For a dwell time limited radar network, the achievable tracking performance can be further enhanced by adaptively tuning in the dwell time allocation strategy to accommodate the future operation scenario. In this paper, considering this dynamical resource allocation problem, a cone programming-based dwell time allocation scheme is proposed for achieving the optimal tracking performance. The basic mechanism is to exploit the feedback of its operating environment based on the interrogation of received echoes for informing the decision of future optimal dwell time allocation. To achieve this purpose, the predicted conditional Cramer-Rao lower bound (PC-CRLB) of target state estimates is developed for evaluating the tracking performance of each candidate allocation strategy conditioned on the cognitive knowledge firstly. And, its trace is chosen as a scalar allocation strategy evaluation metric. On this basis, the closed-form expression of the scalar evaluation metric is derived, which enables us to transform the dwell time allocation problem into the second-order cone program (SOCP). Extensive simulations demonstrate the efficiency and superiority of the proposed allocation scheme.

中文翻译：

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分布式雷达传感器网络通过锥规划跟踪的认知停留时间分配

对于驻留时间有限的雷达网络，可通过自适应调整驻留时间分配策略以适应未来的操作场景，进一步增强可实现的跟踪性能。在本文中，考虑到这种动态资源分配问题，提出了一种基于锥规划的驻留时间分配方案，以实现最佳跟踪性能。基本机制是基于对接收回波的询问，利用其操作环境的反馈来通知未来最佳驻留时间分配的决定。为了实现这一目的，首先开发了目标状态估计的预测条件 Cramer-Rao 下界 (PC-CRLB)，用于评估每个候选分配策略的跟踪性能，该策略首先以认知知识为条件。和，其轨迹被选为标量分配策略评估指标。在此基础上，推导出标量评价指标的闭式表达式，使我们能够将停留时间分配问题转化为二阶锥规划（SOCP）。广泛的模拟证明了所提出的分配方案的效率和优越性。