基于卡尔曼滤波器消除NLOS影响的移动定位

为了克服非视距信号（NLOS）对移动定位的影响，提出了一种基于卡尔曼滤波器的平滑技术．首先对到达时间（TOA）测量数据进行周期性的NLOS环境判决标识，然后根据不同结果利用不同形式的卡尔曼滤波对TOA测量数据进行平滑．将处理后的TOA代入到TDOA算法中进行定位估计．后面的跟踪虽然不能提高定位的精度，但可以平滑移动轨迹．仿真表明，该技术可以达到FCC对定位服务的要求．

Mobile Location Estimation with NLOS Mitigation Using Kalman Filter

A simple and robust techniques using biased Kalman Filter are proposed to smooth and mitigate the NLOS effect.First the raw TOA data is tested to identify NLOS conditions repeatedly.Then biased Kalman Filter is used to smooth NLOS TOA data.The processed TOAs are used for TDOA formulation and provided for location estimation.The further tracking can smooth the mobile trajectory though not improve the accuracy much.From the simulation it can be seen the technique satisfactory with FCC requirement of location services.