Volume 13 Issue 3
Jun.  2024
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SHI Chenguang, TANG Zhicheng, ZHOU Jianjiang, et al. Joint collaborative radar selection and transmit resource allocation in multiple distributed radar networks with imperfect detection performance[J]. Journal of Radars, 2024, 13(3): 565–583. doi: 10.12000/JR23081
Citation: SHI Chenguang, TANG Zhicheng, ZHOU Jianjiang, et al. Joint collaborative radar selection and transmit resource allocation in multiple distributed radar networks with imperfect detection performance[J]. Journal of Radars, 2024, 13(3): 565–583. doi: 10.12000/JR23081

Joint Collaborative Radar Selection and Transmit Resource Allocation in Multiple Distributed Radar Networks with Imperfect Detection Performance

DOI: 10.12000/JR23081
Funds:  The National Natural Science Foundation of China (62271247), The Defense Industrial Technology Development Program (JCKY2021210B004), The Prospective Layout of Scientific Research Special Funds of Nanjing University of Aeronautics and Astronautics, Dreams Foundation of Jianghuai Advance Technology Center (2023-ZM01D001)
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  • Corresponding author: SHI Chenguang, scg_space@163.com
  • Received Date: 2023-05-09
  • Rev Recd Date: 2023-07-14
  • Available Online: 2023-07-18
  • Publish Date: 2023-08-01
  • In this study, a collaborative radar selection and transmit resource allocation strategy is proposed for multitarget tracking applications in multiple distributed phased array radar networks with imperfect detection performance. The closed-form expression for the Bayesian Cramér-Rao Lower Bound (BCRLB) with imperfect detection performance is obtained and adopted as the criterion function to characterize the precision of target state estimates. The key concept of the developed strategy is to collaboratively adjust the radar node selection, transmitted power, and effective bandwidth allocation of multiple distributed phased array radar networks to minimize the total transmit power consumption in an imperfect detection environment. This will be achieved under the constraints of the predetermined tracking accuracy requirements of multiple targets and several illumination resource budgets to improve its radio frequency stealth performance. The results revealed that the formulated problem is a mixed-integer programming, nonlinear, and nonconvex optimization model. By incorporating the barrier function approach and cyclic minimization technique, an efficient four-step-based solution methodology is proposed to solve the resulting optimization problem. The numerical simulation examples demonstrate that the proposed strategy can effectively reduce the total power consumption of multiple distributed phased array radar networks by at least 32.3% and improve its radio frequency stealth performance while meeting the given multitarget tracking accuracy requirements compared with other existing algorithms.

     

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