Unmanned aerial vehicles (UAVs) as aerial base stations (BSs) are able to provide not only the communication service to ground users, but also the sensing functionality to localize targets of interests. In this paper, we consider an airborne integrated sensing and communications (ISAC) system where a UAV, which acts both as a communication BS and a mono-static radar, flies over a given area to transmit downlink signal to a ground communication user. In the meantime, the same transmitted signal is also exploited for mono-static radar sensing. We aim to optimize the UAV trajectory, such that the performance for both communication and sensing (C$\&$S) is explicitly considered. In particular, we first formulate the trajectory design problem into a weighted optimization problem, where a flexible performance trade-off between C$\&$S is achieved. As a step forward, a multi-stage trajectory design approach is proposed to improve the target estimation accuracy. While the resultant optimization problem is difficult to solve directly, we develop an iterative algorithm to obtain a locally optimal solution. Finally, numerical results show that the target estimation error obtained by the trade-off approach is about an order of magnitude better than a communication-only approach with a slight decrease on communication performance.
翻译:作为空基站的无人驾驶航空飞行器(无人驾驶飞行器)不仅能够向地面用户提供通信服务,而且能够提供将利益对象本地化的遥感功能。在本文中,我们考虑的是一个空中综合遥感和通信系统(ISAC),无人驾驶飞行器既作为通信BS又作为单一静态雷达,飞越一个特定区域,向地面通信用户传输下行连接信号。与此同时,同一传输信号也用于单一静态雷达感测。我们的目标是优化无人驾驶飞行器的轨迹,例如明确考虑通信和遥感的性能(C$+$S),特别是,我们首先将轨迹设计问题发展成一个加权优化问题,在轨迹设计上实现C$+$的灵活性能权衡。作为向前一步,建议采用多阶段轨迹设计方法来提高目标估计的准确性。虽然结果优化问题难以直接解决,但我们开发了一种迭代算法,以获得一个当地最佳的解决方案。最后,数字结果显示,从贸易与遥感方法获得的目标估计误差,比通信的性能略下降。