A neural network approach to target classification for active safety system using microwave radar

As a sensor in the active safety system of vehicles, the microwave radar (MWR) would be a good choice for the localization of the nearby targets but could be a bad choice for their classification or identification. In this paper, a target classification system using a 24 GHz microwave radar sensor is proposed for the active safety system. The basic idea of this paper is that the pedestrians and the vehicles have different reflection characteristics for a microwave. A multilayer perceptron (MLP) neural network is employed to classify the targets and the probabilistic fusion is conduct over time to improve the classification accuracy. Some experiments are performed to show the validity of the proposed system. Safety has been a hot issue in recent vehicular technology and a tremendous research has been conducted towards the direction. The researches concerning the safety of the passengers and drivers in the vehicles have produced two paradigms: passive safety system and active safety system. The passive safety system purposes to minimize the damage after car accident and an air bag and safety belt belong to this class (Chan, 2007; Watanabe, Umezawa, & Abe, 1994). The passive system does not aim at reducing the possibility of the car accidents. On the contrary, active safety system purposes to prevent the car accidents before they occur and it is now receiving much attention within vehicular community. Mainly, the active safety system recognizes the surrounding environment around its own car and alerts the car driver about the nearby possible dangers. and pedestrian protection systems (PPS) (Gandhi & Trivedi, 2007) certainly belong to the active safety system. In the active safety system, the key technology is the understanding of the surrounding objects, that is, detection, tracking and identification of the nearby objects. For the purpose, several sensors are used and CCD cameras and range finders are the most common ones. The CCD camera returns rich information about the nearby target objects and provides relatively easy method for target recognition. However, it is difficult to measure the range to the nearby targets from the car. On the contrary, range finders such as a laser scanner or microwave radar easily measure the location of nearby objects and are robust to the variation of the weather or time. But the range finders have difficulty in recognizing the target In this paper, we develop a new microwave radar-based target classification system for an active …