High Fidelity Physics Simulation of 128 Channel MIMO Sensor for 77GHz Automotive Radar
| Autor: | Ushemadzoro Chipengo, Arien P. Sligar, Shawn Carpenter |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Signal processing
Electromagnetics General Computer Science Computer science Fast Fourier transform MIMO General Engineering DoA Advanced driver assistance systems simulation Automotive radar antenna law.invention law FMCW Chirp Electronic engineering General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Radar lcsh:TK1-9971 Computer Science::Information Theory Communication channel |
| Zdroj: | IEEE Access, Vol 8, Pp 160643-160652 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.3021362 |
| Popis: | Automotive radar is one of the enabling technologies for advanced driver assistance systems (ADAS) and subsequently fully autonomous vehicles. Along with determining the range and velocity of targets with fairly high resolution, autonomous vehicles navigating complex urban environments need radar sensors with high azimuth and elevation resolution. Size and cost constraints limit the physical number of antennas that can be used to achieve high resolution direction-of-arrival (DoA) estimation. Multiple-input/multiple-output (MIMO) schemes achieve larger virtual arrays using fewer physical antennas than would be needed for a single-input/multiple-output (SIMO) system. This paper presents a high-fidelity physics simulation of a 77GHz, frequency-modulated continuous-waveform (FMCW)-based 128 channel (8 transmitters (Tx), 16 receivers (Rx)) MIMO radar sensor. The 77GHz synthetic radar returns from full scale traffic scenes are obtained using a high-fidelity physics, shooting and bouncing ray electromagnetics solver. A fast Fourier transform (FFT) based signal processing scheme is used across slow-time (chirp) and space (channel) to obtain range-Doppler and DoA maps, respectively. Detection and angular separation performance comparisons of 16, 64 and 128 channel MIMO radar sensors are made for two complex driving scenarios. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|