• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.235-243
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• 2022

In this paper, in the case of an inertial navigation system, the posture estimation error in the initial alignment due to vertical deflection is analyzed. Posture estimation error due to DOV was theoretically analyzed based on the speed and posture error of INS. Simulations were performed to verify the theoretical grinding, and the results were in good agreement. For example, in the case of η=20", an alignment error of ϕ_N=0.00287°, ϕ_U=0.00196° occurred, and in the case of 𝜉=20", an error of ϕ_E= -0.00286° occurred. Through this, it was confirmed that the vertical posture error caused by the DOV occurred as a coupling characteristic of the INS posture error. It has been shown that an additional posture error may occur due to the DOV, which was not considered in the existing INS alignment, which means that correction for the DOV must be considered when applying high-precision INS.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.674-684
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• 2023

In this paper, a real-time prediction technique for gravity disturbances is proposed using a multi-layer perceptron (MLP) model. To select a suitable MLP model, 4 models with different network sizes were designed to compare the training accuracy and execution time. The MLP models were trained using the data of vehicle moving along the surface of the sea or land, including their positions and gravity disturbance. The gravity disturbances were calculated using the 2160^th degree and order EGM2008 with SHM. Among the models, MLP4 demonstrated the highest training accuracy. After training, the weights and biases of the 4 models were stored in the embedded computer of the INS to implement the MLP network. MLP4 was found to have the shortest execution time among the 4 models. These research results are expected to contribute to improving the navigation accuracy of INS through gravity disturbance compensation in the future.