高轨双星辐射源跟踪的高斯和-容积Kalman滤波算法

针对辐射源运动方程和观测方程的强非线性，提出基于高斯和框架与5阶容积Kalman滤波(5CKF)的跟踪算法GS-5CKF。该方法将起始时刻的时差观测量所确定的位于地球表面的时差线按经度等间隔划分，初始化多个并行的5CKF，线性组合各滤波器的输出获得辐射源运动状态的估计。针对5CKF，提出新的非线性测度并引入滤波器分裂与合并，从而提高了跟踪精度，同时保持GS-5CKF算法复杂度基本不变。仿真表明，相对仅使用单个5CKF和基于高斯和框架但使用3阶容积Kalman滤波器的GS-3CKF等方法，提出的算法具有更高的估计精度。
To tackle the inherent high nonlinearity of motion equation and observation equation of radiation source, a GS (Gaussian-sum) based 5CKF (5th-order cubature Kalman filter) tracking algorithm, referred to as GS-5CKF, was proposed. It consists of multiple parallel 5CKFs, which were initialized through partitioning the candidate source positions determined by the time difference of arrival measurement at the beginning of the tracking process with respect to the source latitude. The linear combination of filter outputs was conducted to estimate the motion state of radiation source. A new nonlinearity measure was advocated, on the basis of which a filtering splitting and merging procedure was developed to further enhance the performance of GS-5CKF while keeping its computational complexity fixed. Simulation results show that: compared with the tracking algorithms using the single 5CKF and the GS-3CKF, the newly proposed GS-5CKF technique exhibits higher source geolocation accuracy.