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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Direction-of-Arrival Estimation Based on Particle Swarm Optimization Searching Approaches for CDMA Signals
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Direction-of-Arrival Estimation Based on Particle Swarm Optimization Searching Approaches for CDMA Signals

机译:基于粒子群优化搜索方法的CDMA信号到达方向估计

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摘要

This paper deals with direction-of-arrival (DOA) estimate problem based on multiple signal classification (MUSIC) criterion with particle swarm optimization (PSO) for code-division multiple access signals. It is shown that the computational complexity and estimate accuracy of the traditional spectral searching MUSIC estimator strictly depends on the number of search grids used during the search. The more accurate DOA estimation, the more searching grids are needed. In conjunction with PSO algorithm, the computational complexity of DOA estimation of MUSIC estimator can be reduced, while the accuracy of estimation performance can be enhanced. But, the optimum solution searching and the convergence of standard PSO iteration process are restricted by using the linearly decreasing intra weights the hard limited conditions of particles moving velocities and position clipping. To promote accurate DOA finding, a modified PSO estimator with the decision strategy of particle velocities and particle position clipping is presented in this paper. In addition, this paper also presents adaptive multiple inertia weights with Newton-Raphson method to speeding up the convergence of modified PSO iteration process. Several computer simulation examples are provided for illustration and comparison.
机译:本文基于码分多址信号的多信号分类(MUSIC)准则和粒子群优化(PSO)技术,解决了到达方向(DOA)估计问题。结果表明,传统频谱搜索MUSIC估计器的计算复杂度和估计精度严格取决于搜索过程中使用的搜索网格的数量。 DOA估算越准确,就需要越多的搜索网格。结合PSO算法,可以降低MUSIC估计器DOA估计的计算复杂度,同时可以提高估计性能的准确性。但是,通过使用线性减小的内部权重,粒子移动速度和位置限幅的严格限制条件,限制了最佳解的搜索和标准PSO迭代过程的收敛性。为了促进精确的DOA查找,本文提出了一种具有粒子速度和粒子位置限幅决策策略的改进的PSO估计器。此外,本文还提出了牛顿-拉夫森方法的自适应多重惯性权重,以加快改进的PSO迭代过程的收敛速度。提供了几个计算机仿真示例,用于说明和比较。

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