DocumentCode :
239618
Title :
Multistatic radar imaging via decentralized and collaborative subspace pursuit
Author :
Gang Li ; Varshney, Pramod K. ; Zhang, Yimin D.
Author_Institution :
EE Dept., Tsinghua Univ. Beijing, Beijing, China
fYear :
2014
fDate :
20-23 Aug. 2014
Firstpage :
710
Lastpage :
714
Abstract :
The task of multistatic radar imaging can be converted to the problem of jointly sparse signal recovery. In this paper, the algorithm named decentralized and collaborative subspace pursuit (DCSP) is utilized in multistatic radar systems to obtain a high-resolution image. By embedding collaboration among radar nodes and fusion strategy into each iteration of the standard subspace pursuit (SP) algorithm, DCSP is capable of providing satisfactory image even if some radar nodes suffer from relatively low signal-to-noise ratios (SNRs). Compared to the existing algorithms based on linear programming, DCSP has much lower computational complexity at the cost of increased communication overhead in the radar network.
Keywords :
computational complexity; image fusion; image resolution; iterative methods; linear programming; radar imaging; radar resolution; DCSP; SNRs; SP algorithm; communication overhead; computational complexity; decentralized and collaborative subspace pursuit; fusion strategy; high-resolution image; jointly sparse signal recovery problem; linear programming; low signal-to-noise ratios; multistatic radar imaging system; radar network; radar nodes; standard subspace pursuit algorithm; Collaboration; Imaging; Multistatic radar; Radar imaging; Signal processing algorithms; Standards; Multistatic radar imaging; compressive sensing; subspace pursuit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2014 19th International Conference on
Conference_Location :
Hong Kong
Type :
conf
DOI :
10.1109/ICDSP.2014.6900756
Filename :
6900756
Link To Document :
بازگشت