Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar–radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.
Today, 77 GHz FMCW (Frequency Modulation Continuous Wave) radar has strong advantages of range and velocity
detection for automotive applications. However, FMCW radar brings out ghost targets and missed targets in multi-target
situations. In this paper, in order to resolve these limitations, we propose an effective pairing algorithm, which consists
of two steps. In the proposed method, a waveform with different slopes in two periods is used. In the 1st pairing
processing, all combinations of range and velocity are obtained in each of two wave periods. In the 2nd pairing step,
using the results of the 1st pairing processing, fine range and velocity are detected. In that case, we propose the range-velocity
windowing technique in order to compensate for the non-ideal beat-frequency characteristic that arises due to
the non-linearity of the RF module. Based on experimental results, the performance of the proposed algorithm is
improved compared with that of the typical method.
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