Volume 12 Issue 3
Jun.  2023
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Article Navigation >  Journal of Radars  > 2023  >  12(3): 590-601
SHI Chenguang, DONG Jing, and ZHOU Jianjiang. Joint transmit power and dwell time allocation for multitarget tracking in radar networks under spectral coexistence[J]. Journal of Radars, 2023, 12(3): 590–601. doi: 10.12000/JR22146
Citation: SHI Chenguang, DONG Jing, and ZHOU Jianjiang. Joint transmit power and dwell time allocation for multitarget tracking in radar networks under spectral coexistence[J]. Journal of Radars, 2023, 12(3): 590–601. doi: 10.12000/JR22146
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Joint Transmit Power and Dwell Time Allocation for Multitarget Tracking in Radar Networks under Spectral Coexistence

DOI: 10.12000/JR22146

  • Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Funds:  The National Natural Science Foundation of China (62271247, 61801212), The National Ministries Foundation, The National Aerospace Science Foundation of China (20200020052005, 20200020052002), The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics
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  • Corresponding author: SHI Chenguang, scg_space@163.com
  • Received Date: 2022-07-13
  • Accepted Date: 2022-08-25
  • Rev Recd Date: 2022-08-24
    • Available Online: 2022-08-25
  • Publish Date: 2022-09-01
    Abstract
  • For the resource allocation problem of multitarget tracking in a spectral coexistence environment, this study proposes a joint transmit power and dwell time allocation algorithm for radar networks. First, the predicted Bayesian Cramér-Rao Lower Bound (BCRLB) with the variables of radar node selection, transmit power and dwell time is derived as the performance metric for multi-target tracking accuracy. On this basis, a joint optimization model of transmit power and dwell time allocation for multitarget tracking in radar networks under spectral coexistence is built to collaboratively optimize the radar node selection, transmit power and dwell time of radar networks, This joint optimization model aims to minimize the multitarget tracking BCRLB while satisfying the given transmit resources of radar networks and the predetermined maximum allowable interference energy threshold of the communication base station. Subsequently, for the aforementioned optimization problem, a two-step decomposition method is used to decompose it into multiple subconvex problems, which are solved by combining the Semi-Definite Programming (SDP) and cyclic minimization algorithms. The simulation results showed that, compared with the existing algorithms, the proposed algorithm can effectively improve the multitarget tracking accuracy of radar networks while ensuring that the communication base station works properly.

     

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