Location Sensor Fusion Mechanisms – A Comparison
نویسنده
چکیده
In order to detect the user's context or location, an application has to process position information from different sources (e.g. based on GPS sensors or cell IDs). A research field that traditionally deals with different position information is robotics. Based on e.g., odometers and ultrasonic distance measurement, a mobile robot computes the most probable location. Established approaches to compute a position from these sensors are Kalman and Particle Filters. Even though these approaches are widely used to process position sensor information, they often cannot be applied to mobile user scenarios due to significant differences: many positioning systems only have a limited coverage and availability and have a non-Gaussian measurement error distribution. Often, we receive a set of incomplete pieces of position knowledge such as: • I currently receive WLAN cell ABC; • checking my IP address, I know, I'm not at home; • one minute ago, I received GPS position xy, and I have a speed of 5 km/h as pedestrian.
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