CN108241160A - A kind of satellite navigation interference source space spectral peak method of estimation - Google Patents
A kind of satellite navigation interference source space spectral peak method of estimation Download PDFInfo
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- CN108241160A CN108241160A CN201711467634.8A CN201711467634A CN108241160A CN 108241160 A CN108241160 A CN 108241160A CN 201711467634 A CN201711467634 A CN 201711467634A CN 108241160 A CN108241160 A CN 108241160A
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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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/21—Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service
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Abstract
The present invention provides a kind of satellite navigation interference source space spectral peak methods of estimation, using the noise subspace feature vector of the reception data covariance matrix after normalization as adaptive nulling weight vector, interference components in the docking collection of letters number are inhibited, save the power component corresponding to interference characteristic vector, so that only comprising noise signal component in the signal power exported after weighting, weak powered interferer component and the high power interference that can be docked simultaneously in the collection of letters number are effectively inhibited, and are easy to Project Realization.
Description
Technical field
It is a kind of to pressing type satellite navigation interference source spacing spectrum peak the invention belongs to the anti-interference field of satellite navigation
Two-dimensional search realizes algorithm.
Background technology
Satellite Navigation Technique is extensive because the features such as its round-the-clock, wide covering and low cost shows powerful competitiveness
Use.But the signal level that satellite-signal reaches earth surface is about -130dBmw, so faint signal is actually being led
Being highly prone to external interference in boat application environment causes satellite navigation receiver can not work normally.Therefore, to interference signal
Orientation perceives and AF panel becomes the important leverage of Satellite Navigation Technique application.
In the signal processing of anti-interference antenna of satellite navigation system, interference suppression algorithm is at entire digital signal
The part of core in reason.Interference suppression algorithm can be divided into adaptive nulling class algorithm and optimal digital multiple beam class algorithm two is big
Class.
The Typical Representative of adaptive nulling class algorithm is power inversion (Power Inversion, PI) algorithm, and the algorithm is not
The prior informations such as satellite position information are needed, null depth is automatically adjusted with the intensity of jamming power, had for high reject signal
Preferable inhibition, thus be widely used in the engineer application in the anti-interference field of satellite navigation.But it lacks
Point is poor for the inhibition of weak jamming signal so that it is in weak jamming environment or exists simultaneously strong jamming and weak jamming
Application in environment is restricted.
Optimal digital multiple beam algorithm uses digital multiplex technology, while forms multiple optimal numbers in visual-field space and connect
Receive wave beam.Typical optimal digital beam is the undistorted response response of minimum variance (Minimum Variance Distorted
Response, MVDR) wave beam.The main lobe of each optimal digital beam is directed toward an aeronautical satellite, while adaptively interfering
Direction forms null.Optimal digital multiple beam algorithm can be with the noise of lifting system output signal while to AF panel
Than.But the algorithm needs the prior informations such as satellite position, array posture to assist, algorithm structure is complicated, calculation amount is larger, it is difficult to
It is used widely in engineer application.
Invention content
For overcome the deficiencies in the prior art, the present invention provides a kind of satellite navigation interference source space spectral peak method of estimation,
It is docked using the noise subspace feature vector of the reception data covariance matrix after normalization as adaptive nulling weight vector
Interference components in the collection of letters number are inhibited, and the weak powered interferer component and high power that can be docked simultaneously in the collection of letters number are done
It disturbs and is effectively inhibited, be easy to Project Realization.
The technical solution adopted by the present invention to solve the technical problems includes the following steps：
The first step, the estimated value Rx of covariance matrix is calculated by the array received data x of NUM snap, and NUM is more than
2Z, Z are the array number of array；Feature decomposition is done to the estimated value Rx of data covariance matrix, obtains characteristic value and corresponding spy
Sign vector；Minimal eigenvalue is sought into derivative action, and corresponding feature vector is multiplied, and obtains weight vector and carries out normalizing
Change；Overlap-add procedure is weighted to array received data x using normalized weight vector and is exported, completes the dry of the docking collection of letters number
Disturb inhibition processing；
Size is divided into L × K sub- matrix-blocks by second step for the spatio-spectral matrix P of M × N-dimensional, and wherein M and N are respectively
The elevation angle of beam scanning and azimuthal number, and L≤M, K≤N,
Third walks, and searches for each submatrix all peak values in the block and records the corresponding line index number of each peak value and row rope
Quotation marks；The minimum value in all peak values is searched for as basic thresholding Pa；
4th step, by M × N number of space spectrum compared with Pa, the rejecting more than Pa, the numerical value less than Pa adds up, and records
Spectrum accumulated value and cumulative points are finally averaged, as noise power mean value in spatial spectrum by cumulative points；
5th step, 2.5 times of threshold values as noise peak of noise power mean value using in spatial spectrum, output are more than thresholding
Azimuth and elevation information corresponding to the peak value of value.
The beneficial effects of the invention are as follows：For Power-inversion algorithm, weight vector calculates as follows：
Wherein, wPIFor the weight vector that Power-inversion algorithm is calculated, dimension size is M × 1；To receive data association side
Poor Matrix Estimation valueInverse matrix, dimension size be M × M；a0=[1,0 ..., 0]TFor constrained vector, dimension size for M ×
1；K is interference source number, and K ＜ M；δ2For system noise power；wjamAnd wnoiseIt is divided into interference signal and noise signal two parts
Corresponding weight vector, dimension size are M × 1.
When the external world is there are (power of interference signal be much larger than noise power) during high reject signal, interference signal to
Characteristic value will be much larger than the corresponding characteristic value of noise signal, i.e.,
It, will corresponding to the power component of interference characteristic vector in best initial weights by formula (2) it is found that with the increase of jamming power
It is less and less.Therefore, power inversion method can be upwardly formed deeper null in strong jamming side, and antijamming capability is stronger.Conversely,
If during the power of interference signal smaller (being slightly larger than noise signal), the power component of interference characteristic vector is corresponded in best initial weights
(first item on the right side of second equal sign in formula (1)) will be slightly less than the weight vector corresponding to noise characteristic component (second in formula (1)
Section 2 on the right side of equal sign), the null of formation shoals, and antijamming capability is poor.And the weight vector w obtained using the present inventionoptIt saves
Corresponding to the power component of interference characteristic vector so that, can be with only comprising noise signal component in the signal power exported after weighting
High reject signal and weak jamming signal are effectively inhibited simultaneously.
Description of the drawings
Fig. 1 is the computational methods flow chart of array beams weighted value of the present invention.
Specific embodiment
The present invention is further described with reference to the accompanying drawings and examples, and the present invention includes but are not limited to following implementations
Example.
The first step：The calculation process of array beams weighted value is as shown in Figure 1, array received data x by NUM snap
The estimated value Rx, NUM for calculating covariance matrix are more than 2Z, and Z is the array number of array；To the estimated value Rx of data covariance matrix
Feature decomposition is done, obtains characteristic value and corresponding feature vector；Minimal eigenvalue is asked into derivative action, and corresponding spy
Multiplication of vectors is levied, weight vector is obtained and is normalized；Using normalized weight vector to the array received data x of step 1 into
Row weighted overlap-add procedure simultaneously exports.So far, the AF panel processing of the docking collection of letters number is completed.
Second step：Size is divided into L × K sub- matrix-blocks for the spatio-spectral matrix P of M × N-dimensional, wherein M and N are respectively
The elevation angle of beam scanning and azimuthal number, and L≤M, K≤N.
Third walks：It searches for each submatrix all peak values in the block and records the corresponding line index number of each peak value and row rope
Quotation marks.
4th step：Minimum value in all peak values that search third walks.
5th step：Calculate noise power mean value in spatial spectrum.
Using the minimum peak that the 4th step obtains as basic thresholding Pa, by M × N number of space spectrum compared with Pa, more than Pa's
It rejects, the numerical value less than Pa adds up, and records cumulative points, finally spectrum accumulated value and cumulative points is averaged, as space
Noise power mean value in spectrum.
6th step：Calculate the threshold value of noise peak.
2.5 times of threshold values as noise peak of noise power mean value using in spatial spectrum.
7th step：Output is more than the azimuth corresponding to the peak value of threshold value and elevation information.
The present invention is suitable for GPS, BDS and GLONASS satellite navigation system AF panel is handled.With 4 unit B D2-B3 frequencies
Point anti-interference antenna illustrates specific embodiment of the invention for resisting two broadband interferences.
Step 1：
Step 1.1：4 yuan of half-wavelengths are calculated to structure the formation the estimated value of square array received data covariance matrixData are adopted
Sample number of snapshots N=256, is calculatedIt is the Hermit matrixes that dimension is 4 × 4, calculating process is as follows：
1.0e-03*[0.2974+0.0000i 0.2216+0.0269i -0.0447+0.0964i -0.1555+
0.2025i
0.2216-0.0269i 0.3018+0.0000i 0.0873-0.0149i -0.0470+0.0984i
-0.0447-0.0964i 0.0873+0.0149i 0.2957+0.0000i 0.2166+0.0269i
-0.1555-0.2025i -0.0470-0.0984i 0.2166-0.0269i 0.2948+0.0000i]
Step 1.2：Feature decomposition operation is carried out to the estimated value for receiving data covariance matrix using Jacobi algorithms, is obtained
Obtain eigenvalue λm(m=1,2 ..., 4) and corresponding feature vector qm(m=1,2 ..., 4).
λ1=0.0007679, λ2=0.0003879, λ3=0.0000340, λ4=0.0000000000243
q1=[- 0.5901+0.0000i, -0.2477+0.0000i, 0.4286+0.0000i, -0.6378-0.0000i],
q2=[- 0.3846+0.1202i, -0.5660-0.3295i, -0.4840-0.2850i, 0.2505-0.1747i],
q3=[0.1025+0.3715i, -0.0183-0.6635i, 0.0014+0.5636i, -0.0868+0.2927i],
q4=[0.3252+0.4849i, 0.1175-0.2354i, 0.2165-0.3691i, -0.2011-0.6052i]
Step 1.3：The minimal eigenvalue λ that step 2 is calculatedminSeek derivative action and corresponding feature to
Amount, which is multiplied, obtains not normalized weight vectorCalculating process is as follows：
Step 1.4：To the not normalized weight vector obtained in step 3It is normalized, obtains normalized
Weight vector wopt, shown in calculating process such as formula (3).
Step 1.5：Using the weight vector w being calculated in step 4optTo the intermediate frequency digital plural number received in the first step
Signal x (n) is weighted overlap-add procedure and exports, shown in calculating process such as formula (4).
So far, the AF panel for completing to receive 4 unit B D2-B3 frequency points signal is handled.
Step 2：36*10 dimension space spectrum matrixs are divided into the submatrix block of 12*10.
Step 3：It searches for each submatrix all peak values in the block and records the corresponding line index number of each peak value and row rope
Quotation marks are：1->(7.5008e+09,5,8), 2->(3.4478e+08,23,3), 3->(9.3945e+08,26,4).
4th step：Minimum value in all peak values that search third walks.
Minimum peak is 3.4478e+08.
5th step：Calculating noise power mean value in spatial spectrum is：1.1527e+08.
6th step：Calculate the threshold value of noise peak.
2.5 times of threshold values as noise peak of noise power mean value is 2.8818e+08 using in spatial spectrum.
7th step：Output is more than the azimuth corresponding to the peak value of threshold value and elevation information.(5,8), (23,3), (26,
4), because being the space by 360 ° of azimuth and 90 ° of 36*10 being divided into of pitch angle, angle is all since 0 °, therefore, corresponding
Angle information be：(40 °, 70 °), (220 °, 20 °), (250 °, 30 °).
Claims (1)
1. a kind of satellite navigation interference source space spectral peak method of estimation, it is characterised in that include the following steps：
The first step, the estimated value Rx, NUM that covariance matrix is calculated by the array received data x of NUM snap are more than 2Z, and Z is
The array number of array；Feature decomposition is done to the estimated value Rx of data covariance matrix, obtains characteristic value and corresponding feature vector；
Minimal eigenvalue is sought into derivative action, and corresponding feature vector is multiplied, and obtains weight vector and is normalized；Using
Normalized weight vector is weighted overlap-add procedure to array received data x and exports, and completes the AF panel of the docking collection of letters number
Processing；
Size is divided into L × K sub- matrix-blocks by second step for the spatio-spectral matrix P of M × N-dimensional, and wherein M and N are respectively wave beam
The elevation angle of scanning and azimuthal number, and L≤M, K≤N,
Third walks, and searches for each submatrix all peak values in the block and records the corresponding line index number of each peak value and column index
Number；The minimum value in all peak values is searched for as basic thresholding Pa；
4th step, by M × N number of space spectrum compared with Pa, the rejecting more than Pa, the numerical value less than Pa adds up, and records cumulative
Spectrum accumulated value and cumulative points are finally averaged, as noise power mean value in spatial spectrum by points；
5th step, 2.5 times of threshold values as noise peak of noise power mean value using in spatial spectrum, output is more than threshold value
Azimuth and elevation information corresponding to peak value.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20000077127A (en) * | 1999-05-03 | 2000-12-26 | 루센트 테크놀러지스 인크 | System and method for controlling the selectivity of a holographic memory system |
| CN101487888A (en) * | 2009-02-23 | 2009-07-22 | 重庆大学 | Spacing spectrum peak search method |
| CN102013911A (en) * | 2010-12-02 | 2011-04-13 | 哈尔滨工程大学 | Broadband signal direction of arrival (DOA) estimation method based on threshold detection |
| CN103490784A (en) * | 2013-09-30 | 2014-01-01 | 中国电子科技集团公司第二十研究所 | Two-channel satellite navigation anti-interference A/D chip |
| CN103630910A (en) * | 2013-12-13 | 2014-03-12 | 武汉大学 | Anti-interference method of GNSS (global navigation satellite system) receiver equipment |
| CN105204006A (en) * | 2015-10-19 | 2015-12-30 | 电子科技大学 | Beam forming method based on subspace interference-plus-noise covariance matrix reconstruction |
| CN106066468A (en) * | 2016-05-25 | 2016-11-02 | 哈尔滨工程大学 | A kind of based on acoustic pressure, the vector array port/starboard discrimination method of vibration velocity Mutual spectrum |
| CN106338713A (en) * | 2016-09-27 | 2017-01-18 | 哈尔滨工程大学 | Vector array target port and starboard discrimination method based on beam nulling weight |
| CN106680837A (en) * | 2016-12-14 | 2017-05-17 | 中国电子科技集团公司第二十研究所 | Interference suppression algorithm for satellite navigation |
-
2017
- 2017-12-29 CN CN201711467634.8A patent/CN108241160A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20000077127A (en) * | 1999-05-03 | 2000-12-26 | 루센트 테크놀러지스 인크 | System and method for controlling the selectivity of a holographic memory system |
| CN101487888A (en) * | 2009-02-23 | 2009-07-22 | 重庆大学 | Spacing spectrum peak search method |
| CN102013911A (en) * | 2010-12-02 | 2011-04-13 | 哈尔滨工程大学 | Broadband signal direction of arrival (DOA) estimation method based on threshold detection |
| CN103490784A (en) * | 2013-09-30 | 2014-01-01 | 中国电子科技集团公司第二十研究所 | Two-channel satellite navigation anti-interference A/D chip |
| CN103630910A (en) * | 2013-12-13 | 2014-03-12 | 武汉大学 | Anti-interference method of GNSS (global navigation satellite system) receiver equipment |
| CN105204006A (en) * | 2015-10-19 | 2015-12-30 | 电子科技大学 | Beam forming method based on subspace interference-plus-noise covariance matrix reconstruction |
| CN106066468A (en) * | 2016-05-25 | 2016-11-02 | 哈尔滨工程大学 | A kind of based on acoustic pressure, the vector array port/starboard discrimination method of vibration velocity Mutual spectrum |
| CN106338713A (en) * | 2016-09-27 | 2017-01-18 | 哈尔滨工程大学 | Vector array target port and starboard discrimination method based on beam nulling weight |
| CN106680837A (en) * | 2016-12-14 | 2017-05-17 | 中国电子科技集团公司第二十研究所 | Interference suppression algorithm for satellite navigation |
Non-Patent Citations (1)
| Title |
|---|
| 曾浩等: "快速子空间谱峰搜索方法", 《计算机应用》 * |
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Application publication date: 20180703 |