Reduction of False Alarm Rate in SAR-MTI Based on Weighted Kurtosis

Lee, Myung-Jun; Lee, Seung-Jae; Ryu, Bo-Hyun; Lim, Byoung-Gyun; Kim, Kyung‐Tae

doi:10.1109/tgrs.2020.3010582

Cited by 7 publications

(2 citation statements)

References 22 publications

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“…At present, target detection methods under sea clutter suppression are mainly divided into four categories in [ 12 , 13 , 14 ]: time-domain cancellation method, subspace decomposition method, neural network clutter suppression method and time-frequency analysis. Time-domain cancellation method mainly includes moving target indication (MTI) [ 15 ], motion target detection (MTD) [ 16 , 17 , 18 , 19 , 20 ], adaptive moving target indication (AMTI) [ 21 , 22 ], space-time adaptive processing (STAP) [ 23 , 24 , 25 , 26 ] and root loop cancellation method [ 27 , 28 ]. The MTI method uses the difference of Doppler frequency between the target signal and the sea clutter signal to design the filter so that the band stop notch of the filter is aligned with the center frequency of sea clutter as much as possible to realize the suppression of the sea clutter.…”

Section: Introductionmentioning

confidence: 99%

Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

Wen

Wei

2022

Entropy

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In marine radar target detection, sea clutter will cause a large number of missed alarms and false alarms, which will affect the accuracy of target detection. In order to suppress sea clutter effectively, a sea clutter suppression and target detection algorithm of marine radar image sequence based on spatio-temporal domain joint filtering is proposed in this paper. The proposed method is to add a sea clutter suppression link before detecting the target. Firstly, the marine radar image sequence is transformed into three-dimensional frequency wavenumber domain by three-dimensional fast Fourier transform (3D-FFT), and then the three-dimensional image spectrum is obtained. According to the fact that the sea clutter spectrum obtained from the image spectrum satisfies the dispersion relation of linear wave theory in the three-dimensional frequency wavenumber domain, a sea clutter model is established. Then, through the established sea clutter model, a spatio-temporal domain joint sea clutter suppressor is designed to filter the image spectrum. After that, the filtered image spectrum is transformed by three-dimensional inverse fast Fourier transform (3D-IFFT) to obtain the image sequence in which sea clutter is suppressed. Finally, target detection is carried out for sea clutter suppressed image sequence. The method is validated by using the real data of X-band marine radar. Compared with the classical Empirical mode decomposition (EMD) method, the improvement of signal-to-noise ratio (SNR) is more obvious, and SNR can be increased by 15.3 db at most. In addition, compared with target detection on original images directly, the proposed method has excellent detection rate and can increase detection rates by at least 8%.

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Section: Introductionmentioning

confidence: 99%

Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

Wen

Wei

2022

Entropy

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“…[26] mentions a new SAR-GMTIm algorithm in the framework of compressed sensing (CS), which is able to obtain high-resolution SAR images with a high focus response and precise localization. In [27,28], a novel MTI scheme, which consists of DPCA detection, clustering and ATI discrimination, is also noted to reduce the probability of false alarms and improve the detection performance. However, although these methods suppress clutter in several ways, such as reducing the number of samples, reducing dimensionality, and selecting uniform samples, they have not fundamentally solved the problem.…”

Section: Introductionmentioning

confidence: 99%

A Robust Dual-Platform GMTI Method against Nonuniform Clutter

Zou

Jin

et al. 2022

Remote Sensing

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The ground moving-target indication (GMTI) technique can detect civil and military moving targets, which means that this technique has received much attention. Strong clutter background suppression is one of the critical problems in this application. However, the detection performance in heterogeneous environment can be degraded due to the inaccurate estimation of the clutter covariance matrix (CCM). In this paper, we propose a robust GMTI method using a spaceborne dual-platform synthetic aperture radar (SAR) system, which can obtain highly accurate CCM in nonuniform clutter. Firstly, the accurate CCM is estimated based on the SAR image obtained by the former platform. Then, space–time adaptive processing (STAP) is carried out using the obtained the CCM. Finally, the detection threshold is set according to the estimated CCM and detection is executed accurately. Compared with the traditional CCM estimation method in STAP using the clutter nearby the cell under test, this method directly estimates the CCM using the clutter of the cell under test, which can avoid CCM estimation mistakes in heterogeneous clutter environment. The clutter can be whitened and depressed more effectively. Additionally, with the accurate threshold acquired from the CCM, the detection probability can be effectively improved under a certain false-alarm criterion. Based on simulation data, GMTI experiments in a heterogeneous environment such as clutter with strong pollution, junction zone of hot and cold clutter, and clutter with nonuniform power are carried out; the results show that the moving targets can be effectively detected with the proposed method.

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