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A Robust and Efficient IMU Array/GNSS Data Fusion Algorithm
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DOI：10.1109/JSEN.2024.3418383.png)
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Abstract
En 中文
The inertial measurement unit (IMU) array, composed of multiple IMUs, has been proven to be able to effectively improve the navigation performance in inertial navigation system (INS)/global navigation satellite system (GNSS) integrated applications. The conventional IMU-level fusion algorithm, using IMU raw measurements, is straightforward and highly efficient but yields poor robustness when the IMU array is not rigidly installed. On the contrary, the classic INS-level fusion algorithm, using navigation results from each IMU, is immune to the nonrigid installation of the IMU array but suffers a heavy computation load. Here, we propose a robust and efficient INS-level fusion algorithm for IMU array/GNSS (eNav-Fusion). Each IMU in the array shares the common state covariance (P matrix) and Kalman gain (K matrix), and the navigation solutions of all IMUs are eventually fused to produce a more accurate solution. The proposed eNav-Fusion was fully evaluated with rigidly and nonrigidly installed IMU arrays. For a rigid 16-IMU array, the processing time of eNav-Fusion was close to that of the IMU-level fusion and only 1.22x to that of the INS/GNSS algorithm for a single IMU; and the navigation performance was improved by 2.51 x , as expected for such scale of array. For a nonrigid 6-IMU array, in which case the traditional IMU-level fusion does not work, eNav-Fusion still maintained the same accuracy as the classic INS-level fusion algorithm, while the computation load is still close to that of the IMU-level fusion. In conclusion, the proposed eNav-Fusion achieves the same robustness as the INS-level fusion, while only consuming comparable computational complexity to the IMU-level fusion.
Keywords:
Navigation
Arrays
Data integration
Global navigation satellite system
Classification algorithms
Computational complexity
Sensors
Data fusion
inertial measurement unit (IMU) array
inertial navigation system (INS)/global navigation satellite system (GNSS)
micro-electromechanical system (MEMS) IMU
Journal
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4.5
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2.1W
Citations:
7.3W
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Cited Papers
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