带势估计的概率假设密度滤波的物理空间意义

为了便于人们深入理解带势估计的概率假设密度滤波,本文在Ozgur Erdin对随机集做的物理空间假设的基础上,采用Bayes公式和全概率公式对带势估计的概率假设密度滤波的迭代过程进行了推导.推导过程详细明了,推导结果与文献一致.这为带势估计的概率假设密度滤波在目标跟踪中的应用及性能改进提供了理论基础.

Derivation of cardinalized probability hyp othesis density filter via the physical-space approach

In order to make the cardinalized probability hypothesis density filter well understood, its function is deduced with the Bayes theorem and the total probability theorem based on the physical-space model made by Ozgur Erdin. The derivation is detailed and clear, and the results of the derivation are identical to those in the literature. This paper will provide the theory basis for the application and the performance improvement of the cardinalized probability hypothesis density filter in target tracking.
Keywords： random set probability hypothesis density filter multi-target tracking