摘要
基于CSS(Chirp Spread Spectrum,线性调频扩频)技术的无线测距是基于TOA(time of arrival,到达时间)的测距方法,在室内应用中,存在较多的NLOS(Non-Line of Sight,非视距)干扰,因此测距精度低。针对这个问题,对传统卡尔曼滤波进行改进,将NLOS误差加入状态向量进行估计,进行两步卡尔曼滤波,从而抑制NLOS误差对测距的影响。考虑到LOS(Line of Sight,视距)和NLOS并存的情况,对两步卡尔曼滤波算法进行改进,在第二步滤波中对NLOS误差鉴别和滤波处理部分做出改进,并应用到测距系统中。实验表明,利用该测距优化方法,TOA测距的精度和抗干扰能力得到了明显的提高。
Wireless ranging based on CSS( Chirp Spread Spectrum) is TOA( time of arrival) based ranging method,there are a lot of NLOS( Non-Line of Sight) error in the indoor environment,so the precision of ranging is low. For this reason this paper improve the traditional Kalman filter,add the NLOS error to the state vector,and use two step Kalman filter,to suppress the influence of NLOS error on ranging. Considering the coexistence of LOS( Line of Sight) and NLOS,this paper improve the two step Kalman filtering algorithm,improve the the NLOS error identification and filtering process in the second step filter,and apply to the ranging system. The experimental results show that with the range optimization method which is described in this paper,TOA ranging accuracy and anti-jamming capability have been significantly improved.
出处
《指挥控制与仿真》
2016年第3期131-135,共5页
Command Control & Simulation
基金
中央高校基本科研业务费专项资金(NZ2015202)