计算机应用与软件2024，Vol.41Issue(5)：79-84,6.DOI:10.3969/j.issn.1000-386x.2024.05.012
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
摘要
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分类
计算机与自动化引用本文复制引用
戴敏,路晶,惠国腾..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[J].计算机应用与软件,2024,41(5):79-84,6.基金项目
国家自然科学基金民航联合基金重点项目(U1233202/F01) （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). （FZ2020ZZ02）
