Particle swarm optimization for time-difference-of-arrival based localization

K. Lui, Jun Zheng, H. So
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引用次数: 25

Abstract

Time-difference-of-arrival (TDOA) based source localization has been intensively studied and broadly applied in many fields. In this paper, particle swarm optimization (PSO) is employed for positioning with TDOA measurements in the circumstances of known and unknown propagation speed. The optimization criterion is first developed and the PSO technique is then employed to search the global minimum of the cost function. For sufficiently small noise conditions, simulation results show that the PSO approach provides accurate source location estimation for both known and unknown propagation speed, and also gives an efficient speed estimate in the later case.
基于到达时差定位的粒子群优化
基于到达时差分(TDOA)的源定位技术在许多领域得到了广泛的研究和应用。本文将粒子群算法(PSO)应用于传播速度已知和未知情况下的TDOA定位。首先建立优化准则,然后利用粒子群算法搜索代价函数的全局最小值。仿真结果表明,在噪声足够小的情况下,粒子群算法对已知和未知的传播速度都能给出准确的源定位估计,对未知的传播速度也能给出有效的估计。
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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