Vehicle Classification Based on the Radar Measurement of Height Profiles

Abstract

Abstract-The problem of classifying road vehicles according to vehicle type is considered. The proposed solution is based on using vehicle height and length and height profiles obtained by a microwave (MW) radar sensor. We show that if the radar sensor satisfies certain requirements, then a precise feature vector can be extracted, and simple deterministic algorithms can be applied to determine the vehicle class. Field trials using a spread-spectrum MW radar sensor system operating on these principles have been carried out. They confirm that accurate classification of a large number of vehicle classes can be reached.

Density-Based Statistical Clustering: Enabling Sidefire Ultrasonic Traffic Sensing in Smart Cities

“…In the field of radar and ultrasonic sensors, several top-down sensor solutions are available, which require the placement above a specific street lane for single-lane car profile measurements [10,[14][15][16][17][18]. These techniques allow obtaining the complete height profile of vehicles for detection and classification but require a gantry or bridge over the street for mounting the sensors, which is infeasible in many situations.…”

Real-time classification of vehicles by type within infrared imagery

“…For vehicle targets we can assume an average height for a given vehicle type determined from earlier vehicle type classification (as projected vehicle height, y, does not varying with viewing angle of the vehicle in the plane). Despite commonly held beliefs, empirical study has shown height variation within a given type classification of vehicle to be minimal [8]. In this study we use Y = {height car , height SU V , height LGV , height HGV } for {height car = 1.5m, height SU V = 1.8m, height LGV = 2.1m, height HGV = 2.9m} based on statistical evaluation of a moderate pool of vehicles.…”

“…By contrast, here we present an approach for the automatic classification of vehicles by sub-type, such that a similar photogrammetric localization and tracking strategy can be employed. Identifying vehicle sub-type is a key governing factor in determining the suitable height assumption for use in such photogrammetric localization (supported by prior work of [8]) in addition to providing a higher granularity of target reporting within a deployed multi-sensor network.…”

Modeling and Implementation Of Wireless Embedded System For Intelligent Transport System Application

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