CN1014469B - Moving target adaptive detector basing upon the max. entropy spectrum estimation - Google Patents
Moving target adaptive detector basing upon the max. entropy spectrum estimationInfo
- Publication number
- CN1014469B CN1014469B CN 89102262 CN89102262A CN1014469B CN 1014469 B CN1014469 B CN 1014469B CN 89102262 CN89102262 CN 89102262 CN 89102262 A CN89102262 A CN 89102262A CN 1014469 B CN1014469 B CN 1014469B
- Authority
- CN
- China
- Prior art keywords
- coefficient
- clutter
- matrix
- moving
- moving target
- 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.)
- Expired
Links
- 238000001228 spectrum Methods 0.000 title claims abstract description 15
- 230000003044 adaptive effect Effects 0.000 title description 4
- 238000000034 method Methods 0.000 claims abstract description 43
- 238000001514 detection method Methods 0.000 claims abstract description 27
- 238000012545 processing Methods 0.000 claims abstract description 7
- 239000011159 matrix material Substances 0.000 claims description 37
- 230000003595 spectral effect Effects 0.000 claims description 14
- 238000001914 filtration Methods 0.000 claims description 11
- 238000012937 correction Methods 0.000 claims description 7
- 238000000354 decomposition reaction Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 5
- 230000001427 coherent effect Effects 0.000 claims description 4
- 230000009467 reduction Effects 0.000 claims description 4
- 229940050561 matrix product Drugs 0.000 claims description 2
- 238000006467 substitution reaction Methods 0.000 claims description 2
- 230000006870 function Effects 0.000 abstract description 3
- 230000002401 inhibitory effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 14
- 230000005764 inhibitory process Effects 0.000 description 3
- 230000001568 sexual effect Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000004744 fabric Substances 0.000 description 2
- 238000007667 floating Methods 0.000 description 2
- VMXUWOKSQNHOCA-UKTHLTGXSA-N ranitidine Chemical compound [O-][N+](=O)\C=C(/NC)NCCSCC1=CC=C(CN(C)C)O1 VMXUWOKSQNHOCA-UKTHLTGXSA-N 0.000 description 2
- 230000001373 regressive effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 241001269238 Data Species 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000005654 stationary process Effects 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
Images
Landscapes
- Radar Systems Or Details Thereof (AREA)
Abstract
The present invention belongs to a radar signal processing and detecting technique and provides a new technique scheme and a device thereof on the basis of the self-adaptive moving target detection of maximum entropy spectrum estimation. The present invention not only can inhibit fixed clutters, but also can inhibit moving clutters (comprising more than one moving clutters or the moving clutters having a plurality of spectrum peaks), can simultaneously detect moving target signals at the time of inhibiting moving clutters, can keep constant false alarm rate in various kinds of non-Gaussian clutter amplitude distribution and can keep the functions at the time of the self movement of radars; if the present invention adopts a weight coefficient time average method, the present invention can inhibit point-shaped clutters or clutter edges.
Description
The invention belongs to Radar Signal Processing and detection technique field.
In the echo that radar receives, except useful target reflection echo, also has the echo of a large amount of irrelevant target (as atural object, wave, flying bird etc.) reflections.The irrelevant target of this class can be divided two big classes, and a class is actionless (as atural object), and another kind of then is movable (as sexual intercourse, wave, flying bird etc.), and the former Doppler shift is zero, and the latter then has Doppler shift.The echo that these irrelevant targets form is referred to as clutter usually, their amplitude is often very strong, influences the detection of radar to useful target, therefore how to suppress these clutters, improving the ability of radar to useful target detection, is one of important topic of being paid close attention to of present technique field technology personnel.Common radar moving target indicator utilizes useful target echo to have Doppler shift and ground clutter does not have these characteristics of Doppler shift and suppresses land clutter and the show events target, and apparent this moving-target indicator is the movable clutter that can not suppress the to have Doppler shift echo of clutter reflections (when also the comprising radar motion itself from).In order to address this problem, normally cascade Doppler filter group is improved the detectability of target, i.e. moving target detector behind common moving-target indicator.Its theory diagram as shown in Figure 1.1-1 is that analog/digital converter, 1-2 are that table tennis data memory, 1-3 are that zero-speed wave filter, 1-4 are that common moving-target indicator, 1-5 are that Doppler filter group, 1-6 are that to ask the width of cloth, 1-7 be that thresholding, 1-8 are that clutter map, 1-9 are regressive filters in weighting.The weak point of this moving target detector is that the filter weight coefficient is fixed, for the actual clutter that changes, particularly can't Adaptive Suppression to movable clutter, and when clutter is nongausian process, can't keep CFAR.Be developed into various types of self-adaptation moving-target indicators (or being called noise filter) at this problem those skilled in the art, wherein advanced is that United States Patent (USP) " adaptive Doppler wave filter " patent No. is US 6569685.It is a utilization Gram-Schmidt orthogonalization method, adopts decorrelation cancellation circuit clutter reduction, makes clutter output minimum value.But still there is following weak point in this invention: 1. owing to adopt orthogonalization algorithm, its operand is big, needs many with device; 2. owing to how to detect judgement when consider adopting the self-adaptation moving-target indicator, can not keep the false-alarm probability under the various situations constant; 3. owing to only considered decorrelation, and do not consider when contain useful target in the echoed signal echo, owing to the decorrelation meeting the also repressed problem of target, so the possibility of this technical application is little.
The objective of the invention is for overcoming the deficiency of above-mentioned technology existence, a kind of new method for designing is proposed, constitute a kind of new self-adaptation moving target detector, to improve radar detectability to useful target under various clutter conditions, prevent that target is by " albefaction ", remain on the CFAR characteristic under the non-gaussian clutter situation, make it have the practicality and the better ratio of performance to price.
Technical essential of the present invention is:
The present invention adopts the upper and lower triangular matrix decomposition method of the correction of Maximum Entropy Spectral Estimation to calculate each space cell noise filter weighting coefficient, reduces operand; Adopt covariance method to ask the coherent element of input data, with abundant reflection noise performance; Adopt the method for weighting coefficient storage and time, space average to calculate the actual noise filter coefficient of getting rid of target, solved the difficult problem that target and clutter were suppressed thereby can not detect target simultaneously; Adopt nonlinear detection method to remain on CFAR under the non-gaussian clutter situation; Adopt programmable method, to change the number of data points of handling, the method for weighting coefficient number and estimation coefficient.
Below method and apparatus is described in detail respectively:
One. method:
1. the upper and lower triangular matrix decomposition method of the correction of employing maximum entropy power estimation is estimated the weighting coefficient of each space cell noise filter.Because the restriction of antenna beamwidth, the target echo number that radar receives is less usually, and actual environment changes at any time, the movable clutter that becomes when suppressing, must estimate the power spectrum of clutter in real time, calculate the weighting coefficient of clutter reduction wave filter (being the self-adaptation moving-target indicator) according to clutter power spectrum, adopt maximum entropy method to be particularly suitable for the spectrum of this sequence in short-term of radar echo signal is estimated.The weighting coefficient that maximum entropy method is estimated is separating of one group of system of linear equations, it is equivalent to the finding the solution of Wei Na-Huo Fu (Wiener-Hopf) matrix equation of correction, for making system finish the high-speed real-time processing requirements, reduce used device, the present invention has adopted a kind of new fast algorithm that is called MLUD, promptly the upper and lower triangular matrix decomposition method of Xiu Zhenging is utilized the separating of method group of equations of matrix inversion to guarantee the good of estimated performance, and has been avoided direct matrix to invert in concrete calculating.Utilize every element in conjugate symmetry, centre symmetry and the recursiveness estimated matrix of matrix element, utilize Wei Nage Rider (Winograd) principle to reduce and calculate the required multiplication number of times of every element, simultaneously when asking plural solution of equations, complex matrix is transformed into real number matrix, has reduced operand; Utilize square-root method that real number matrix is resolved into upper and lower triangular matrix product and calculate solution of equations by back substitution.Eliminate extracting operation and reduced division.
2. adopt covariance method to ask the every element of correlation matrix of input data, what existing noise filter clutter correlation matrix when the calculating filter weighting coefficient adopted is autocorrelation matrix, it is abundant based on the input data, and be the hypothesis of stationary process, and the input echo data that radar receives is than short, and right and wrong stably, therefore adopts autocorrelation matrix can not fully reflect noise performance.Covariance matrix is applicable to time-limited data sequence, and data can right and wrong stably.Covariance matrix is to estimate that with least square method the unit of the relevant battle array of clutter usually realizes.
3. adopt weighting coefficient storage and time, the method of space average: realize that in order to solve clutter suppresses and unlikely this difficult problem of elimination target, the present invention has adopted weight coefficient storage and average design and method, utilization activity clutter is (as sexual intercourse, chaff etc.), its power spectrum changes characteristics slowly in certain zone and in the certain hour, at first the weight coefficient of each space cell clutter reduction wave filter is stored with the magnanimity memory, similar according to adjacent unit with the to-be-measured cell noise performance, can be used as the weight coefficient of to-be-measured cell noise filter with the weighted mean value of each coefficient of adjacent unit, because the space cell very little (being considered as individual unit usually) that target occupies, shared status is just little in average, so reduced the inhibition to target; Also adopted the average method of the same space unit different scanning cycle gained weighting coefficient to prevent that target is suppressed.
4. adopt nonlinear detection method, remain on the non-gaussian clutter interference and have good constant false alarm rate down.Because radar clutter becomes when being not only, also be non-Gauss usually, best linear matched Filtering Processing also can't keep constant false alarm rate.The present invention has adopted two kinds of non-linear detection methods, and a kind of method is to reject the method for " wild value ", promptly before matched filtering with data sorting, several data points of removal amplitude maximum, it is set is zero, remakes matching treatment; Another kind method is " soft limiting " method, and it is not merely the point of amplitude maximum to be removed after ordering finishes, but their amplitude is defined as the value of amplitude maximum in the remainder strong point, keeps original phase information, remakes matching treatment then.
5. employing programmable way is to change number of data points, the exponent number of wave filter and the method for handling of estimation coefficient.
Two. device, 2 describe the present invention in conjunction with the accompanying drawings: orthogonal double channels I, Q signal are behind 12 analog/digital converter 2-1, deposit table tennis data memory 2-2 in, two coherent cell datas are eliminated the ground clutter (also can without and lead directly to) of no Doppler shifts through common moving-target indicator 2-3, and output data (A) a tunnel is delivered to self-adaptation moving-target indicator 2-6; Another road is delivered to the plain estimator 2-4 of relevant array element and is estimated each element of clutter covariance matrix (B), find the solution the weight coefficient of estimated power spectrum again by power spectrum coefficient estimation circuit 2-5 realization covariance matrix, the coefficient that estimates (C) is sent into the filter coefficient storage, coefficient on average reaches among the target detection circuit 2-8, simultaneously the coefficient (E) of elapsed time among the 2-8 or space average is delivered to self-adaptation moving-target indicator 2-6.In non-linear detection circuitry 2-7, sort and pick " wild value " or " soft limiting " (G) through the self-adaptation filtered data of moving-target indicator 2-6 (D), send Doppler filter group 2-9 to do the correction matched filtering again.It is target or clutter edge that coupling back data (F) send target detection circuit 2-8 to differentiate, reduces false-alarm.Full machine is made controller by microprocessor, finishes various operating functions by keyboard.
Advantage of the present invention is:
1. not only can suppress fixedly ground clutter but also can inhibition activity clutter, as sexual intercourse, wave, chaff etc.;
2. can be the time or movable clutter operate as normal when a plurality of spectrums peak is arranged more than a movable clutter, promptly still can curb movable clutter in the case;
3. can in inhibition activity clutter, detect the moving target signal, and have good detection performance;
4. can when various non-gaussian clutter amplitude distribution (the actual measurement clutter is often like this), still can keep good CFAR characteristic;
5. when moving, radar itself still can keep above-mentioned functions;
6. as adopting the time averaging method of weight coefficient, can suppress point-like clutter or clutter edge.
Embodiment:
Accompanying drawing 3 is that the present invention is installed in the S-band airport control system chart that air traffic control radar constituted, 3-1 is an antenna, 3-2 is a radar head, and 3-3 is that self-adaptation moving target detector, the 3-5 that orthogonal double channels phase detector, 3-4 are based on Maximum Entropy Spectral Estimation is data handling machine.Air traffic control radar can be 797 homemade radars, can replace the common MT1 of its classics with the present invention, and air traffic control radar also can be the ASR-9 radar of U.S.'s Westinghouse Electrical Corp., replaces comparatively advanced moving target detector (MTD) with the present invention.Its input interface is the output of orthogonal double channels phase detector, and its output then can directly be added to data handling machine.
Accompanying drawing 4 is correlation matrix elements estimator block diagrams, and it comprises that data memory 4-1, parallel multiplication 4-2, fixed point-floating-point change-over circuit are tabled look-up and logical combination 4-3 and bit slice serial device 4-4.It is that 12 bit data of input are finished the product of Xi, Xj and adding, subtracting of product term respectively under the control of bit slice serial device, calculates each element in the correlation matrix
N is the input number of data points in the formula, M is the number of weighting coefficient] owing to adopt fast algorithm, finish correlation matrix elements with the shortest time and estimate, the element value that will estimate fixed point then is through tabling look-up and logic combination circuit converts floating data to, to improve computational accuracy.
Accompanying drawing 5 is power Spectral Estimation circuit block diagrams, and it comprises data memory 5-1, coefficient memory 5-2, signal processor sheet 5-3, instruction storage 5-4, reciprocal table 5-5.After relevant array element element is sent into the signal Processing sheet, finishing Matrix Solving under instruction control (comprises the plural number battle array is converted to the real number battle array, with matrix decomposition is upper and lower triangular matrix and real, the imaginary part of obtaining weight coefficient), when calculating division, utilization is tabled look-up and is directly obtained the inverse of divisor, accelerate arithmetic speed, the coefficient that calculates send memory 5-2 storage.
Accompanying drawing 7 is non-linear detection circuit block diagrams, and it comprises data memory 7-1, data sorting 7-2, selection 7-3, rejecting " wild value " 7-4, soft limiting 7-5, output memory 7-6.It with filtering the echo data of movable clutter (i.e. self-adaptation moving-target indicator filtering), earlier by the ordering of amplitude size, select then or reject maximal value (wild value), or adopt soft limiting that data are made Nonlinear Processing, the result send the output memory.
Accompanying drawing 8 is the average and target detection circuit block diagrams of coefficient storage, it comprises coefficient memory 8-1, magnanimity memory 8-2, new coefficient memory 8-3, the selector switch 8-4 that estimates, parallel multiplication 8-5, weight coefficient memory 8-6, bit slice serial device 8-7, relatively adjudicates 8-8.It with each unit estimation come out the time become weight coefficient and deposit the magnanimity memory in, make space average as required, be about to the weighted mean that coefficient adds up through multiplication around the to-be-measured cell, as the filter factor of to-be-measured cell, export through the coefficient memory; Perhaps make time average, send the magnanimity memory back to after the coefficient weighted mean of soon new coefficient of estimating and former storage, after the data after the Doppler filter group correction matched filtering are sent the judgement of comparison decision circuit, deliver to display, whole work is done sequential control by the bit slice serial device.
Description of drawings:
Accompanying drawing 1 has the moving target detector theory diagram of Doppler filter
The 1-1 analog/digital converter
The 1-2 data memory of rattling
1-3 zero-speed wave filter
The common moving-target indicator of 1-4
1-5 Doppler filter group
The width of cloth is asked in the 1-6 weighting
The 1-7 thresholding
The 1-8 clutter map
The 1-9 regressive filter
M output
The 2-1 analog/digital converter
The 2-2 data memory of rattling
The common moving-target indicator of 2-3
2-4 correlation matrix elements estimator
2-5 power spectrum coefficient estimation circuit
2-6 self-adaptation moving-target indicator
The 2-7 non-linear detection circuitry
The storage of 2-8 filter coefficient, coefficient on average reach the target detection circuit
2-9 Doppler filter group
H output
The system chart that accompanying drawing 3 the present invention are installed on the air traffic control radar to be constituted
The 3-1 antenna
The 3-2 radar head
3-3 orthogonal double channels phase detector
3-4 is based on the self-adaptation moving target detector of Maximum Entropy Spectral Estimation
The 3-5 data handling machine
Accompanying drawing 4 correlation matrix elements estimator block diagrams
The 4-1 data memory
The 4-2 parallel multiplication
4-3 fixed point-floating-point change-over circuit
4-4 bit slice serial device
A is the echo data of filtering fixed clutter
The B floating number
Accompanying drawing 5 power spectrum coefficient estimation circuit block diagrams
The 5-1 data memory
5-2 coefficient memory
5-3 signal processor sheet
The 5-4 instruction storage
The 5-5 reciprocal table
Accompanying drawing 6 self-adaptation moving-target indicator block diagrams
The 6-1 data memory
6-2 exports memory
The 6-3 parallel multiplication
The 6-4 instruction control circuit
6-5 self-adaptation variable coefficient memory
Accompanying drawing 7 non-linear detection circuitry block diagrams
The 7-1 data memory
The 7-2 data sorting
7-3 selects
7-4 rejects " wild value "
The 7-5 soft limiting
7-6 exports memory
Average and the storage circuit block diagram of accompanying drawing 8 coefficients
8-1 coefficient memory
8-2 magnanimity memory
The new coefficient memory of estimating of 8-3
The 8-4 selector switch
The 8-5 parallel multiplication
8-6 weight coefficient memory
8-7 bit slice serial device
8-8 is decision circuit relatively
E send the self-adaptation moving-target indicator
F exports from the Doppler filter group
Display is sent in the output of H court verdict
Claims (6)
1, a kind of auto-adaptive moving target detection method based on Maximum Entropy Spectral Estimation is characterized in that adopting the upper and lower triangular matrix decomposition method of the correction of Maximum Entropy Spectral Estimation to calculate each space cell noise filter weighting coefficient; Adopt covariance method to ask the coherent element of input data; Adopt the method for weighting coefficient storage and time, space average to calculate the actual noise filter coefficient of getting rid of target; Employing non-linear detection method remains on the CFAR under the non-gaussian clutter situation; Adopt that programmable method changes that deal with data is counted, weighting coefficient number and method of estimation.
2, the auto-adaptive moving target detection method of saying according to claim 1 based on Maximum Entropy Spectral Estimation, the upper and lower triangular matrix decomposition method of correction that it is characterized in that said Maximum Entropy Spectral Estimation is to utilize the characteristic of matrix, by calculating some elementary items, and these elementary items are combined into every element of matrix; Further reduce the multiplication number of times that calculates elementary item with Wei Nage Rider principle.When asking plural solution of equations, earlier complex matrix is reduced to real symmetric matrix, utilizes square-root method that real matrix is decomposed into upper and lower triangular matrix product again, calculate solution of equations by back substitution.
3, the auto-adaptive moving target detection method of saying according to claim 1 based on Maximum Entropy Spectral Estimation is characterized in that said covariance method asks the coherent element of input data, is to adopt least square method to estimate that the unit of the relevant battle array of clutter usually realizes.
4, the auto-adaptive moving target detection method of saying according to claim 1 based on Maximum Entropy Spectral Estimation, the method that it is characterized in that said weighting coefficient storage and time, space average is at first with the magnanimity memory weight coefficient of each space cell clutter reduction wave filter to be stored, the weighted mean value of each coefficient of adjacent unit can be used as the weight coefficient of to-be-measured cell according to all kinds of noise performances, the time weighted average of also available the same space unit different scanning cycle gained is used as the weight coefficient of to-be-measured cell.
5, the auto-adaptive moving target detection method of saying according to claim 1 based on Maximum Entropy Spectral Estimation, it is characterized in that said non-linear detection method can adopt the method for rejecting " wild value ", promptly before matched filter with data sorting, several data points of removal amplitude maximum, be set to zero, do matching treatment again; Can adopt the soft limiting method, promptly after ordering, be not merely the point of amplitude maximum to be removed yet, but their amplitude is defined as the value of amplitude maximum in the remainder strong point, keeps its original phase information, and then do matching treatment.
6, a kind of self-adaptation moving target detector based on Maximum Entropy Spectral Estimation, by analog/digital converter, ping, pang data memory, common moving-target indicator, the Doppler filter group constitutes, it is characterized in that adopting the plain estimator of relevant array element to estimate the every element of clutter covariance matrix, find the solution with power spectral coefficient estimator realization covariance matrix, provide the power spectrum coefficient of estimation, store by filter coefficient again, coefficient on average reaches the target detection circuit and estimates to-be-measured cell noise filter coefficient, by self-adaptation moving-target indicator filtering activity adaptively clutter, and reject the Nonlinear Processing of " wild value " and " soft limiting " by non-linear detection circuitry, remain on the CFAR under the non-gaussian clutter situation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 89102262 CN1014469B (en) | 1989-04-20 | 1989-04-20 | Moving target adaptive detector basing upon the max. entropy spectrum estimation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 89102262 CN1014469B (en) | 1989-04-20 | 1989-04-20 | Moving target adaptive detector basing upon the max. entropy spectrum estimation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN1046608A CN1046608A (en) | 1990-10-31 |
| CN1014469B true CN1014469B (en) | 1991-10-23 |
Family
ID=4854623
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 89102262 Expired CN1014469B (en) | 1989-04-20 | 1989-04-20 | Moving target adaptive detector basing upon the max. entropy spectrum estimation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN1014469B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ATE446521T1 (en) * | 2002-12-20 | 2009-11-15 | Saab Ab | ADAPTIVE GROUND DISTURBANCE SUPPRESSION |
| CN102445309A (en) * | 2011-11-09 | 2012-05-09 | 北京爱社时代科技发展有限公司 | Supersonic gas leakage detector with capability of resistance to transient environmental noise interference |
| CN107315172A (en) * | 2017-07-10 | 2017-11-03 | 中国人民解放军海军航空工程学院 | The strong maneuvering target tracking method of three dimensions based on intelligent sub-band filter |
| CN108663666B (en) * | 2018-03-27 | 2020-11-10 | 陕西长岭电子科技有限责任公司 | Multi-target detection method for latent radar in strong clutter marine environment |
| CN108957387B (en) * | 2018-05-21 | 2022-06-21 | 西安电子科技大学 | Method and system for estimating two-dimensional arrival angle of satellite signal |
| CN110568300B (en) * | 2019-06-24 | 2021-07-13 | 昆明理工大学 | Power distribution network single-phase earth fault identification method based on multi-source information |
-
1989
- 1989-04-20 CN CN 89102262 patent/CN1014469B/en not_active Expired
Also Published As
| Publication number | Publication date |
|---|---|
| CN1046608A (en) | 1990-10-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7990311B2 (en) | Adaptive clutter filter for maritime surface search radar | |
| CN109471072B (en) | FPGA-based monopulse radar two-dimensional CFAR detection method and system | |
| CN111624567B (en) | Constant false alarm detection method and device | |
| CN1653353A (en) | A noise suppression system and method for phased-array based systems | |
| CN106842194A (en) | A kind of adaptive targets detection method and device | |
| CN107229040B (en) | high-frequency radar target detection method based on sparse recovery space-time spectrum estimation | |
| CN112180341B (en) | Method for realizing selection of background self-adaptive CFAR algorithm | |
| CN1014469B (en) | Moving target adaptive detector basing upon the max. entropy spectrum estimation | |
| CN114217315A (en) | Millimeter wave radar dynamic target rapid detection method | |
| CN102222221B (en) | Target detection method based on multispectral image filtering output statistical distribution regularity | |
| JPH06148324A (en) | Method and apparatus for three-dimensional maximum acquired tracking | |
| KR102215062B1 (en) | Apparatus for processing signal of multi-mode radar for detecting unmanned aerial vehicle and method thereof | |
| CN106950546A (en) | The non-homogeneous clutter suppression method weighted again based on mahalanobis distance | |
| CN114609595A (en) | Frequency division orthogonal MIMO radar signal processing method | |
| CN104375128A (en) | Fast high maneuvering target accumulating and detecting method based on cross-correlation functions | |
| CN111948613A (en) | Ship-borne ground wave radar target detection method based on self-adaptive background area selection | |
| CN110208752A (en) | A kind of radar MTI/MTD implementation method based on GPU | |
| CN115113208A (en) | Continuous wave radar clutter cancellation method based on accurate clutter feature recognition | |
| CN107678008A (en) | A kind of plural clutter map CFAR detection method | |
| CN113534054A (en) | Improved radar target detection method based on homogeneous clutter content sharing | |
| Wang et al. | An adaptive hierarchal CFAR for optimal target detection in mixed clutter environments | |
| CN111273249A (en) | Intelligent clutter partition method based on radar false alarm preprocessing time | |
| Li et al. | A mainlobe interference suppression system based on mismatched filtering | |
| Zhang et al. | Research on knowledge-based STAP technology | |
| CN116643248B (en) | Constant false alarm detection method, storage medium and equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C06 | Publication | ||
| PB01 | Publication | ||
| C13 | Decision | ||
| GR02 | Examined patent application | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C19 | Lapse of patent right due to non-payment of the annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |