Optimal allocation of shared resources is key to deliver the promise of jointly operating radar and communications systems. In this paper, unlike prior works which examine synergistic access to resources in colocated joint radar-communications or among identical systems, we investigate this problem for a distributed system comprising heterogeneous radars and multi-tier communications. In particular, we focus on resource allocation in the context of multi-target tracking (MTT) while maintaining stable communications connections. By simultaneously allocating the available power, dwell time and shared bandwidth, we improve the MTT performance under a Bayesian tracking framework and guarantee the communications throughput. Our a{a} lter n{n} ating allo c{c} ation of h{h} eterogene o{o} us r{r} esources (ANCHOR) approach solves the resulting non-convex problem based on the alternating optimization method that monotonically improves the Bayesian Cramér-Rao bound. Numerical experiments demonstrate that ANCHOR significantly improves the tracking error over two baseline allocations and stability under different target scenarios and radar-communications network distributions.

中文翻译：

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异步贝叶斯跟踪框架下异构分布式联合雷达通信的资源分配


共享资源的优化分配是实现雷达和通信系统联合运行承诺的关键。在本文中，与先前研究共置联合雷达通信或相同系统之间对资源的协同访问的研究不同，我们研究了由异构雷达和多层通信组成的分布式系统的这个问题。特别是，我们专注于多目标跟踪（MTT）背景下的资源分配，同时保持稳定的通信连接。通过同时分配可用功率、停留时间和共享带宽，我们提高了贝叶斯跟踪框架下的 MTT 性能并保证了通信吞吐量。我们的 a{a} lter n{n} ating alloc c} of h{h} eterogene o{o} us r{r} 资源 (ANCHOR) 方法基于交替优化方法解决了由此产生的非凸问题单调改进贝叶斯 Cramér-Rao 界限。数值实验表明，ANCHOR 显着改善了两个基线分配的跟踪误差以及不同目标场景和雷达通信网络分布下的稳定性。