COMPARISONS OF PHD FILTER AND CPHD FILTER FOR SPACE OBJECT TRACKING

被引：0
|
作者：
Cheng, Yang [1 ]
Fruh, Carolin [2 ]
DeMars, Kyle J. [3 ]
机构：
[1] Mississippi State Univ, Dept Aerosp Engn, Mississippi State, MS 39762 USA
[2] Air Force Res Lab, Kirtland AFB, NM 87117 USA
[3] Missouri Univ Sci & Technol, Dept Mech & Aerosp Engn, Rolla, MO 65409 USA
来源：
ASTRODYNAMICS 2013, PTS I-III | 2014年 / 150卷
关键词：
HYPOTHESIS DENSITY FILTER;
D O I：
暂无
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
The Probability Hypothesis Density (PHD) filter and the Cardinalized PHD (CPHD) filter are two computationally tractable approximate Bayesian multi object filters within the Finite Set Statistics framework. The PHD filter estimates the intensity function; the CPHD filter estimates the intensity function and the conditional distribution of the number of objects. The two filters are compared in an example of tracking three space objects, where the CPHD filter is shown to estimate the number of objects as well as the intensity function more accurately.
引用
收藏
页码：1043 / 1054
页数：12
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