Multiellipsoidal extended target tracking with known extent using sequential Monte Carlo framework
نویسندگان
چکیده
منابع مشابه
A Sequential Monte Carlo Framework for Extended Object Tracking
In this paper we consider the problem of extended object tracking. An extended object is modelled as a set of point features in a target reference frame. The dynamics of the extended object are formulated in terms of the translation and rotation of the target reference frame relative to a fixed reference frame. This leads to realistic, yet simple, models for the object motion. We assume that th...
متن کاملJoint Target Tracking and Classification via Sequential Monte Carlo Filtering
A sequential Monte Carlo algorithm is suggested for joint maneuvering target tracking and classification, based on kinematic measurements. A mixture Kalman filter is designed for two-class identification of air targets: commercial and military aircraft. Speed and acceleration constraints are imposed on the target behaviour models in order to improve the classification process. The class is mode...
متن کاملSequential Monte Carlo-guided ensemble tracking
A great deal of robustness is allowed when visual tracking is considered as a classification problem. This paper combines a finite number of weak classifiers in a SMC framework as a strong classifier. The time-varying ensemble parameters (confidence of weak classifiers) are regarded as sequential arriving states and their posterior distribution is estimated in a Bayesian manner. Therefore, both...
متن کاملPulse pressure variation tracking using sequential Monte Carlo methods
The pulse pressure variation (PPV) is a measure of the respiratory effect on the variation of systemic arterial blood pressure (ABP) in patients receiving full mechanical ventilation. It is a promising predictor of increases in cardiac output due to an infusion of fluid. We describe a novel automatic algorithm to estimate the PPV of ABP signals recorded under full respiratory support. The algor...
متن کاملMultiple target tracking using Sequential Monte Carlo Methods and statistical data association
This paper presents two approaches for the problem of Multiple Target Tracking (MTT) and specifically people tracking. Both filters are based on Sequential Monte Carlo Methods (SMCM) and Joint Probability Data Association (JPDA). The filters have been implemented and tested on real data from a laser measurement system. Experiments show that both approaches are able to track multiple moving pers...
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: TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
سال: 2019
ISSN: 1303-6203
DOI: 10.3906/elk-1811-52