[en] This paper focuses on optimal time-of-arrival (TOA) sensor placement for multiple target localization simultaneously. In previous work, different solutions only using non-shared sensors to localize multiple targets have been developed. Those methods localize different targets one-by-one or use a large number of mobile sensors with many limitations, such as low effectiveness and high network complexity. In this paper, firstly, a novel optimization model for multi-target localization incorporating shared sensors is formulated. Secondly, the systematic theoretical results of the
optimal sensor placement are derived and concluded using the A-optimality criterion, i.e., minimizing the trace of the inverse Fisher information matrix (FIM), based on rigorous geometrical derivations. The reachable optimal trace of Cramér-Rao lower bound (CRLB) is also derived. It can provide optimal conditions for many cases and even closed form solutions for some special cases. Thirdly, a novel numerical optimization algorithm to quickly find and calculate the (sub-)optimal placement and achievable lower bound is explored, when the model becomes complicated with more practical constraints. Then, a hybrid method for solving the most general situation, integrating both the analytical and numerical solutions, is proposed. Finally, the correctness and effectiveness of the proposed theoretical and mathematical methods are demonstrated by several simulation examples.
Disciplines :
Ingénierie électrique & électronique
Auteur, co-auteur :
Xu, Sheng; Shenzhen Institute of Advanced Technology
WU, Linlong ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
Doğançay, Kutluyıl; University of South Australia > UniSA STEM
Autre collaborateur :
ALAEEKERAHROODI, Mohammad ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A Hybrid Approach to Optimal TOA-Sensor Placement With Fixed Shared Sensors for Simultaneous Multi-Target Localization
Date de publication/diffusion :
23 février 2022
Titre du périodique :
IEEE Transactions on Signal Processing
ISSN :
1053-587X
Maison d'édition :
Institute of Electrical and Electronics Engineers, Etats-Unis
Peer reviewed :
Peer reviewed vérifié par ORBi
Projet européen :
H2020 - 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
Projet FnR :
FNR12734677 - Signal Processing For Next Generation Radar, 2018 (01/09/2019-31/08/2022) - Bjorn Ottersten
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