| 基于核密度杂波估计的改进MHT算法 |
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| 引用本文： | 王子微,孙进平,赵楚楚. 基于核密度杂波估计的改进MHT算法[J]. 信号处理, 2021, 37(6): 991-999. DOI: 10.16798/j.issn.1003-0530.2021.06.011 |
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| 作者姓名： | 王子微 孙进平 赵楚楚 |
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| 作者单位： | 北京航空航天大学电子信息工程学院 |
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| 基金项目： | 国家自然科学基金（62073334） |
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| 摘 要： | 传统多假设跟踪(Multiple Hypothesis Tracker,MHT)算法假定杂波强度先验已知,在未知杂波的观测场景中,杂波强度误差将导致数据关联的准确性急剧下降.针对这一问题,本文提出一种基于核密度估计(Kernel Density Estimation,KDE)的在线杂波估计MHT算法.首先利用核密度函数...
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| 关 键 词： | 多假设跟踪 核密度估计 杂波强度 杂波空间分布 航迹得分 |
| 收稿时间： | 2021-01-29 |
An Improved MHT Method with Kernel Density Clutter Estimation |
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| Affiliation: | School of Electronic and Information Engineering, Beihang University |
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| Abstract: | The traditional multiple hypothesis tracking (MHT) algorithm assumes that the clutter intensity is known a priori. In the observation scene of unknown clutter, the clutter intensity error will lead to a sharp decline in the accuracy of data association. To solve this problem, this paper proposes an improved MHT method with clutter estimation based on kernel density estimation (KDE). Firstly, the kernel density function is used to fit the unknown clutter spatial distribution, and the clutter intensity in the gate at that time is estimated adaptively; then the score function of the track hypothesis is calculated by using the obtained clutter intensity, which improves the accuracy of data association and the stability of target tracking. Simulation results show that MHT-KDE algorithm can effectively improve the track continuity and reduce the number of false tracks in unknown clutter observation scene. |
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