Measurement-Based Statistical Fusion Methods for Distributed Sensor Networks

In distributed sensor networks (DSNs), the fusion problems naturally arise when overlapping regions are covered by a set of sensor nodes. The sensor nodes typically consist of specialized sensor hardware and/or software, and consequently their outputs are related to the actual object features in a complicated manner, which is often modeled by probability distributions. In DSNs, the sensor distributions can be arbitrarily complicated. In addition, deriving closed form expressions for sensor distributions is a very difficult and expensive task since it requires the knowledge of a variety of areas such as device physics, electrical engineering, and statistical modeling. Due to the generic nature of the sensor fusion problem described here, it is related to a number of similar problems in a wide variety of areas. In general, for sensor fusion problems, however, the interdependence between the sensors is a main feature to be exploited to overcome the limitations of single sensors.