基于卡尔曼滤波的无人机测向定位算法研究  

Study of UAV DF Location Algorithm Based on KF

作　　者：刘畅[1] 刘湘伟[1] 郭建蓬[1] 李子杰[1] 

机构地区：[1]电子工程学院,合肥230037

出　　处：《舰船电子对抗》2013年第1期21-25,共5页Shipboard Electronic Countermeasure

摘　　要：为了提高无人机测向定位精度,并直观地表示出一定概率下目标可能的位置区域,给出了一种基于卡尔曼滤波(KF)的无人机测向定位算法。首先使用无人机前两次测向线,计算目标位置测量的初始值;其次采用KF算法估计不同时刻目标位置的估计值,并计算每一时刻经卡尔曼滤波后的测角误差;最后将滤波后的测角误差代入目标可能位置概率椭圆算法,计算目标可能位置区域的位置及大小。结果表明:经卡尔曼滤波计算后的位置估计值逼近真实值的速度更快,所得的目标可能位置区域的面积更小,定位精度有了较明显的提高。To improve the precision of direction finding （DF） location of unmanned aerial vehicle （UAV） and show the possible position area of target directly under definite probability,this paper presents an UAV DF location algorithm based on Kalman filtering （KF）. Firstly the initial value of target position measurement is calculated by using the first two direction finding lines of UAV; then the estimation values of target position at different moments are estimated by using KF algo-rithm and the angle measurement error at every moment after KF is calculated; finally, the angle measurement errors after filtering are put into the possible target position probability ellipse algo- rithm to calculate the position and size of possible target area. The result shows that the position estimation value after KF calculation approaches the real value faster and the possible target posi-tion area obtained is smaller, and the location precision rises more obviously.

关 键 词：测向定位 测角误差 卡尔曼滤波 可能位置概率椭圆 

分 类 号：TN971.1[电子电信—信号与信息处理]