杂波环境下的机动目标检测和跟踪算法

交互多模式(IMM)是一种有效的机动目标跟踪算法,但由于其要求具有很多的先验前提条件而不利于工程实现.研究了一种杂波环境下更适合于工程实现的机动目标(同样适用非机动目标)的跟踪算法,该算法通过一种由测量位置估计误差决定的机动检测函数来实现杂波背景中的机动目标检测,并通过改变Kalman滤波的相关参数,实现自适应跟踪.该算法克服了IMM算法的模式限制和复杂性,同时也避免了对非机动目标的跟踪中,在跟踪模式间相互切换时所换造成的影响.通过在空管系统(ATC)的大量模拟实验,验证了该算法的有效性和重大应用价值.

Maneuvering Detection and Tracking Algorithm in Clutter Environment

There must be some prior knowledge to get the Markov transition probability in the interaction multiple mode(IMM) estimator algorithm. It was very difficult for those who couldn't get prior knowledge to adopt IMM estimator algorithn to track the maneuver targets. A versatile maneuvering detection and tracking algorithm was proposed for this situation in this paper and it aimed to provide a solution to these issues. The proposed algorithm would detect maneuvering according to the detection function which changed via measurement error. And it could adaptively modify Kalman Filter parameters and track targets while detected maneuvering. Simulation results in air traffic control (ATC) illustrate that the performance is similarity to IMM estimator algorithm and its complexity and prior knowledge are not so severely as IMM estimator algorithm. It is very suitable to realize in ATC projects.