Report
Trajectory PHD Filter with Unknown Detection Profile and Clutter Rate
| العنوان: | Trajectory PHD Filter with Unknown Detection Profile and Clutter Rate |
|---|---|
| المؤلفون: | Wei, Shaoxiu, Zhang, Boxiang, Yi, Wei |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | In this paper, we derive the robust TPHD (R-TPHD) filter, which can adaptively learn the unknown detection profile history and clutter rate. The R-TPHD filter is derived by obtaining the best Poisson posterior density approximation over trajectories on hybrid and augmented state space by minimizing the Kullback-Leibler divergence (KLD). Because of the huge computational burden and the short-term stability of the detection profile, we also propose the R-TPHD filter with unknown detection profile only at current time as an approximation. The Beta-Gaussian mixture model is proposed for the implementation, which is referred to as the BG-R-TPHD filter and we also propose a L-scan approximation for the BG-R-TPHD filter, which possesses lower computational burden. Comment: 7 pages |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2111.03871 |
| رقم الانضمام: | edsarx.2111.03871 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |