标题： 具有能量感知约束的高空平台雷达系统轨迹和资源优化 显示英文标题

标题： Joint Trajectory and Resource Optimization for HAPs-SAR Systems with Energy-Aware Constraints

摘要： 本文研究了高空平台站合成孔径雷达（HAPs-SAR）系统的轨迹规划与资源分配的联合优化。 为了支持实时感知并节约HAPs的有限能量预算，所提出的框架假设获取的雷达数据实时传输到地面基站以进行SAR图像重建。 开发了一个动态轨迹模型，并全面分析了与雷达感知、数据传输和环形飞行相关的能耗。 此外，考虑了太阳能收集以提高系统可持续性。 提出了一个面向能源的混合整数非线性规划（MINLP）问题，以在满足操作约束的同时最大化雷达波束覆盖范围。 为了解决这个具有挑战性的问题，提出了一种基于次优连续凸逼近（SCA）的框架，结合了迭代优化和有限搜索。 仿真结果验证了所提出算法的收敛性，并证明了其在平衡SAR性能、通信可靠性和能源效率方面的有效性。 对一个9目标晶格场景的最终SAR成像仿真进一步证实了所提出解决方案的实际可行性。 显示英文摘要

摘要： This paper investigates the joint optimization of trajectory planning and resource allocation for a high-altitude platform stations synthetic aperture radar (HAPs-SAR) system. To support real-time sensing and conserve the limited energy budget of the HAPs, the proposed framework assumes that the acquired radar data are transmitted in real time to a ground base station for SAR image reconstruction. A dynamic trajectory model is developed, and the power consumption associated with radar sensing, data transmission, and circular flight is comprehensively analyzed. In addition, solar energy harvesting is considered to enhance system sustainability. An energy-aware mixed-integer nonlinear programming (MINLP) problem is formulated to maximize radar beam coverage while satisfying operational constraints. To solve this challenging problem, a sub-optimal successive convex approximation (SCA)-based framework is proposed, incorporating iterative optimization and finite search. Simulation results validate the convergence of the proposed algorithm and demonstrate its effectiveness in balancing SAR performance, communication reliability, and energy efficiency. A final SAR imaging simulation on a 9-target lattice scenario further confirms the practical feasibility of the proposed solution.