Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (5): 1012-1017.doi: 10.3969/j.issn.1001-506X.2018.05.08

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Moving target detection algorithm based on sparse recovery and sample selection for airborne radar

GONG Qingyong, WANG Chengyan   

  1. College of Telecommunications &Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Online:2018-04-28 Published:2018-04-24

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Abstract:

A moving target detection algorithm based on sparse recovery and sample selection for airborne radar is proposed, which overcomes interfering target in selected training samples, to solve the degradation of moving target detection probability in heterogeneous training samples. It makes full use of the sparse property of samples, and attempts to select training samples whose clutter locations are similar to that of the sample in the cell under test. Eliminate the interfering target in the selected training samples to overcome the influence on moving target detection probability. Use the processed training samples and the data of the undetected distance cell to construct the covariance matrix. Simulation experiments are carried out to compare the improvement factor, range cell output power and target signal extraction.The comparison shows that this method can improve moving target detection probability for airborne radar.

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