Low complexity subspace fitting method for wideband signal location

Jin Wang, Yongjun Zhao, Zhigang Wang
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引用次数: 11

Abstract

Weighted subspace fitting (WSF) method has superior performance compared to other subspace-based techniques in broadband signal location, but it is a heavy computational task. An adaptive Particle Swarm Optimization algorithm (PSO) is proposed to solve nonlinear global optimization problem of WSF. The multi-stage Wiener filter is applied to construct the aim function for complexity reduction. Since DOA is estimated without eigen-decomposition and multidimensional search is done in an intelligent way, significant reduction in complexity is achieved. Simulation results demonstrate the effectiveness of the proposed methods.
宽带信号定位的低复杂度子空间拟合方法
加权子空间拟合(WSF)方法在宽带信号定位中具有比其他基于子空间的方法优越的性能,但计算量较大。针对WSF的非线性全局优化问题,提出了一种自适应粒子群优化算法(PSO)。采用多级维纳滤波器构造目标函数,降低了目标函数的复杂度。由于不需要进行特征分解来估计DOA,并且以智能的方式进行多维搜索,因此大大降低了复杂性。仿真结果验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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