OFDM-ISAC系统中的目标检测：一种多径利用方法
Target Detection in OFDM-ISAC Systems: A Multipath Exploitation Approach
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中文总结 AI 辅助
针对OFDM基ISAC系统的目标检测问题，提出利用延迟-多普勒域分集增益的加权GLRT检测器，结合子载波功率与检测器权重联合优化框架，用MM迭代算法求解非凸问题，显著提升多径环境下的检测性能。
中文摘要 AI 辅助
本文研究了多径利用对于提升基于正交频分复用（OFDM）的集成感知与通信（ISAC）系统目标检测性能的潜力，旨在通过利用延迟-多普勒域的分集增益改善目标检测效果。我们提出了一种加权广义似然比检验（GLRT）检测器，可有效利用基站（BS）与目标之间的多径传播特性。为进一步提升检测精度，本文构建了一个联合优化框架，用于优化发射端的子载波功率分配与GLRT检测器的权重系数，优化目标是在满足总发射功率约束与通信接收机信噪比（SNR）约束的前提下，最大化目标检测概率。本文采用基于优化-最小化（MM）方法的迭代算法求解由此产生的非凸优化问题。仿真结果验证了所提算法的有效性，证实了在多径丰富的环境下，多径利用对OFDM-ISAC系统目标检测的增益作用。
英文摘要
This paper investigates the potential of multipath exploitation for enhancing target detection in orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems. The study aims to improve target detection performance by harnessing the diversity gain in the delay-Doppler domain. We propose a weighted generalized likelihood ratio test (GLRT) detector that effectively leverages the multipath propagation between the base station (BS) and the target. To further enhance detection accuracy, a joint optimization framework is developed for subcarrier power allocation at the transmitter and weight coefficients of the GLRT detector. The objective is to maximize the probability of target detection while satisfying constraints on total transmit power and the communication receiver's signal-to-noise ratio (SNR). An iterative algorithm based on the majorization-minimization (MM) method is employed to address the resulting non-convex optimization problem. Simulation results demonstrate the efficacy of the proposed algorithm and confirm the benefits of multipath exploitation for target detection in OFDM-ISAC systems under multipath-rich environments.
