Title :
An efficient data fusion architecture for infrared and ultrasonic sensors, using FPGA
Author :
Conde, M.E. ; Cruz, S. ; Munoz, D.M. ; Llanos, Carlos H. ; Fortaleza, E.L.F.
Author_Institution :
Dept. of Mech. Eng., Univ. of Brasilia, Brasilia, Brazil
fDate :
Feb. 27 2013-March 1 2013
Abstract :
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.
Keywords :
Kalman filters; field programmable gate arrays; infrared detectors; sensor fusion; stochastic processes; ultrasonic transducers; FPGA; acquisition system; efficient data fusion architecture; fitting curves; infrared sensors; sensor fusion technique; stochastic filtering area application; ultrasonic sensors; Acoustics; Equations; Field programmable gate arrays; Hardware; Sensor fusion; Sensor phenomena and characterization; FPGAs; Kalman filter; sensor characterization; sensor fusion; static estimation;
Conference_Titel :
Circuits and Systems (LASCAS), 2013 IEEE Fourth Latin American Symposium on
Conference_Location :
Cusco
Print_ISBN :
978-1-4673-4897-3
DOI :
10.1109/LASCAS.2013.6519059