TR2020-039
Slow-Time MIMO-FMCW Automotive Radar Detection With Imperfect Waveform Separation
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- "Slow-Time MIMO-FMCW Automotive Radar Detection with Imperfect Waveform Separation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053892, April 2020, pp. 8634-8638.BibTeX TR2020-039 PDF Video
- @inproceedings{Wang2020apr,
- author = {Wang, Pu and Boufounos, Petros T. and Mansour, Hassan and Orlik, Philip V.},
- title = {Slow-Time MIMO-FMCW Automotive Radar Detection with Imperfect Waveform Separation},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2020,
- pages = {8634--8638},
- month = apr,
- publisher = {IEEE},
- doi = {10.1109/ICASSP40776.2020.9053892},
- issn = {2379-190X},
- isbn = {978-1-5090-6631-5},
- url = {https://www.merl.com/publications/TR2020-039}
- }
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- "Slow-Time MIMO-FMCW Automotive Radar Detection with Imperfect Waveform Separation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053892, April 2020, pp. 8634-8638.
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MERL Contacts:
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Research Areas:
Abstract:
This paper considers object detection in the case of imperfect waveform separation, in the context of automotive radars with a slow-time MIMO-FMCW signaling scheme. We develop an explicit signal model that accounts for waveform separation residuals and propose a Kronecker subspace-based object detector in the framework of generalized likelihood ratio test (GLRT). Our exact theoretical analysis under both hypotheses shows that the proposed detector holds the desired property of constant false alarm rate (CFAR). Numerical simulations validate our proposed object detection scheme.
Related News & Events
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NEWS MERL presenting 13 papers and an industry talk at ICASSP 2020 Date: May 4, 2020 - May 8, 2020
Where: Virtual Barcelona
MERL Contacts: Petros T. Boufounos; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Philip V. Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & AudioBrief- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.
Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.
This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.