This paper presents a high performance 77GHz FMCW radar sensor for automotive applications. Powerful automotive radar systems are currently under development for various applications. Radar sensor based comfort systems like Adaptive Cruise Control (ACC) are already available on the market. The main objective from a radar sensor point of view is to detect all targets inside the observation area and estimate target range and relative velocity simultaneously with a high update rate.FMCW radar sensors have the advantages of very high range resolution but a serious task occurs in multiple target situations to suppress so-called ghost targets. In classical F M C W waveforms this has been solved in using multiple chirp signals with different slope. But in this case a long measurement time (approximately 50ms) is needed which is a contradiction to a high update rate. Therefore, in this paper a new waveform design is presented which has all advantages of FMCW radars but needs an extremely low measurement time (loms) in a radar sensor with 3 different antenna beams.
Abstract-This paper describes an approach for pedestrian detection in infrared images. The developed system has been implemented on an experimental vehicle equipped with an infrared camera and preliminarily tested in different situations.It is based on the localization of warm symmetrical objects with specific size and aspect ratio; since also road infrastructures and other road participants may have such characteristics, a set of matched filters was added in order to reduce false detections. A final validation process, based on the human shape's morphological characteristics, is used to build the list of pedestrian appearing in the scene.No temporal correlation, nor motion cues are used in this first part of the project.
This paper describes a system for pedestrian detection in infrared images, which has been implemented on an experimental vehicle equipped with an infrared camera. The proposed system has been tested in many situations and has proven to be efficient and with a very low false-positive rate. It is based on a multiresolution localization of warm symmetrical objects with specific size and aspect ratio; anyway, because road infrastructures and other road participants may also have such characteristics, a set of matched filters is included in order to reduce false detections. A final validation process, based on human shape's morphological characteristics, is used to build the list of pedestrian appearing in the scene. Neither temporal correlation nor motion cues are used in this first part of the project: the processing is based on the analysis of single frames only.
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