Cognitive Resource Allocation for Target Tracking in Location-Aware Radar Networks

In this letter, a general framework of cognitive resource allocation for target tracking in radar networks is proposed. Firstly, an allocation strategy evaluation metric is established in this framework, i.e., the predicted conditional Cramer-Rao lower bound (PC-CRLB), for evaluating the future resp...

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Bibliographic Details
Published in:IEEE signal processing letters Vol. 27; pp. 650 - 654
Main Authors: Liu, Xinghua, Xu, Zhenhai, Dong, Wei, Wang, Luoshengbin, Li, Xiangyang
Format: Journal Article
Language:English
Published: New York IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Cognitive resource allocation
conic programming
Cramer-Rao bounds
Dwell time
Lower bounds
Mathematical analysis
Optimization
Radar cross-sections
Radar networks
Radar tracking
Resource allocation
Resource management
Strategy
Target tracking
ISSN:1070-9908, 1558-2361
Online Access:Get full text
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Summary:In this letter, a general framework of cognitive resource allocation for target tracking in radar networks is proposed. Firstly, an allocation strategy evaluation metric is established in this framework, i.e., the predicted conditional Cramer-Rao lower bound (PC-CRLB), for evaluating the future response of each candidate allocation strategy. Then, the optimal resource allocation strategy can be found by solving a constrained optimization problem. To specify the framework implementation details, a dwell time allocation problem is considered. For this given problem, the analytical expressions of PC-CRLB and its derived scalar strategy evaluation metric are derived, enabling us to convert the allocation problem to a second-order cone program (SOCP). Numerical results demonstrate the effectiveness of the proposed framework.
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2020.2987208