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Sensors 2014, 14(9), 17055-17067; doi:10.3390/s140917055

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

1,2,* , 1,2
,
2
and
2
1
College of Computer and Information Engineering, Hohai University, Nanjing 211100, China
2
Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing University of Aeronautics and Astronautics), Ministry of Education, Nanjing 210016, China
*
Author to whom correspondence should be addressed.
Received: 7 July 2014 / Revised: 9 September 2014 / Accepted: 10 September 2014 / Published: 12 September 2014
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [1747 KB, uploaded 12 September 2014]   |  

Abstract

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. View Full-Text
Keywords: space-time adaptive processing; sparse reconstruction; clutter suppression space-time adaptive processing; sparse reconstruction; clutter suppression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Shen, M.; Wang, J.; Wu, D.; Zhu, D. An Efficient Moving Target Detection Algorithm Based on Sparsity-Aware Spectrum Estimation. Sensors 2014, 14, 17055-17067.

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