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Constrained MEMS-Based GNSS/INS Tightly Coupled System With Robust Kalman Filter for Accurate Land Vehicular Navigation | IEEE Journals & Magazine | IEEE Xplore

Constrained MEMS-Based GNSS/INS Tightly Coupled System With Robust Kalman Filter for Accurate Land Vehicular Navigation


Abstract:

Special approaches are required to integrate low-cost MEMS-based inertial navigation system (MEMS-INS) with global navigation satellite system (GNSS). This article propos...Show More

Abstract:

Special approaches are required to integrate low-cost MEMS-based inertial navigation system (MEMS-INS) with global navigation satellite system (GNSS). This article proposes a robust GNSS/MEMS-strapdown inertial navigation system (SINS), the tightly coupled navigation approach aided by non-holonomic constraint (NHC). The tight integration model is adopted to overcome the accuracy degradation caused by changing satellite geometry and frequent GNSS outages in urban areas. The innovation-based test statistic is devised to enhance the filtering with the resistance to GNSS outliers. To further improve the stand-alone accuracy during relatively long GNSS outages, the virtual measurement is also introduced using the NHC condition that land vehicle does not slip and always remain in contact with the ground. The field test results with continuous GNSS aiding indicate that the proposed algorithm can improve overall accuracy in position, velocity, and attitude by about 16, 43, and 19% with immunity from GNSS outliers, compared with the traditional loosely coupled (LC) method. Even during 60-s GNSS outages, the proposed algorithm can effectively compensate MEMS-SINS errors, accomplishing the overall accuracy improvements by about 46% (position), 35% (velocity), and 15% (attitude), compared with the traditional LC counterpart.
Published in: IEEE Transactions on Instrumentation and Measurement ( Volume: 69, Issue: 7, July 2020)
Page(s): 5138 - 5148
Date of Publication: 09 December 2019

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