An Efficient Moving Target Detection Algorithm Based on Sparsity-Aware Spectrum Estimation

Sensors

Mingwei Shen¹  Jie Wang¹  Di Wu² 

[1] College of Computer and Information Engineering, Hohai University, Nanjing 211100, China; E-Mail:;Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing University of Aeronautics and Astronautics), Ministry of Education, Nanjing 210016, China; E-Mails:

关键词: space-time adaptive processing;    sparse reconstruction;    clutter suppression;   

DOI  :  10.3390/s140917055

来源: mdpi

【 摘 要 】

In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.