文章摘要
汪家宝, 陈树新, 吴昊, 何仁珂, 郝思冲.基于反馈判决的鲁棒自适应机动目标跟踪算法[J].空军工程大学学报:自然科学版,2021,22(1):70-76
基于反馈判决的鲁棒自适应机动目标跟踪算法
A Robust Adaptive Maneuvering Target Tracking Algorithm Based on Feedback Decision
  
DOI:
中文关键词: 目标跟踪  容积卡尔曼滤波  鲁棒自适应算法  反馈判决
英文关键词: target tracking  cubature kalman filter  robust adaptability algonithm  feedback decision
基金项目:国家自然科学基金(62073337;61673392)
作者单位
汪家宝, 陈树新, 吴昊, 何仁珂, 郝思冲 1.空军工程大学信息与导航学院 西安 710077 2.93184部队 北京 100076 
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中文摘要:
      针对平方根容积卡尔曼滤波(SRCKF)在机动目标跟踪中面临测量异常和模型失准时估计精度下降的问题,提出了一种基于反馈判决的鲁棒自适应算法。利用Huber函数对观测残差序列处理获得权重向量以修正测量协方差,增强算法的抗差能力以克服测量异常问题;同时,引入多重渐消因子调整预测误差协方差,从而改变滤波增益,增强算法的自适应性以解决模型失准问题。最后,根据马氏距离构建异常误差判别因子,采用反馈判决实现2种处理方式的合理切换。仿真实验表明:与现有算法相比,该算法能够有效处理测量异常和模型失准带来的误差,具备良好的抗差能力和自适应性。
英文摘要:
      Aimed at the problem that estimation accuracy reduces when square root cubature Kalman filter (SRCKF) faces measurement abnormalities and model mismatch in maneuvering target tracking, a robust adaptive algorithm based on feedback decision is proposed. The algorithm is to utilize the Huber function for processing the observation residual sequence to obtain a weight vector to correct the measurement covariance, and enhance the algorithm’s robustness to overcome measurement anomalies, and at the same time, multiple fading factors are introduced into the adjustable prediction error covariance, changing the filter gain, and enhancing the adaptability of the algorithm to solve the problem of model mismatch. Finally, according to the Mahalanobis distance, the abnormal error discrimination factor is constructed to realize the reasonable switching of the two processing methods by the feedback decision. As compared with the existing algorithms, the proposed algorithm can effectively deal with errors caused by measurement anomalies and model inaccuracy, and is good in the robustness and the adaptability.
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