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| Citation: | YUAN Ye, YANG Jian, LIU Xinyu, et al. Multiradar collaborative task planning based on task utility maximization[J]. Journal of Radars, 2023, 12(3): 550–562. doi: 10.12000/JR23013
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Multiradar Collaborative Task Planning Based on Task Utility Maximization
doi: 10.12000/JR23013
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Abstract
A utility maximization-based multiradar online task planning algorithm aiming at the real-time multitask planning problem is proposed in this paper. Using the maximization of the task utility function as the objective, multiradar task planning is formulated as an integer programming-based mixed multivariable optimization problem. Then, two algorithms, namely heuristic greedy search and convex relaxation-based two-step decoupling are proposed to solve the resulting NP-hard optimization problem in polynomial time, respectively. Simulation experiments demonstrate that compared with the optimal exhaustive search algorithm, the proposed algorithms can effectively reduce the computing time or improve solution efficiency such that the real-time requirement of online task planning can be satisfied. -
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References
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- Figure 1. An illustration of the concepts for task arrangement and task scheduling
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Figure 2. Schematic diagram of the task scheduling with
$N = 2,{\text{ }}Q = 8$ - Figure 3. Schematic diagram of the CRTSD algorithm
- Figure 4. Task scenario of multiradar with multitask
- Figure 5. Multiradar-multitask scheduling results of the three algorithms
- Figure 6. The task execution order of each radar under the three algorithms
- Figure 7. Task utility values of the three algorithms with different number of tasks Q
- Figure 8. Runtime of the three algorithms with different number of tasks Q
- Figure 9. Task scheduling results of CRTSD algorithm with different radar configurations
- Figure 10. Task utility values of CRTSD algorithm with different task priorities