集成传感与通信的OTFS调制波束空间MIMO雷达

Saeid K. Dehkordi, Lorenzo Gaudio, M. Kobayashi, G. Colavolpe, G. Caire
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引用次数: 6

摘要

受集成传感与通信(ISAC)最新进展的激励,我们研究了一种工作在毫米波(mmWave)频段的ISAC系统,其中配备了一个共定位雷达接收器的基站(BS)通过数字调制的正交时频空间(OTFS)波形传输数据,同时从后向散射信号进行雷达估计。我们考虑两种系统功能模式。在发现模式下,一个单一的公共数据流在一个广角扇区上广播,雷达接收器检测到尚未捕获的目标的存在,并执行粗略的参数估计(到达角、延迟和多普勒)。在跟踪模式下,BS通过波束成形将多个单独的数据流发送给已经获得的用户,而雷达接收器执行精细分辨率参数估计。在这项工作中,考虑了毫米波下射频波束形成的现实混合数字模拟方案,其中用于调制/解调的射频链的数量明显小于阵列天线元件的数量。因此,标准MIMO雷达方法的直接应用是不可能的。相反,我们考虑雷达接收机的射频域“约简矩阵”(从天线到射频链)的设计,其作用是在角度域的探测能力和波束形成方向图的指向性之间进行权衡。在这种情况下,我们提出了一种高效的极大似然方案来联合进行目标检测和参数估计。数值结果表明,该方法能够可靠地检测多个目标,同时基本达到参数估计的cram rs - rao下界。
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Beam-Space MIMO Radar with OTFS Modulation for Integrated Sensing and Communications
Motivated by recent advances of Integrated Sensing and Communication (ISAC), we study an ISAC system operating at millimeter waves (mmWave) frequency bands where a Base Station (BS) equipped with a co-located radar receiver transmits data via a digitally modulated orthogonal time frequency space (OTFS) waveform and simultaneously performs radar estimation from the backscattered signal. We consider two system function modes. In Discovery mode, a single common data stream is broadcast over a wide angular sector where the radar receiver detects the presence of not yet acquired targets and performs coarse parameter estimation (angle of arrival, delay, and Doppler). In Tracking mode, the BS sends multiple individual data streams to already acquired users via beamforming, while the radar receiver performs fine-resolution parameter estimation. In this work a realistic hybrid digital-analog scheme for RF beamforming at mmWave is considered, where the number of RF chains for modulation/demodulation is significantly smaller than the number of array antenna elements. Hence, a direct application of standard MIMO radar approaches is not possible. Instead, we consider the design of the RF-domain “reduction matrix” (from antennas to RF chains) of the radar receiver, whose role is to trade off between the exploration capability of the angle domain and the directivity of the beamforming patterns. Under this setup, we propose an efficient maximum likelihood scheme to jointly perform target detection and parameter estimation. Our numerical results demonstrate that the proposed approach is able to reliably detect multiple targets while essentially achieving the Cramér-Rao lower bound for parameter estimation.
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