Piezoelectrics & Acoustooptics, Volume. 46, Issue 4, 478(2024)

Integrated Navigation Algorithm Based on Interactive Multi-Model Square-Root Cubature Kalman Filter

MEI Fangyu1... QIU Haitao1, WANG Tianyu1 and ZHANG Feng2 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    To address the issue of reduced filtering accuracy in integrated navigation systems caused by variable noise interference, an algorithm based on interactive multi-model (IMM) and square-root cubature Kalman filter(SCKF) is proposed. The IMM-SCKF filtering algorithm employs multiple model sets and adjusts the probability of the sub-model while fusing the output, allowing it to simulate the actual noise covariance to a certain degree. Simulation and road test results show that the root mean square (RMS) error of the IMM-SCKF algorithm is superior to that of the traditional single-model CKF algorithm, effectively enhancing the reliability of the integrated navigation system. Compared to the traditional CKF algorithm, the IMM-SCKF algorithm reduced the RMS error in eastward, northward, and up speed errors by 52%, 55%, and 30%, respectively, and the RMS error in position by 47%,60%, and 32%, respectively. The IMM-SCKF algorithm significantly improves the positioning accuracy and antiinterference ability of the system.

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    MEI Fangyu, QIU Haitao, WANG Tianyu, ZHANG Feng. Integrated Navigation Algorithm Based on Interactive Multi-Model Square-Root Cubature Kalman Filter[J]. Piezoelectrics & Acoustooptics, 2024, 46(4): 478

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    Paper Information

    Received: Apr. 9, 2024

    Accepted: --

    Published Online: Sep. 18, 2024

    The Author Email:

    DOI:10.11977/j.issn.1004-2474.2024.04.011

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