Box-Particle Labeled Multi-Bernoulli Filter for Mltiple Extended Target Tracking
نویسندگان
چکیده
منابع مشابه
Box-Particle Labeled Multi-Bernoulli Filter for Multiple Extended Target Tracking
This paper focuses on real-time tracking of multiple extended targets in clutter based on labeled multiBernoulli filter. To address this problem, a novel approach is proposed within the recently presented box-particle framework. Unlike the traditional point-particle approach, the measurements of extended targets are modeled as interval measurements in this work, and the corresponding likelihood...
متن کاملBox-Particle PHD Filter for Multi-Target Tracking
This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable to deal with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-PHD filter reduces the numbe...
متن کاملA New Modified Particle Filter With Application in Target Tracking
The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...
متن کاملProbabilistic Detection-based Particle Filter for Multi-target Tracking
In this paper, we present a Probabilistic Detection-based Particle Filter (PD-PF) for tracking a variable number of interacting targets. When the objects do not interact with each other, our method performs like the deterministic detection-base methods. When the objects are in close proximity, the interactions and occlusions are modelled by a mixed proposal constructed by probabilistic detectio...
متن کاملMulti-Target Tracking Based on Multi-Bernoulli Filter with Amplitude for Unknown Clutter Rate
Knowledge of the clutter rate is of critical importance in multi-target Bayesian tracking. However, estimating the clutter rate is a difficult problem in practice. In this paper, an improved multi-Bernoulli filter based on random finite sets for multi-target Bayesian tracking accommodating non-linear dynamic and measurement models, as well as unknown clutter rate, is proposed for radar sensors....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Radioengineering
سال: 2016
ISSN: 1210-2512
DOI: 10.13164/re.2016.0527