Volume 11 Issue 5
Oct.  2022
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SHI Chenguang, WANG Yijie, DAI Xiangrong, et al. Joint transmit resources and trajectory planning for target tracking in airborne radar networks[J]. Journal of Radars, 2022, 11(5): 778–793. doi: 10.12000/JR22005
Citation: SHI Chenguang, WANG Yijie, DAI Xiangrong, et al. Joint transmit resources and trajectory planning for target tracking in airborne radar networks[J]. Journal of Radars, 2022, 11(5): 778–793. doi: 10.12000/JR22005

Joint Transmit Resources and Trajectory Planning for Target Tracking in Airborne Radar Networks

doi: 10.12000/JR22005
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
More Information
  • Corresponding author: SHI Chenguang, scg_space@163.com
  • Received Date: 2022-01-07
  • Accepted Date: 2022-02-28
  • Rev Recd Date: 2022-02-27
  • Available Online: 2022-03-09
  • Publish Date: 2022-03-21
  • This paper investigates the joint optimization problem of transmit resources and trajectory planning for target tracking in airborne radar networks. First, the analytical expression for the Bayesian Cramér-Rao Lower Bound (BCRLB) with the variables of the radar transmit power, dwell time, transmit signal Gaussian pulse length and signal bandwidth, and speed and heading angle of airborne nodes is derived and adopted as the metric function to evaluate the target tracking accuracy. In addition, the analytical expression of intercept probability with the variables of the radar transmit power, dwell time, and speed and heading angle of airborne nodes is also derived and utilized as the metric function to gauge the radio frequency stealth performance of the overall system. On this basis, a joint optimization model of transmit resources and trajectory planning for target tracking in airborne radar networks is established to jointly optimize the radar transmit power, dwell time, transmit signal Gaussian pulse length and signal bandwidth, and speed and heading angle of airborne nodes. This is done to minimize the target estimation error BCRLB under the constraints of given system resources, aircraft maneuvering and intercept probability threshold, thereby improving the target tracking accuracy of airborne radar network. Subsequently, a five-step decomposition iterative algorithm incorporating the particle swarm algorithm is used to solve the underlying optimization problem. The simulation results demonstrate that the target tracking accuracy of the proposed algorithm outperforms other existing approaches.

     

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