A New Approach for Deep Integration of GNSS and Vision-Aided MEMS IMU

V. Barreau, B. Priot, M. Sahmoudi, V. Calmettes

Abstract:	In this paper, we introduce a new approach for deep integration of GNSS and vision-aided IMU (Inertial Measurement Unit) systems. Instead of standard DLL/FLL/PLL loops, a bank of scalar Kalman filters is designed for tracking weak GNSS signals. These local weak signal trackers estimate the propagation delay and Doppler frequency for the satellites in visibility. Estimates elaborated by these tracking modules are provided to a federated INS/GPS Kalman integration filter which determines the user position, velocity and attitude. To obtain performance improvements of the tracking modules, we use a vision-aided inertial system, which provides the vehicle acceleration in the satellites-receiver LOS (line-of-sight). Such IMU, calibrated by camera, allows reducing the receiver noise bandwidth by compensating for the user dynamics. The multi-sensor navigation solution (position and velocity) and the calibrated acceleration are used to directly control local signal generators. In a friendly environment, a GNSS/INS deeply integrated system offers potential improvements to GNSS navigation and allows achieving accelerometers calibration. However, in constrained GNSS environments, as in urban navigation, using the poor GNSS measurements we are not able to estimate and correct properly the accumulated MEMS-based INS errors, thus extern aids are needed for calibration. In order to improve further the performance of the GNSS/INS navigation system in difficult environments, we study, in this paper, the merits of coupling the MEMS-based INS with a monocular camera. The idea is to integrate a camera as an optical odometer to achieve INS calibration in severe GNSS environments. Therefore, we adopt a federated Kalman filter approach to fuse a collection of local estimators whose solutions are combined by a global fusion and estimator module. We present our prior simulation results showing that the developed scheme is a promising low-cost robust navigation system.
Published in:	Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010) September 21 - 24, 2010 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	464 - 475
Cite this article:	Barreau, V., Priot, B., Sahmoudi, M., Calmettes, V., "A New Approach for Deep Integration of GNSS and Vision-Aided MEMS IMU," Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010), Portland, OR, September 2010, pp. 464-475.
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