基于当前统计模型的三维空间机动目标跟踪算法

A maneuvering target-tracking algorithm in the three-demension based on current statistical model

对可以观测距变率和角变率的雷达观测系统提出了在三维空间中引入距变率(径向速度)和角变率(角速度)的当前统计卡尔曼滤波算法。针对三维空间中的机动目标,将新提出的算法和传统算法进行仿真,结果表明,当引入距变率和角变率时,其收敛速度加快,收敛精度提高,改善了跟踪性能,具有工程实践指导意义。

In the three-dimensional space,a new method for the current statistical kalman filtering algorithm using the radial velocity is presented for radar awareness system, which can detect target radial velocity and target angular velocity, A simulation about the pseudo Kalman filtering put forward by this thesis and the traditional Kalman filtering is given, which aim at the maneuvering target in three-demension. Simulation results indicate that the convergent velocity is accelerated and the convergent precision is increased when the radial velocity and angular velocity is adopted. The new pseudo Kalman filtering has some significance for project practice.