多光电跟踪设备异步序贯分布式目标跟踪算法

针对多光电跟踪设备组网后出现的异步测量问题，提出了一种异步分布式序贯目标跟踪算法。该算法由局部滤波器和融合滤波器构成，先利用状态转换方法，将多光电跟踪设备节点及其邻节点的异步测量对齐到融合时刻，得到拟测量方程。随后，利用射影原理对拟测量方程和目标运动状态方程构成的目标跟踪系统，提出异步序贯局部滤波器来计算较为精确的局部滤波值。再以协方差交叉算法为基础，提出基于扩散策略的融合滤波器，对局部估计值进行融合计算，来提高目标跟踪精度，并降低组网后各光电跟踪设备节点融合估计值的差异程度。最后对所提出的算法进行了仿真实验，以验证其有效性。

Distributed asynchronous sequential fusion algorithm for multiple optic-electronic tracking devices

An asynchronous distributed sequential fusion algorithm was proposed for the asynchronous measurements which were measured by the networked optic-electronic tracking devices. The asynchronous distributed sequential fusion algorithm was composed of a local estimator and a fusion estimator. First, by using the state transformation method, the asynchronous measurements obtained by a sensor node was aligned to the fusion instant to get the pseudo-measurements. Then, a local sequential estimator was developed with respect to the pseudo-measurements and the target motion model to calculate the local estimation, by using orthogonal projection. Subsequently, by modifying the covariance intersection algorithm, a diffusion-based fusion estimator was designed to fuse the local estimation in the neighborhood. The simulation results of a target tracking system validate the effectiveness of the proposed target tracking algorithm.