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Adaptive Redundant Inertial Measurement Unit/Global Positioning System Integration Filter Structure for Fault Tolerant Navigation

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This paper proposes a new adaptive filter structure containing two subfilters, a fault detection and isolation (FDI) filter, and a main-filter for redundant inertial measurement unit (RIMU)/global positioning system (GPS) integrated navigation system tolerant toward faults of inertial sensors. The purpose of subfilters is compensation of sensor level bias (SLB) of the RIMU during in-flight alignment for successful FDI processing. Also, that of the main-filter is providing of error compensated navigation solution based on the good FDI result. To achieve these purposes, two coordinate frames, sub-body frame (SBF) and master-body frame (MBF), are defined first. Then, two different error models for the RIMU are formulated in the SBF for sensor level compensation and in the MBF for module level compensation, respectively. Based on the formulated error models, an adaptive filter structure is designed. Some numerical simulations are performed to validate the performance of the proposed adaptive filter structure.
Title: Adaptive Redundant Inertial Measurement Unit/Global Positioning System Integration Filter Structure for Fault Tolerant Navigation
Description:
This paper proposes a new adaptive filter structure containing two subfilters, a fault detection and isolation (FDI) filter, and a main-filter for redundant inertial measurement unit (RIMU)/global positioning system (GPS) integrated navigation system tolerant toward faults of inertial sensors.
The purpose of subfilters is compensation of sensor level bias (SLB) of the RIMU during in-flight alignment for successful FDI processing.
Also, that of the main-filter is providing of error compensated navigation solution based on the good FDI result.
To achieve these purposes, two coordinate frames, sub-body frame (SBF) and master-body frame (MBF), are defined first.
Then, two different error models for the RIMU are formulated in the SBF for sensor level compensation and in the MBF for module level compensation, respectively.
Based on the formulated error models, an adaptive filter structure is designed.
Some numerical simulations are performed to validate the performance of the proposed adaptive filter structure.

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