基于高斯和-容积Kalman滤波的高轨双星辐射源跟踪

高轨双星系统可通过测量辐射源信号的到达时差、频差和到达高轨卫星的多普勒频移,跟踪沿地球表面巡航且载频固定、已知的运动辐射源。针对辐射源运动方程和观测方程的强非线性,提出了基于高斯和框架与5阶容积Kalman滤波的运动辐射源跟踪算法GS-5CKF。算法将起始时刻的时差观测量所确定的处于地球表面的时差线按辐射源经度等间隔划分,初始化多个并行的5阶容积Kalman滤波器,线性组合各滤波器每个时刻的输出以获得辐射源运动状态的估计。针对5阶容积Kalman滤波器,提出了相应的非线性测度并引入滤波器分裂与合并,以提高跟踪精度并保持GS-5CKF算法计算复杂度基本不变。仿真表明,相对仅使用单个5阶容积Kalman滤波器和基于高斯和框架但使用3阶容积Kalman滤波器的GS-3CKF等算法,提出的跟踪算法具有更高的估计精度。

Gaussian-Sum Based 5th-Order Cubature Kalman Filter for Source Geolocation Using Dual GEO Satellites

This paper considers the problem of tracking a cruising ground source with known altitude and carrier frequency using two geostationary (GEO) satellites. The source motion parameters are identified from the source signal time difference of arrival (TDOA), frequency difference of arrival (FDOA) and Doppler shift estimated at the GEO satellites. To tackle the high nonlinearity inherent in the above tracking problem, a Gaussian-sum (GS) based 5th-order cubature Kalman filter (5CKF), referred to as GS-5CKF, is proposed. It consists of multiple parallel 5CKFs and they are initialized through partitioning the candidate source positions determined by the measured TDOA at the beginning of the tracking process with respect to the source latitude. Besides, a new nonlinearity measure is advocated, on the basis of which a splitting and merging procedure is developed to further enhance the performance of GS-5CKF while keeping its computational complexity fixed. Simulation results show that compared with the tracking algorithm using a single 5CKF as well as the GS-3CKF method developed in literature, the newly proposed GS-5CKF technique exhibits higher source geolocation accuracy.