一种适用于机动目标跟踪的改进卡尔曼滤波算法  

Improved Kalman Filter Algorithm for Maneuvering Target Tracking

作　　者：高增敏[1] 王首勇[2] 郑作虎[1] 郑岱堃[1] 

机构地区：[1]空军雷达学院研究生管理大队,武汉430019 [2]空军雷达学院三系,武汉430019

出　　处：《空军雷达学院学报》2011年第5期339-342,346,共5页Journal of Air Force Radar Academy

基　　金：国家部委级资助项目

摘　　要：针对卡尔曼滤波跟踪强机动目标时性能下降的问题,提出了一种适用于机动目标跟踪的改进卡尔曼滤波算法.该算法在卡尔曼滤波算法的基础上,根据当前量测目标航向与前一目标航向之间的航向角度差,判断机动强弱并计算出加权函数值,然后用加权函数值根据量测数据依次修正机动目标加速度预测值和目标预测状态,最终改进目标的状态估计.仿真结果表明,目标强机动时该算法具有较高的跟踪精度.Concerning for the performance of Kalman filter tracking strong maneuvering target being reduced,this paper proposes an improved Kalman filter algorithm appropriate for the maneuvering target tracking.Based on Kalman filter algorithm,this algorithm decides the strong or week of maneuvering and calculates the weighted function value according to the course heading difference between the target heading currently measured and the previous one,and then,modifies successively the predicted acceleration value of the maneuvering target and the predicted state of the target using the weighted function value in terms of the measured data,thus improving the estimation of the target state.Simulation results show that the improved algorithm is of higher accuracy for strong maneuvering target tracking.

关 键 词：目标跟踪 机动目标 卡尔曼滤波算法 航向角度差 

分 类 号：TN957[电子电信—信号与信息处理]