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Single Snapshot DOA Estimation by Minimizing the Fraction Function in Sparse Recovery

机译:稀疏恢复中通过最小化分数函数进行单快照DOA估计

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摘要

Sparse recovery is one of the most important methods for single snapshot DOA estimation. Due to fact that the originall0-minimization problem is a NP-hard problem, we design a new alternative fraction function to solve DOA estimation problem. First, we discuss the theoretical guarantee about the new alternative model for solving DOA estimation problem. The equivalence between the alternative model and the original model is proved. Second, we present the optimal property about this new model and a fixed point algorithm with convergence conclusion are given. Finally, some simulation experiments are provided to demonstrate the effectiveness of the new algorithm compared with the classic sparse recovery method.
机译:稀疏恢复是单快照DOA估计最重要的方法之一。由于originall0最小化问题是一个NP困难问题,我们设计了一种新的替代分数函数来求解DOA估计问题。首先,讨论了求解DOA估计问题的新备选模型的理论保证。证明了替代模型与原始模型之间的等价性。其次,给出了该新模型的最优性质,并给出了具有收敛结论的定点算法。最后,通过仿真实验验证了新算法与经典稀疏恢复方法相比的有效性。

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