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一种基于模型概率单调性变化的自适应IMM-UKF改进算法

王平波 陈强 卫红凯 贾耀君 沙浩然

王平波, 陈强, 卫红凯, 贾耀君, 沙浩然. 一种基于模型概率单调性变化的自适应IMM-UKF改进算法[J]. 电子与信息学报, 2024, 46(1): 41-48. doi: 10.11999/JEIT230380
引用本文: 王平波, 陈强, 卫红凯, 贾耀君, 沙浩然. 一种基于模型概率单调性变化的自适应IMM-UKF改进算法[J]. 电子与信息学报, 2024, 46(1): 41-48. doi: 10.11999/JEIT230380
WANG Pingbo, CHEN Qiang, WEI Hongkai, JIA Yaojun, SHA Haoran. Improved Adaptive IMM-UKF Algorithm Based on Monotonous Transformation of Model Probability[J]. Journal of Electronics & Information Technology, 2024, 46(1): 41-48. doi: 10.11999/JEIT230380
Citation: WANG Pingbo, CHEN Qiang, WEI Hongkai, JIA Yaojun, SHA Haoran. Improved Adaptive IMM-UKF Algorithm Based on Monotonous Transformation of Model Probability[J]. Journal of Electronics & Information Technology, 2024, 46(1): 41-48. doi: 10.11999/JEIT230380

一种基于模型概率单调性变化的自适应IMM-UKF改进算法

doi: 10.11999/JEIT230380
详细信息
    作者简介:

    王平波:男,博士,教授,研究方向为水声信号处理、声呐作战使用、目标定位跟踪等

    陈强:男,硕士生,研究方向为水声信号处理、目标定位跟踪

    卫红凯:男,博士,讲师,研究方向为水声信号处理、目标定位跟踪

    贾耀君:男,博士生,研究方向为主动声呐信号与信息处理

    沙浩然:男,本科生,研究方向为目标定位跟踪

    通讯作者:

    卫红凯 whk200605@163.com

  • 中图分类号: TN929.3; TN953

Improved Adaptive IMM-UKF Algorithm Based on Monotonous Transformation of Model Probability

  • 摘要: 针对现有交互式多模型(IMM)算法模型间切换迟滞和转换速率慢的缺点,提出一种基于模型概率单调性变化的自适应交互式多模型无迹卡尔曼滤波改进算法(mIMM-UKF)。该算法利用后验信息模型概率的单调性,对马尔可夫转移概率矩阵及模型估计概率进行二次修正,加快了匹配模型的切换速度及转换速率。仿真结果表明,与现有算法相比,该算法通过快速切换匹配模型,有效提高了水下目标跟踪精度。
  • 图  1  IMM-UKF算法流程图

    图  2  CA-CV-CT轨迹3种算法跟踪轨迹对比

    图  3  CA-CV-CT轨迹3种算法均方根误差对比

    图  4  CA-CV-CT轨迹3种算法模型概率对比

    图  5  CV-CT(左)-CT(右)轨迹3种算法跟踪轨迹对比

    图  6  CV-CT(左)-CT(右)轨迹3种算法均方根误差对比

    图  7  CV-CT(左)-CT(右)3种算法模型概率对比

    表  1  CA-CV-CT轨迹3种算法ARMSE对比

    算法位置ARMSE(m)速度ARMSE(m/s)
    本文算法77.723.8
    文献[14]算法82.704.1
    文献[15]算法80.843.9
    下载: 导出CSV

    表  2  CV-CT(左)-CT(右)3种算法ARMSE对比

    算法位置ARMSE(m)速度ARMSE(m/s)
    本文算法14.301.27
    文献[14]算法16.351.43
    文献[15]算法14.971.33
    下载: 导出CSV
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  • 被引次数: 0
出版历程
  • 收稿日期:  2023-05-05
  • 修回日期:  2023-07-17
  • 网络出版日期:  2023-07-21
  • 刊出日期:  2024-01-17

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