Manoeuvring target tracking using multiple bistatic range and range-rate measurements

Petsios, MN; Alivizatos, EG; Uzunoglu, NK

dc.contributor.author	Petsios, MN	en
dc.contributor.author	Alivizatos, EG	en
dc.contributor.author	Uzunoglu, NK	en
dc.date.accessioned	2014-03-01T01:26:34Z
dc.date.available	2014-03-01T01:26:34Z
dc.date.issued	2007	en
dc.identifier.issn	0165-1684	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18138
dc.subject	Cramer-Rao bound	en
dc.subject	Interacting multiple model	en
dc.subject	Iterated unscented Kalman filter	en
dc.subject	Manoeuvring target	en
dc.subject	Multistatic radar	en
dc.subject	Nonlinear tracking	en
dc.subject	Sequential iterated extended Kalman filter	en
dc.subject	Target tracking	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Algorithms	en
dc.subject.other	Computational complexity	en
dc.subject.other	Computer simulation	en
dc.subject.other	Error analysis	en
dc.subject.other	Kalman filtering	en
dc.subject.other	Mathematical models	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Problem solving	en
dc.subject.other	Radar	en
dc.subject.other	Cramer-Rao bound	en
dc.subject.other	Interacting multiple model	en
dc.subject.other	Iterated unscented Kalman filter	en
dc.subject.other	Manoeuvring target	en
dc.subject.other	Multistatic radar	en
dc.subject.other	Nonlinear tracking	en
dc.subject.other	Sequential iterated extended Kalman filter	en
dc.subject.other	Target tracking	en
dc.subject.other	Tracking (position)	en
dc.title	Manoeuvring target tracking using multiple bistatic range and range-rate measurements	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.sigpro.2006.07.003	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.sigpro.2006.07.003	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	This paper investigates the problem of manoeuvring target tracking, using multiple bistatic range and bistatic range-rate measurements from a number of bistatic radars, consisting a multistatic radar. The contribution of the paper is twofold. First, a theoretical lower bound of the performance error is derived and analyzed. Second, four filtering algorithms are proposed, presented and compared to the theoretical bound. The proposed algorithms include: (i) sequential iterated extended Kalman filter (SI-EKF), (ii) iterated unscented Kalman filter (I-UKF), (iii) interactive multiple model algorithm combined with sequential iterated extended Kalman filter (IMM-SI-EKF), and (iv) interactive multiple model algorithm combined with iterated unscented Kalman filter (IMM-I-UKF). Monte Carlo simulation demonstrates the track accuracy performance and computational complexity of each algorithm for manoeuvring targets. (c) 2006 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Signal Processing	en
dc.identifier.doi	10.1016/j.sigpro.2006.07.003	en
dc.identifier.isi	ISI:000242727800007	en
dc.identifier.volume	87	en
dc.identifier.issue	4	en
dc.identifier.spage	665	en
dc.identifier.epage	686	en