Robust GNSS/SINS positioning based on the SE2(3)-EKF framework

doi:10.11947/j.AGCS.2023.20220526

Abstract

Abstract: For GNSS/SINS integrated navigation, the large errors, such as attitude misalignment angle, will cause the inconsistent coordinates definition of state error and large linearization error, thus the performance of traditional filtering and positioning is reduced, especially in the complex GNSS observation environment. In this paper, the attitude, velocity, and position states are reconstructed as a special SE₂(3) group element, considering the bias of gyro and accelerometer, a group-vector mixed error model is formed, and then one GNSS/SINS robust filtering algorithm (RLIEKF) based on left invariant measurement is studied. The superiority of the proposed method is validated via the vehicle integrated navigation experiment with large misalignment angle error and GNSS outliers in urban environment. The experimental results show that, compared with traditional EKF method, the attitude angle error is considered in time update and GNSS measurement update of the proposed RLIEKF, thus it has a fast convergence speed under different large misalignment angles, without complicated and long-time attitude alignment steps, which can better deal with the problem such the interrupt GNSS signal during a short time. Because the accuracy of innovation is significantly improved, thus it is more robust to complex observation environment, and with a fast computational efficiency, therefore it has excellent engineering practical value.

Key words: GNSS/SINS, large misalignment, robust filtering, integrated positioning

CLC Number:

P227

LI Xin, MENG Shuolin, HUANG Guanwen, ZHANG Qin, LI Hanxu. Robust GNSS/SINS positioning based on the SE₂(3)-EKF framework[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(10): 1640-1649.

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Robust GNSS/SINS positioning based on the SE₂(3)-EKF framework

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