System architecture for synchronizing, signal level fusing, simulating and implementing sensors

We present a modular system architecture for simplifying the signal level fusion and sensor configuration of multiple sensors with different sample rates. The fusion process is subdivided into three modules: synchronization, adaptation and fusion. Methods for all three stages are proposed and compared with classical approaches. All sensor sample times, even if they are not periodic, are propagated to the next sample time of the control unit. In the adaptation module we focus on the double integration of biased signals and the determination of the unknown initial conditions. We distinguish four different types of sensors and propose sensor models suitable for off-line simulation that can be automatically changed to interface blocks in case of an online simulation with real sensors. All methods needed for handling our system architecture are embedded in a Matlab toolbox