IEICE Transactions on Communications
Online ISSN : 1745-1345
Print ISSN : 0916-8516
Regular Section
Hardware Implementation of a Real-Time MEMS IMU/GNSS Deeply-Coupled System
Tisheng ZHANGHongping ZHANGYalong BANKunlun YANXiaoji NIUJingnan LIU
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2013 Volume E96.B Issue 11 Pages 2933-2942

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Abstract

A deeply-coupled system can feed the INS information into a GNSS receiver, and the signal tracking precision can be improved under dynamic conditions by reducing tracking loop bandwidth without losing tracking reliability. In contrast to the vector-based deep integration, the scalar-based GNSS/INS deep integration is a relatively simple and practical architecture, in which all individual DLL and PLL are still exist. Since the implementation of a deeply-couple system needs to modify the firmware of a commercial hardware GNSS receiver, very few studies are reported on deep integration based on hardware platform, especially from academic institutions. This implementation-complexity issue has impeded the development of the deeply-coupled GNSS receivers. This paper introduces a scalar-based MEMS IMU/GNSS deeply-coupled system based on an integrated embedded hardware platform for real-time implementation. The design of the deeply-coupled technologies is described including the system architecture, the model of the inertial-aided tracking loop, and the relevant tracking errors analysis. The implementation issues, which include platform structure, real-time optimization, and generation of aiding information, are discussed as well. The performance of the inertial aided tracking loop and the final navigation solution of the developed deeply-coupled system are tested through the dynamic road test scenarios created by a hardware GNSS/INS simulator with GPS L1 C/A signals and low-level MEMS IMU analog signals outputs. The dynamic tests show that the inertial-aided PLL enables a much narrow tracking loop bandwidth (e.g. 3Hz) under dynamic scenarios; while the non-aided loop would lose lock with such narrow loop bandwidth once maneuvering commences. The dynamic zero-baseline tests show that the Doppler observation errors can be reduced by more than 50% with inertial aided tracking loop. The corresponding navigation results also show that the deep integration improved the velocity precision significantly.

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© 2013 The Institute of Electronics, Information and Communication Engineers
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