Cognitive Dwell Time Allocation for Distributed Radar Sensor Networks Tracking via Cone Programming

For a dwell time limited radar network, the achievable tracking performance can be further enhanced by adaptively tuning in the dwell time allocation strategy to accommodate the future operation scenario. In this paper, considering this dynamical resource allocation problem, a cone programming-based...

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Vydané v:IEEE sensors journal Ročník 20; číslo 10; s. 5092 - 5101
Hlavní autori: Liu, Xinghua, Xu, Zhen-Hai, Wang, Luoshengbin, Dong, Wei, Xiao, Shunping
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 15.05.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1530-437X, 1558-1748
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Shrnutí:For a dwell time limited radar network, the achievable tracking performance can be further enhanced by adaptively tuning in the dwell time allocation strategy to accommodate the future operation scenario. In this paper, considering this dynamical resource allocation problem, a cone programming-based dwell time allocation scheme is proposed for achieving the optimal tracking performance. The basic mechanism is to exploit the feedback of its operating environment based on the interrogation of received echoes for informing the decision of future optimal dwell time allocation. To achieve this purpose, the predicted conditional Cramer-Rao lower bound (PC-CRLB) of target state estimates is developed for evaluating the tracking performance of each candidate allocation strategy conditioned on the cognitive knowledge firstly. And, its trace is chosen as a scalar allocation strategy evaluation metric. On this basis, the closed-form expression of the scalar evaluation metric is derived, which enables us to transform the dwell time allocation problem into the second-order cone program (SOCP). Extensive simulations demonstrate the efficiency and superiority of the proposed allocation scheme.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2020.2970280