CN105738883B - Method for detecting smooth generalized likelihood ratio in part uniform sea clutter background - Google Patents
Method for detecting smooth generalized likelihood ratio in part uniform sea clutter background Download PDFInfo
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- CN105738883B CN105738883B CN201610219017.5A CN201610219017A CN105738883B CN 105738883 B CN105738883 B CN 105738883B CN 201610219017 A CN201610219017 A CN 201610219017A CN 105738883 B CN105738883 B CN 105738883B
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- 238000000034 method Methods 0.000 title claims abstract description 14
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 21
- 239000011159 matrix material Substances 0.000 claims abstract description 18
- 238000009499 grossing Methods 0.000 claims description 7
- 238000010998 test method Methods 0.000 claims description 6
- 238000010606 normalization Methods 0.000 claims description 4
- 230000000750 progressive effect Effects 0.000 claims description 4
- 238000001514 detection method Methods 0.000 abstract description 19
- 238000007476 Maximum Likelihood Methods 0.000 abstract description 7
- 230000003044 adaptive effect Effects 0.000 description 5
- 238000002474 experimental method Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 210000004027 cell Anatomy 0.000 description 3
- 230000007812 deficiency Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000013178 mathematical model Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 210000005056 cell body Anatomy 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
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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
- 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
- G01S7/414—Discriminating targets with respect to background clutter
-
- 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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
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- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a method for detecting a smooth generalized likelihood ratio in the partially uniform sea clutter background. The method is a target detection method based on the smooth generalized likelihood ratio in the partially uniform sea clutter background. Firstly, a mathematical expression of a GLRT detector is given. Then, the normalized sample covariance matrix algorithm or the approximated maximum likelihood estimation algorithm is used as the estimation algorithm of a covariance M, and the median algorithm is used as the estimation algorithm of a smooth factor theta h. Finally, a scale parameter beta in the GLRT mathematical expression is replaced by beta theta h, and the expression of the smooth GLRT detector is obtained.
Description
Technical field
The present invention relates to the smooth generalized likelihood test method under a kind of uniform sea clutter background in part, belongs to radar mesh
Mark detection technique field.
Background technology
In sea-surface target detection, using the adaptive targets detection algorithm for being matched with sea clutter statistics and correlation properties it is
A kind of technological means for generally adopting.Thus, the characteristic of unit clutter to be detected and the design of adaptive detector, detection performance
It is closely related.With the further raising of radar resolution ratio, radar receives echo and is changed into non-equal from previous uniform clutter
Even clutter environment.The characteristics of uniform sea clutter in part has instantaneous power fluctuation larger, this larger frequency fluctuation can be straight
Connect the performance for affecting detector.At present, the adaptive detector design under sea clutter background is reduced often in order to simplify calculating
The complexity of detector, and it is uniform noise performance to assume that handled radar receives echo, and or in order to tackle part
Even sea clutter, and introduce complex signal processing algorithm.For example, Beijing environmental characteristics studies apllied invention specially
Profit：Method and system (the number of patent application of target detection in ocean clutter cancellation and sea clutter background：
CN201310556638.9, publication number：CN103645467 A).The patent application extracts reality from actual measurement time-space dispersive relation
Speed term parameter is surveyed, the intrinsic time-space dispersive relation of the sea clutter based on the intrinsic speed item parameter is determined, and then is reconstructed
Obtain the course figure of the sea clutter one-dimensional range profile of estimation.Subtract each other to come with the course figure estimated eventually through actual measurement gained course figure
The view data of the course figure of the one-dimensional range profile for suppressing sea clutter is obtained, so as to reach the purpose for eliminating Doppler frequency shift.Should
Patent application is disadvantageous in that：When caused by considering elimination radar movable institute the fact that Doppler frequency shift, have ignored
Uniform this another objective fact of sea clutter in part.So, its view data for finally giving suppression sea clutter introduces non-homogeneous
The interference characteristic of sea clutter.Again for example, the patent of invention of Xian Electronics Science and Technology University's application：Sub-band adaptive under sea clutter background
GLRT-LTD detection method (number of patent applications：CN201510030360.0, publication number：CN 104569948A), the patent application
The uniform sea clutter in part is tackled by way of constructing sub-filter, so as to realize accurately detection judgement, inspection is improve
Survey performance.But the main deficiency of the patent is：The filial generation wave filter of introducing is excessively complicated, and amount of calculation is larger.This will certainly affect
The conversion speed of detector.And the present invention can be solved the problems, such as above well.
The content of the invention
Present invention aim at solving above-mentioned the deficiencies in the prior art, propose under a kind of uniform sea clutter background in part
Smooth generalized likelihood test method, the method improve detection on the premise of GLRT detector computation complexities are not increased
The performance of device.
The present invention solves its technical problem and is adopted the technical scheme that：It is smooth under a kind of uniform sea clutter background in part
Generalized likelihood test method, the method, can be in Observed sea clutter experiments on the premise of computation complexity is not increased
Obtain preferably detection performance.
Method flow：
Step 1：Using GLRT detectors as S-GLRT detectors mathematics prototype；Described GLRT detector mathematical tables
Up to formula it is：
Wherein M represents the covariance matrix of clutter, and p is Doppler's steering vector, and z represents that radar receives unit to be detected
Echo, H represent conjugate transpose, and β is scale parameter, and ξ is decision threshold.
Step 2：With normalization sample covariance matrix (normalized sample covariance matrix,
NSCM) estimate or progressive maximum likelihood (approximated maximum likelihood, AML) is estimated as clutter association side
The algorithm for estimating of difference matrix M, to take mediant estimation as smoothing factorAlgorithm for estimating；Described clutter covariance matrix M
Normalization sample covariance matrix (normalized sample covariance matrix, NSCM) estimated form be：
Progressive maximum likelihood (approximated maximum likelihood, AML) estimated form is：
Accordingly, take the smoothing factor of mediant estimationExpression formula is：
Step 3, the scale parameter β in GLRT detector mathematic(al) representations is replaced withObtain repairing for GLRT detectors
Positive form, that is, smooth the expression formula of GLRT (smooth GLRT, S-GLRT) detector；Described smooth GLRT (smooth
GLRT, S-GLRT) expression formula of detector is：
Beneficial effect：
The present invention has advantages below compared with the prior art：
(1) smooth GLRT (smooth GLRT, S-GLRT) detector proposed by the present invention is compared with GLRT detectors,
On the premise of not increasing computation complexity, preferably detection performance can be obtained in Observed sea clutter experiment.
(2) S-GLRT detectors proposed by the present invention, the smoothing factor which introduces is primarily to weakened part is uniformly extra large
Impact of the clutter to detector performance.But versatility is not lost, for the target detection under uniform sea clutter background, S-GLRT detections
Device is still with the detection performance close with GLRT detectors.Meet actual clutter environment requirement.
(3) S-GLRT proposed by the present invention has CFAR characteristic to scale parameter.
(4) smoothing factor in S-GLRT detectorsUsing mediant estimation algorithm is taken, have in actual environment preferable
Performance.
Description of the drawings
Fig. 1 is method of the present invention flow chart.
Fig. 2 is Performance comparision figures of the S-GLRT proposed by the present invention and GLRT in the case of actual measurement clutter.
Specific embodiment
The invention is described in further detail with reference to Figure of description.
The present invention under the uniform sea clutter background in part, the method for improving GLRT detector performances, main skill therein
Art problem includes：
(1) smoothing factorThe selection of algorithm for estimating.
(2) derivation of S-GLRT detectors mathematic(al) representation.
In the uniform sea clutter in part of the present invention, the smooth adaptive detection algorithm of radar target includes following technology
Measure：First, provide the mathematical model of GLRT detectors.Then, NSCM is respectively adopted to clutter covariance matrix M and AML estimates
Calculating method, smoothing factorUsing taking mediant estimation algorithm.Finally, by the scale parameter β in GLRT detector mathematic(al) representations
Replace withObtain the mathematical model of smooth GLRT (smooth GLRT, S-GLRT) detector.
As shown in figure 1, the invention provides smooth generalized likelihood test side under a kind of uniform sea clutter background in part
Method, the method include：
Step 1：Initially with GLRT detectors mathematic(al) representation as mathematics prototype：
In formula (1), M represents the covariance matrix of clutter, and p is Doppler's steering vector, and it is to be detected that z represents that radar is received
The echo of unit, H represent conjugate transpose, and β is scale parameter, and ξ is decision threshold.
Step 2：When with normalization sample covariance matrix (normalized sample covariance matrix,
NSCM) estimate as clutter covariance matrix M algorithm for estimating, using take mediant estimation algorithm asValue algorithm when,'s
Expression formula is
What the k in formula (2) was represented is the number of samples of radar return.Take that mediant estimation algorithm median represents is concrete
Be meant that, to brace in all numeric ratios compared with size, take size that numerical value placed in the middle as value.
When with progressive maximum likelihood (approximated maximum likelihood, AML) estimate as clutter association side
The algorithm for estimating of difference matrix M, using take mediant estimation algorithm asValue algorithm when,Expression formula be
Step 3：For formula (1), scale parameter β is replaced withCorresponding GLRT detectors are revised as：
Formula (4) is smooth GLRT (smooth GLRT, S-GLRT) detector proposed by the present invention.
Smooth GLRT (smooth GLRT, S-GLRT) detectors proposed by the present invention can be entered by following experiment
One step is demonstrate,proved.The sea clutter data that gathered using IPIX radars of experiment are analyzing the detection performance of S-GLRT, there is provided the net of data
Location：http://soma.mcmaster.ca/ipix.php, data are entitled：(range resolution ratio is 19980223-170435
15m), HH polarization, the data contain 600 00 time pulses, 34 range cells altogether.In view of partial distance cell data
May be contaminated, so inventor have chosen the data of 26 pure sea clutter units, target is added in the 15th range cell.
Fig. 2 is S-GLRT proposed by the present invention and detection performance ratios of the tradition GLRT under different covariance matrix
Compared with.Obviously, whether NSCM estimators or AML estimators, in actual measurement clutter, the detection performance of S-GLRT is substantially better than
The detection performance of GLRT.
Claims (2)
1. the smooth generalized likelihood test method under a kind of uniform sea clutter background in part, it is characterised in that methods described bag
Include following steps：
Step 1：Using GLRT detectors mathematic(al) representation as smooth GLRT detectors mathematics prototype；
Step 2：Estimated using normalization sample covariance matrix or progressive maximal possibility estimation estimating as clutter covariance matrix M
Calculating method, to take mediant estimation as smoothing factorAlgorithm for estimating；
Step 3, the scale parameter β in GLRT detector mathematic(al) representations is replaced withObtain the amendment shape of GLRT detectors
Formula, that is, smooth the expression formula of GLRT detectors.
2. the smooth generalized likelihood test method under the uniform sea clutter background in part according to claim 1, wherein walking
GLRT detector mathematic(al) representations described in rapid 1 are：
Wherein M represents the covariance matrix of clutter, and p is Doppler's steering vector, and z represents that radar receives returning for unit to be detected
Ripple, H represent conjugate transpose, and β is scale parameter, and ξ is decision threshold.
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| CN106199552B (en) * | 2016-07-28 | 2019-03-29 | 南京邮电大学 | A kind of grouping generalized likelihood test method under local uniform sea clutter background |
| CN107179531B (en) * | 2017-03-29 | 2020-04-07 | 南京邮电大学 | Modified sample covariance matrix estimation algorithm based on maximum posterior |
| CN111624573A (en) * | 2020-07-20 | 2020-09-04 | 上海无线电设备研究所 | Time domain self-adaptive target detection method under sea clutter background |
| CN112965040B (en) * | 2021-02-05 | 2024-01-23 | 重庆邮电大学 | Self-adaptive CFAR target detection method based on background pre-screening |
| CN113009444B (en) * | 2021-02-26 | 2023-06-06 | 南京邮电大学 | Target detection method and device under generalized Gaussian texture sea clutter background |
| CN113933808A (en) * | 2021-09-29 | 2022-01-14 | 中国电子科技集团公司第二十九研究所 | Airborne radar moving target detection method, device, equipment and storage medium |
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| US8872693B1 (en) * | 2009-04-29 | 2014-10-28 | The United States of America as respresented by the Secretary of the Air Force | Radar signature database validation for automatic target recognition |
| US8284098B2 (en) * | 2010-11-24 | 2012-10-09 | Mitsubishi Electric Research Laboratories, Inc. | Persymmetric parametric adaptive matched filters for detecting targets using space-time adaptive processing of radar signals |
| CN103364769B (en) * | 2013-07-05 | 2015-06-03 | 南京邮电大学 | Adaptive estimation method for spatially non-uniform sea clutter covariance matrix |
| CN104569948B (en) * | 2015-01-21 | 2018-02-02 | 西安电子科技大学 | Sub-band adaptive GLRT LTD detection methods under sea clutter background |
| CN105093196B (en) * | 2015-07-24 | 2017-06-20 | 西安电子科技大学 | Based on the coherence detection under inverse gamma texture complex Gaussian model |
| CN105137396B (en) * | 2015-08-24 | 2017-10-17 | 电子科技大学 | The detection method that a kind of SMSP interference and C＆I are disturbed |
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