Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motion-based tracking framework which makes no such assumptions. Object is represented by

介绍了三点垂直线阵被动定位的原理. 结合矢量水听器测得的方位角和高低角及到达 阵元间的时延差, 建立了三维坐标下的状态方程和观测方程.运用扩展卡尔曼滤波算法, 研究了该系统的目标运动分析问题. 通过蒙特卡洛模拟仿真试验, 结果表明上述方法具有较高的定位性能,有较强的使用价值. -Introduced three vertical linear array passive location principle of vector hydrophone. Combining the meas

假设一物体围绕一圆周运动，角加速度是白噪声，观测噪声也是零均值的白噪声。编程使用卡尔曼滤波器实现运动物体的跟踪。-Suppose an object around a circular motion, the angular acceleration is white noise, measurement noise is zero mean white noise. Programming using a Kalman filter to achieve tracking moving obj