基于遗传算法优化神经网络的定位算法  

A location algorithm based on BP neural network optimized by genetic algorithm

作　　者：毛永毅[1] 谢川[2] 

机构地区：[1]西安邮电大学电子工程学院,陕西西安710121 [2]西安邮电大学通信与信息工程学院,陕西西安710121

出　　处：《西安邮电大学学报》2014年第4期45-48,共4页Journal of Xi’an University of Posts and Telecommunications

基　　金：陕西省自然科学基金资助项目(2009JM8015);陕西省教育厅专项科研基金资助项目(2010JK815)

摘　　要：为了减小非视距(Non Line of Sight,NLOS)误差对移动台定位精度的影响,提出一种基于遗传优化后向传播(Back Propagation,BP)神经网络的无线定位算法。先利用遗传算法优化BP神经网络的初始权值,再利用优化后的GA-BP神经网络修正到达时间差(Time Difference Of Arrival,TDOA)测量值,最后使用Chan氏算法确定移动台的位置,以避免由于神经网络初始权值的随机性所带来的网络震荡,克服网络容易陷入局部解的问题。仿真结果表明,新算法能够实现移动台的静态定位,并且性能优于传统BP神经网络与最小二乘(Least Square,LS)算法。In order to reduce the influence of NLOS errors on mobile positioning accuracy,a loca-tion algorithm based on BP neural network optimized by genetic algorithm is proposed.The ge-netic algorithm is able to correct the initial weights of BP neural network and then the NLOS er-rors can be corrected by the optimized GA-BP neural network.Furthermore,the positions of MS can be estimated by Chan ’s algorithm.This new algorithm overcomes the networks shock brought by the randomness of the initial weights and solves the problem of network solutions easy to fall into local issues.Simulation results show that the new algorithm can achieve static positio-ning of the mobile station and the performance is better than traditional BP neural network and LS algorithm.

关 键 词：无线定位 遗传算法 神经网络 到达时间差 

分 类 号：TN929.53[电子电信—通信与信息系统]