CN116430302A - Low-complexity direction finding system for self-adaptive wide and narrow-band signals - Google Patents

Low-complexity direction finding system for self-adaptive wide and narrow-band signals Download PDF

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CN116430302A
CN116430302A CN202310260443.3A CN202310260443A CN116430302A CN 116430302 A CN116430302 A CN 116430302A CN 202310260443 A CN202310260443 A CN 202310260443A CN 116430302 A CN116430302 A CN 116430302A
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signal
signals
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covariance matrix
received
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马雅楠
范广腾
曹璐
田世伟
赵鑫
黄昊
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National Defense Technology Innovation Institute PLA Academy of Military Science
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/14—Systems for determining direction or deviation from predetermined direction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/04—Details
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/04—Details
    • G01S3/12—Means for determining sense of direction, e.g. by combining signals from directional antenna or goniometer search coil with those from non-directional antenna
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a low-complexity direction finding method and a system for a self-adaptive wide and narrow-band signal, wherein the method comprises the following steps: receiving signals sent by a signal source by utilizing a plurality of antennas; signal sampling is carried out on the received signal; distinguishing the sampled signals to determine a wideband signal and a narrowband signal; performing down-conversion processing on the signal to obtain a baseband signal, and performing decimation filtering processing on the baseband signal; calibrating the filtered signals by using pre-stored antenna amplitude phase calibration parameters; calculating a covariance matrix of the signal according to the calibrated signal; extracting eigenvalues and eigenvectors of the covariance matrix; and constructing a signal subspace and a noise subspace according to the eigenvalues and the eigenvectors, and estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace. The invention can realize automatic sorting, transmission and direction finding of wide and narrow band signals; meanwhile, the filter is used for extracting and filtering, so that the complexity of estimating the direction finding of the spatial spectrum can be further reduced, and the direction finding cost is reduced.

Description

Low-complexity direction finding system for self-adaptive wide and narrow-band signals
Technical Field
The invention relates to the technical field of signal processing, in particular to a low-complexity direction finding method and system for a self-adaptive wide and narrow-band signal.
Background
As the wireless technology is continuously developed, the contemporary electronic warfare environment tends to observe the direction changes of scene change, multiple signal types, changeable signal modulation modes and processing frequency bandwidth. Therefore, the electronic reconnaissance device is required to be capable of processing the broadband signal and the narrowband signal which arrive simultaneously within the monitoring bandwidth, and has high processing efficiency, so that the electronic reconnaissance device can rapidly conduct direction finding positioning on the enemy electronic device.
The direction-finding system is one of key components in the electronic reconnaissance equipment, and the traditional direction-finding system is generally designed for narrowband signals or broadband signals, and when the broadband signals and the narrowband signals exist at the same time, the traditional direction-finding system cannot sort the signals well and cannot adapt to the direction-finding of the broadband signals and the narrowband signals. In addition, the traditional direction-finding system directly adopts a classical spatial spectrum estimation direction-finding algorithm to process a received signal, so that the complexity is high, the running speed is low, and the real requirement of quickly mastering a target situation in a battlefield environment can not be met.
Disclosure of Invention
In order to solve part or all of the technical problems in the prior art, the invention provides a low-complexity direction finding method and a system for a self-adaptive wide and narrow-band signal.
The technical scheme of the invention is as follows:
in a first aspect, a low complexity direction finding method for an adaptive wide and narrow band signal is provided, including:
receiving signals sent by a signal source by utilizing a plurality of antennas, wherein the antennas are arranged in a uniform linear array mode, and the space between adjacent antennas is half wavelength;
signal sampling is carried out on the received signals of the antenna at a preset sampling rate;
distinguishing the sampled signals to determine a wideband signal and a narrowband signal;
performing down-conversion processing on the signal to obtain a baseband signal, and performing decimation filtering processing on the baseband signal;
calibrating the filtered signals by using pre-stored antenna amplitude phase calibration parameters;
if the signal is a broadband signal, performing fast Fourier transform processing on the calibrated signal to decompose the broadband signal into a plurality of narrowband components in a frequency domain, and calculating a covariance matrix of the signal according to the signal after the fast Fourier transform processing; if the signal is a narrow-band signal, calculating a covariance matrix of the signal according to the calibrated signal;
extracting eigenvalues and eigenvectors of the covariance matrix;
and constructing a signal subspace and a noise subspace according to the eigenvalues and the eigenvectors, and estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace.
In some possible implementations, the wideband signal and the narrowband signal are distinguished according to a ratio of a bandwidth of the signal to a carrier frequency.
In some possible implementations, a signal is a narrowband signal if its bandwidth to carrier frequency ratio is below 10%, otherwise a wideband signal.
In some possible implementations, for a narrowband signal, the covariance matrix of the received signal is calculated using the following formula:
Figure BDA0004131030960000021
for wideband signals, the covariance matrix of the received signal is calculated using the following formula:
Figure BDA0004131030960000022
wherein,,
Figure BDA0004131030960000023
represents the covariance matrix of the received signal, L represents the snapshot number, X (t) represents the received signal at time t,
Figure BDA0004131030960000024
indicating that the received signal is at f j Covariance matrix of frequency point, N represents frequency domain snapshot number, X n (f j ) The signal representing the nth snapshot is at f j Fourier transform of frequency points.
In some possible implementations, estimating the azimuth angle of the received signal from the signal subspace and the noise subspace includes:
calculating a pseudo-spectrum function of the MUSIC algorithm according to the signal subspace and the noise subspace;
and taking the search angle corresponding to the minimum value obtained by the MUSIC algorithm pseudo spectrum function as the azimuth angle of the received signal.
In some possible implementations, the MUSIC algorithm pseudo-spectral function is calculated for the narrowband signal using the following formula:
Figure BDA0004131030960000025
for wideband signals, the pseudo-spectral function of the MUSIC algorithm is calculated by using the following formula:
Figure BDA0004131030960000026
wherein P (θ) search ) Representing the search angle θ search Corresponding MUSIC algorithm pseudo-spectral function, a (θ search ) Representing the search angle θ search Space steering vectors of corresponding linear arrays, E N Representation ofNoise matrix, a (f j ,θ search ) Represented at f j Frequency point theta search Space steering vector of angular linear array E N (f j ) Represented at f j Noise matrix of frequency points.
In a second aspect, there is also provided a low complexity direction finding system for adaptive wide and narrow band signals, comprising:
the antennas are arranged in a uniform linear array mode, and the space between the adjacent antennas is half wavelength and is used for receiving signals sent by external signal sources;
the sampling module is respectively connected with the plurality of antennas and the wide and narrow signal sorting module, and is used for sampling signals of the antenna at a preset sampling rate and sending the signals to the wide and narrow signal sorting module;
the wide-narrow signal sorting module is connected with the down-conversion and filtering module and is used for distinguishing the received signals to determine a wide-band signal and a narrow-band signal and sending the distinguished wide-band signal or narrow-band signal to the down-conversion and filtering module;
the down-conversion and filtering module is connected with the calibration module and is used for performing down-conversion processing on the received signals to obtain baseband signals, performing extraction and filtering processing on the baseband signals and sending the processed signals to the calibration module;
the calibration module is respectively connected with the FFT processing module and the covariance matrix generation module, and is used for calibrating the received signals by utilizing the pre-stored antenna amplitude phase calibration parameters, transmitting the calibrated received signals corresponding to the broadband signals to the FFT module, and transmitting the calibrated received signals corresponding to the narrowband signals to the covariance matrix generation module;
the FFT module is connected with the covariance matrix generation module and is used for carrying out fast Fourier transform processing on the received signal so as to decompose the received signal into a plurality of narrowband components on a frequency domain and sending the processed signal to the covariance matrix generation module;
the covariance matrix generation module is connected with the eigenvalue decomposition module and is used for calculating a covariance matrix of the received signal;
the characteristic value decomposition module is connected with the spectrum peak search module and is used for extracting characteristic values and characteristic vectors of the covariance matrix;
the spectrum peak searching module is used for constructing a signal subspace and a noise subspace according to the eigenvalue and the eigenvector of the covariance matrix, and estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace.
In some possible implementations, the down-conversion and filtering module includes:
the multiplier comprises two multipliers, wherein the input ends of the two multipliers are connected and used as the input ends of the down-conversion and filtering module;
the direct digital frequency synthesizer is respectively connected with the two multipliers and is used for generating discrete signals of cos (2 pi ft) and sin (2 pi ft) under a preset sampling rate, and the discrete signals are respectively input into the two multipliers so as to multiply the discrete signals with a received signal to obtain a baseband signal; wherein f represents the center frequency of the received signal, and t represents the time length;
the filter comprises two filters, the output end of each multiplier is connected with one filter, and the filter is used for carrying out extraction and filtering processing on the baseband signals output by the multipliers so as to filter useless frequency components which cannot be used for direction finding and complete aliasing-free extraction on the signals.
In some possible implementations, the filter is a CIC filter.
In some possible implementations, the covariance matrix generation module employs a multiply accumulator.
The technical scheme of the invention has the main advantages that:
according to the low-complexity direction finding method and system for the self-adaptive wide and narrow-band signals, the wide and narrow-band signals can be automatically sorted, transmitted and direction-found by configuring the bandwidth, frequency points and other parameter information of the signals; meanwhile, after digital down conversion is carried out on the received signals, extraction and filtering processing is carried out by using a filter, so that the complexity of space spectrum estimation direction finding can be further reduced, and the direction finding cost is reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and without limitation to the invention. In the drawings:
FIG. 1 is a flow chart of a low complexity direction finding method for adaptive wide and narrow band signals according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a low complexity direction-finding system for adaptive wide and narrow band signals according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a down-conversion and filtering module according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a covariance matrix generation module according to an embodiment of the invention;
FIG. 5 is a schematic diagram of another embodiment of a low complexity direction-finding system for adaptive wide and narrow band signals;
FIG. 6 is a schematic diagram showing the comparison of the estimated angle of a single frequency signal with the real angle without noise according to example 1 of the present invention;
FIG. 7 is a schematic diagram showing the comparison of the estimated angle and the true angle of a single frequency signal under the noise condition of 10dB according to the present invention in example 1;
FIG. 8 is a schematic diagram showing the comparison of the estimated angle and the true angle of a narrowband signal without noise according to example 2 of the present invention;
FIG. 9 is a schematic diagram showing the comparison of the estimated angle and the true angle of a narrowband signal under 10dB noise condition according to example 2 of the present invention;
FIG. 10 is a schematic diagram showing the comparison of the estimated angle and the true angle of a narrowband signal without noise according to example 3 of the present invention;
fig. 11 is a schematic diagram showing a comparison of an estimated angle and a true angle of a narrowband signal under 10dB noise condition according to example 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to specific embodiments of the present invention and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The following describes in detail the technical scheme provided by the embodiment of the invention with reference to the accompanying drawings.
Referring to fig. 1, in a first aspect, an embodiment of the present invention provides a low complexity direction finding method for an adaptive wide and narrow band signal, the method comprising the steps of S1-S8:
step S1, signals sent by a signal source are received by utilizing a plurality of antennas, wherein the plurality of antennas are arranged in a uniform linear array mode, and the distance between the adjacent antennas is half a wavelength.
In an embodiment of the present invention, in order to achieve accurate direction-finding and positioning of external signal sources, the number of antennas is not less than 4, and the space between adjacent antennas is half a wavelength. Specifically, the spacing between adjacent antennas is calculated using the following formula:
Figure BDA0004131030960000051
where d represents the spacing between adjacent antennas, λ represents the signal wavelength, c represents the speed of light, and f represents the signal carrier frequency. If the signal carrier frequency changes within a certain range, the signal carrier frequency with the highest value is taken to calculate the distance.
Further, the diameter of the antenna satisfies the following formula so that the distance between the antenna and the signal source satisfies the far field condition:
Figure BDA0004131030960000052
wherein,,D 0 represents the diameter of the antenna, lambda represents the signal wavelength, L 0 Indicating the distance of the antenna from the signal source.
And S2, performing signal sampling on the received signal of the antenna at a preset sampling rate.
In an embodiment of the present invention, the sampling rate is specifically set according to the actual situation.
Step S3, distinguishing the sampled signals to determine a wideband signal and a narrowband signal.
In one embodiment of the invention, the wideband signal and the narrowband signal are distinguished according to the ratio of the bandwidth of the signal to the carrier frequency.
Specifically, if the ratio of the bandwidth of the signal to the carrier frequency is below 10%, the received signal is determined to be a narrowband signal, and if the ratio of the bandwidth of the signal to the carrier frequency exceeds 10%, the received signal is determined to be a wideband signal.
And S4, performing down-conversion processing on the signal to obtain a baseband signal, and performing decimation filtering processing on the baseband signal.
Specifically, after the differentiation of the signals is completed, the signals are subjected to down-conversion processing to acquire baseband signals.
In an embodiment of the present invention, the purpose of the down-conversion processing of the signal is to change the received signal with a certain frequency offset into a baseband signal for subsequent filtering processing.
Specifically, setting: the number of the antennas is M, the M antennas are arranged in a straight line at equal intervals to form a uniform linear array, and K far-field signals s are arranged in the space k (t), k=1, …, K is incident on the antenna array, the incoming wave azimuth angle of the ith signal source reaching the antenna array is theta i Azimuth indicates the one-dimensional normal angle to the antenna array.
Based on the above setting, with the first antenna element of the antenna array as the reference point, the spatial steering vector of the uniform linear array is expressed as:
Figure BDA0004131030960000061
where d represents the spacing between adjacent antennas, λ represents the signal wavelength, and e represents a natural constant.
Further, setting: after down-conversion processing is performed on the signal, the baseband signal received by the mth antenna at the time of the t sampling is x m (t) then signal x m (t) satisfies:
Figure BDA0004131030960000062
wherein n is m And (t) represents a noise vector received by the mth antenna.
Further, in an embodiment of the present invention, the purpose of the decimating and filtering process is to filter out unwanted frequency components that cannot be used for direction finding, to preserve the useful frequency components used for direction finding, and to perform aliasing-free decimating on the signal.
In one embodiment of the invention, a CIC filter is used to filter the baseband signal obtained by the down-conversion process.
And S5, calibrating the filtered signals by using the pre-stored antenna amplitude phase calibration parameters.
In one embodiment of the present invention, the antenna amplitude phase calibration parameters include: azimuth calibration parameters and elevation calibration parameters.
Specifically, in one embodiment of the present invention, the azimuth calibration parameters are obtained by:
placing a signal source at a position of 0 DEG and 0 DEG of pitching relative to the antenna, and calculating an antenna calibration parameter according to data when the incoming wave direction is 0 DEG; changing azimuth angle into-45 degrees to 45 degrees, collecting antenna receiving data, utilizing antenna calibration parameters to compensate azimuth phase delay of the receiving data, observing whether amplitude phase of the receiving data of the antenna is consistent, if so, the frequency point antenna calibration parameters are accurate, if not, indicating that the antenna calibration parameters are greatly influenced by azimuth angle, storing all angle calibration parameters, changing frequency points, and repeating the process.
Further, in an embodiment of the present invention, the pitch calibration parameters are obtained by:
and (3) placing a signal source at a position of 0 DEG relative to the azimuth of the antenna, collecting antenna receiving data, compensating the receiving data according to antenna calibration parameters of 0 DEG, setting the pitching angle to be-45 DEG to 45 DEG after the compensation is completed, collecting the antenna receiving data, observing whether the amplitude phase of the antenna receiving data is consistent, if so, accurately calibrating the frequency point calibration parameters, if not, indicating that the antenna calibration parameters are greatly influenced by the pitching angle, correcting and storing the antenna receiving data under different azimuth angles and pitching angles, changing the frequency point, and repeating the process.
Further, taking four antennas as an example, the incoming wave direction of the signal source is set to be 0 °, and the received data of the four antennas are expressed as:
cha1＝vol0+jvol1
cha2＝vol2+jvol3
cha3＝vol4+jvol5
cha4＝vol6+jvol7
wherein, vol0, vol2, vol4 and vol6 are four-channel I-channel signals, and vol1, vol3, vol5 and vol7 are four-channel Q-channel signals.
At this time, four antenna calibration parameters were calculated using the following formula:
cal1＝1./cha1
cal2＝1./cha2
cal3＝1./cha3
cal4＝1./cha4
where cal1, cal2, cal3, and cal4 are four antenna calibration parameters.
By calibrating the signals by using the antenna amplitude phase calibration parameters obtained in the mode, the accuracy of a covariance matrix obtained subsequently can be improved, and the accuracy of a direction finding result is further improved.
S6, if the signal is a broadband signal, performing fast Fourier transform processing on the calibrated signal to decompose the broadband signal into a plurality of narrowband components in a frequency domain, and calculating a covariance matrix of the signal according to the signal after the fast Fourier transform processing; if the signal is a narrowband signal, calculating a covariance matrix of the signal according to the calibrated signal.
In order to achieve direction finding of the wideband signal, in an embodiment of the present invention, a Fast Fourier Transform (FFT) process is performed on the wideband signal, that is, decomposition is performed on the wideband signal in a frequency domain range to decompose the wideband signal into a plurality of narrowband components, and then each narrowband component is processed by referring to a processing manner of the narrowband signal.
Further, for the above baseband signal x m The expression of (t), expressed as a matrix form, can be obtained:
X(t)＝A(θ)S(t)+N(t)
wherein X (t) = [ X ] 1 (t),x 2 (t),...,x M (t)] T A (θ) represents an array direction matrix, a (θ) = [ a (θ) 1 ),a(θ 2 ),…,a(θ K )] M×K S (t) represents a signal vector matrix, S (t) = [ S ] 1 (t),s 2 (t),…,s K (t)] T N (t) represents a noise matrix, N (t) = [ N ] 1 (t),n 2 (t),…,n M (t)] T 。
Since the direction of the wideband signal is related to frequency, if the received signal is a wideband signal, the data received by the antenna array in the time domain cannot be represented as a matrix vector expression, and thus is described by using a frequency domain model. Specifically, fourier transforming the time domain received signal of the antenna array can be expressed as:
Figure BDA0004131030960000081
wherein X is m (f j ) Indicating that the signal received by the mth antenna is at f j Fourier transform of frequency point, a m (f j ,θ k ) Indicating that the mth antenna is at f j Frequency point theta k Angle steering vector s k (f j ) Indicating that the kth signal is at f j Fourier transform of frequency point, N m (f j ) Indicating that the noise received by the mth antenna is at f j And the Fourier transform of the frequency points, J, represents the number of narrowband components obtained by decomposing the broadband signal in the frequency domain range.
Further, the above formula is expressed in a matrix form, and can be obtained:
X(f j )＝A(f j ,θ)S(f j )+N(f j ),j＝1,2,…,J
wherein X (f) j )＝[X 1 (f j ),X 2 (f j ),...,X M (f j )] T ，A(f j ,θ)＝[a(f j ,θ 1 ),…,a(f j ,θ K )] T ，a(f j ,θ)＝[a 1 (f j ,θ 1 ),…,a M (f j ,θ k )] T ，S(f j )＝[s 1 (f j ),…,s K (f j )] T ，N(f j )＝[N 1 (f j ),…,N M (f j )] T 。
Further, in an embodiment of the present invention, for a narrowband signal, a covariance matrix of a received signal is calculated using the following formula:
Figure BDA0004131030960000091
for wideband signals, the covariance matrix of the received signal is calculated using the following formula:
Figure BDA0004131030960000092
wherein,,
Figure BDA0004131030960000093
represents the covariance matrix of the received signal, L represents the snapshot number, X (t) represents the received signal at time t,
Figure BDA0004131030960000094
indicating that the received signal is at f j Covariance matrix of frequency point, N represents frequency domain snapshot number, X n (f j ) The signal representing the nth snapshot is at f j Fourier transform of frequency points.
And S7, extracting eigenvalues and eigenvectors of the covariance matrix.
In an embodiment of the present invention, a Jacobi algorithm is used to perform feature decomposition on the covariance matrix to obtain a feature value and a feature vector of the covariance matrix. The basic idea of Jacobi algorithm is: a series of opposite matrix matrixes are generated by carrying out a series of plane rotation transformation on the covariance matrix, two elements in the matrix become zero after each rotation transformation, after multiple iterations, the matrix tends to be a diagonal matrix, the main diagonal element of the diagonal matrix is the eigenvalue of the covariance matrix, and the column vector of the rotation matrix used for transformation is the eigenvector.
And S8, constructing a signal subspace and a noise subspace according to the eigenvalues and the eigenvectors, and estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace.
Since signal direction finding exploits the mutual orthogonality of the signal subspace and the noise subspace, i.e. the noise subspace is also orthogonal to the steering vector of the signal subspace. Therefore, in an embodiment of the present invention, a signal subspace and a noise subspace are constructed according to the eigenvalue and the eigenvector, and then the azimuth angle of the received signal is estimated according to the signal subspace and the noise subspace.
Specifically, the signal subspace is formed by eigenvectors corresponding to signals in a covariance matrix of the signals received by the antenna array.
The noise subspace is constructed in the following manner:
the eigenvalues are arranged according to descending order, and based on the eigenvalues arranged in order, eigenvectors corresponding to M-K eigenvalues with smaller values are taken to form a noise subspace.
Further, in an embodiment of the present invention, estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace further includes:
calculating a pseudo-spectrum function of the MUSIC algorithm according to the signal subspace and the noise subspace;
and taking the search angle corresponding to the minimum value obtained by the MUSIC algorithm pseudo spectrum function as the azimuth angle of the received signal.
In an embodiment of the present invention, in order to avoid division operation, so that the method can be directly implemented in an FPGA, for a narrowband signal, a pseudo-spectral function of a MUSIC algorithm is calculated by using the following formula:
Figure BDA0004131030960000101
for wideband signals, the pseudo-spectral function of the MUSIC algorithm is calculated by using the following formula:
Figure BDA0004131030960000102
wherein P (θ) search ) Representing the search angle θ search Corresponding MUSIC algorithm pseudo-spectral function, a (θ search ) Representing the search angle θ search Space steering vectors of corresponding linear arrays, E N Represents a noise matrix, a (f j ,θ search ) Represented at f j Frequency point theta search Space steering vector of angular linear array E N (f j ) Represented at f j Noise matrix of frequency points.
In an embodiment of the present invention, the reciprocal of the pseudo spectrum function of the MUSIC algorithm forms a spatial spectrum, and the angle corresponding to the largest spatial spectrum function value is used as the azimuth angle of the received signal, i.e. the angle corresponding to the smallest pseudo spectrum function value of the MUSIC algorithm is used as the azimuth angle of the received signal.
If there are multiple receiving signals, the angle corresponding to the largest multiple spatial spectrum function values is taken as the azimuth angle of the multiple receiving signals, namely, the angle corresponding to the smallest multiple MUSIC algorithm pseudo spectrum function values is taken as the azimuth angle of the multiple receiving signals.
Referring to fig. 2, in a second aspect, an embodiment of the present invention further provides a low complexity direction finding system for an adaptive wide and narrow band signal, the system comprising:
a plurality of antennas 101, wherein the plurality of antennas 101 are arranged in a uniform linear array, and the space between adjacent antennas 101 is half a wavelength for receiving signals sent by external signal sources;
the sampling module 102 is respectively connected with the plurality of antennas 101 and the wide and narrow signal sorting module 103, and is used for sampling signals of the antenna 101 at a preset sampling rate and sending the signals to the wide and narrow signal sorting module 103;
the wide-narrow signal sorting module 103 is connected with the down-conversion and filtering module 104 and is used for distinguishing the received signals to determine a wide-band signal and a narrow-band signal and sending the distinguished wide-band signal or narrow-band signal to the down-conversion and filtering module 104;
the down-conversion and filtering module 104 is connected with the calibration module 105, and is used for performing down-conversion processing on the received signal to obtain a baseband signal, performing decimation filtering processing on the baseband signal, and sending the processed signal to the calibration module 105;
the calibration module 105 is respectively connected with the FFT processing module 106 and the covariance matrix generation module 107, and is configured to calibrate the received signal by using the antenna amplitude phase calibration parameter stored in advance, send the calibrated received signal corresponding to the wideband signal to the FFT module 106, and send the calibrated received signal corresponding to the narrowband signal to the covariance matrix generation module 107;
an FFT module 106, connected to the covariance matrix generation module 107, for performing a fast fourier transform process on the received signal to decompose the received signal into a plurality of narrowband components in the frequency domain, and transmitting the processed signal to the covariance matrix generation module 107;
a covariance matrix generation module 107, connected to the eigenvalue decomposition module 108, for calculating a covariance matrix of the received signal;
the eigenvalue decomposition module 108 is connected with the spectrum peak search module 109 and is used for extracting eigenvalues and eigenvectors of the covariance matrix;
the spectral peak searching module 109 is configured to construct a signal subspace and a noise subspace according to the eigenvalue and the eigenvector of the covariance matrix, and estimate an azimuth angle of the received signal according to the signal subspace and the noise subspace.
In an embodiment of the present invention, each module is a device corresponding to the steps of the method, and the specific working principle of each module and the beneficial effects thereof may refer to the above.
Further, in one embodiment of the present invention, sampling module 102 employs a CX8242 sampling chip.
Wherein the sampling module 102 is connected to the antenna 101 through a radio frequency channel.
Further, referring to fig. 3, in an embodiment of the present invention, the down-conversion and filtering module 104 includes:
the multiplier comprises two multipliers, wherein the input ends of the two multipliers are connected and used as the input ends of the down-conversion and filtering module;
the direct digital frequency synthesizer is respectively connected with the two multipliers and is used for generating discrete signals of cos (2 pi ft) and sin (2 pi ft) under a preset sampling rate, and the discrete signals are respectively input into the two multipliers so as to multiply the discrete signals with a received signal to obtain a baseband signal; wherein f represents the center frequency of the received signal, and t represents the time length;
the filter comprises two filters, the output end of each multiplier is connected with a filter, and the filter is used for carrying out extraction and filtering processing on the baseband signals output by the multipliers so as to filter useless frequency components which cannot be used for direction finding and complete aliasing-free extraction on the signals.
Specifically, assume that: the center frequency of the received signal is f, and the sampling rate is f s . In signal down conversion, cos (2pi ft) and sin (2pi ft) are generated at sampling rate f by configuring direct digital frequency synthesizer s The discrete signal is multiplied by the received signal to realize spectrum shifting so as to convert the received signal with a certain frequency offset into a baseband signal.
Wherein the frequency control word of the direct digital frequency synthesizer is configured to:
Figure BDA0004131030960000121
λ represents the data bit width of the phase accumulation value in the direct digital frequency synthesizer and round (·) represents the rounding operation.
In an embodiment of the invention, the filter adopts the CIC filter, compared with the FIR filter, the hardware complexity of the CIC filter is extremely low, only the adder is consumed, and complex multiplier resources are not occupied.
Further, in an embodiment of the present invention, a CIC filter structure with 5-stage cascade connection is used, and the stop band attenuation can reach 67.3dB. Wherein the frequency response of the CIC filter is configured to:
Figure BDA0004131030960000122
d represents the decimation factor of the CIC filter, M 0 Represents a differential delay factor, M 0 Taken as 1 or 2, L represents the number of cascaded stages of CIC filters, l=5.
Since the passband of the CIC filter is not flat and its attenuation increases with increasing cascade number, in conventional signal processing architecture, a cascade compensation filter is typically used after the CIC filter to ensure flatness of the passband frequency response. In an embodiment of the invention, the output of the CIC filter is directly used for subsequent direction finding processing, the distortion brought by the CIC filter to the signal is adapted through a direction finding algorithm, and the signal compensation is carried out without a compensation filter, so that the hardware resource expenditure of the system can be obviously reduced.
Further, in an embodiment of the present invention, the FFT module 106 adopts a parallel iterative processing structure, that is, one FFT operation unit repeatedly invokes processing. Specifically, as the number of the butterfly knots of each stage of FFT operation unit is the same, all the butterfly knots of one stage can be combined to form an FFT module, and when each stage of computation is carried out, the FFT algorithm is sequentially invoked.
Further, in an embodiment of the present invention, the covariance matrix generation module 107 is configured to calculate a covariance matrix of the received signal, which can obtain the covariance matrix according to the data matrix, specifically, calculate a matrix to be multiplied by its own transpose, so as to obtain a symmetric covariance matrix.
To this end, referring to fig. 4, in an embodiment of the present invention, the covariance matrix generation module 107 employs a multiply accumulator, comprising: the input end of the adder is respectively connected with the output end of the multiplier and the output end of the adder.
Further, referring to fig. 5, in an embodiment of the present invention, the system further includes: serdes interface 110, serdes interface 110 is connected to the output of sampling module 102 and the input of Wide/narrow Signal sorting module 103, respectively, for transmitting signals.
By setting the Serdes interface, the transmission speed of signals can be improved, and the communication cost is reduced.
Further, in an embodiment of the present invention, when the system performs transmission of a wideband signal and a narrowband signal, the wideband signal and the narrowband signal are transmitted by separate paths.
By setting independent paths for the broadband signal and the narrowband signal, the influence of different broadband and narrowband signals on the direction-finding performance of the system can be directly compared and analyzed.
According to the low-complexity direction finding method and system for the self-adaptive wide and narrow-band signals, which are provided by the embodiment of the invention, the wide and narrow-band signals can be automatically sorted, transmitted and direction-found by configuring the bandwidth, frequency points and other parameter information of the signals; meanwhile, after digital down conversion is carried out on the received signals, extraction and filtering processing is carried out by using a filter, so that the complexity of space spectrum estimation direction finding can be further reduced, and the direction finding cost is reduced.
The following describes, with reference to specific embodiments, the beneficial effects of the low complexity direction finding method and system for adaptive wide and narrow band signals provided in an embodiment of the present invention:
example 1: single frequency signal direction finding performance analysis
In this example, a uniform linear array is formed using 4 antennas, the antenna positions being in units of half the source wavelength. Further, matlab is adopted to generate a transmitting signal, the carrier frequency of the linear frequency modulation signal is set to be 3GHz, the carrier frequency after down-conversion is set to be 5MHz, the sampling rate is 180MHz, and the interval between 4 antennas is 0.05m.
Based on the set parameters, the direction finding method and system with low complexity for the self-adaptive wide and narrow band signal provided by the embodiment of the invention are used for carrying out direction finding under the noise-free condition and the 10dB noise condition respectively, so that the direction finding results shown in fig. 6 and 7 are obtained.
It can be seen that the azimuth angle of the single-frequency signal can be accurately estimated by using the low-complexity direction finding method and system for the adaptive wide-narrow-band signal according to the embodiment of the invention.
Example 2: narrow-band signal direction finding performance analysis
In this example, a uniform linear array is formed using 4 antennas, the antenna positions being in units of half the source wavelength. Further, matlab is adopted to generate a transmitting signal, the carrier frequency of the linear frequency modulation signal is set to be 3GHz, the carrier frequency after down-conversion is set to be 10MHz, the bandwidth is set to be 1MHz, the sampling rate is 180MHz, and the interval between 4 antennas is set to be 0.05m.
Based on the set parameters, the direction finding method and system with low complexity for the self-adaptive wide and narrow band signal provided by the embodiment of the invention are used for carrying out direction finding under the noise-free condition and the 10dB noise condition respectively, so that the direction finding results shown in fig. 8 and 9 are obtained.
It can be seen that the azimuth angle of the narrowband signal can be accurately estimated by using the low-complexity direction finding method and system for the adaptive wideband signal according to the embodiment of the invention.
Example 3: broadband signal direction finding performance analysis
In this example, a uniform linear array is formed using 4 antennas, the antenna positions being in units of half the source wavelength. Further, matlab is adopted to generate a transmitting signal, the carrier frequency of the linear frequency modulation signal is set to be 3GHz, the carrier frequency after down-conversion is set to be 10MHz, the bandwidth is set to be 5MHz, the sampling rate is set to be 180MHz, and the interval between 4 antennas is set to be 0.05m.
Based on the set parameters, the direction finding method and system with low complexity for the adaptive wide and narrow band signal provided by the embodiment of the invention are used for carrying out direction finding under the noise-free condition and the 10dB noise condition respectively, so that the direction finding results shown in fig. 10 and 11 are obtained.
It can be seen that the azimuth angle of the wideband signal can be accurately estimated by using the low-complexity direction finding method and system for the adaptive wideband signal according to the embodiment of the invention.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. In this context, "front", "rear", "left", "right", "upper" and "lower" are referred to with respect to the placement state shown in the drawings.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting thereof; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A low complexity direction finding method for an adaptive wide and narrow band signal, comprising:
receiving signals sent by a signal source by utilizing a plurality of antennas, wherein the antennas are arranged in a uniform linear array mode, and the space between adjacent antennas is half wavelength;
signal sampling is carried out on the received signals of the antenna at a preset sampling rate;
distinguishing the sampled signals to determine a wideband signal and a narrowband signal;
performing down-conversion processing on the signal to obtain a baseband signal, and performing decimation filtering processing on the baseband signal;
calibrating the filtered signals by using pre-stored antenna amplitude phase calibration parameters;
if the signal is a broadband signal, performing fast Fourier transform processing on the calibrated signal to decompose the broadband signal into a plurality of narrowband components in a frequency domain, and calculating a covariance matrix of the signal according to the signal after the fast Fourier transform processing; if the signal is a narrow-band signal, calculating a covariance matrix of the signal according to the calibrated signal;
extracting eigenvalues and eigenvectors of the covariance matrix;
and constructing a signal subspace and a noise subspace according to the eigenvalues and the eigenvectors, and estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace.
2. The method of claim 1, wherein the wideband signal and the narrowband signal are distinguished according to a ratio of a bandwidth of the signal to a carrier frequency.
3. The method of claim 2, wherein the signal is a narrowband signal if the ratio of bandwidth to carrier frequency is below 10%, and is otherwise a wideband signal.
4. The method of claim 1, wherein the covariance matrix of the received signal is calculated for the narrowband signal using the following formula:
Figure FDA0004131030950000011
for wideband signals, the covariance matrix of the received signal is calculated using the following formula:
Figure FDA0004131030950000012
wherein,,
Figure FDA0004131030950000013
represents the covariance matrix of the received signal, L represents the snapshot number, X (t) represents the received signal at time t,
Figure FDA0004131030950000014
indicating that the received signal is at f j Covariance matrix of frequency point, N represents frequency domain snapshot number, X n (f j ) The signal representing the nth snapshot is at f j Fourier transform of frequency points.
5. The method of low complexity direction finding for adaptive wide and narrow band signals according to claim 1, wherein estimating the azimuth angle of the received signal from the signal subspace and the noise subspace comprises:
calculating a pseudo-spectrum function of the MUSIC algorithm according to the signal subspace and the noise subspace;
and taking the search angle corresponding to the minimum value obtained by the MUSIC algorithm pseudo spectrum function as the azimuth angle of the received signal.
6. The method of claim 5, wherein the MUSIC algorithm pseudo-spectral function is calculated for the narrowband signal using the following formula:
Figure FDA0004131030950000021
for wideband signals, the pseudo-spectral function of the MUSIC algorithm is calculated by using the following formula:
Figure FDA0004131030950000022
wherein P (θ) search ) Representing the search angle θ search Corresponding MUSIC algorithm pseudo-spectral function, a (θ search ) Representing the search angle θ search Space steering vectors of corresponding linear arrays, E N Represents a noise matrix, a (f j ,θ search ) Represented at f j Frequency point theta search Space steering vector of angular linear array E N (f j ) Represented at f j Noise matrix of frequency points.
7. A low complexity direction finding system for adaptive wide and narrow band signals, comprising:
the antennas are arranged in a uniform linear array mode, and the space between the adjacent antennas is half wavelength and is used for receiving signals sent by external signal sources;
the sampling module is respectively connected with the plurality of antennas and the wide and narrow signal sorting module, and is used for sampling signals of the antenna at a preset sampling rate and sending the signals to the wide and narrow signal sorting module;
the wide-narrow signal sorting module is connected with the down-conversion and filtering module and is used for distinguishing the received signals to determine a wide-band signal and a narrow-band signal and sending the distinguished wide-band signal or narrow-band signal to the down-conversion and filtering module;
the down-conversion and filtering module is connected with the calibration module and is used for performing down-conversion processing on the received signals to obtain baseband signals, performing extraction and filtering processing on the baseband signals and sending the processed signals to the calibration module;
the calibration module is respectively connected with the FFT processing module and the covariance matrix generation module, and is used for calibrating the received signals by utilizing the pre-stored antenna amplitude phase calibration parameters, transmitting the calibrated received signals corresponding to the broadband signals to the FFT module, and transmitting the calibrated received signals corresponding to the narrowband signals to the covariance matrix generation module;
the FFT module is connected with the covariance matrix generation module and is used for carrying out fast Fourier transform processing on the received signal so as to decompose the received signal into a plurality of narrowband components on a frequency domain and sending the processed signal to the covariance matrix generation module;
the covariance matrix generation module is connected with the eigenvalue decomposition module and is used for calculating a covariance matrix of the received signal;
the characteristic value decomposition module is connected with the spectrum peak search module and is used for extracting characteristic values and characteristic vectors of the covariance matrix;
the spectrum peak searching module is used for constructing a signal subspace and a noise subspace according to the eigenvalue and the eigenvector of the covariance matrix, and estimating the azimuth angle of the received signal according to the signal subspace and the noise subspace.
8. The low complexity direction-finding system of adaptive wide and narrow band signals according to claim 7, wherein said down-conversion and filtering module comprises:
the multiplier comprises two multipliers, wherein the input ends of the two multipliers are connected and used as the input ends of the down-conversion and filtering module;
the direct digital frequency synthesizer is respectively connected with the two multipliers and is used for generating discrete signals of cos (2 pi ft) and sin (2 pi ft) under a preset sampling rate, and the discrete signals are respectively input into the two multipliers so as to multiply the discrete signals with a received signal to obtain a baseband signal; wherein f represents the center frequency of the received signal, and t represents the time length;
the filter comprises two filters, the output end of each multiplier is connected with one filter, and the filter is used for carrying out extraction and filtering processing on the baseband signals output by the multipliers so as to filter useless frequency components which cannot be used for direction finding and complete aliasing-free extraction on the signals.
9. The low complexity direction finding system of claim 8, wherein the filter is a CIC filter.
10. The low complexity direction finding system of an adaptive wide narrowband signal according to any of claims 7-9, wherein the covariance matrix generation module employs a multiply accumulator.
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