CN114609605A - Subarray echo data matching angle measurement method based on maximum likelihood - Google Patents
Subarray echo data matching angle measurement method based on maximum likelihood Download PDFInfo
- Publication number
- CN114609605A CN114609605A CN202210503914.4A CN202210503914A CN114609605A CN 114609605 A CN114609605 A CN 114609605A CN 202210503914 A CN202210503914 A CN 202210503914A CN 114609605 A CN114609605 A CN 114609605A
- Authority
- CN
- China
- Prior art keywords
- angle
- subarray
- echo data
- measurement
- dimension
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- 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
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention discloses a sub-array echo data matching angle measurement method based on maximum likelihood, which utilizes radar sub-array echo sampling data to obtain a covariance inverse matrix between channels; weighting the subarray echo data by using an inverse matrix, and extracting target information from the weighted echo data; and finally, matching the target information with the guide vector to finally obtain the angle information of the target. In order to avoid the problem of large calculation amount of engineering realization, the method is realized by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to a subarray echo data matching angle measuring method based on maximum likelihood.
Background
The array signal processing means that a group of sensors capable of sensing spatial propagation signals and transmitting in a certain form are distributed on different positions in space according to a certain sequence to form a sensor array, and the sensor array receives the spatial propagation signals, so that discrete data of spatial incident signals are obtained.
The purpose of array signal processing is to make the beam former enhance the interesting or needed useful signal and simultaneously suppress the undesired interference and noise components by performing specific processing on the incident signal received by the antenna array, so as to effectively obtain the characteristic information of the needed signal and perform performance analysis.
The adaptive beam forming is one of important contents for array signal processing, can automatically measure clutter and interference characteristics of a working environment, analyze the action mode of main interference, automatically adopt a corresponding anti-interference scheme, and can adaptively adjust working parameters along with the change of the environment to achieve certain optimal performance.
However, in phased array radars, particularly multi-function phased array radars, the array typically contains hundreds to thousands of array elements. If array element-level digital beam forming is carried out on the large array, each receiving channel comprises an amplifying device, a mixing device and an analog-to-digital conversion device, so that the system overhead is greatly increased, and meanwhile, the consistency among the channels is poor due to the excessive number of the channels. Thus, for large arrays, a subarray structure is often used, which reduces hardware cost and complexity of engineering implementation. The subarray level self-adaptive processing has the advantages of small calculated amount, high convergence speed, less hardware equipment of a receiving system and the like. Therefore, the adaptive digital beamforming research at the sub-array level is one of the key technologies of the phased array radar.
The angle measurement is a basic task of a radar system, and the radar system undertakes a guidance or precise tracking task, and the angle measurement and tracking of a target are required to be realized with higher precision. At present, the relevant literature of the angle measurement function aiming at the subarray echo data is few, and the research in the field is still in a weak link. Therefore, it is necessary to pay attention to and enhance the goniometric study on the subarray echo data.
Disclosure of Invention
In view of the problems in the prior art, the present invention aims to provide a subarray echo data matching angle measurement method based on maximum likelihood, which is implemented by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement.
The technical scheme adopted by the invention is as follows:
a subarray echo data matching angle measurement method based on maximum likelihood is disclosed, wherein radar subarray echo sampling data is utilized to obtain covariance inverse matrix between channels; weighting the subarray echo data by using an inverse matrix, and extracting target information from the weighted echo data; and finally, traversing the target information and the guide vector to obtain a correlation coefficient, and taking an angle corresponding to the maximum value of the correlation coefficient as an angle measurement result of the target.
Further, the method takes the following subarray echo data as a calculation basis:
setting the subarray echo data asDimension ofI.e. the square number of the sub-array level isThe number of pitches is。
Further, the method comprises:
Wherein the content of the first and second substances,in order to select the sub-array echo data samples,which represents the transpose of the conjugate,Iis a unit array.
Further, the weighting the sub-array echo data by the inverse matrix is as follows:
Further, the extracting target information of the weighted echo data is: set a target atA distance door, then
Further, the method comprises:
roughly measuring the angle of the target;
1) setting a search range of the angle rough measurement,
orientation dimension,For the azimuth dimension, the maximum value of the search range, the pitch dimension,Searching the maximum value of the range for the pitch dimension;searching step length for the angle rough measurement;
2) calculating a steering vector corresponding to the angle rough measurement search angle
whereinjIs a unit of an imaginary number, and is,is the carrier frequency, and is,andsearch range for traversing rough measurement angleAndthe corresponding angle is set to be the same as the angle,andis an index of the distance between the two objects,is shown asReference array elements of the individual sub-arrays areThe distance in the axial direction relative to the reference array elements of the original array,then relative toThe distance in the axial direction, d is the distance between the azimuth dimension and the pitch dimension array element;
3) calculating the correlation coefficient between the guiding vector of the angle rough measurement and the target information, and defining as
Wherein, the first and the second end of the pipe are connected with each other,weighting the subarray echo data for the inverse matrix and extracting target information;
4) taking the angle corresponding to the maximum value of the correlation coefficient of the angle rough measurement as a rough measurement angle result
Wherein the content of the first and second substances,is the angle rough measurement result, namely the angle rough measurement resultThe angle corresponding to the medium maximum value.
Still further, the method comprises: carrying out fine measurement on the angle of the target; the result of the rough measurement is used as the basis of the azimuth dimension searching range and the pitch dimension searching range, and the angle is used for accurately measuring the searching step lengthAnd performing traversal calculation as a search step length, and taking an angle corresponding to the maximum value of the angle precision measurement correlation coefficient as a precision angle measurement result.
Further, setting the angle precision measurement search range as
Angle fine measurement to obtain coarse measurement resultOn the basis of the search range of the orientation dimensionPitch dimension search range:;and searching step length for angle precision measurement.
The beneficial results are that:
the invention provides a subarray echo data matching angle measurement method based on maximum likelihood, which provides technical support for the subarray echo data angle measurement field and improves the weak current situation of the current adaptive beam forming angle measurement field; meanwhile, in order to avoid the problem of large calculation amount of engineering realization, the method is realized by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement.
Drawings
FIG. 1 is a schematic diagram of subarray division;
FIG. 2 is a screenshot of an interference sample selection interface;
FIG. 3 is a screenshot of a result interface after weighting of the subarray echo data by the inverse matrix;
FIG. 4 is a schematic diagram of the result of coarse angle measurement of the subarray echo data;
FIG. 5 is a schematic diagram of the result of the accurate angle measurement of the subarray echo data;
FIG. 6 is a graph showing the variation of the sub-array SNR with the angle measurement result of the sub-array echo data in the embodiment;
fig. 7 shows antenna patterns after the sub-array echo data are synthesized into beams.
Detailed Description
The technical solution of the present invention will be explained with reference to the accompanying drawings. The described embodiments and their description are intended to be illustrative of the invention and should not be construed as restrictive.
The embodiment discloses a subarray echo data matching angle measurement method based on maximum likelihood, radar subarray level echo sampling data are utilized, covariance inverse matrixes among channels are obtained, information of a target is extracted from weighted echo data and matched with a guide vector, and finally target angle information is obtained. In order to avoid the problem of large calculation amount of engineering realization, the method is realized by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement. The method specifically comprises the following steps:
suppose the subarray echo data isDimension ofI.e. the square number of the sub-array level isThe number of pitches is;
Step 1: selecting a subarray echo data sample with the length of the sample beingL
And 3, step 3: weighting the subarray echo data with an inverse matrix
And 4, step 4: extracting target information
And 5: coarse angle measurement of subarray echo data
Setting angular rough measurement search range
Direction dimension,For the azimuth dimension, searching the maximum value of the range, the pitch dimension,Searching the maximum value of the range for the pitch dimension;the step length is searched for the angle rough measurement and can be set to be 0.2 degrees;
calculating a steering vector corresponding to the search angle
Wherein the content of the first and second substances,is the frequency of the carrier wave,andneeds to traverse the angle rough measurement search rangeAndthe corresponding angle is set to be the same as the angle,andis a distance index, the former representing the distanceReference array elements of the individual sub-arrays areDistance in the axial direction with respect to the reference array element of the original array, the latter with respect to the reference array elementAnd d is the distance between the azimuth dimension and the pitch dimension array element.
Calculating the correlation coefficient between the guiding vector of the angle rough measurement and the target information
Taking the angle corresponding to the maximum value of the phase relation number as the angle measurement result
Step 6: accurate angle measurement of subarray echo data
Setting the search range of angle precision measurement
The searching range of the azimuth dimension is as follows:pitch dimension search range:;the angle searching step length during accurate angle measurement can be set to be 0.01 degree;
calculating a steering vector corresponding to the search angle
WhereinjIs the unit of an imaginary number,andneeds to traverse the search range of the accurate measurement angleAndroughly measuring other parameters of the corresponding angle at the same angle, wherein d is the spacing between the azimuth dimension and the pitch dimension array element;
calculating correlation coefficient between guide vector and target information
Taking the angle corresponding to the maximum value of the phase relation number as the final angle measurement result
The specific embodiment is as follows:
the azimuth is 32 array elements, the pitching is 64 array elements, and the azimuth pitching interval is half wavelength; the azimuth and elevation (8 × 16) array elements are combined into 1 sub-array, and as shown in fig. 1, the number of sub-arrays is 4 × 4= 16. 2 pressed disturbances, wherein the disturbance azimuth and the pitching angle are (2.2, -1.8) ° (2.5, 1.7) ° (1-2.8), and the disturbance ratio is 30-40 dB, as shown in Table 1; the target is at the 468 th range gate and the subarray is divided as shown in FIG. 1.
TABLE 12 interference parameter information
Number of interferences | Azimuth (°) | Angle of pitch (°) |
1 | 2.2 | -1.8 |
2 | -2.5 | 1.7 |
The results of the sub-array echo data angle measurement embodiment are embodied according to the basic operation steps:
step 1: a subarray echo data sample is selected, with a sample length of 64, see fig. 2.
And step 3: the subarray echo data is weighted with an inverse matrix and the echo results are shown in figure 3.
And 4, step 4: echo data of 16 subarrays are extracted from the echoes and are marked as tar _ info. Specific values are shown in Table 2.
TABLE 2 tar _ info values
Subarray channel number echo data
1 7.57-0.08i 9 5.72-5.36i
2 9.04+3.32i 10 12.28-1.48i
3 5.62+7.36i 11 9.84+1.79i
4 4.73+9.27i 12 6.22+5.45i
5 8.78-1.50i 13 6.90-7.27i
6 10.95+2.53i 14 5.21-1.80i
7 8.50+5.93i 15 8.12+1.26i
8 6.59+6.22i 16 9.84+2.62i
And 5: setting the azimuth dimension (-2.5: 0.2: 2.5) DEG and the pitch dimension (-2: 0.2: 2) DEG of an angle search range by coarsely measuring the angle of the subarray echo data; calculating steering vectors corresponding to the search angles, e.g., -2.5, -2) DEG for the first azimuth and pitch anglesThe dimensions are shown in Table 3.
1 0.54+0.07i 9 -0.32-0.99i
2 -0.22-1.13i 10 -1.06+0.68i
3 -0.25+0.92i 11 1.24+0.08i
4 0.60+0.22i 12 -0.07-0.79i
5 0.26-0.96i 13 -0.58+0.20i
6 -1.25+0.06i 14 0.06+0.91i
7 0.81+0.85i 15 0.53-0.77i
8 0.57-0.72i 16 -0.45-0.12i
Calculating correlation coefficient between steering vector corresponding to azimuth and pitch angle (-2.5, -2) and target information
After traversing all the azimuth angles and the pitch angles in the rough angle measurement, carrying out normalization processing, and takingThe angle corresponding to the maximum is the rough angle result, see fig. 4.
The results of the rough angle measurement were (0.5, -0.6) °.
Step 6: accurate angle measurement of subarray echo data
Setting azimuth dimension (0.3:0.01:0.7) degree and pitch dimension (-0.8:0.01: minus 0.4) degree of an angle search range;
at the moment, the corresponding angle range of the guide vector is a precise angle measurement range, the other steps are the same as the rough angle measurement, and finally the angle is obtainedThe angle corresponding to the maximum value is the result of the accurate angle measurement, and the figure is shownAnd 5, accurately measuring the angle to obtain a result of (0.47, -0.55) °, wherein the angle measurement result is consistent with a target real result (0.48, -0.55).
Fig. 6 shows that the interference is 40dB, and the angle measurement result changes with the sub-array SNR. It can be seen that when the target SNR is low, the error of the angle measurement result is large, and as the SNR increases, the angle measurement result continuously tends to and finally converges to the true value.
The technical solution of the present invention is not limited to the limitations of the above-mentioned specific embodiments, and all technical modifications made according to the technical solution of the present invention fall within the scope of the present invention.
Claims (6)
1. A subarray echo data matching angle measurement method based on maximum likelihood is characterized in that subarray echo sampling data are utilized to obtain covariance inverse matrixes among channels; weighting the subarray echo data by using an inverse matrix, and extracting target information from the weighted subarray echo data; finally, traversing the target information and the guide vector to obtain a correlation coefficient, and taking an angle corresponding to the maximum value of the correlation coefficient as a target angle measurement result;
the method takes the following subarray echo data as a calculation basis:
setting the subarray echo data asDimension ofI.e. the square number of the sub-array level isThe number of pitches is;
The method comprises the following steps: calculating covariance matrix of subarray echo dataAnd inverse covariance matrix:
3. The maximum likelihood-based subarray echo data matching angle measurement method according to claim 2, wherein the extracting target information for the weighted subarray echo data is: set a target atA distance door, then
4. The maximum likelihood-based subarray echo data matching goniometry method of claim 3, wherein the method comprises:
roughly measuring the angle of the target;
setting a search range of the angle rough measurement,
direction dimension,For the azimuth dimension, the maximum value of the search range, the pitch dimension,Searching the maximum value of the range for the pitch dimension;searching step length for the angle rough measurement;
calculating a steering vector corresponding to the angle rough measurement search angle
wherein the content of the first and second substances,jis the unit of an imaginary number,is the carrier frequency, and is,andsearch range for traversing rough measurement angleAndthe corresponding angle is set to be the same as the angle,andis an index of the distance between the two objects,is shown asReference array elements of the individual sub-arrays areThe distance in the axial direction relative to the reference array elements of the original array,is relative toThe distance in the axial direction, d is the distance between the azimuth dimension and the pitch dimension array element;
calculating the correlation coefficient between the guiding vector of the angle rough measurement and the target information, and defining as
Wherein the content of the first and second substances,weighting the subarray echo data for the inverse matrix and extracting target information;
taking the angle corresponding to the maximum value of the correlation coefficient of the angle rough measurement as a rough measurement angle result
5. A maximum-based maximum as in claim 4A method for matching and angle measurement of likelihood subarray echo data, the method comprising: carrying out fine measurement on the angle of the target; the result of the rough measurement is used as the basis of the azimuth dimension searching range and the pitch dimension searching range, and the angle is used for accurately measuring the searching step lengthAnd performing traversal calculation as a search step length, and taking an angle corresponding to the maximum value of the angle precision measurement correlation coefficient as a precision angle measurement result.
6. The maximum likelihood-based subarray echo data matching angle measurement method according to claim 5, wherein the angle precision measurement search range is set to
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210503914.4A CN114609605B (en) | 2022-05-10 | 2022-05-10 | Subarray echo data matching angle measurement method based on maximum likelihood |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210503914.4A CN114609605B (en) | 2022-05-10 | 2022-05-10 | Subarray echo data matching angle measurement method based on maximum likelihood |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114609605A true CN114609605A (en) | 2022-06-10 |
CN114609605B CN114609605B (en) | 2022-08-09 |
Family
ID=81869770
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210503914.4A Active CN114609605B (en) | 2022-05-10 | 2022-05-10 | Subarray echo data matching angle measurement method based on maximum likelihood |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114609605B (en) |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH07140221A (en) * | 1993-11-18 | 1995-06-02 | Mitsubishi Electric Corp | Angle measuring system |
WO2001050406A1 (en) * | 2000-01-06 | 2001-07-12 | Lockheed Martin Corporation | Subarray matching beamformer apparatus and method |
CN102520395A (en) * | 2011-10-18 | 2012-06-27 | 西安电子科技大学 | Clutter suppression method based on bistatic multiple-input and multiple-output radar |
CN103383452A (en) * | 2013-06-26 | 2013-11-06 | 西安电子科技大学 | Estimation method of target angle of arrival of distributed array |
CN105738891A (en) * | 2014-12-09 | 2016-07-06 | 南京理工大学 | Method for tracking weak maneuvering target angle through airborne digital array radar |
CN106855622A (en) * | 2015-12-08 | 2017-06-16 | 中国航空工业集团公司雷华电子技术研究所 | A kind of angle-measuring method of phased array at subarray level radar |
CN108459312A (en) * | 2018-03-26 | 2018-08-28 | 西安电子科技大学 | Weighting multifrequency maximum likelihood elevation estimate method based on the estimation of the composite multi-path factor |
CN108508423A (en) * | 2018-01-25 | 2018-09-07 | 西安电子科技大学 | Submatrix number based on special-shaped battle array and poor Monopulse estimation method |
CN108549059A (en) * | 2018-03-26 | 2018-09-18 | 西安电子科技大学 | A kind of low target elevation estimate method under MODEL OVER COMPLEX TOPOGRAPHY |
CN110058226A (en) * | 2019-04-17 | 2019-07-26 | 北京遥感设备研究所 | One kind being based on the chirped phased-array radar angle measuring system of positive and negative chirp rate |
CN111427022A (en) * | 2020-05-08 | 2020-07-17 | 北京理工大学重庆创新中心 | Array radar angle measurement method based on maximum likelihood estimation |
-
2022
- 2022-05-10 CN CN202210503914.4A patent/CN114609605B/en active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH07140221A (en) * | 1993-11-18 | 1995-06-02 | Mitsubishi Electric Corp | Angle measuring system |
WO2001050406A1 (en) * | 2000-01-06 | 2001-07-12 | Lockheed Martin Corporation | Subarray matching beamformer apparatus and method |
CN102520395A (en) * | 2011-10-18 | 2012-06-27 | 西安电子科技大学 | Clutter suppression method based on bistatic multiple-input and multiple-output radar |
CN103383452A (en) * | 2013-06-26 | 2013-11-06 | 西安电子科技大学 | Estimation method of target angle of arrival of distributed array |
CN105738891A (en) * | 2014-12-09 | 2016-07-06 | 南京理工大学 | Method for tracking weak maneuvering target angle through airborne digital array radar |
CN106855622A (en) * | 2015-12-08 | 2017-06-16 | 中国航空工业集团公司雷华电子技术研究所 | A kind of angle-measuring method of phased array at subarray level radar |
CN108508423A (en) * | 2018-01-25 | 2018-09-07 | 西安电子科技大学 | Submatrix number based on special-shaped battle array and poor Monopulse estimation method |
CN108459312A (en) * | 2018-03-26 | 2018-08-28 | 西安电子科技大学 | Weighting multifrequency maximum likelihood elevation estimate method based on the estimation of the composite multi-path factor |
CN108549059A (en) * | 2018-03-26 | 2018-09-18 | 西安电子科技大学 | A kind of low target elevation estimate method under MODEL OVER COMPLEX TOPOGRAPHY |
CN110058226A (en) * | 2019-04-17 | 2019-07-26 | 北京遥感设备研究所 | One kind being based on the chirped phased-array radar angle measuring system of positive and negative chirp rate |
CN111427022A (en) * | 2020-05-08 | 2020-07-17 | 北京理工大学重庆创新中心 | Array radar angle measurement method based on maximum likelihood estimation |
Non-Patent Citations (3)
Title |
---|
A.L. SWINDLEHURST等: "Maximum likelihood methods in radar array signal processing", 《PROCEEDINGS OF THE IEEE》 * |
吴佳妮等: "阵列雷达波束内双目标的极大似然角度估计方法", 《国防科技大学学报》 * |
巫书航等: "分布式数字合成阵列主辅波束优化", 《现代雷达》 * |
Also Published As
Publication number | Publication date |
---|---|
CN114609605B (en) | 2022-08-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108549059B (en) | Low-altitude target elevation angle estimation method under complex terrain condition | |
CN109212526B (en) | Distributed array target angle measurement method for high-frequency ground wave radar | |
CN108693511B (en) | Moving target angle calculation method of time division multiplexing MIMO radar | |
CN110058193B (en) | Digital multi-beam angle measurement method and system based on single receiving channel | |
CN112612005B (en) | Radar main lobe interference resistance method based on deep learning | |
CN110673086A (en) | Two-dimensional angle super-resolution method based on digital array radar | |
CN111337895B (en) | Multi-channel sea clutter space-time correlation analysis method | |
CN113189592B (en) | Vehicle-mounted millimeter wave MIMO radar angle measurement method considering amplitude mutual coupling error | |
CN108828586B (en) | Bistatic MIMO radar angle measurement optimization method based on beam domain | |
CN111352083B (en) | Automatic calibration method and device for gain of multiple receiving channels of high-frequency ground wave radar | |
CN112612010A (en) | Meter-wave radar low elevation height measurement method based on lobe splitting pretreatment | |
CN115436896A (en) | Rapid radar single-snapshot MUSIC angle measurement method | |
CN110196417B (en) | Bistatic MIMO radar angle estimation method based on emission energy concentration | |
CN109188373B (en) | Main lobe interference resisting method based on subarray blocking matrix preprocessing | |
CN114609605B (en) | Subarray echo data matching angle measurement method based on maximum likelihood | |
CN111812607A (en) | Meter-wave MIMO radar low elevation angle estimation method based on beam space | |
CN116430303A (en) | Broadband planar array multi-beam forming method and amplitude comparison angle measurement method | |
CN111368256A (en) | Single snapshot direction finding method based on uniform circular array | |
CN110231590B (en) | Array target angle measurement method based on DFT (discrete Fourier transform) | |
CN111366891B (en) | Pseudo covariance matrix-based uniform circular array single snapshot direction finding method | |
CN112255625B (en) | One-dimensional linear array direction finding method based on deep learning under two-dimensional angle dependent error | |
CN114325560A (en) | Super-resolution target direction finding method for beam scanning radar | |
CN113917389A (en) | Phased array cooperative detection system and difference beam angle estimation method | |
CN114779198B (en) | Conformal array airborne radar space-time clutter spectrum adaptive compensation and clutter suppression method | |
CN110954887B (en) | Phased array MIMO beam forming method based on spherical invariant constraint and antisymmetry |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |