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多扩展目标的高斯混合概率假设密度滤波器 被引量：13

Gaussian-Mixture Probability Hypothesis Density Filter for Multiple Extended Targets
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摘要 针对多扩展目标跟踪中状态信息难以估计的问题,提出了一种可以估计扩展目标运动状态和形状信息的多扩展目标高斯混合概率假设密度(RHM-GMPHD)滤波器。首先利用描述凸星形扩展目标量测源分布的随机超曲面模型和传感器量测方程,建立扩展目标运动状态及形状信息与量测之间关系的伪量测函数;然后结合扩展目标状态预报信息,推导了扩展目标状态更新方程,递推地对扩展目标运动状态及形状信息进行估计跟踪。此外,还建立了Jaccard距离来度量RHMGMPHD滤波器对目标形状的估计性能。与联合概率数据关联(JPDA)滤波器和GMPHD滤波器相比,RHM-GMPHD滤波器不仅可以估计凸星形扩展目标的形状信息,并能有效提高对目标数和运动状态的估计精度。仿真实验表明,RHM-GMPHD滤波器对质心估计的均方根误差分别约为JPDA和GMPHD滤波器的1/3和1/2,对目标数的估计接近真实值,对形状估计的Jaccard距离一般小于0.2。 A multiple extended-target Gaussian-mixture probability hypottlesls density t l GMPHD） filter, which provides the kinematic state and the extension state of extended targets, is proposed to address the difficultly estimated extension state. The pseudo-measurement likelihood function describing the relationship between kinematic state and extension state of extended target and measurements is constructed via the random hypersurface model（RHM） for convex-star extended target and sensor measurement function. Then the predicted state is considered, the update of extend target filter is derived to recursively estimate the kinematic state and extension state for extended targets. Moreover, the Jaccard distance is presented to evaluate the performance of the estimate extension state. Compared with the ioint probabilistic data association（JPDA） and GMPHD filter, RHM-GMPHD provides the extension state and enhances the precision of the estimate number and the estimate kinematic state. Simulations indicate that the root-mean-square error of centroid from RHM-GMPHD gets 1/3 of that from JPDA or 1/2 of that from GMPHD. The estimation number of extended targets approaches the true value, andJaccard distance gets usually less than O. 2.
作者 韩玉兰 朱洪艳 韩崇昭 王静
机构地区 西安交通大学电子与信息工程学院 西安邮电大学电子工程学院
出处 《西安交通大学学报》 EI CAS CSCD 北大核心 2014年第4期95-101,共7页 Journal of Xi'an Jiaotong University
基金 国家自然科学基金资助项目(61203220 61221063 61074176) 国家"973计划"资助项目(2013CB329405)
关键词 扩展目标跟踪 高斯混合概率假设密度 随机超曲面模型 形状估计 extended target tracking Gaussian-mixture probability hypothesis density randomhypersurface model estimate of the extension state
分类号 TN274 [电子电信—物理电子学]
  • 相关文献

参考文献14

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共引文献42

同被引文献75

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引证文献13

二级引证文献59

西安交通大学学报
2014年 第4期

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