锐化遗传直接定位快速估计算法

发布时间：2018-03-05 01:32

本文选题：无源定位　切入点：直接定位　出处：《西安电子科技大学学报》2017年04期 　论文类型：期刊论文

【摘要】：针对直接定位目标函数在峰值附近变化平缓导致难以寻优的问题,提出了锐化遗传直接定位快速估计算法.该算法首先通过构造锐化函数对目标函数进行锐化,增强算法的选优能力;然后在收敛过程中结合部分种群初始化,改善种群多样性,防止算法陷入局部最优,最终实现直接定位快速估计.仿真结果表明,该算法相对原始遗传算法进行直接定位快速估计,能够在高信噪比下定位精度损失更小;相对现有基于最大似然网格搜索直接定位算法,能够以95%概率获得高精度定位结果,同时计算量下降3个数量级,计算效率有较大提升.
[Abstract]:Aiming at the problem that the change of direct location target function in the vicinity of peak value makes it difficult to find optimization, a fast estimation algorithm based on sharpening genetic direct location is proposed. Firstly, the objective function is sharpened by constructing sharpening function. The optimization ability of the algorithm is enhanced, and then some populations are initialized in the convergence process to improve the diversity of the population, to prevent the algorithm from falling into the local optimum, and finally to realize the fast estimation of direct location. The simulation results show that, Compared with the original genetic algorithm, the proposed algorithm can estimate directly the location accuracy with less loss of location accuracy under high SNR, compared with the existing direct location algorithm based on maximum likelihood grid search, which can obtain high precision localization results with 95% probability. At the same time, the amount of calculation is reduced by 3 orders of magnitude, and the calculation efficiency is greatly improved.
【作者单位】：信息工程大学信息系统工程学院;
【基金】：国家高技术研究发展计划资助项目(2012AA01A502,2012AA01A505) 国家自然科学基金资助项目(61401513)
【分类号】：TN911.7;TP18

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