This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is dedicatedly deployed to assist an access point (AP) to sense a target at its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. The AP aims to estimate the target's direction-of-arrival (DoA) with respect to the IRS based on the echo signal from the AP-IRS-target-IRS-AP link. Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the DoA estimation error in terms of Cram\'er-Rao lower bound (CRLB). Towards this end, we first obtain the closed-form expression of CRLB for DoA estimation. Next, we optimize the joint beamforming design to minimize the obtained CRLB, via alternating optimization, semi-definite relaxation, and successive convex approximation. Finally, numerical results show that the proposed design based on CRLB minimization achieves improved sensing performance in terms of lower estimation mean squared error (MSE), as compared to the traditional schemes with signal-to-noise ratio maximization and separate beamforming designs.
翻译:本文调查智能反射表面(IRS)使非视觉(NLOS)无线的无线遥感,在该图中,我们专门部署IRS协助一个接入点(AP)在NLOS区域感知目标;假设AP配备了多天天线,IRS配备了统一的线性阵列;AP的目的是根据AP-IRS-目标(NLOS)-IRS-AP链接的回声信号,估计目标抵达方向(DoA)相对于IRS的光学阵列。在此设置下,我们联合设计了AP-IRS-目标(NLOS-AP)的传送信号,帮助一个接入点(AP)和IRS区域的反射波波波成像仪,以尽可能减少在Cram\'er-Rao较低约束(CRCLB)方面对DoA的测算错误。我们首先获得CRLB(DoA)的封闭式表达方式。接下来,我们优化联合成型设计,通过交替优化、半确定性放松和连续的信号近似。最后,数字结果显示根据REMS的更低的图像进行的拟议设计,将最低性、最低性、最低性、最低性评估。