IEEE Transactions on Intelligent Transportation Systems, Year (2019-1)

Title : ( Multi-Target State Estimation Using Interactive Kalman Filter for Multi-Vehicle Tracking )

Authors: Maryam Baradaran Khalkhali , Abedin Vahedian Mazloum , Hadi Sadoghi Yazdi ,

Citation: BibTeX | EndNote

Abstract

Abstract— In this paper, an interactive Kalman filter -IKF-1is proposed to demonstrate the interaction between targets as to2how the behavior of a desired target is affected by the behavior of3its neighbors. The IKF utilizes two types of interactions available4in multi-agent systems, namely, cooperative and competitive.5The IKF is similar to the distributed Kalman filter -DKF- in6terms of architecture, method of representation of equations, and7use of neighborhood weight matrix while IKF appears to be a8general form of DKF. In this method, a network of IKF nodes is9constructed such that each node is associated with every target.10There are edges between nodes for which the corresponding11targets have effect on each other. Time-varying weights are12used to control the interaction information exchanged among13IKF nodes. The method of calculating interaction weights in14the weight matrix plays a key role on the estimation results.15The calculation of optimal IKF gain and evaluations on MOTP,16MOTA, and MSE metrics illustrate the effectiveness of the17proposed filter in vehicle tracking

Keywords

, Distributed Kalman filter, interactive Kalman19filter, multi agent systems, multi-target state estimation, 20multi-vehicle tracking, time-varying weights
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@article{paperid:1073637,
author = {Baradaran Khalkhali, Maryam and Vahedian Mazloum, Abedin and Sadoghi Yazdi, Hadi},
title = {Multi-Target State Estimation Using Interactive Kalman Filter for Multi-Vehicle Tracking},
journal = {IEEE Transactions on Intelligent Transportation Systems},
year = {2019},
month = {January},
issn = {1524-9050},
keywords = {Distributed Kalman filter; interactive Kalman19filter; multi agent systems; multi-target state estimation;20multi-vehicle tracking; time-varying weights},
}

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%0 Journal Article
%T Multi-Target State Estimation Using Interactive Kalman Filter for Multi-Vehicle Tracking
%A Baradaran Khalkhali, Maryam
%A Vahedian Mazloum, Abedin
%A Sadoghi Yazdi, Hadi
%J IEEE Transactions on Intelligent Transportation Systems
%@ 1524-9050
%D 2019

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