基于高斯和滤波的高轨双星高超音速目标跟踪

摘要

This paper considers tracking a cruising hypersonic object with known altitude using the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements obtained at two geosynchronous satellites.A new tracking algorithm,referred to as GMM-AEKF,is proposed.The algorithm utilizes a discrete-time process equation under the WGS-84 ellipsoidal Earth model,which is established through discretizing the continuous-time equation of target motion with Euler sampling.GMM-AEKF generalizes the existing GMM-EKF algorithm in the sense that it implicitly takes into account the object moving along the earth surface with known altitude.It also includes a new method that can yield a more uniform GMM representation of the TDOA measurement,the alternative extended Kalman filter (AEKF) for FDOA track update,and a Kullback-Leibler (KL) divergence-based Gaussian component management scheme.Simulation results reveal that with the use of AEKF,TDOA and FDOA track updates of GMM-AEKF are the same as the state update of standard linear Kalman filter (KF).GMM-AEKF is also shown to be able to converge faster,which makes it more suitable for hypersonic object tracking other state-of-art benchmarks.%针对基于高轨双星时频差观测的无源跟踪问题,提出一种适用于跟踪高超音速巡航目标GMM-AEKF算法,该算法使用基于Euler采样建立的WGS-84椭球下的目标离散时间运动方程,在已有的GMM-EKF跟踪框架的基础上引入时差均匀高斯混合(GMM)表示、替代扩展卡尔曼滤波(AEKF)和基于Kullback-Leibler散度的高斯分量管理.仿真实验结果表明,AEKF的引入使得跟踪算法的状态更新运算变为线性,其估计精度收敛速度较快,适用于高超音速目标跟踪.