Millimeter-Wave AWR1642 RADAR for Obstacle Detection: Autonomous Vehicles

Iyer, Nalini C.; Pillai, Preeti S.; Bhagyashree, K.; Mane, Venkatesh; Shet, Raghavendra M.; Nissimagoudar, P. C.; Krishna, Gopi; Nakul, V. R.

doi:10.1007/978-981-15-3172-9_10

Cited by 9 publications

(1 citation statement)

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“…The experimental research utilizes the Texas Instruments AWR 1642 BOOST [19] radar, employing frequency-modulated continuous waves (FMCW or chirps) transmitted by the onboard Cortex®-R4F MCU. Chirp settings are configured for transmission, and RX antennas capture reflected signals.…”

Section: System Descriptionmentioning

confidence: 99%

Enhancing Outdoor Moving Target Detection: Integrating Classical DSP with mmWave FMCW Radars in Dynamic Environments

Chowdhury,

Melige,

Pal

et al. 2023

Electronics

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This paper introduces a computationally inexpensive technique for moving target detection in challenging outdoor environments using millimeter-wave (mmWave) frequency-modulated continuous-wave (FMCW) radars leveraging traditional signal processing methodologies. Conventional learning-based techniques for moving target detection suffer when there are variations in environmental conditions. Hence, the work described here leverages robust digital signal processing (DSP) methods, including wavelet transform, FIR filtering, and peak detection, to efficiently address variations in reflective data. The evaluation of this method is conducted in an outdoor environment, which includes obstructions like woods and trees, producing an accuracy score of 92.0% and precision of 91.5%. Notably, this approach outperforms deep learning methods when it comes to operating in changing environments that project extreme data variations.

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Section: System Descriptionmentioning

confidence: 99%