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Robust clutter suppression in heterogeneous environments based on multi frames and similarities

Abstract

A method of robust clutter suppression with space–time adaptive processing (STAP) for airborne radar in heterogeneous environments is proposed, which is based on multi frames and the similarity between the cell under test and each training sample. The proposed method deals with the problem of covariance matrix estimation for STAP in heterogeneous clutter. Firstly, the method expands the set of training samples by selecting similar training frames from past frames. Secondly, initial training samples are selected from the expanded training samples set, that are composed of the samples of the current frame and past frames. Thirdly, initial training samples which may be contaminated by target signal are discarded. Fourthly, the similarities between the cell under test and the remaining training samples are estimated, and training samples which are more similar to the cell under test are assigned higher weights in the estimation of the clutter covariance matrix. The proposed method overcomes the problems of training samples’ heterogeneity and insufficiency in the estimation of the clutter covariance matrix. The accuracy of the estimated clutter character is improved significantly, and thus the performance of clutter suppression is improved. Experimental results based on measured data demonstrate the performance of the proposed method.

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Abbreviations

STAP:

Space–time adaptive processing

CUT:

Cell under test

NHD:

Non-homogeneous detectors

IID:

Independent and identically distributed

DOF:

Degree of freedom

CPI:

Coherent process interval

MSMI:

Modified sample matrix inversion

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Acknowledgements

This study was supported by the China Postdoctoral Science Foundation funded project Under Grant Number 2019M651994 and the Aviation Science Foundation of China Under Grant Number 20172007002, and the Postdoctoral Science Foundation of Jiangsu Province Under Grant Numbers 2018K048C and 2019Z101, as well.

Funding

The China Postdoctoral Science Foundation (grant number 2019M651994) and the Postdoctoral Science Foundation of Jiangsu Province (grant numbers 2018K048C and 2019Z101) support the study, and the Aviation Science Foundation (under grant number 20172007002) supports the data of the study.

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Contributions

Jia Duan and Yifeng Wu proposed the main idea. The work of Xiaobo Deng was mainly about experiments. The work of Yufeng Cheng and Jun Tang was mainly about the problem of discarding samples and the discussion.

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Correspondence to Yifeng Wu.

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The authors declare that they have no conflict of interest.

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Duan, J., Wu, Y., Deng, X. et al. Robust clutter suppression in heterogeneous environments based on multi frames and similarities. Multidim Syst Sign Process (2021). https://doi.org/10.1007/s11045-021-00792-x

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Keywords

  • Airborne radar
  • Heterogeneous clutter suppression
  • Space–time adaptive processing (STAP)
  • Covariance matrix estimation