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Compressed sensing radar imaging using approximate message passing
TANG Lin , JIAO Shuhong
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
Abstract: In order to solve the great computational complexity in compressed sensing radar imaging due to a large observation matrix, an approximate observation model based approximate message passing algorithm is proposed in this paper. It uses inverse chirp scaling operator to approximate the large observation matrix in compressed sensing radar imaging, thereby effectively reducing the computational complexity by the current mature decoupling technology, and in the meantime, the approximate message passing is used to improve convergence rate. The theoretical analysis and simulation show that compared to the currently used compressed sensing radar imaging methods, the proposed method exhibits higher convergence rate while suffers same computational complexity in each iteration. It realizes compressed sensing radar imaging of non-complete observation data.
Key words: radar imaging     compressed sensing     approximate observation model     approximate message passing     belief propagation

1 信号模型

2 成像算法 2.1 近似消息传递算法

2.2 基于近似观测模型的近似消息传递算法

t=0,初始化设置X0=0；Z0=Y

t≥1; 执行以下主迭代步骤：

1) 使用逆线调频变标算子计算Gamma项

2) 对执行软阈值操作获得更新的场景Xt

3)使用线调频变标算子计算残差Zt

4)更新软阈值算子的阈值。

t>tmax或误差小于一定阈值停止，否则继续迭代。

2.3 性能分析

20Nlog2N+36N+4m+16(mNa+mrN)

20Nlog2N+36N+16(mNa+mrN)

3 实验结果

 图 1 单点目标成像结果 Fig. 1 Point target imaging results

 图 2 单点目标成像距离方位向剖面 Fig. 2 Range section and azimuth section of point target

 算法 RD CS AAMP TBR 39.67 38.27 112.85

 SNR CS AIST AAMP 15 dB 31.111 5 53.461 4 53.257 5 10 dB 30.503 1 51.062 2 50.890 4 5 dB 29.492 9 47.572 1 47.424 4 0 dB 26.974 1 43.601 6 43.479 0 -5 dB 24.367 7 41.570 1 41.445 1 -10 dB 21.138 8 38.931 7 38.794 9 -15 dB 17.667 6 35.886 0 35.745 6

 图 4 计算量与收敛速度 Fig. 4 Computational complexity and convergence rate
4 结束语

DOI: 10.3969/j.issn.1673-4785.201411025

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#### 文章信息

TANG Lin, JIAO Shuhong

Compressed sensing radar imaging using approximate message passing

CAAI Transactions on Intelligent Systems, 2015, 10(04): 592-598.
DOI: 10.3969/j.issn.1673-4785.201411025