Waveform Selection for FMCW and PMCW 4D-Imaging Automotive Radar Sensors

Nazila Karimian Sichani, Moein Ahmadi, E. Raei, M. Alaee-Kerahroodi, B. M. R., E. Mehrshahi, Seyyed Ali Ghorashi
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Abstract

The emerging 4D-imaging automotive MIMO radar sensors necessitate the selection of appropriate transmit wave-forms, which should be separable on the receive side in addition to having low auto-correlation sidelobes. TDM, FDM, DDM, and inter-chirp CDM approaches have traditionally been proposed for FMCW radar sensors to ensure the orthogonality of the transmit signals. However, as the number of transmit antennas increases, each of the aforementioned approaches suffers from some drawbacks, which are described in this paper. PMCW radars, on the other hand, can be considered to be more costly to implement, have been proposed to provide better performance and allow for the use of waveform optimization techniques. In this context, we use a block gradient descent approach to design a waveform set for MIMO-PMCW that is optimized based on weighted integrated sidelobe level in this paper, and we show that the proposed waveform outperforms conventional MIMO-FMCW approaches by performing comparative simulations.
FMCW和PMCW 4d成像汽车雷达传感器波形选择
新兴的4d成像汽车MIMO雷达传感器需要选择合适的发射波形,除了具有低自相关旁瓣外,在接收端还应该是可分离的。为了保证发射信号的正交性,传统上提出了TDM、FDM、DDM和频间CDM方法用于FMCW雷达传感器。然而,随着发射天线数量的增加,上述每种方法都存在一些缺点,本文对此进行了描述。另一方面,PMCW雷达可以被认为是更昂贵的实现,已经提出提供更好的性能,并允许使用波形优化技术。在这种情况下,我们使用分块梯度下降方法设计了一种基于加权综合旁瓣电平优化的MIMO-PMCW波形集,并通过进行对比仿真表明,所提出的波形优于传统的MIMO-FMCW方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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