Vehicle localization systems: towards low-cost architectures

Authors: SAKHI SAMIR, ABDELHAFID ELOUARDI, BOUAZIZ SAMIR, MAHMOUD BELHOCINE

Abstract: the accuracy of an inertial navigation system alone. However, its implementation complexity has been a challenge to most embedded systems. This paper proposes a low-cost FPGA-based INS-GPS integration system, which consists of a Kalman filter and a soft processor. Moreover, we also evaluate the navigation algorithm on a low-cost ARM processor. Processing times and localization accuracy are compared in both cases for single and double precision floating-point format. Experimental results show the advantages of the FPGA-based approach over the ARM-based approach. The proposed architecture can operate at 100 Hz and demonstrates the advantage of using FPGAs to design low-cost INS-GPS localization systems.

Keywords: INS-GPS sensors integration, Kalman filter, field-programmable gate array, hardcore and softcore processor

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