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非平稳异常噪声条件下的扩展目标跟踪方法

陈辉 张欣雨 连峰 韩崇昭 张光华

符渭波, 苏涛, 赵永波, 何学辉. 空间色噪声环境下基于时空结构的双基地MIMO雷达角度和多普勒频率联合估计方法[J]. 电子与信息学报, 2011, 33(7): 1649-1654. doi: 10.3724/SP.J.1146.2011.00016
引用本文: 陈辉, 张欣雨, 连峰, 韩崇昭, 张光华. 非平稳异常噪声条件下的扩展目标跟踪方法[J]. 电子与信息学报, 2025, 47(3): 803-813. doi: 10.11999/JEIT240824
Fu Wei-Bo, Su Tao, Zhao Yong-Bo, He Xue-Hui. Joint Estimation of Angle and Doppler Frequency for Bistatic MIMO Radar in Spatial Colored Noise Based on Temporal-spatial Structure[J]. Journal of Electronics & Information Technology, 2011, 33(7): 1649-1654. doi: 10.3724/SP.J.1146.2011.00016
Citation: CHEN Hui, ZHANG Xinyu, LIAN Feng, HAN Chongzhao, ZHANG Guanghua. Extended Target Tracking Method under Non-stationary Abnormal Noise Conditions[J]. Journal of Electronics & Information Technology, 2025, 47(3): 803-813. doi: 10.11999/JEIT240824

非平稳异常噪声条件下的扩展目标跟踪方法

doi: 10.11999/JEIT240824
基金项目: 国家自然科学基金(62163023, 61873116, 62366031, 62363023),甘肃省基础研究创新群体(25JRRA058),中央引导地方科技发展资金项目(25ZYJA040),甘肃省重点人才项目(2024RCXM86),甘肃省军民融合发展专项资金
详细信息
    作者简介:

    陈辉:男,教授,博士生导师,研究方向为多目标跟踪、数据融合、最优控制等

    张欣雨:女,硕士生,研究方向为扩展目标跟踪和最优滤波技术

    连峰:男,教授,博士生导师,研究方向为目标跟踪、信息融合与传感器管理

    韩崇昭:男,教授,博士生导师,研究方向为多源信息融合、随机控制与自适应控制、非线性频谱分析等

    张光华:男,副教授,博士生导师,研究方向为多源信息融合、目标跟踪、传感器管理

    通讯作者:

    陈辉 huich78@hotmail.com

  • 中图分类号: TN911.7; TP274

Extended Target Tracking Method under Non-stationary Abnormal Noise Conditions

Funds: The National Natural Science Foundation of China (62163023, 61873116, 62366031, 62363023), Gansu Provincial Basic Research Innovation Group of China (25JRRA058), The Central Government’s Funds for Guiding Local Science and Technology Development of China (25ZYJA040), Gansu Provincial Key Talent Project of China (2024RCXM86), Gansu Provincial Special Fund for Military-Civilian Integration Development of China
  • 摘要: 针对非平稳异常噪声环境下扩展目标跟踪问题,该文提出一种基于高斯-学生t混合(GSTM)扩展目标跟踪方法。首先,将过程噪声和量测噪声建模为GSTM分布,以表征非平稳厚尾噪声,并通过引入伯努利随机变量,将目标的运动状态和量测似然函数建模为分层高斯形式。其次,在随机矩阵(RMM)滤波框架下,使用变分贝叶斯方法详细推导了非平稳厚尾噪声下的GSTM扩展目标跟踪算法。该算法通过建模高斯噪声与厚尾噪声之间的非平稳过程,精确表征噪声特性,从而在非平稳异常噪声环境下稳健捕捉扩展目标的质心位置和轮廓形态。最后,构建非平稳异常噪声环境下的扩展目标跟踪仿真实验,并通过高斯-瓦瑟斯坦距离对实验结果进行效果评估,验证了所提出算法的合理性。此外,真实场景实验结果进一步证明了该算法在实际应用中的有效性和鲁棒性。
  • 图  1  扩展目标轨迹跟踪图

    图  2  目标质心跟踪误差

    图  3  不同阶段的轮廓放大图

    图  4  椭圆扩展目标GWD

    图  5  扩展目标轨迹跟踪图

    图  6  目标质心跟踪误差

    图  7  不同阶段的轮廓放大图

    图  8  椭圆扩展目标GWD

    图  9  不同时刻效果图

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出版历程
  • 收稿日期:  2024-09-27
  • 修回日期:  2025-02-23
  • 网络出版日期:  2025-03-01
  • 刊出日期:  2025-03-01

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