Reference : Integrated Trajectory Optimization and Cubature Kalman Filter for UAV-Based Target Tr...

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/53615

Title :	Integrated Trajectory Optimization and Cubature Kalman Filter for UAV-Based Target Tracking with Unknown Initial Position
Language :	English
Author, co-author :	Xu, Sheng [> >]
	Wu, Linlong [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC]
	MR, Bhavani Shankar [> >]
	Babu, Prabhu [> >]
Publication date :	2022
Main document title :	2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)
Pages :	331--335
Peer reviewed :	Yes
Event name :	2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)
Event date :	from 20-06-2022 to 23-06-2022
Event organizer :	IEEE
Abstract :	[en] This paper investigates the target localization/tracking by angle-of-arrival (AOA) sensors carried on an unmanned aerial vehicle (UAV). In many practical applications, the UAV's own position is not available, since the global position system (GPS) can hardly work in the indoor environment or interference region. Therefore, considering the unknown initial position of the UAV, a modified cubature Kalman filter (CKF) is developed to estimate both the target states and UAV's initial position jointly by leveraging a benchmark anchor. To further improve the estimation efficiency, we propose an algorithm to optimize the UAV flying trajectory by minimizing the the trace of the estimation covariance matrix in the CKF. According to the simulation results, an observation is found that the UAV will keeping flying alternatively between the anchor and target to guarantee the estimation performance.
Permalink :	http://hdl.handle.net/10993/53615
Framework Programme / European Project :	H2020 ; 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
FnR project :	FnR ; FNR12734677 > Bjorn Ottersten > SPRINGER > Signal Processing For Next Generation Radar > 01/09/2019 > 31/08/2022 > 2018

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