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Proceedings Paper

Comparative of signal processing techniques for micro-Doppler signature extraction with automotive radar systems
Author(s): Berta Rodriguez-Hervas; Michael Maile; Benjamin C. Flores
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Paper Abstract

In recent years, the automotive industry has experienced an evolution toward more powerful driver assistance systems that provide enhanced vehicle safety. These systems typically operate in the optical and microwave regions of the electromagnetic spectrum and have demonstrated high efficiency in collision and risk avoidance. Microwave radar systems are particularly relevant due to their operational robustness under adverse weather or illumination conditions. Our objective is to study different signal processing techniques suitable for extraction of accurate micro-Doppler signatures of slow moving objects in dense urban environments. Selection of the appropriate signal processing technique is crucial for the extraction of accurate micro-Doppler signatures that will lead to better results in a radar classifier system. For this purpose, we perform simulations of typical radar detection responses in common driving situations and conduct the analysis with several signal processing algorithms, including short time Fourier Transform, continuous wavelet or Kernel based analysis methods. We take into account factors such as the relative movement between the host vehicle and the target, and the non-stationary nature of the target’s movement. A comparison of results reveals that short time Fourier Transform would be the best approach for detection and tracking purposes, while the continuous wavelet would be the best suited for classification purposes.

Paper Details

Date Published: 29 May 2014
PDF: 14 pages
Proc. SPIE 9077, Radar Sensor Technology XVIII, 90771A (29 May 2014); doi: 10.1117/12.2053323
Show Author Affiliations
Berta Rodriguez-Hervas, The Univ. of Texas at El Paso (United States)
Mercedes-Benz Research & Development North America, Inc. (United States)
Michael Maile, The Univ. of Texas at El Paso (United States)
Mercedes-Benz Research & Development North America, Inc. (United States)
Benjamin C. Flores, The Univ. of Texas at El Paso (United States)
Mercedes-Benz Research & Development North America, Inc. (United States)


Published in SPIE Proceedings Vol. 9077:
Radar Sensor Technology XVIII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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