Improving DOA Estimation and Preventing Target Split Using Automotive Radar Sensor Arrays

Song, Heemang; Cho, Seunghoon; You, Kyung-Jin; Shin, Hyun-Chool

doi:10.1587/transfun.e101.a.590

Cited by 3 publications

(1 citation statement)

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“…In each scan, identical signals are transmitted. If the signal transmitted from the FMCW radar is reflected by L objects, the received signal in the kth array is expressed as follows [22], [23]:…”

Section: Radar Modelmentioning

confidence: 99%

Classification and Spectral Mapping of Stationary and Moving Objects in Road Environments Using FMCW Radar

Song

Shin

2020

IEEE Access

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In order to establish a reliable map of the road environment, this paper aims to classify the stationary and moving objects unlike the previous researches which generally focus on object recognition. The characteristics of the radar signals of stationary and moving objects were analyzed and the relation between the slope of pattern in radar time-frequency spectrum and relative velocity of the object was described mathematically. To discriminate the stationary and moving objects, the difference between the measured velocity by the slope and the velocity of the ego-vehicle was proposed as a feature. The statistical characteristics of stationary and moving objects according to the proposed feature were modeled using Gaussian model. To investigate the performance of the proposed method, the similarity between modeling of stationary and moving objects was quantified. Additionally, the receiver operating characteristics (ROC) curve and the correlation coefficient between the proposed feature and the ground-truth feature map was applied to verify the performance. INDEX TERMS Automotive radar, radar signal processing, road environment map, FMCW radar, object classification.

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Section: Radar Modelmentioning

confidence: 99%