摘要
针对传统的Chan算法在实际的非视距环境中性能将会受到很大影响这一问题,提出了一种基于神经网络的TDOA定位改进算法,这种算法通过对非视距误差进行修正,使其具有更好的定位效果.仿真实验结果表明,与传统的Chan算法相比,这种算法具有更好的定位精度和收敛速度,是一种有效的定位算法.
According to the problem that the traditional Chan algorithm performance will be greatly affected in actual NLOS environment, a new improved arithmetic of TDOA location based on neural network is presented. This algorithm has better location effect by modifying error in NLOS. The simulation results show that the proposed method has better accuracy and convergence rate than conventional Chan algorithms and it is a kind of effective location algorithms.
出处
《河南师范大学学报（自然科学版）》
CAS
北大核心
2014年第4期139-143,共5页
Journal of Henan Normal University(Natural Science Edition)
基金
总装备部基金资助项目(5140104C703CB0102)
