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Noise MIMO radar target imaging based on Bayesian compressive sensing


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Noise MIMO radar target imaging based on Bayesian compressive sensing
Wang ChaoyuHe YapengHu HengZhu Xiaohua
School of Electronic Engineering and Optoelectronic Technology,NUST,Nanjing 210094,China
Bayesian compressive sensing noise multiple input multiple output radar target imaging
To enhance the performance of the compressive sensing radar imaging in the low signal to noise ratio,the noise multiple input multiple output(MIMO)radar target imaging based on the Bayesian compressive sensing(BCS)is proposed.The sparse sensing model of the noise MIMO radar and the Bayesian probability density function are presented,and an optimization method based on maximum a posteriori is employed to solve the above problem.The estimate signal vector of the target scene closes to the best optimize results.Compared with the traditional compressed sensing reconstruction method,the proposed method can effectively reduce errors of the estimate,improve the quality of the two dimensional image,and show the better robustness to noise.Simulation results demonstrate the effectiveness of the method.


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Last Update: 2013-04-30