AI 中文总结
该研究针对多用户双基地ISAC系统，在发射符号已知和未知两种场景下，分别采用FP-SCA迭代设计与AO方法，联合优化波束成形和雷达接收滤波器，可在通信约束下提升雷达性能。
AI 中文摘要
本文研究多用户双基地集成感知与通信（ISAC）系统中波束成形与雷达接收滤波器的联合设计，旨在通信信干噪比（SINR）和发射功率约束下最大化最小雷达信干噪比（SINR）。考虑两种场景：雷达接收机处的发射信号为已知或未知。针对两种场景下的非凸优化问题，开发了可处理的解决方案。对于已知信号场景，推导了闭式雷达接收滤波器，并使用分式规划（FP）和逐次凸逼近（SCA）迭代设计波束成形。对于未知场景，采用交替优化（AO）方法联合设计波束成形和接收滤波器。数值结果表明，虽然两种方法在每时隙优化下实现了可比性能，但发射符号的知识通过相干积分在多时隙处理中提供了显著增益。此外，所提出的ISAC设计在适度通信要求下表现接近仅雷达基准。
英文摘要
This paper investigates the joint design of beamforming and radar receive filters in a multiuser bistatic integrated sensing and communications (ISAC) system, aiming to maximize the minimum radar signal-to-interference-plus-noise ratio (SINR) under communications SINR and transmit power constraints. We consider two scenarios: transmitted signals are either known or unknown at the radar receiver. We develop tractable solutions to the resulting non-convex optimization problems in both cases. For the known-signal case, we derive closed-form radar receive filters and iteratively design beamforming using fractional programming (FP) and successive convex approximation (SCA). For the unknown case, we adopt an alternating optimization (AO) approach to jointly design the beamforming and receive filters. Numerical results demonstrate that, while both approaches achieve comparable performance under per-slot optimization, knowledge of the transmitted symbols provides significant gains in multi-slot processing via coherent integration. Moreover, the proposed ISAC designs perform close to the radar-only benchmark under moderate communication requirements.
Comments5 pages, 3 figures. Accepted for presentation at the IEEE SPAWC 2026 conference
