一种新的基于机动检测的机动目标跟踪算法

A new algorithm on tracking maneuvering target based on maneuver detection

摘要:

针对Kalman滤波跟踪机动目标发散和目前多数自适应Kalman滤波算法对运动模型适应性不强的问题,提出了一种新的基于机动检测的机动目标跟踪算法,通过实时自适应的改变滤波模型提高对机动目标跟踪精度。对这种方法与Kalman滤波算法进行了计算机仿真比较,结果表明,该方法计算量小,可实时精确地自适应匹配目标的运动模型,可实现对机动目标稳定可靠的跟踪。

Abstract:

Divergence may occur in Kalman filter tracking maneuvering target, many of self-adjusting Kalman filters cannot well adjust to any movement model. To solve the problems, a new algorithm on tracking maneuvering target based on maneuver detection is brought forward. With this method, the tracking precision is improved by real-time self-adjusting the filter model. The simulations on this algorithm and Kalman filter are made by computer, the results show that this algorithm has the following merits, the computing quantity is less, it can real-time self-adjust the filter model to adapt to target movement so the tracking is steady.