本文選題：無源定位　切入點：直接定位　出處：《西安電子科技大學學報》2017年04期 　論文類型：期刊論文

【摘要】：針對直接定位目標函數(shù)在峰值附近變化平緩導致難以尋優(yōu)的問題,提出了銳化遺傳直接定位快速估計算法.該算法首先通過構造銳化函數(shù)對目標函數(shù)進行銳化,增強算法的選優(yōu)能力;然后在收斂過程中結合部分種群初始化,改善種群多樣性,防止算法陷入局部最優(yōu),最終實現(xiàn)直接定位快速估計.仿真結果表明,該算法相對原始遺傳算法進行直接定位快速估計,能夠在高信噪比下定位精度損失更小;相對現(xiàn)有基于最大似然網格搜索直接定位算法,能夠以95%概率獲得高精度定位結果,同時計算量下降3個數(shù)量級,計算效率有較大提升.
[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.
【作者單位】： 信息工程大學信息系統(tǒng)工程學院;
【基金】：國家高技術研究發(fā)展計劃資助項目(2012AA01A502,2012AA01A505) 國家自然科學基金資助項目(61401513)
【分類號】：TN911.7;TP18

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本文編號：1568191