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

Conference paper

Sichani, N. K., Ahmadi, M., Raei, E., Alaee-Kerahroodi, M., Shankar, M. R. B., Mehrshahi, E. and Ghorashi, S. 2023. Waveform Selection for FMCW and PMCW 4D-Imaging Automotive Radar Sensors. European Signal Processing Conference, EUSIPCO 2023. Helsinki, Finland 04 - 08 Sep 2023 European Association for Signal Processing (EURASIP).
AuthorsSichani, N. K., Ahmadi, M., Raei, E., Alaee-Kerahroodi, M., Shankar, M. R. B., Mehrshahi, E. and Ghorashi, S.
TypeConference paper
Abstract

The emerging 4D-imaging automotive MIMO radar sensors necessitate the selection of appropriate transmit waveforms, 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 designing a waveform set 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.

Keywords4D-Imaging; Automotive Radar; FMCW; PMCW; CDM-MIMO; WISL
Year2023
ConferenceEuropean Signal Processing Conference, EUSIPCO 2023
PublisherEuropean Association for Signal Processing (EURASIP)
Accepted author manuscript
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Anyone
Publication dates
Print04 Sep 2023
Publication process dates
Accepted29 May 2023
Deposited14 Jun 2023
Web address (URL)http://eusipco2023.org/
Copyright holder© 2023, The Author(s)
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