Multistatic radar imaging via decentralized and collaborative subspace pursuit

Gang Li, P. Varshney, Yimin D. Zhang
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引用次数: 3

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.
基于分散协同子空间追踪的多基地雷达成像
多基地雷达成像任务可以转化为联合稀疏信号恢复问题。本文将分散协同子空间追踪(DCSP)算法应用于多基地雷达系统中,以获取高分辨率图像。通过在标准子空间追踪(SP)算法的每次迭代中嵌入雷达节点之间的协作和融合策略,即使某些雷达节点的信噪比(SNRs)相对较低,DCSP也能够提供令人满意的图像。与现有的基于线性规划的算法相比,DCSP算法的计算复杂度大大降低,但代价是增加了雷达网络中的通信开销。
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