火力与指挥控制2024，Vol.49Issue(3)：19-24,6.DOI:10.3969/j.issn.1002-0640.2024.03.003
改进的自适应扩展卡尔曼滤波雷达目标跟踪算法
An Improved Adaptive Extended Kalman Filter Algorithm for Radar Target Tracking
摘要
Abstract
Kalman filter(KF)algorithm is the most commonly used algorithm in radar target tracking.However the tracking accuracy of KF filtering algorithm decreases when the adaptation of nonlinear motion model and the noise model mismatches.According to these problems,an improved adaptive extended kalman filter(EKF)algorithm for radar target tracking is proposed in the maneuvering target scene,the predicted position information is corrected through the deviation range of the target position.And then the back-propagation(BP)neural network algorithm is used to adapt to the correction of the predicted information results with the EKF algorithm.According to the noise impact of the actual situation,the adjusted update factor is used for the weight processing of the corrected EKF prediction position information,the measured information and the corrected BP-EKF prediction information value.The optimal location prediction information is adaptively selected based on the optimization model.The simulation results show that the filtering accuracy and stability are improved in target tracking.关键词
机动目标跟踪/扩展卡尔曼滤波/BP神经网络/更新因子/优化模型Key words
maneuvering target tracking/extended kalman filter/BP neural network/update factor/optimization model分类
信息技术与安全科学引用本文复制引用
杨遵立,张衡,吕伟,余娟,张从胜..改进的自适应扩展卡尔曼滤波雷达目标跟踪算法[J].火力与指挥控制,2024,49(3):19-24,6.基金项目
国家自然科学基金资助项目(61601509) （61601509）
