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arXiv 2308.03387eess.SP
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一种用于MIMO-OFDM ISAC系统的联合角度-距离-速度估计新方法

A Novel Joint Angle-Range-Velocity Estimation Method for MIMO-OFDM ISAC Systems

Zichao Xiao, Rang Liu, Ming Li, Qian Liu, A. Lee Swindlehurst

AI总结:

本文提出一种用于MIMO-OFDM ISAC系统的联合角度-距离-速度估计算法,利用CPI内所有回波信号实现联合估计,获得更高SNR增益和分辨率,并显著降低RMSE。

摘要:

集成感知与通信(ISAC)正成为下一代无线系统的关键技术。为了在普及的移动网络中加速ISAC的实际部署,拥有广泛部署的具备雷达感知能力的基站至关重要。因此,利用标准化的多输入多输出(MIMO)正交频分复用(OFDM)硬件架构和波形,对于实现有效通信与感知功能的无缝集成至关重要。本文提出了一种用于MIMO-OFDM ISAC系统的联合角度-距离-速度估计新算法。该方法仅依赖于无线通信中广泛采用的传统MIMO-OFDM波形格式。具体而言,通过利用相干处理间隔(CPI)内的所有接收回波信号,联合提取潜在目标的角度-距离-速度信息。所提出的联合估计算法通过充分利用回波信号并联合估计角度-距离-速度信息,能够获得更大的信噪比(SNR)处理增益和更高的分辨率。提供了关于最大无模糊距离、分辨率和SNR处理增益的理论分析,以验证所提出的联合估计算法的优势。最后,大量数值实验结果表明,所提出的联合估计方法在单目标和多目标场景下,均能显著降低角度/距离/速度估计的均方根误差(RMSE)性能。

英文摘要:

Integrated sensing and communication (ISAC) is emerging as a key technique for next-generation wireless systems. In order to expedite the practical implementation of ISAC in pervasive mobile networks, it is crucial to have widely deployed base stations with radar sensing capabilities. Thus, the utilization of standardized multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) hardware architectures and waveforms is pivotal for realizing seamless integration of effective communication and sensing functionalities. In this paper, we introduce a novel joint angle-range-velocity estimation algorithm for MIMO-OFDM ISAC systems. This approach exclusively depends on the format of conventional MIMO-OFDM waveforms that are widely adopted in wireless communications. Specifically, the angle-range-velocity information of potential targets is jointly extracted by utilizing all the received echo signals within a coherent processing interval (CPI). The proposed joint estimation algorithm can achieve larger signal-to-noise-ratio (SNR) processing gains and higher resolution by fully exploiting the echo signals and jointly estimating the angle-range-velocity information. A theoretical analysis for maximum unambiguous range, resolution, and SNR processing gains is provided to verify the advantages of the proposed joint estimation algorithm. Finally, the results of extensive numerical experiments are presented to demonstrate that the proposed joint estimation approach can achieve significantly lower root-mean-square-error (RMSE) performance for angle/range/velocity estimation for both single- and multi-target scenarios.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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