sampling when the sky of snap for interval time T with
The signal sampled, so that matrix is constructed according to the signal of each sampling, specifically, referring to Fig. 3, i.e. step S10 includes:
Step S11 determines the optical path difference and phase difference of the adjacent received each signal of array element；
Assuming that k-th of signal source sk(t) opposite incidence angle is vk, then received each signal s of adjacent array elementk(t) light
Path difference is xk=dsinvk, phase difference isThe signal of k-th of signal source is monochromatic wave, can be expressed as
sk(t)=Aksin(ωkt+θk)。
Step S12 determines that other each array elements are to be measured to each using the target array element of the aerial array as reference point
The corresponding function of the inductive signal of signal source；
It in the present embodiment, can be with first array element of aerial array determining t time equidistant straight line as a reference point
The inductive signal of m-th pair of k-th of signal source in battle array, inductive signal is the corresponding output signal of m-th of array element, to sk
(t)=Aksin(ωkt+θk) convert, m-th of delayed output signals function expression is obtained, namelyFirst array element is target array element, and certainly, target array element may be used also
To be other array elements, first array element is not limited.
Step S13, the array element sampled when determining n times sky according to the optical path difference, the phase difference and the function
The corresponding objective function of output signal；
In order to facilitate the discussion of model, unnecessary parameter is reduced, it will by Euler's formula It is rewritten as plural form, is rewritten as the function of plural form are as follows:
Optical path difference and phase difference are substituted into functionIn, it obtains
To sK, m(t)=A (k, m) exp (j ωkT), wherein A (k, m) contains the information of term amplitude and phase term: θk,vk；J is
Complex unit.
Further, consider the noise in all signal source incoming waves and transmission channel, it, can be true according to function obtained above
The output signal of fixed m-th of array element:
As a result, in the sky of n times snap in sampling, choosing was 0 moment at the time of sampling for the first time, carries out time interval and is
The sampling of the n times of T, then the N of t=T (n-1), n=1,2,3 ..., according to t andObtain the function of the output signal of m array element of n-th snap are as follows:
The function is target letter
Number.
Step S14, the corresponding objective function of output signal of the array element sampled when according to n times sky, to construct the M battle arrays
First signal matrix of the member to K measured signal source.
It is write above-mentioned objective function as matrix form, namely obtains the first signal matrix, the first signal matrix X=WA+E,
Wherein,Namely W is N row K column
Matrix, W include the information of the frequency parameter about K signal source；
Namely A is the matrix of K row M column, A includes about K signal
The initial phase item θ in sourcek, term amplitude AkAnd angle v of k-th of initial signal source relative to arraykInformation；
Namely E is the matrix of N row M column, E represents in n times sampling M
Noise on channel.
Step S20 determines corresponding first covariance matrix of first signal matrix, and to the first covariance square
Battle array carries out the decomposition of characteristic value to determine noise vector and signal vector；
After determining the first signal matrix, the first covariance matrix of the first signal matrix is taken, the first covariance matrix is fixed
Justice are as follows:
Rx=E { XXT}==E { (WA+E) (WA+E)T, assume further according to pre-set noise to the first covariance square
Battle array carries out Eigenvalues Decomposition and obtains noise vector and signal vector, specifically, referring to figure 4. namely step S20 includes:
Step S21 is converted to obtain association side to be decomposed according to preset noise hypothesis to first covariance matrix
Poor matrix；
Step S22 carries out the decomposition of characteristic value to the covariance matrix to be decomposed, obtains multiple descending sequences
Characteristic value；
Step S23, according to each characteristic value and the corresponding sequence serial number of each characteristic value determine signal to
Amount and noise vector.
In the present embodiment, noise assumes that as white Gaussian noise is irrelevant, and white Gaussian noise and each letter to be measured
Number source is also uncorrelated, is converted to obtain covariance matrix to be decomposed to the first covariance matrix according to noise hypothesis as a result, to
Decompose covariance matrix: Rx=E { XXT}=E { (WA) (WA)T}+E{EET}；Due to noise it is assumed that then E { EET}=σ2I, therefore,
Rx=E { (WA) (WA)T}+σ2I is converting the expression formula to obtain covariance matrix to be decomposed, R againx=R+ σ2I,
In, R=E { (WA) (WA)T, the first covariance matrix and transformed covariance matrix to be decomposed are actually identical.
It follows that the first item of covariance matrix to be decomposed indicates the covariance matrix that signal vector generates, Section 2
Indicate the covariance matrix generated by noise vector.It thus can be to transformed covariance matrix R to be decomposedxCarry out characteristic value
It decomposes, obtains Rx=U Λ UT, wherein Λ=diag (λ1,λ2,…λN), the diagonal matrix that the characteristic value for being R is constituted.After changing
Covariance matrix to be decomposed decomposition, it can be seen that the first covariance matrix also can be analyzed to following form: Rx=U Λ UT=U
(Σ+σ2I)UT, wherein Σ=diag (λ1-σ2,λ2-σ2,…λK-σ2... 0 ... 0), and the diagonal matrix that the characteristic value for being R is constituted.
By the decomposition to covariance matrix, the influence of noise signal in characteristic value is stripped out, the contribution of characteristic value
It is divided into two parts, a part is contributed by signal vector, and another part is contributed by noise vector.In RxEigenvalues Decomposition
In obtained N number of characteristic value, preceding K bigger characteristic values are generated by signal vector, then N-K smaller characteristic values
It is generated by noise signal.So carrying out descending sequence to each characteristic value after decomposition obtains multiple characteristic values, obtaining
The collating sequence for having each characteristic value to constitute, each characteristic value have corresponding sequence serial number, take K sequence serial number preceding
Characteristic value is as object feature value, that is, each object feature value is all larger than the spy of other each mesh in addition to object feature value
Value indicative, the corresponding feature vector of object feature value is signal vector, the corresponding feature vector of other characteristic values be noise to
Amount.
Step S30 determines the solution function of frequency parameter according to the noise vector and the signal vector；
After determining each noise vector and signal vector, frequency parameter is determined according to noise vector and signal vector
Solution function, specifically, referring to figure 5., i.e. step S30 includes:
Step S31 determines that corresponding first matrix of each noise vector and each signal vector are corresponding
Second matrix；
Step S32 determines second matrix and institute according to the orthogonality between signal subspace and noise subspace
The function that the corresponding multiplication of the first matrix is zero is stated, to find out the solution function of frequency parameter；
According to the orthogonality between signal subspace and noise subspace, in the present embodiment, if preceding each target signature
Value λ1,λ2,…λKCorresponding signal vector is s1, s2…sK, remember S=[s1,s2,…sK]；Other each eigenvalue λsK+1,λK+2,…
λNCorresponding noise vector is gK+1,gK+2,…gN, remember G=[gK+1,gK+2,…gN], then have:
Wherein, P=diag (λ1,λ2,…λK), Q=diag (λK+1,
λK+2,…λN), S is corresponding second matrix of each signal vector actually, and G is corresponding first matrix of each noise vector,As intermediate function.
Further, it is contemplated that the orthogonality of signal subspace and noise subspace, by It is available And RxG=E { (WA) (WA)T}G+σ2IG subtracts each other according to two formula as a result, and E { (WA) (WA) can be obtainedTG=0,
As WE { (A) (A)T}WTG=0, two side of equation is simultaneously multiplied by GT, obtain GTWE{(A)(A)T}WTG=0.Due to E { (A) (A)T}
It is nonsingular, it is known that, WTG=0, that is, the matrix comprising signal source frequency parameter information and the feature vector structure comprising noise information
At matrix be orthogonal.Therefore by it, each column of W matrix is substituted into, W (i)=(1, exp (j ω is obtained1T (n-1), exp (j ωiT(n-1)))T, i=1,2,3 ... K；To obtain W (i)TThus G=0 obtains the solution of the frequency parameter about i-th of signal
Function.
Step S40 scans for the frequency parameter according to the solution function, to obtain the K measured signals
The common frequency parameter of the signal of source transmitting, wherein the common frequency parameter is the common cycle of multiple signals.
After determining solution function, frequency parameter is scanned for, meets ω=ω working asiWhen, it obtainsThe peak value of the function is taken again, to estimate to obtain K signal sources transmittings to be tested according to peak value
Common frequency the parameter ω, ω of signal be the corresponding common cycle of multiple signals.
It should be noted that the determination method of the common cycle of above-mentioned multiple signals can using with economy and finance field,
That is the corresponding signal of time series data of the corresponding economy and finance of each signal, device analyze entire gold according to such signal
Melt the time cycle in field, to determine the correct time period.Pass through the determination method of the common cycle of multiple signals, it may be determined that
The common cycle in economy and finance field is 42 months, 100 months and 200 months.Certainly, it is true that the above method can also be used in device
The common cycle for determining multiple signals of other field, is not limited in the application in economy and finance field.
In technical solution provided in this embodiment, the common cycle determining device of multiple signals is equipped with aerial array, day
Linear array includes multiple array elements, and device can receive the signal of multiple measured signal source outputs simultaneously.Device is a to the M of bay
The output signal in array element received K measured signal source sample when the sky of n times snap, to be measured to K to construct M array element
The signal matrix of signal source, then determine the corresponding covariance matrix of signal matrix, and characteristic value is carried out to covariance matrix and is divided
Solution obtains signal vector and noise vector, and device determines the solution letter of frequency parameter according to noise vector and signal vector
Number finally scans for frequency parameter according to solution function, to obtain the common of the signal of each measured signal source output
Frequency parameter, common frequency parameter are the common cycle of multiple signals.Since device simultaneously analyzes each signal, with
The corresponding data of multiple signals are subjected to global analysis, and carry out the separation of noise vector and signal vector to each signal,
Reduce interference of the noise to common cycle, the period of things has accurately been determined.
Referring to Fig. 6, Fig. 6 is the second embodiment of the determination method of the common cycle of the multiple signals of the present invention, is based on first
Embodiment, the determination method of the common cycle of multiple signals further include:
Step S50 carries out n times snap to the output signal of the received multiple signal sources of M array element of the bay
Sky when sample, with determine the second covariance matrix, and to second covariance matrix carry out Eigenvalues Decomposition obtain it is multiple
Feature vector；
In the present embodiment, the accurate of the common cycle of multiple signals determines the base for being built upon appropriate number of signal source
On plinth.If the quantity of signal source is improper, when carrying out Mutual coupling, it may occur that pseudo- peak is failed to report or generated to spectral peak.
In this regard, before the common cycle for determining multiple signals, it is thus necessary to determine that appropriate number of signal source.
H signal source can be first set, and device is again to the output signal of the received H signal source of M array element of bay
Sample when the sky of n times snap, so that it is determined that the second covariance matrix, the determination of the second covariance matrix and the first covariance
Matrix determines that unanimously this is no longer going to repeat them.
After determining the second covariance matrix, then the decomposition for carrying out characteristic value to the second covariance matrix obtains multiple features
Vector, the Eigenvalues Decomposition that the specific decomposition process of the characteristic value of the second covariance matrix is put to the proof referring to the first covariance.
Step S60, determines the corresponding weight of each described eigenvector, and according to each described eigenvector and each
The corresponding weight of described eigenvector constructs second signal matrix；
After determining each feature vector, the corresponding weight of each feature vector is determined, when the weight of feature vector is bigger,
The magnification level of noise vector is bigger, and the diminution degree of signal vector is smaller.Specifically, weight is characterized the inverse of value, and make an uproar
The characteristic value of sound vector is smaller, thus the inverse of noise vector is larger, to be exaggerated noise vector；Similarly, signal vector
Characteristic value is larger, therefore reciprocal smaller, reduces signal vector.It can make the effect of signal vector by the reasonable setting of weight
It dies down, is equivalent in spatial spectrum algorithm the case where noise vector is only utilized.And by the way that feature vector is weighted, from
Right amplification and noise vector is remained, and reduce signal vector, avoids sorting operation and noise to characteristic value
The problem that the division in space causes Eigenvalue Bounds fuzzy.Device is corresponding by each feature vector and each feature vector
Weight constructs second signal matrix, specifically, referring in Fig. 7 namely step S60 according to each described eigenvector and each
The corresponding weight of described eigenvector constructs second signal matrix
Step S61 determines the corresponding characteristic value of each described eigenvector；
Step S62 determines the corresponding coefficient of each characteristic value, and using the coefficient as the multiple of the characteristic value
Side is to obtain the corresponding numerical value of each described eigenvector；
Step S63 determines the inverse of each numerical value, and according to each building second signal matrix reciprocal.
Each feature vector has corresponding characteristic value, and each characteristic value is followed successively by λ1,λ2,…λN, characteristic value have pair
Coefficient c is answered, coefficient c is for adjusting weight.C is obtained the corresponding number of each feature vector by device
Value, then by the reciprocal to construct second signal matrix of each numerical value of determination, inverse is feature vector weight.Second signal matrix
The matrix that all feature vectors weighting of as the first covariance matrix is constituted, second signal matrixSecond signal matrix U is converted to obtain
Step S70 determines space spectral function according to the second signal matrix, and carries out wave to the space spectral function and reach
The spectral peak quantity is determined as the quantity of signal source to determine spectral peak quantity by the estimation in direction, wherein the signal source
Quantity is K；
Device can determine space spectral function, space spectral function by second signal matrix
The estimation of direction of arrival is being carried out to space spectral function, to obtain spectral peak quantity, spectral peak quantity can be identified as signal source
Quantity, the quantity of signal source are K, and H is also determined as K.
Step S80 is executed described to the bay behind the quantity setting signal source according to determining signal source
The output signal in the received K measured signal source of M array element sample when the sky of n times snap, to construct the M array elements
The step of to the first signal matrix of K signal source.
Device is adjusted to quantity K after determining the quantity of signal source, by quantity H, to carry out the letter of K signal source sending
Number common cycle.Namely device executes step S10- step S40.
In technical solution provided in this embodiment, device is to M array element of bay received H measured signal member
Output signal carry out n times snap sky when sample, to construct M array element to the second covariance matrix of each signal source, and
The multiple feature vectors of decomposition of characteristic value are carried out to the second covariance matrix, then determine the corresponding weight of each feature vector, with
Matrix is constructed according to each feature vector and corresponding weight, so that space spectral function is obtained according to matrix, further according to space
Spectral function carries out obtaining spectral peak quantity when the estimation of direction of arrival, and spectral peak quantity can be the quantity of signal source；Due to ideal shape
Under state, spectral peak quantity is identical as the quantity of signal source, it is possible thereby to accurately determine the setting number of signal source according to spectral peak quantity
Amount, and then the period of things has accurately been determined.
Referring to Fig. 8, Fig. 8 is the 3rd embodiment of the determination method of the common cycle of the multiple signals of the present invention, is based on first
Embodiment, the determination method of the common cycle of the multiple signal, further includes:
Step S90 carries out N to the output signal in received multiple measured signal sources of M array element of the bay
It is sampled when the sky of secondary snap, to determine third covariance matrix, and Eigenvalues Decomposition is carried out to the third covariance matrix and is obtained
To multiple characteristic values；
In the present embodiment, device determines the quantity of signal source by explanation dynamics.L signal source, device can be first set
It is sampled when carrying out the sky of n times snap to the output signal of the received L signal source of M array element of bay again, so that it is determined that
Third covariance matrix, the determination of third covariance matrix and the first covariance matrix determine that unanimously this is no longer going to repeat them.
After determining third covariance matrix, then the decomposition for carrying out characteristic value to third covariance matrix obtains multiple features
Value, the Eigenvalues Decomposition that the specific decomposition process of the characteristic value of third covariance matrix is put to the proof referring to the first covariance.
Step S100 determines explanation dynamics, and object feature value is determined in each characteristic value, wherein Ge Gesuo
State other characteristic values that object feature value is all larger than in addition to the object feature value；
After obtaining multiple characteristic values, device determines object feature value in each characteristic value.Specifically, by each feature
Value is ranked up to obtain sequence according to sequence from big to small, takes preceding L characteristic value as object feature value in the sequence, namely
Each object feature value is all larger than other each characteristic values in addition to object feature value.Device determines explanation dynamics again, explains
Dynamics is to explain the dynamics of a things essence, explains the unit of dynamics as percentage.Explanation dynamics can be special by preceding L target
The summation of value indicative accounts for the ratio of all characteristic value summations, namely explains that dynamics characterizes as the variance contribution degree of preceding L variable, and side
Poor contribution degree can be determined by principal component thought.Specifically,
Assuming that one group of variable x1,…xp, they can be mathematically transformed into one group of new variable (variable calls ingredient)
y1,…ypSo that:
(1) each y is the linear combination of x, it may be assumed that yi=ai1 x1+ai2 x2+…+aip xp；
(2) coefficient aipQuadratic sum be 1, i.e. aiIt is unit vector；
(3)y1It is that variance is maximum in these linear combinations, y2For and y1Variance is maximum in incoherent linear combination,
So go down, generally, yjFor with y1,y2Deng the maximum linear combination of all incoherent and variance.
Preceding several variables (principal component) have usually contained most information due to its variance maximum, can be used to describe
Originally the phenomenon that explained with p variable.In actual treatment, aiAs x1,…xpCorrelation matrix ith feature
Value λiCorresponding feature vector, yiVariance contribution degree are as follows:
It should be noted that the dynamics of explanation can be determined by technical staff namely technical staff inputs explanation strengths in a device
Degree.
Step S110 judges the quantity of the object feature value according to the explanation dynamics and each object feature value
Whether preset condition is met；
After determining explanation dynamics and each object feature value, device is according to the dynamics of explanation and each object feature value
It determines whether the quantity of object feature value meets preset condition, specifically, the dynamics of explanation can be determined by variance contribution degree, explains
Dynamics can lead to the sum of corresponding variance contribution degree of preceding L characteristic value and determine, that is,According to this public affairs
Formula, the first summation namely the first summation calculated between all characteristic values is the sum of all characteristic values, and it is special to calculate each target
The second summation between value indicative, the second summation is the sum of each object feature value, and is calculated between the second summation and the first summation
Ratio, then judge whether ratio is greater than or equal to explanation dynamics, if ratio is greater than explanation dynamics, and ratio and explain dynamics
Between difference be less than preset threshold, then can determine that the quantity of object feature value meets preset condition.
Step S120, when the quantity of the object feature value meets preset condition, by the quantity of the object feature value
It is determined as the quantity of signal source, wherein the quantity of the signal source is K；
Meet preset condition in the quantity of object feature value, then it can be using the quantity of object feature value as the number of signal source
L is also changed to K so that the quantity according to signal source resets signal source by amount.
Step S130 is executed described to the bay behind the quantity setting signal source according to determining signal source
The output signal in received K measured signal source of M array element sampled when the sky of n times snap, to construct M battle arrays
The step of member is to the first signal matrix of K signal source.
Device is adjusted to quantity K after determining the quantity of signal source, by quantity L, to carry out the letter of K signal source sending
Number common cycle.Namely device executes step S10- step S40.
In technical solution provided in this embodiment, M array element received L measured signal source of the device to bay
Output signal carry out n times snap sky when sample, to construct M array element to the third covariance matrix of each signal source, and
The decomposition that third carries out characteristic value to covariance matrix obtains multiple characteristic values, then determines explanation dynamics and in each characteristic value
Middle determining object feature value finally judges whether the quantity of object feature value is full according to the dynamics of explanation and each object feature value
The quantity of object feature value is then determined as the quantity of signal source, and then accurately determination is got over if meeting by sufficient preset condition
The period of object.
In one embodiment, device if ratio is less than explanation dynamics, then shows selected by device after determining ratio
Object feature value quantity it is very few so that ratio is unable to reach explanation dynamics.In this regard, device is again true in each characteristic value
Set the goal characteristic value, and the quantity of object feature value is greater than the last quantity namely current goal for determining object feature value again
Quantity L ' the > L of characteristic value.The quantity of the object feature value redefined can be according to the difference between explanation dynamics and ratio
It determines, explains that the difference between dynamics and ratio is bigger, the quantity for redefining object feature value is bigger.
After redefining object feature value, then regain ratio, if ratio again less than the dynamics of explanation, then again
Object feature value is determined, until the quantity of object feature value meets preset condition.
In technical solution provided in this embodiment, device redefines target after determining that ratio is less than explanation dynamics
Characteristic value, the quantity of the object feature value redefined is greater than the quantity of the last object feature value determined, to carry out again
Whether the quantity of object feature value meets the judgement of preset condition, until determining the target for meeting the object feature value of preset condition
The intelligence degree of quantity, device is higher.
In one embodiment, it when ratio is greater than explanation dynamics, needs to further calculate between ratio and explanation dynamics
Difference, then judge whether the difference is less than or equal to preset threshold, if difference is greater than preset threshold, then it is assumed that ratio mistake
Greatly, at this time, it may be necessary to determine that the quantity of object feature value, the quantity for redefining object feature value are small in each characteristic value again
In the quantity for the object feature value that the last time determines, and then judge whether the ratio redefined is greater than explanation dynamics again, directly
It is greater than explanation dynamics to the ratio redefined, and the difference between the ratio redefined and explanation dynamics is less than or equal in advance
If threshold value, at this point, the quantity of the corresponding object feature value of the ratio redefined is destination number, which is signal
The setting quantity in source.The quantity of the object feature value redefined can be determining according to the difference between ratio and explanation dynamics,
Difference between ratio and explanation dynamics is bigger, and the quantity for redefining object feature value is smaller.
In technical solution provided in this embodiment, device is determining that it is default that the difference between ratio and explanation dynamics is greater than
Threshold value, ratio is excessive, needs to redefine object feature value, and the quantity of the object feature value redefined is less than last determine
Object feature value quantity, until determine meet preset condition object feature value destination number, the intelligent journey of device
It spends higher.
The present invention also provides a kind of common cycle determining device of multiple signals, the common cycle devices of the multiple signal
Equipped with aerial array and signal acquisition module, the aerial array is equipped with M array element, and each array element receives signal source hair
The signal sent, the signal acquisition module are used to acquire array element and receive the signal that signal source is sent；The multiple signal it is common
Cycle determining device further includes memory, processor and is stored in the memory and what can be run on the processor be total to
Synperiodic determining program, the signal acquisition module are connected to the processor, and the determination program of the common cycle is located
Reason device executes multiple signals described in embodiment as above common cycle when executing determines each step of method.
The present invention also provides a kind of readable storage medium storing program for executing, the readable storage medium storing program for executing is stored with the determination journey of common cycle
Sequence, the determination program of the common cycle realize the common cycle of multiple signals described in embodiment as above when being executed by processor
Determine each step of method.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the device that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or device.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone,
Computer, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of common cycle of multiple signals determines method, which is characterized in that the common cycle determination side of the multiple signal
Method is applied to the terminal equipped with aerial array, and the aerial array is equipped with M array element, and each array element receives measured signal
Source send signal, the common cycle of the multiple signal determine method the following steps are included:
It is adopted when carrying out the sky of n times snap to the output signal in the M array element received K measured signal source of the bay
Sample, to construct the M array elements to first signal matrix in K measured signal source；
It determines corresponding first covariance matrix of the signal matrix, and characteristic value is carried out to first covariance matrix and is divided
Solution is to determine noise vector and signal vector；
The solution function of frequency parameter is determined according to the noise vector and the signal vector；
The frequency parameter is scanned for according to the solution function, to obtain the signal of the K measured signal source transmittings
Common frequency parameter, wherein the common frequency parameter be multiple signals common cycle.
2. the common cycle of multiple signals as described in claim 1 determines method, which is characterized in that described to first association
Variance matrix carries out the decomposition of characteristic value to include: the step of determining noise vector and signal vector
First covariance matrix is converted to obtain covariance matrix to be decomposed according to preset noise hypothesis；
The decomposition that characteristic value is carried out to the covariance matrix to be decomposed, obtains the characteristic value of multiple descending sequences；
According to each characteristic value and the corresponding sequence serial number of each characteristic value determine signal vector and noise to
Amount.
3. the common cycle of multiple signals as claimed in claim 2 determines method, which is characterized in that described according to each described
The step of characteristic value and the corresponding sequence serial number of each characteristic value determine signal vector and noise vector include:
According to the sequence serial number of each characteristic value, K object feature value is determined, wherein the K object feature values are big
In other each characteristic values for removing the object feature value；
Using the corresponding feature vector of the described object feature value of K as signal vector, and will it is each described in other characteristic values correspondence
Feature vector as noise vector.
4. the common cycle of multiple signals as described in claim 1 determines method, which is characterized in that described according to the noise
Vector determines that the step of solution function of frequency parameter includes: with the signal vector
Determine corresponding first matrix of each noise vector and corresponding second matrix of each signal vector；
The function that second matrix and first matrix multiple are zero is determined, to find out the solution function of frequency parameter.
5. the common cycle of multiple signals as described in claim 1 determines method, which is characterized in that described to the antenna array
The M array element received K measured signal source of member sample when the sky of n times snap, with construct a array elements of M it is a to K to
Survey signal source the first signal matrix the step of include:
Determine the optical path difference and phase difference of the adjacent received each signal of array element；
Induction of other each array elements to each measured signal source is determined by reference point of the target array element of the aerial array
The corresponding function of signal；
The output signal of the array element sampled when determining n times sky according to the optical path difference, the phase difference and the function is corresponding
Objective function；
The corresponding objective function of output signal of the array element sampled when according to n times sky, it is to be measured to K to construct the M array elements
First signal matrix of signal source.
6. the common cycle of multiple signals as claimed in claim 5 determines method, which is characterized in that described according to the light path
Poor, the described phase difference and the function determine the step of output signal of the array element sampled when n times sky corresponding objective function
Include:
The function is rewritten as to the function of plural form according to Euler's formula；
The optical path difference and the phase difference are substituted into the function of plural form, to determine the output signal sampled when n times sky
Corresponding objective function.
7. the common cycle of multiple signals as claimed in any one of claims 1 to 6 determines method, which is characterized in that the multiple
The common cycle of signal determines method, further includes:
It is sampled when carrying out the sky of n times snap to the output signal of the received multiple signal sources of M array element of the bay, with
It determines the second covariance matrix, and Eigenvalues Decomposition is carried out to second covariance matrix and obtains multiple feature vectors；
Determine the corresponding weight of each described eigenvector, and according to each described eigenvector and each described eigenvector
Corresponding weight constructs second signal matrix；
Determine space spectral function according to the second signal matrix, and to the space spectral function carry out the estimation of direction of arrival with
It determines spectral peak quantity, the spectral peak quantity is determined as to the quantity of signal source, wherein the quantity of the signal source is K；
Behind the quantity setting signal source according to determining signal source, connecing for the M array element to the bay is executed
The output signal in K measured signal source of receipts sample when the sky of n times snap, to construct the M array elements to K signal source
The first signal matrix the step of.
8. the common cycle of multiple signals as claimed in any one of claims 1 to 6 determines method, which is characterized in that the multiple
The common cycle of signal determines method, further includes:
When carrying out the sky of n times snap to the output signal in received multiple measured signal sources of M array element of the bay
Sampling to determine third covariance matrix, and carries out Eigenvalues Decomposition to the third covariance matrix and obtains multiple characteristic values；
It determines explanation dynamics, and determines object feature value in each characteristic value, wherein each object feature value is equal
Greater than other characteristic values in addition to the object feature value；
According to the explanation dynamics and each object feature value judge the object feature value quantity whether meet it is default
Condition；
When the quantity of the object feature value meets preset condition, the quantity of the object feature value is determined as signal source
Quantity, wherein the quantity of the signal source is K；
Behind the quantity setting signal source according to determining signal source, connecing for the M array element to the bay is executed
The output signal in K measured signal source of receipts sample when the sky of n times snap, to construct the M array elements to K signal source
The first signal matrix the step of.
9. a kind of common cycle determining device of multiple signals, which is characterized in that the common cycle device of the multiple signal is set
There are aerial array and signal acquisition module, the aerial array is equipped with M array element, and each array element receives signal source and sends
Signal, the signal acquisition module be used for acquire array element receive signal source send signal；The common week of the multiple signal
Phase determining device further includes memory, processor and is stored in the memory and can run on the processor common
The determination program in period, the signal acquisition module are connected to the processor, and the determination program of the common cycle is processed
The common cycle of the described in any item multiple signals of claim 1-8 such as is executed when device executes determines each step of method.
10. a kind of readable storage medium storing program for executing, which is characterized in that the readable storage medium storing program for executing is stored with the determination program of common cycle,
Being total to such as claim 1-8 described in any item multiple signals is realized when the determination program of the common cycle is executed by processor
With each step of cycle determination method.
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