中央差分多模型算法在蛇形机动目标跟踪问题中的应用

将中央差分卡尔曼滤波算法整合融入多模型算法,提出一类中央差分多模型算法并将其应用于典型的非线性跟踪问题,针对蛇形机动目标进行仿真验证。结果表明,和经典非线性多模型滤波器相比,该算法具有更高的估计精度和更快的收敛速度,且计算量适中,易于实现实时跟踪。

Central Difference Multiple Model Kalman Filter with Application to S Maneuver Target Tracking

A class of central difference multiple model Kalman Filter was proposed through in-tegrating central difference Kalman Filter into multiple model Kalman Filter. Then the proposed filter was applied to a typical nonlinear tracking problem. Simulation test was done for a typical S maneuver target and results showed that compared to the classical nonlinear multiple model fil-ter, the proposed filter guaranteed higher estimation accuracy and faster convergence speed, and moderate level of computation cost made it easy for real time implementation.