论文部分内容阅读
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。
Aiming at the problem of asynchronous measurement after multi-optoelectronic tracking device networking, an asynchronous distributed sequential target tracking algorithm is proposed. The algorithm consists of a local filter and a fusion filter. The state transition method is used to align the asynchronous measurements of a multi-optoelectronic tracking device node and its neighbors to the integration moment to obtain the proposed measurement equation. Subsequently, the projective sequential local filter is proposed to calculate the more accurate local filtering value by using the projective principle for the target tracking system composed of the quasi-measurement equation and the target kinematic equation. Based on the covariance crossover algorithm, a fusion filter based on the diffusion strategy is proposed to fuse the local estimation values to improve the tracking accuracy and reduce the difference of the fusion estimation values of the tracking devices. Finally, the proposed algorithm is simulated to verify its validity.