低空无人机辅助双基地信息感知与通信一体化：闭式三维克拉美罗下界及覆盖分析
Low-Altitude UAV-Assisted Bistatic ISAC: Closed-form 3D CRLB and Coverage Analysis
浏览论文内容
中文总结 AI 辅助
研究无人机辅助ISAC系统三维定位性能极限，推导闭式三维CRLB表达式，验证其能紧密预测最大似然估计性能，还引入CRLB约束感知覆盖概念，揭示无人机相关因素对可靠感知区域的影响。
中文摘要 AI 辅助
本文研究了无人机辅助的综合感知与通信（ISAC）系统中三维定位的基本性能极限。具体而言，基站借助无人机作为灵活的空中锚节点来估计感知目标的三维位置。我们推导了三维克拉美罗下界（CRLB）的闭式表达式，它明确量化了可实现的定位精度与无人机位置和目标位置的函数关系。CRLB自然地分解为分别由信号传播延迟、角度测量及其耦合效应产生的三个不同分量。为验证分析结果，我们考虑了一个基于代表性正交频分复用（OFDM）的ISAC系统，并证明推导的CRLB能紧密预测不同几何配置和无人机移动模式下最大似然估计的性能。此外，我们引入了CRLB约束感知覆盖的概念来表征能保证规定定位精度的空间区域。通过局部边界近似和覆盖大小评估，揭示了无人机位移、高度和CRLB阈值如何共同塑造可靠感知区域的范围和几何形状。
英文摘要
This paper investigates the fundamental performance limits of three-dimensional (3D) localization in unmanned aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) systems. Specifically, a base station (BS) estimates the 3D position of a sensing target with the aid of a UAV acting as a flexible aerial anchor node. We derive a closed-form expression for the 3D Cramer-Rao lower bound (CRLB), which explicitly quantifies the achievable localization accuracy as a function of both the UAV's location and the target's position. The CRLB is shown to decompose naturally into three distinct components, arising from signal propagation delay, angular measurements, and their coupling effect, respectively. To validate the analytical results, we consider a representative orthogonal frequency-division multiplexing (OFDM)-based ISAC system and demonstrate that the derived CRLB closely predicts the performance of maximum-likelihood estimation across diverse geometric configurations and UAV mobility patterns. Furthermore, we introduce the notion of CRLB-constrained sensing coverage to characterize the spatial region within which a prescribed localization accuracy can be guaranteed. Through local boundary approximations and coverage-size evaluations, we reveal how UAV displacement, altitude, and the CRLB threshold jointly shape the extent and geometry of the reliable sensing region.
