卡尔曼滤波在水下载体被动弹道跟踪系统中的应用

由于水声环境和信道的复杂性及水下航行载体的高速机动性,被动弹道跟踪系统测量的弹道样点野值较多,平滑性差.要对弹道进行较准确的实时跟踪,需要对弹道测量样点进行统计平滑处理.为了提高被动跟踪系统的定位精度和对机动目标的跟踪适应能力,采用卡尔曼滤波算法对弹道进行处理是常用的做法.介绍一种经过实用且效果较好的卡尔曼滤波算法,阐述了卡尔曼滤波算法原理和系统采用的信号模型及算法实现,并通过水下目标实航试验监测弹道及算法滤波处理结果的比较,说明该算法具有良好特性.

Application of Kalman filtering in passive trajectory tracking system of underwater carrier

Because of the complication of the sound environment and underwater channel, moreover, the high mobility of the underwatercamer, there are a great number of trajectory samples away from the truth in the passive trajectory tracking system caused the worse smoothness. In order to track the trajectory accurately on time, it is necessary to smooth statistically for the test samples. For improving the location veracity and adaption of moving object in passive trajectory tracking system,it is common that Kalman filtering algorithm is used to process the trajectory. This paper introduce one of the better Kalman filtering algorithm which has been used and also account for the principle of Kalman filtering algorithm, signal model, algorithm accomplish in the system. The article illuminate the wonderful characteristic through comparing the result of filter and the measurement of objective trajectory in true navigation test.