仅有角度测量跟踪问题中的中央差分算法改进

为解决仅有角度测量的目标跟踪系统初始误差大、可观性弱、精确实时跟踪困难等问题,研究了一种改进中央差分卡尔曼滤波算法。仿真结果表明,同传统估计方法相比,该算法精度高,收敛速度快,且计算量适中,易于在实战中实时跟踪。

Improved Central Difference Kalman Filter with Applications to Bearings-only Tracking

Under many circumstances, bearings-only target tracking was characterized by large initial estimation error and weak observability, making it difficult for precise real time tracking. In order to solve such problem, an improved central difference Kalman Filter was investigated in this paper. Simulation results showed that compared to traditional tracking filter, the proposed method guaranteed higher estimation accuracy and faster convergence speed, and moderate level of computation made it easy for real time tracking in battlefield case.