摘要
针对过程误差难以确定、观测精度较差、目标位置较远时卡尔曼滤波性能下降的情况,结合目标当前运动状态,定义了基于当前观测值置信度的权重矩阵,推导了基于权重矩阵的修正卡尔曼滤波观测更新方程,实现目标状态协方差矩阵、增益矩阵快速自适应调整,提高了算法稳健性。实验验证了算法的可行性和改进性。
In view of the difficulty of determining the process error, the poor observation accuracyand the performance degradation of the Kalman filtering when the target position is relatively far, incombination with the current target movement status, the weight matrix is defined based on the cur？rent confidence coefficient of the observation value, and the updated observation equations of themodified Kalman filtering are derived based on the weight matrix, realizing the covariance matrix ofthe target status and rapid adaptive adjustment of the gain matrix, and improving the robustness ofthe algorithm. The feasibility and improvement of the algorithm are verified via the test.
出处
《雷达与对抗》
2017年第4期11-14,29,共5页
Radar & ECM
关键词
目标跟踪
卡尔曼滤波
自适应滤波
target tracking
Kalman filtering
adaptive filtering
