摘要
为抑制非视距传播造成的定位误差,提出一种基于对各基站TOA测量结果进行NLOS判别的误差抑制算法。与传统基于TOA统计信息的NLOS抑制不同,算法直接利用移动台多天线接收数据判别基站视距状态,然后融合LOS和NLOS基站测量结果解算移动台位置。NLOS判别机制采用多天线接收数据估计信道莱斯K因子,利用K因子在LOS/NLOS下服从的不同概率分布在信号处理层面对NLOS基站进行判别。算法最后采用约束最优化方法融合识别后的LOS和NLOS基站的TOA测量结果解算移动台位置。仿真结果表明,所提融合NLOS基站TOA定位算法可有效提高NLOS存在时的定位精度。
A NLOS mitigation algorithm based on NLOS base station identification of TOA measurements was proposed to eliminate position location bias caused by NLOS propagation. Different from conventional NLOS mitigation algorithm based TOA statistics, this algorithm directly identified NLOS station through multi-antenna received data and fused LOS and NLOS TOAs to calculate the location of mobile station. Taking the advantage of probability distribution function difference of rician K-factor under LOS and NLOS scenarios, the NLOS station was identified through the estimated K-factor from multi-antenna received data. Finally MS location was calculated via constrained programming fusing TOA measurements of LOS and NLOS base station. Simulation results showed that the proposed algorithm could achieve good identification performance and high location precision with NLOS measurements through fusing NLOS measurements.
作者
赵卫波
冯志勇
张宇
Zhao Weibo Feng Zhiyong Zhang Yu(Unit 31437, Shenyang 110000, China)
出处
《电子对抗》
2017年第1期32-38,共7页
Electronic Warfare
关键词
定位
多天线
非视距误差抑制
信道莱斯K因子
约束最优化
position location
multi-antenna
none-line-of-sight mitigation
rician K-factor
constrained programming