论文部分内容阅读
本文叙述当雷达探测设备以高数据率在极座标系中测量距离、方位和仰角时、机动目标在直角座标系中的卡尔曼滤波器。为确定用微机在线实现时的滤波器增益,推导了增益的近似算法。这种算法计算三个解耦的滤波器增益,再乘以所测目标位置和方位确定的雅可比变换。本文就海炮火控系统中典型的目标轨迹对这种算法与扩展的卡尔曼滤波器作了比较,我们的算法其滤波增益和跟踪误差与扩展卡尔曼滤波器的非常接近,而计算量则少了四分之三。
This article describes the Kalman filter for maneuvering targets in a Cartesian coordinate system when radar detection equipment measures distance, azimuth and elevation in a polar coordinate system at high data rates. In order to confirm the gain of the filter when the microcomputer realizes online, the approximate algorithm of gain is deduced. This algorithm calculates the three decoupled filter gains, multiplied by the Jacobian transform determined by the target position and bearing. This paper compares the proposed algorithm with the extended Kalman filter for a typical target trajectory in the gun fire control system. The proposed algorithm has very small filtering gain and tracking error compared with the extended Kalman filter, Three quarters.