Improvement of Sensory Information using Multi-Sensor and Model-Based Sensor Systems

Many approaches can be pursued in order to improve information delivered by a sensor system. A signal processing based on the modeling of the sensor characteristic can be used in order to reduce undesired effects influencing the sensor signal. In this case we deal with an inverse reconstruction problem in which the measured quantity is calculated using a priori knowledge, e. g. collected during calibration processes. A further approach is to model the dependence on a steering quantity and to solve the corresponding inverse identification problem. In this case a set of sensor operating points are available at the same value of the measured quantity permitting new possibilities for improving sensory information. This kind of sensor systems can be called varied input sensor (VIS) and closes the gap between single sensors and multi sensor systems. Multi-sensor systems reach many advantages through integration of redundant and diverse sensor signals in order to achieve advantages, such as a better accuracy, a higher reliability or a better dynamic response