Abstract
Unmanned aerial vehicles (UAVs) which can work as a new platform have been applied widely in traffic detection. Accurate identification of ground vehicles from UAVs is the premise. As the unique information of targets, micro-Doppler effect is increasingly used to distinguish different targets. Focusing on typical rotating micro-Doppler, this paper firstly builds a model illustrating the relationship between a ground wheeled vehicle and an UAV. Mathematical expression of Doppler signal in the model is also derived. Then, according to micro-Doppler modulation in echo signal, an arithmetic estimating rotating micro-Doppler parameters based on smooth pseudo-Wegner distribution (SPWD) and image enhancement is proposed to deal with echo signals of the ground wheeled vehicle when the UAV are hovering and moving linearly respectively. By saving the ridge of the spectrogram obtained by SPWD as an image, approaches in image enhancement are utilized. At last, comparison between proposed method and traditional generalized Hough transform is given. Results show that micro-Doppler parameters estimated via proposed arithmetic has higher precision while needs less computation so that vehicles with rotating movement can be identified correctly.
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