Results 231 to 240 of about 785,259 (279)

Dim Target Tracking Base on GM-PHD Filter

2012
In this paper, a real time method for detecting and tracking multiple dim targets in deep space background is presented. We matched the stars in tow continuous images to get their speed at first and found moving targets through speed in both images. Using the targets in the common frame data association is achieved.
Lei Li 0009, Jinqiu Sun, Yu Zhu 0004, Haisen Li   +3 more
openaire   +1 more source

Interacting Methods for Manoeuvre Handling in the GM-PHD Filter

IEEE Transactions on Aerospace and Electronic Systems, 2011
Probability hypothesis density (PHD) filter implementations with jump Markov linear system (JMLS) manoeuvre handling are well known. A new derivation, following the method of the popular interacting multiple model (IMM) filter from single target tracking, is presented and is shown to be equivalent to existing implementations.
openaire   +1 more source

An explicit track continuity algorithm for the GM-PHD filter

2019 Chinese Control And Decision Conference (CCDC), 2019
In this study, an explicit track continuity algorithm is proposed for multi-target tracking (MTT) based on the Gaussian mixture (GM) implementation of the probability hypothesis density (PHD) filter. In this approach, the Gaussian components are classified and labeled, and multi-target state extraction is converted into multiple single-state ...
Yiyue Gao, Ni Fang, Defu Jiang, Wei Fu, Su Guo   +4 more
openaire   +1 more source

Road-Map Aided GM-PHD Filter for Multivehicle Tracking With Automotive Radar

IEEE Transactions on Industrial Informatics, 2022
Nowadays, accurate and real-time vehicle tracking is critical to ensure the safety of intelligent vehicles. However, tracking in the complex traffic environments still remains a challenging issue. In this article, we present a road-map aided Gaussian mixture probability hypothesis density (RA-GMPHD) filter for multivehicle tracking with automotive ...
Kun Shi 0003, Zhiguo Shi 0001, Chaoqun Yang 0001, Shibo He, Jiming Chen 0001, Anjun Chen   +5 more
openaire   +2 more sources

Data association for GM-PHD with track oriented PMHT

2010 3rd International Symposium on Systems and Control in Aeronautics and Astronautics, 2010
Gaussian Mixture probability hypothesis density (GM-PHD) filter is a closed-form solution to the probability hypothesis density filter, which could estimate states and time-varying number of targets based on theory of random finite set. Probability multiple hypotheses tracking (PMHT) is a multi-target tracking algorithm combining data association and ...
null Shicang Zhang, null Jianxun Li, null Binyi Fan, null Liangbin Wu   +3 more
openaire   +1 more source

A GM-PHD filter for new appearing targets tracking

2013 6th International Congress on Image and Signal Processing (CISP), 2013
Simulations reveal that the usual implementations of the Gaussian Mixture PHD filter can detect new targets only if its target-birth model is based on a priori knowledge of where new targets might appear. Otherwise, it cannot detect new targets (unless they happen to be near existing tracks) since it prunes Gaussian components that are not associated ...
Hongjiang Zhang, Jin Wang, Bei Ye, Yuewu Zhang   +3 more
openaire   +1 more source

Tracking Ground Targets with Road Constraints Using a JMS-GM-PHD Filter

2021 13th International Conference on Machine Learning and Computing, 2021
The probability hypothesis density filter with linear Gaussian jump Markov system multi-target models is an attractive approach to tracking multiple maneuvering targets in the presence of data association uncertainty, clutter, noise, and detection uncertainty.
Jihong Zheng, He He, Longteng Cong
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An improved GM-PHD tracker with track management for multiple target tracking

2015 International Conference on Control, Automation and Information Sciences (ICCAIS), 2015
The probability hypothesis density (PHD) filter is a promising tool for tracking the time-varying number of targets in real time. The Gaussian mixture PHD filter is an analytic solution to the PHD filter for linear Gaussian multi-target models. By using Gaussian component labels in GM-PHD filter, the identities of individual target can be obtained ...
Huanqing Zhang, Jinlong Yang 0002, Hongwei Ge, Le Yang 0001   +3 more
openaire   +2 more sources

Performance Improvement of Pedestrian Detection using a GM-PHD Filter

Journal of the Institute of Electronics and Information Engineers, 2015
Pedestrian detection has largely been researched as one of the important technologies for autonomous driving vehicle and preventing accidents. There are two categories for pedestrian detection, camera-based and LIDAR-based. LIDAR-based methods have the advantage of the wide angle of view and insensitivity of illuminance change while camera-based ...
Yeon-Jun Lee, Seung-Woo Seo
openaire   +1 more source

Occluded targets tracking using improved GM-PHD tracker

2012 IEEE 11th International Conference on Signal Processing, 2012
The closed-form solution for Probability Hypothesis Density (PHD) filter is Gaussian Mixture PHD (GM-PHD) filter which is applied for multiple-target tracking in noisy observation set. The main drawback of GM-PHD filter is its failure in keeping trajectories of targets. To solve the problem of GM-PHD filter, we propose Improved GM-PHD (IGM-PHD) tracker
Ali Adeli, Mahdi Yazdian-Dehkordi, Zohreh Azimifar, Omid Reza Rojhani   +3 more
openaire   +1 more source