Reference : A Hybrid Approach to Optimal TOA-Sensor Placement With Fixed Shared Sensors for Simul...
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/53597
A Hybrid Approach to Optimal TOA-Sensor Placement With Fixed Shared Sensors for Simultaneous Multi-Target Localization
English
Xu, Sheng mailto [Shenzhen Institute of Advanced Technology]
Wu, Linlong mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC >]
Doğançay, Kutluyıl mailto [University of South Australia > UniSA STEM]
Alaeekerahroodi, Mohammad mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC >]
23-Feb-2022
IEEE Transactions on Signal Processing
Institute of Electrical and Electronics Engineers
Yes
International
1053-587X
United States
[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.
http://hdl.handle.net/10993/53597
H2020 ; 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
FnR ; FNR12734677 > Bjorn Ottersten > SPRINGER > Signal Processing For Next Generation Radar > 01/09/2019 > 31/08/2022 > 2018

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