基于高斯和滤波的高轨双星高超音速目标跟踪

Gaussian Sum-based Filtering for Hypersonic Object Tracking from Two Geosynchronous Satellites

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。

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.