机场场面多点定位中结合M估计与EKF的高精度位置估计方法
A HIGH PRECISION MLAT METHOD COMBINING M-ESTIMATION AND EXTENDED KALMAN FILTER IN AIRPORT SURFACE SURVEILLANCE
戴敏 1路晶 2惠国腾2
作者信息
- 1. 中国民用航空飞行学院监察员培训学院 四川广汉 618307
- 2. 中国民用航空飞行学院计算机学院 四川广汉 618307
- 折叠
摘要
传统机场场面飞机多点定位(Multilateration,MLAT)方法的精度易受非视距(NLOS)环境中观测误差的影响.针对该问题,提出一种结合M估计与扩展Kalman滤波(EKF)的高精度多点定位方法.将场面接收站测量的到达时间差(TDOA)数据构建成一个数值模型;利用Huber-M估计的思想,将标准EKF中的观测更新步骤更改为一个加权最小二乘线性回归问题,以此提高EKF对非高斯观测噪声的抗干扰能力;将该改进型EKF用于位置估计.仿真结果表明,该方法对TDOA观测噪声具有很好的鲁棒性,获得了较高的定位精度.
Abstract
The positioning accuracy of traditional multilateration method(MLAT)in airport surface surveillance is easily affected by the observation error in NLOS environment.To solve this problem,a high-precision MLAT method combining M-estimation and extended Kalman filter(EKF)is proposed.The TDOA data measured by the surface receiving station was constructed into a numerical model.Using the idea of Huber-M estimation,the observation updating step in standard EKF was changed to a weighted least square linear regression problem,so as to improve the anti-interference ability of EKF to non-Gaussian observation noise.The improved EKF was applied to location estimation.The simulation results show that the proposed method is robust to the observation noise of TDOA and achieves high positioning accuracy.
关键词
机场场面监控/多点定位/M估计/扩展Kalman滤波/NLOS环境Key words
Airport surface surveillance/Multilateration/M-estimation/Extended Kalman filter/NLOS引用本文复制引用
基金项目
国家自然科学基金-中国民用航空总局联合资助重点项目(U1233202/F01)
民航飞行技术与飞行安全重点实验室自主研究项目(FZ2020ZZ02)
出版年
2024
国家科技期刊平台
NSTL
万方数据