基于迭代自组织数据分析的测向定位新算法  

A New Algorithm in Finding Location Based on Iterative Self-Organizing Data Analysis Techniques

作　　者：杨志飞 孙吉 郭卫平 王晓攀 

机构地区：[1]解放军63888部队,河南济源454650 [2]解放军63891部队,河南洛阳471003

出　　处：《通信对抗》2010年第3期7-10,共4页Communication Countermeasures

摘　　要：针对传统交会定位方法精度不高的问题，从概率论角度出发，利用离信号源真实位置越近出现定位点概率越大的统计特性，首次提出将迭代自组织数据分析算法（ISODATA）应用到定位计算中。新算法自动对交会点进行聚类，消除聚类程度低的点集，选择聚类程度高的点集，然后利用最小二乘算法进行定位计算。理论分析和仿真结果表明，新算法能有效提高定位精度，尤其在低信噪比情况下性能表现较传统算法优越。The positioning accuracy of traditional method was very poor. In the view of probabihty theory, the paper apphed iterative self-organizing data analysis techniques to positioning calculation for the first time, using the statistical characteristics that the closer to the source areas the greater probabiliW to appear intersection points. The new algorithm clustered intersection points automatically, ehminated low level intersection points and selected the optimal the positioning points. Then, the location was calculated by the least square method. Theoretical analysis and simulation results show that the algorithm can effectively improve the positioning accuracy and the performance is superior especially in low SNR case.

关 键 词：测向定位 迭代自组织数据分析算法 定位精度 

分 类 号：O231[理学—运筹学与控制论]