摘要
A kalman filter in the spherical-rectangular coordinate system to track a maneuvering target is introduced. A dynamic model with extended state vector is proposed in this paper to improve the state estimation (i.e. position, velocity and acceleration) even the sensor data(i.e. range, azimuth angle and elevation angle ) is color contaminated. The Kalman filter equations are decoupled by proper coordinate transformation and using filter gain rotation algorithm. Monto Carlo simulation is performed for different kinds of target trajectories(with the same measurement noise) and the root mean square values of estimation errors are computed. Results show that there is significant improvement in tracking capability over the methods discussed by other researchers.
本文介绍了在球面－直角坐标系下跟踪机动目标的卡尔曼滤波算法．为克服观测噪声非白，本文引入了扩充向量，并应用旋转增益算法，对卡尔曼滤波的协方差阵及增益阵实现了解耦．通过仿真计算，对本文提出的算法与国外两种类似的算法在相同的机动和量测噪声特性情况下进行了比较，其结果显示了本算法的优越性．
基金
国防科研基金
