An efficient data fusion architecture for infrared and ultrasonic sensors, using FPGA

This paper shows the hardware implementation of a sensor fusion technique applied to both an ultrasonic and an infrared sensors, for estimating the distance, using an FPGA. Sensor fusion is a natural application of stochastic filtering area (such as Kalman filters), being applied extensively in different areas such as mobile robotics, signal processing, bioengineering, among others. This technique permits to combine the information provided by the sensors, improving the estimate of the measured variable, as well as its uncertainity. The sensors have previously been characterized using the same acquisition system that was used for the sensor fusion, and the fitting curves have been calculated for them. Finally, synthesis and simulation results demonstrate that the architecture implemented in the FPGA is suitable for calculating the estimate and uncertainity of the overall fusion process.