A Loosely Coupled Architecture for INS/GNSS Integration with Tracking Loops Aiding
MetroAutomotive(2023)
Abstract
Loosely Coupled architectures based on Micro Electromechanical Systems (MEMS) Inertial Navigation Systems (INS), and multi-band GNSS are widely adopted to improve the availability of the integrated solution under difficult conditions, characterized by frequent obscurations of the GNSS signal. Typical scenarios include automotive urban tracks or open sky under dynamics, in presence of bridges and short tunnels. Low Earth Orbit (LEO) satellites also fall in this scope, as their lower altitude results in a Doppler curve with stronger rate variations, which sum up to receiver dynamics and are more challenging to track than traditional GNSS. In this paper, a hybrid solution is presented, where a classic loosely coupled scheme is complemented by deep integration. The INSaided solution combines with GNSS satellites velocities and accelerations to derive code, Doppler, and Doppler rate observables predictions. Validation and performance assessment are conducted on a compact two-chip hardware platform, based on the state-of-the-art multi-band GNSS receiver STA8135 (TeseoV) and the MEMS IMU ASM330LHH from STMicroelectronics. Deep aiding has the potential to broaden the applicability of loosely coupled INS integration to the cases where signal weakness and the combined user to satellites dynamics exceed the tracking loops capability. Partially obscured automotive scenarios, reception of attenuated signals under high dynamics and assisted LEO satellites acquisition and tracking are among the applications that can benefit from the proposed scheme.
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Key words
GNSS,MEMS,INS,LEO,sensor fusion,predictions,satellite navigation,automotive,precise positioning,multi-band,high dynamics
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