针对已有的算法在基于到达时间差(time difference of arrival,TDOA)测量方案中存在的搜索能力不均衡,导致三维定位区域局部存在定位精度低甚至求解失败的问题,提出了一种基于改进探路者优化算法(pathfinder algorithm,PFA)的TDOA定位算法,通过将自适应Levy飞行和改进后的PFA算法进行融合,增强了个体对定位区域复杂环境的适应性,解决算法早熟、易陷入局部最优等问题,提升了算法综合性能.通过仿真和实验,结果表明:与Taylor算法、LM算法相比,本文提出的算法(Levy-pathfinder algorithm,LPFA)可以提高定位精度;与PSO算法、PFA算法相比,LPFA算法可以在提高运算速度的同时得到更准确的定位结果.
Aiming at the problem that existing algorithms in the time difference of arrival(TDOA)measurement scheme show unbalanced search ability, leading to low positioning accuracy and even failure in solution in the part of the three-dimensional positioning area, a new approach based on improved approach is proposed. The TDOA positioning algorithm based on pathfinder algorithm(PFA)enhances the individual's adaptability to the complex environment of the positioning area by integrating the adaptive Levy flight and the improved PFA algorithm, and solves the problems of premature algorithm and easy localization, thus improving the comprehensive performance of the algorithm. Through simulation and experiments, the results show that compared with Taylor algorithm and LM algorithm, the algorithm proposed in this paper(Levy-pathfinder algorithm, LPFA)can improve the positioning accuracy; compared with PSO algorithm and PFA algorithm, LPFA algorithm can improve the operation speed and obtain more accurate positioning results.
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