具有进化泊松先验的pmht直方图

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI:10.1109/ICASSP.2015.7178734

H. Vu, S. Davey, S. Arulampalam, F. Fletcher, C. Lim

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引用次数: 10

摘要

直方图-概率多假设跟踪器(H-PMHT)是一种针对检测前跟踪(TkBD)问题的高效多目标跟踪方法。然而，它不能充分处理波动的目标，这可能会降低跟踪管理的性能。通过假设一个基于泊松分布的替代测量模型，可以重新推导H-PMHT算法，以纳入分量混合项的时间相关估计，从而改进轨道质量的测量。

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Histogram-PMHT with an evolving Poisson prior

The Histogram-Probabilistic Multi-Hypothesis Tracker (H-PMHT) is an efficient multi-target tracking approach to the Track-Before-Detect (TkBD) problem. However, it cannot adequately deal with fluctuating targets and this can degrade track management performance. By assuming an alternative measurement model based on a Poisson distribution, the H-PMHT algorithm can be re-derived to incorporate a time-correlated estimate of the component mixing terms, allowing for an improved measure for track quality.

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2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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