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Task Priority-Driven Resource Scheduling for Multi-Target Tracking in Asynchronous Phased Array Radar Networks
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DOI：10.1109/taes.2026.3733918.png)
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Abstract
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For multi-target mission scenarios, achieving perfect consistency in sampling frequency and precise time synchronization across the nodes of a radar system is often infeasible. In addition, due to significant differences in target categories, distances, and potential threat levels, the system must fully account for the impact of task priorities on performance. To address the multi-target tracking (MTT) problem in asynchronous phased array radar networks (APARNs) with heterogeneous sampling frequencies, this paper proposes a task priority-driven joint radar-to-target assignment and dwell time allocation (TP-JRADTA) strategy. The core idea is to coordinate the asynchronous dwell time resources of phased array radars (PARs) with different sampling frequencies to improve the MTT performance of the APARN in the track-and-search mode. By considering the task priority and measurement arrival time of each target within a fusion interval, the posterior Cramér–Rao lower bound (PCRLB) of the APARN is predicted to quantify the accuracy of asynchronous fusion estimation. Then, by combining the asynchronous resource constraints of the APARN with task timing requirements, a TP-JRADTA optimization problem is formulated. Taking into account the coupling among multiple variables and the non-convexity induced by task sequencing, this problem is NP-hard and cannot be directly solved by conventional optimization methods. Therefore, by combining multidimensional variable decoupling with a sequential dynamic programming (SDP) algorithm, an SDP-based two-stage approach is proposed to effectively solve this problem. Simulation results verify that under the task priority-driven resource scheduling framework, the proposed TP-JRADTA strategy optimizes resource allocation by minimizing the total tracking error, thereby improving the overall MTT performance.
Keywords:
Asynchronous radar network
resource scheduling
PCRLB
multi-target tracking
dynamic programming
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