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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| Veröffentlicht in: | IEEE signal processing letters Jg. 27; S. 650 - 654 |
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2020
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| Abstract | 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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| AbstractList | 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. |
| Author | Xu, Zhenhai Wang, Luoshengbin Liu, Xinghua Dong, Wei Li, Xiangyang |
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| SubjectTerms | 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 |
| Title | Cognitive Resource Allocation for Target Tracking in Location-Aware Radar Networks |
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