Browsing by Subject "Target differentiation and localization"

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    Differentiation and localization using infrared sensors
    (2002-08) Aytaç, Tayfun
    In this thesis different approaches for the differentiation and localization of targets using low cost infrared sensors are presented. The intensity readings obtained with such sensors are highly dependent on the location and properties of targets in a way which cannot be represented in a simple manner, making the differentiation and localization process difficult. We propose the use of angular intensity scans and present different approaches to process them. Using these approaches, targets of different geometrical shapes but identical surface properties targets of difffferent surface properties but identical geometry, and targets having both different geometrical shapes and surface properties are differentiated and localized in a position-invariant manner. Maximum correct differentiation rates of 97% 87% and 65% are respectively achieved in these cases, indicating that the geometrical properties of targets are more distinctive than their surface properties in the differentiation process. The different approaches are verified experimentally with target types of commonly encountered geometries in indoor environments and with surfaces of different reflection properties. The results indicate that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for.
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    Rule-based target differentiation and position estimation based on infrared intensity measurements
    (SPIE, 2003) Aytaç, T.; Barshan, B.
    This study investigates the use of low-cost infrared sensors in the differentiation and localization of target primitives commonly encountered in indoor environments, such as planes, corners, edges, and cylinders. The intensity readings from such sensors are highly dependent on target location and properties in a way that cannot be represented in a simple manner, making the differentiation and localization difficult. We propose the use of angular intensity scans from two infrared sensors and present a rule-based algorithm to process them. The method can achieve position-invariant target differentiation without relying on the absolute return signal intensities of the infrared sensors. The method is verified experimentally. Planes, 90-deg corners, 90-deg edges, and cylinders are differentiated with correct rates of 90%, 100%, 82.5%, and 92.5%, respectively. Targets are localized with average absolute range and azimuth errors of 0.55 cm and 1.03 deg. The demonstration shows that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for.