面向多目标公平性的异构多雷达功率―时间联合优化方法

    A Joint Power-time Resource Optimization Method for Multi-target Fairness in Heterogeneous Multi-radar Systems

    • 摘要: 针对异构多雷达多目标跟踪资源受限时最不利目标跟踪性能易下降的问题,文中提出了一种面向多目标公平性的功率―驻留时间联合优化方法。首先,根据不同雷达的资源特性构建异构多雷达跟踪模型,以贝叶斯克拉美-罗下界(BCRLB)表征目标跟踪精度;然后引入最不利情况准则,以最小化最大BCRLB为目标建立联合优化模型,使有限资源优先向观测条件较差的目标倾斜;最后采用原对偶投影次梯度方法求解。仿真结果表明,所提方法能够有效降低最不利目标的BCRLB,缩小目标间跟踪精度差距,提高资源受限条件下的多目标跟踪性能均衡性。

       

      Abstract: To address the issue of degraded tracking performance of the worst-case target in heterogeneous multi-radar multi-target tracking under resource constraints, a joint power-dwell time optimization method for multi-target fairness is proposed. First, a heterogeneous multi-radar tracking model is established according to the resource characteristics of different radars, and the Bayesian Cramér-Rao lower bound (BCRLB) is adopted to characterize target tracking accuracy. Then, a joint optimization model is formulated by introducing a worst-case criterion and aiming to minimize the maximum BCRLB, thereby prioritizing the allocation of limited resources to targets with poor observation conditions. Finally, a primal-dual projected subgradient method is employed to solve the optimization problem. Simulation results demonstrate that the proposed method can effectively reduces the BCRLB of the worst-case target, narrow the tracking accuracy gap among targets, and improve the balance of multi-target tracking performance under resource-limited conditions.

       

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