Abstract
This paper puts forward a cooperative node selection and resource allocation strategy for search and track applications in radar network. The strategy is proposed to minimize the total energy consumption for searching and multi-target tracking (MTT) tasks by optimizing radar node selection, dwell time and transmit power allocation of multiple radar nodes cooperatively, while satisfying the given search and track requirements and several system resource budgets. We utilize the detection probability as the metric for searching, and the predicted Bayesian Cramér-Rao lower bound (BCRLB) is derived as the criterion for MTT performance, which are both concerned as constraints in the optimization model. Subsequently, a two-step solution algorithm based on the interior point method and cyclic minimization framework is proposed to tackle the underlying optimization problem. Simulation results verify that the proposed strategy consumes the least energy while ensuring the specified search and track performance demands, when compared with other existing algorithms.
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Acknowledgments
This work was supported by the Key Laboratory of Equipment Pre-Research Foundation under Grant 6142401200402.
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Shi, Z., Shi, C., Salous, S., Wang, F., Zhou, J. (2023). Cooperative Node Selection and Resource Allocation for Search and Track Applications in Radar Network. In: Fu, W., Gu, M., Niu, Y. (eds) Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022). ICAUS 2022. Lecture Notes in Electrical Engineering, vol 1010. Springer, Singapore. https://doi.org/10.1007/978-981-99-0479-2_120
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DOI: https://doi.org/10.1007/978-981-99-0479-2_120
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