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In this article, we propose a novel harmonic clutter recognition and suppression method to overcome the deterioration of a target-or vehicle-detection performance due to harmonic clutters. Although several studies have been performed on the reflection and diffraction on road surfaces for automotive radar sensors, most of them did not consider the case where metallic structures such as iron tunnels with greater reflection are densely distributed. The proposed method measures the periodicity of harmonic clutters by analyzing the spectral characteristics of the received radar signal with various road conditions. The proposed method can successfully recognize harmonic clutters. In addition, experimental results show that early detection of a target vehicle in an iron tunnel under adaptive cruise control is improved using the proposed clutter suppression method.

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Recently, as one of the intelligent transportation systems, radar systems that monitor traffic on the road have received attention. To ensure the reliable detection performance of the traffic monitoring radar, it is necessary to distinguish stationary road structures from moving vehicles. Therefore, in this paper, we propose a method for discriminating stationary targets in traffic monitoring radar systems. First, we install a frequency-modulated continuous wave radar system using a center frequency of 24.15 GHz on an overpass to monitor multiple lanes on the road. Then, we process the raw data obtained by the radar sensor to extract target information such as the distance, angle, velocity, and radar cross-section. Finally, we analyze the target characteristics in the angle-velocity domain to classify stationary targets and moving vehicles. In this domain, stationary targets appear as points lying around a straight line, and if we estimate that line, we can extract the stationary targets among all targets. To find the trend line, we use a random sample consensus-based estimation method, which can extract a dominant line component from a set of sample points. Through the proposed method, we can effectively remove the stationary targets in the field of view of the radar system.

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