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Recursive joint Cramér‐Rao lower bound for parametric systems with two‐adjacent‐states dependent measurements

Li, Xianqing; Duan, Zhansheng; Hanebeck, Uwe D. 1,2
1 Graduiertenkolleg 1126: Intelligente Chirurgie (Graduiertenkolleg 1126), Karlsruher Institut für Technologie (KIT)
2 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

Joint Cramér-Rao lower bound (JCRLB) is very useful for the performance evaluation of joint state and parameter estimation (JSPE) of non-linear systems, in which the current measurement only depends on the current state. However, in reality, the non-linear systems with two-adjacent-states dependent (TASD) measurements, that is, the current measurement is dependent on the current state as well as the most recent previous state, are also common. First, the recursive JCRLB for the general form of such non-linear systems with unknown deterministic parameters is developed. Its relationships with the posterior CRLB for systems with TASD measurements and the hybrid CRLB for regular parametric systems are also provided. Then, the recursive JCRLBs for two special forms of parametric systems with TASD measurements, in which the measurement noises are autocorrelated or cross-correlated with the process noises at one time step apart, are presented, respectively. Illustrative examples in radar target tracking show the effectiveness of the JCRLB for the performance evaluation of parametric TASD systems.


Verlagsausgabe §
DOI: 10.5445/IR/1000135765
Veröffentlicht am 22.07.2021
Originalveröffentlichung
DOI: 10.1049/sil2.12025
Scopus
Zitationen: 5
Web of Science
Zitationen: 5
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 06.2021
Sprache Englisch
Identifikator ISSN: 1751-9675, 1751-9683
KITopen-ID: 1000135765
Erschienen in IET signal processing
Verlag Institution of Engineering and Technology (IET)
Band 15
Heft 4
Seiten 221–237
Vorab online veröffentlicht am 21.04.2021
Nachgewiesen in Scopus
Dimensions
Web of Science
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