Sparse MIMO radar with phase mismatch
ICASSP（2013）
摘要
In this paper we propose a sparse model to accurately estimate target locations in a distributed multiple-input multiple-output (MIMO) radar system with phase mismatches at transmitters and receivers. We formulate the localization problem based on maximum a posteriori (MAP) estimation. To reduce the effect of phase mismatches we develop a novel alternating minimization approach based on sparse signal recovery and structured matrix perturbation. Using numerical simulations, we show that our algorithms significantly improve the performance of the distributed MIMO radar system.
更多查看译文
关键词
radar transmitters,mimo radar,distributed multiple-input multiple-output radar system,sparse mimo radar,maximum likelihood estimation,matrix algebra,numerical analysis,map estimation-based localization problem,alternating minimization,sparse model,sparse signal recovery,structured matrix perturbation,target location estimation,phase mismatch,maximum a posteriori estimation-based localization problem,radar receivers,distributed mimo radar,numerical simulations,distributed mimo radar system,optimization,mimo,mathematical model,transmitters
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要