CN109782251A - A kind of slower-velocity target discrimination method after ocean clutter cancellation - Google Patents
A kind of slower-velocity target discrimination method after ocean clutter cancellation Download PDFInfo
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Abstract
The invention discloses the slower-velocity target discrimination methods under a kind of sea clutter background.When land-based radar detects sea-surface target, the presence of sea clutter will cause false-alarm and false dismissal, influence the detection performance of target, therefore, preceding to naval target detection to usually require clutter recognition.Adaptive ocean clutter cancellation filter is a kind of effective ocean clutter cancellation method, but there are problems that slower-velocity target and sea clutter while inhibiting, and The present invention gives the slower-velocity target discrimination methods after a kind of ocean clutter cancellation.In the concrete realization, input data is handled using adaptive ocean clutter cancellation filter first, later, for slower-velocity target that may be present, is handled using Short Time Fourier Transform, identify the true and false of suspected target finally by threshold judgement.The method of the invention can effectively distinguish slower-velocity target and sea clutter.
Description
Technical field:
Slower-velocity target identification side present invention is mainly used for radar signal processing field, under specially a kind of sea clutter background
Method.
Background technique:
Small target deteection under sea clutter modeling, ocean clutter cancellation and strong sea clutter background is current sea-surface target detection
The hot and difficult issue of area research has important reality to the detection of radar system design, Radar Signal Processing and sea-surface target
Meaning.
Common ocean clutter cancellation method be using sea clutter and target amplitude information, in terms of difference
It both distinguishes, is reached with this and inhibit sea clutter purpose.But under strong sea clutter background, target is often submerged in sea clutter
In, it is difficult to distinguish target and clutter from amplitude information.Therefore, based on the ocean clutter cancellation technology of sea clutter power spectrum
Just it attracts attention.
Traditional ocean clutter cancellation method based on frequency domain is one high-pass filter of design, and it is larger to retain Doppler frequency shift
Clutter, inhibit the lesser clutter of Doppler frequency shift.But in actual marine environment, the Doppler frequency spectrum of sea clutter
Distribution be at any time, the change of wind direction and wind speed and change, be difficult to obtain stable filter result using fixed filter.
In order to improve the ocean clutter cancellation effect of fixed high-pass filter, Y.L.Shi et al. utilizes the correlation and power spectrum of sea clutter
The adaptive ocean clutter cancellation algorithm (ASCSF) of feature extraction, due to the sea clutter of adjacent radar resolution cell have it is stronger
Correlation obtains unit sea clutter to be processed by real-time mediant estimation using adjacent radar resolution cell as training unit
Power spectrum, and then solve the parameter of ocean clutter cancellation filter.But the use scope of this method is limited, this method is only applicable in
In the Doppler frequency not situation in sea clutter main Doppler domain of target, for target at a slow speed, doppler spectral and sea
Clutter aliasing, when carrying out ocean clutter cancellation, target energy can be also weakened.
Short Time Fourier Transform (STFT) is a kind of common Time-Frequency Analysis Method, passes through the one piece of data in interception time window
To indicate the signal characteristic at certain moment.When targets are present, frequency spectrum is more stable relative to sea clutter, passes through point of STFT
Analysis, can be to sea clutter and target distinguishes at a slow speed.During STFT, the length of window function determines the time of spectrogram
Resolution ratio and frequency resolution, window function is longer, and the signal of interception is longer, and frequency resolution is higher after STFT, temporal resolution
It is poorer；On the contrary, window function is shorter, the signal of interception is shorter, and frequency resolution is poorer, and temporal resolution is better.In the application,
It needs to carry out design window in conjunction with specific requirements long.
Summary of the invention:
Naval target detection the problem of facing weak signal to noise ratio always, promotes the normal of signal to noise ratio when to effective inhibition of sea clutter
With one of method.On the basis of carrying out ocean clutter cancellation based on ASCSF method, STFT is applied to ocean clutter cancellation by the present invention
Data afterwards are calculated by spectrum mean and threshold judgement identify doubtful slower-velocity target that may be present in sea clutter.
The present invention has followed technical solution below:
1, extra large data to be detected are handled using ASCSF algorithm, realizes ocean clutter cancellation；
2, to there are the regions of doubtful slower-velocity target to carry out STFT processing；
3, what analysis STFT was handled identifies thresholding as a result, calculating, and distinguishes slower-velocity target and sea clutter by threshold judgement, real
Now to the identification of low-speed motion target.
During the ocean clutter cancellation based on ASCSF, to high-speed moving object, Doppler frequency is much higher than sea clutter
Doppler frequency, ASCSF processing after, target remains to preferably retain.But for slower-velocity target, Doppler frequency with
The Doppler frequency domain of sea clutter has overlapping, the low Doppler frequency spectrum detected after ocean clutter cancellation, only from Doppler frequency
On, it is difficult to slower-velocity target and sea clutter are distinguished, therefore, the present invention handles the data after ocean clutter cancellation using STFT,
Identification thresholding is calculated according to STFT processing result, slower-velocity target and sea clutter are further discriminated between by threshold judgement, is realized
The identification of low-speed motion target.
Detailed description of the invention:
Fig. 1: slower-velocity target identification flow after ocean clutter cancellation
Fig. 2: the ocean clutter cancellation effect picture based on ASCSF
Fig. 3: STFT processing result
Specific embodiment:
See Fig. 1, the present invention proposes the slower-velocity target discrimination method after a kind of ocean clutter cancellation, and realization process specifically includes:
Ocean clutter cancellation, STFT processing and target genuine-fake deterministic process based on ASCSF.Firstly, according to the sea clutter of adjacency door
The parameter of estimation filter obtains corresponding ASCSF filter, and carries out the ocean clutter cancellation based on ASCSF, then again to sea
Data after clutter recognition are handled using STFT, are calculated according to STFT result and are identified thresholding, distinguished finally by threshold judgement
Slower-velocity target and sea clutter.Above-mentioned steps are described in detail below.
1, based on the ocean clutter cancellation of ASCSF
The premise for carrying out ASCSF processing is that the doppler spectral of sea clutter is modeled as autoregression model.It treats each wait press down
Unit processed selects the data of adjacent unit as its training data, is estimated training data to obtain sea by Burg algorithm
The parameter of clutter doppler spectral model.Due to using neighbouring multiple units, estimated in the implementation using the intermediate value of multiple units
Meter obtains the doppler values of each Frequency point, completes the doppler spectral estimation of sea clutter.It is calculated and is used according to the doppler spectral of estimation
It has been provided in the prior art in the specific implementation process of the filter spectrum H (f) of clutter recognition, the step.
For data block z to be suppressed, the ocean clutter cancellation based on ASCSF is carried out by following formula (1).
Z (f)=DFT (z) H (f) (1)
DFT () in formula indicates discrete Fourier transform, and Z (f) is sea clutter frequency spectrum after clutter recognition, is in inverse Fu to it
Leaf transformation be inhibited after sea clutter data z'.
Under normal circumstances, it includes sea clutter, white Gaussian noise and target echo that may be present that radar, which receives echo sequence,.
The power of white Gaussian noise is evenly distributed in Doppler domain, and sea clutter is mainly distributed on the lower region of Doppler frequency, and
Target echo is then concentrated mainly in a Doppler frequency unit.When target Doppler frequency is far from the main how general of sea clutter
When strangling domain, target is retained after formula (1) carries out ocean clutter cancellation.But the Doppler frequency of slower-velocity target and sea
The Doppler domain of clutter has overlapping, and after ocean clutter cancellation, slower-velocity target can be weakened with sea clutter.
Target detection is carried out in frequency domain to the sea clutter after inhibition, being difficult to differentiate between to the target of lower Doppler frequency is
Target or sea clutter, therefore STFT processing is carried out to it, it is further to be distinguished.
2, STFT is handled
STFT is a kind of common Time-Frequency Analysis Method, and way is: being segmented to signal in time-domain, to every section of progress Fu
In leaf transformation, obtain temporal frequency figure FSTFT(m, n), m are doppler cells serial number, and n is the data block coding for carrying out STFT processing
Number.The length of every segment data determines the resolution ratio of STFT.When data segment is too long, obtained frequency resolution is high, but every number of segment
According to stationarity will receive influence, in addition temporal resolution degenerates, it is difficult to embody target and sea clutter on time-domain domain
Difference, i.e. target are gradual in time-domain, but variation of the sea clutter frequency spectrum in time-domain is more violent than target.This will
Ask the length of data segment cannot be too long.
Simultaneously in order to distinguish target and sea clutter on frequency domain, need to have higher resolution ratio on frequency domain, specific
Realization in, the length L of data segment in STFT processing is selected by following formula, which is also referred to as the window length of STFT.
Wherein, frFor radar pulse repetition frequency, τsFor the space correlation time of sea clutter, fcFor sea clutter Doppler.
Therefore, the window function g (n) for being L for the length obtained by formula (2), the expression formula of STFT are as follows:
In formula, z'(k) indicate k-th of data of the sea clutter sequence after inhibiting.
3, target genuine-fake judges
After STFT processing, by comparing the frequency spectrum of doubtful target at a slow speed and the frequency spectrum of surrounding adjacent unit, to suspected target
The true and false provide judgement.
To weaken the influence of sea clutter and noise to decision threshold, the time average that each doppler cells frequency spectrum is utilized comes
It calculates and identifies thresholding, the calculating formula of the spectrum mean of m-th of doppler cells is as follows:
N is the data block number for carrying out STFT processing, by the length of handled data, STFT window length, adjacent block overlapping length
Degree codetermines.
When the corresponding doppler cells of doubtful slower-velocity target are k, target genuine-fake identifies the calculating formula of thresholding are as follows:
τ is sea clutter doppler cells number shared on frequency domain in above formula, and value can be calculated as follows.
Fix () is to be rounded.
Finally, threshold judgement detection according to the following formula can distinguish slower-velocity target and sea clutter:
T is threshold parameter, the value usually between 3-6, M=FmeanIt (k), is the spectrum mean of suspected target, H1Indicate detection
To slower-velocity target, H0Indicate exist in unit to be detected without target.
In order to verify the validity for proposing method in text, it is real that we select the Observed sea clutter CSIR in South Africa to carry out
It tests.The ocean clutter cancellation based on ASCSF is carried out to radar return data first, as shown in Figure 2.Before Fig. 2 (a) is ocean clutter cancellation
Spectrogram, Fig. 2 (b) is spectrogram after ocean clutter cancellation.From Fig. 2 (b) as can be seen that there are spike near 0 frequency after inhibiting,
But the spike is that sea clutter or slower-velocity target are still difficult to differentiate between, and therefore, is carried out at STFT to the data after ocean clutter cancellation
Reason, obtains Fig. 3.Fig. 3 is judged using the discriminator of this patent, can be obtained, the 228th Doppler's door meets formula (7), thus
The spike that may infer that 0 frequency attachment in radar return data is slower-velocity target.
Claims (3)
1. the slower-velocity target discrimination method after a kind of ocean clutter cancellation, it is characterised in that have follow steps:
1) sea clutter data are subjected to adaptive-filtering, realize ocean clutter cancellation, and mesh is carried out in frequency domain to data after inhibition
Mark detection；
2) when there are when doubtful slower-velocity target, carrying out Short Time Fourier Transform to the sea clutter after inhibition in testing result
(STFT), temporal frequency figure F is obtainedSTFT(m, n), m are doppler cells serial number, and n is the data block number for carrying out STFT processing；
3) based on obtained temporal frequency figure FSTFT(m, n) divides the frequency spectrum for the doubtful slower-velocity target that step 1) detects
Analysis, and its true and false is distinguished by threshold judgement.
When carrying out STFT processing 2. method as claimed in claim 1, in step 2), to guarantee spectral resolution that STFT is handled
Meets the needs of target identification, each data block length L needs to meet
Wherein, frFor radar pulse repetition frequency, τsFor the space correlation time of sea clutter, fcFor sea clutter Doppler.
3. method as claimed in claim 1, in step 3), to weaken the influence of sea clutter and noise to decision threshold, it is utilized each
Doppler cells, which handle the spectrum mean in the time and calculate, identifies thresholding, the calculating formula of the spectrum mean of m-th of doppler cells
It is as follows:
N is the data block number for carrying out STFT processing, is total to by the length of handled data, data block length, adjacent block overlap length
With decision.
When the corresponding doppler cells of doubtful slower-velocity target are k, target genuine-fake identifies the calculating formula of thresholding are as follows:
τ is sea clutter doppler cells number shared on frequency domain in above formula, and value can be calculated as follows.
Fix () is to be rounded.Therefore, the discriminate that the slower-velocity target true and false identifies is as follows:
T is threshold parameter, the value usually between 3-6, M=FmeanIt (k), is the spectrum mean of suspected target, H1Expression detects low
Fast target, H0Indicate exist in unit to be detected without target.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110275150A (en) * | 2019-07-16 | 2019-09-24 | 北京航空航天大学 | The variable accelerated motion target correlative accumulation method being fitted based on empirical mode decomposition and iteration endpoint |
| CN110632590A (en) * | 2019-09-19 | 2019-12-31 | 华中科技大学 | Sea surface correlation time obtaining method and system under radar small incidence angle |
| CN110736971A (en) * | 2019-11-05 | 2020-01-31 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | real-time recognition method for non-cooperative targets in sea clutter measurement area of shore-based radar |
| CN111856411A (en) * | 2020-07-28 | 2020-10-30 | 北京环境特性研究所 | Double-threshold target detection method and device |
| CN112255607A (en) * | 2020-09-30 | 2021-01-22 | 中国人民解放军海军工程大学 | Sea clutter suppression method |
| CN113569695A (en) * | 2021-07-22 | 2021-10-29 | 中国人民解放军海军航空大学航空作战勤务学院 | Sea surface target detection method and system based on bispectrum three characteristics |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102928835A (en) * | 2012-10-09 | 2013-02-13 | 北京航空航天大学 | Human body target motion state identifying method based on improved generalized S conversion |
| CN103558597A (en) * | 2013-11-15 | 2014-02-05 | 武汉大学 | Method for detecting dim target in sea clutter on basis of spectrum kurtosis |
| CN106093908A (en) * | 2016-08-09 | 2016-11-09 | 西安电子科技大学 | A kind of radar target detection method based on piecemeal segmentation AIC model |
| CN108318866A (en) * | 2018-01-22 | 2018-07-24 | 西安电子科技大学 | Ocean clutter cancellation method based on the joint accumulation of multiframe echo |
| JP2018197689A (en) * | 2017-05-23 | 2018-12-13 | 三菱電機株式会社 | Radio wave characteristic analysis device |
| CN109116326A (en) * | 2018-09-27 | 2019-01-01 | 中国科学院电子学研究所苏州研究院 | A kind of adaption radar ocean clutter cancellation method based on medion estimator |
| CN109270501A (en) * | 2018-10-29 | 2019-01-25 | 安徽四创电子股份有限公司 | A kind of ocean clutter cancellation method for all solid state VTS radar |
| CN111077524A (en) * | 2019-12-19 | 2020-04-28 | 西安电子科技大学 | SAR-GMTI moving target repositioning improvement method |
-
2019
- 2019-03-14 CN CN201910192392.9A patent/CN109782251A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102928835A (en) * | 2012-10-09 | 2013-02-13 | 北京航空航天大学 | Human body target motion state identifying method based on improved generalized S conversion |
| CN103558597A (en) * | 2013-11-15 | 2014-02-05 | 武汉大学 | Method for detecting dim target in sea clutter on basis of spectrum kurtosis |
| CN106093908A (en) * | 2016-08-09 | 2016-11-09 | 西安电子科技大学 | A kind of radar target detection method based on piecemeal segmentation AIC model |
| JP2018197689A (en) * | 2017-05-23 | 2018-12-13 | 三菱電機株式会社 | Radio wave characteristic analysis device |
| CN108318866A (en) * | 2018-01-22 | 2018-07-24 | 西安电子科技大学 | Ocean clutter cancellation method based on the joint accumulation of multiframe echo |
| CN109116326A (en) * | 2018-09-27 | 2019-01-01 | 中国科学院电子学研究所苏州研究院 | A kind of adaption radar ocean clutter cancellation method based on medion estimator |
| CN109270501A (en) * | 2018-10-29 | 2019-01-25 | 安徽四创电子股份有限公司 | A kind of ocean clutter cancellation method for all solid state VTS radar |
| CN111077524A (en) * | 2019-12-19 | 2020-04-28 | 西安电子科技大学 | SAR-GMTI moving target repositioning improvement method |
Non-Patent Citations (4)
| Title |
|---|
| CUNSUO PANG 等: ""Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT"", 《SENSORS 2016》 * |
| SHI S N 等: ""Detection of low-velocity and floating small target in sea clutter via income-reference particle filters"", 《SIGNAL PROCESSING》 * |
| 武鹏 等: ""基于极化特征分解的海上小目标检测算法研究"", 《电子与信息学报》 * |
| 金燕: "海杂波背景下的弱目标检测算法研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110275150A (en) * | 2019-07-16 | 2019-09-24 | 北京航空航天大学 | The variable accelerated motion target correlative accumulation method being fitted based on empirical mode decomposition and iteration endpoint |
| CN110275150B (en) * | 2019-07-16 | 2021-01-08 | 北京航空航天大学 | Variable acceleration moving target coherent accumulation method based on empirical mode decomposition and iterative endpoint fitting |
| CN110632590A (en) * | 2019-09-19 | 2019-12-31 | 华中科技大学 | Sea surface correlation time obtaining method and system under radar small incidence angle |
| CN110736971A (en) * | 2019-11-05 | 2020-01-31 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | real-time recognition method for non-cooperative targets in sea clutter measurement area of shore-based radar |
| CN111856411A (en) * | 2020-07-28 | 2020-10-30 | 北京环境特性研究所 | Double-threshold target detection method and device |
| CN111856411B (en) * | 2020-07-28 | 2023-09-29 | 北京环境特性研究所 | Double-threshold target detection method and device |
| CN112255607A (en) * | 2020-09-30 | 2021-01-22 | 中国人民解放军海军工程大学 | Sea clutter suppression method |
| CN112255607B (en) * | 2020-09-30 | 2022-06-07 | 中国人民解放军海军工程大学 | Sea clutter suppression method |
| CN113569695A (en) * | 2021-07-22 | 2021-10-29 | 中国人民解放军海军航空大学航空作战勤务学院 | Sea surface target detection method and system based on bispectrum three characteristics |
| CN113569695B (en) * | 2021-07-22 | 2024-04-30 | 中国人民解放军海军航空大学航空作战勤务学院 | Sea surface target detection method and system based on bispectrum three characteristics |
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