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A GNSS/INS Integrated Navigation Compensation Method Based on CNN–GRU + IRAKF Hybrid Model During GNSS Outages | IEEE Journals & Magazine | IEEE Xplore

A GNSS/INS Integrated Navigation Compensation Method Based on CNN–GRU + IRAKF Hybrid Model During GNSS Outages


Abstract:

The integrated navigation system, which consists of the global navigation satellite system (GNSS) and inertial navigation system (INS), is widely used in various platform...Show More

Abstract:

The integrated navigation system, which consists of the global navigation satellite system (GNSS) and inertial navigation system (INS), is widely used in various platforms. However, when the GNSS signal is unavailable, the GNSS/INS integrated navigation system will be converted into INS working alone. The error will gradually diverge. To solve this problem, this article constructs a hybrid neural network model composed of convolutional neural network (CNN) and gated recurrent unit (GRU). It combines the Pseudo-measurement information of GNSS predicted by the model with INS for integrated navigation to compensate for the interruption of GNSS and correct the error of INS. At the same time, considering that the predicted GNSS position information has a significant error, if the estimation is not accurate, the filtering accuracy of the system will decrease. Therefore, this article proposes an improved robust adaptive Kalman filter (IRAKF) algorithm to estimate the measurement noise covariance matrix for GNSS pseudo-measurement information. The actual road test results show that the addition of the CNN–GRU model and IRAKF algorithm improves the overall accuracy of the system.
Article Sequence Number: 2510015
Date of Publication: 23 February 2024

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I. Introduction

The global navigation satellite system (GNSS) has developed rapidly in the past few decades. It mainly includes the global position system (GPS) of the United States, the Global Navigation Satellite System (GLONASS) of Russia, the Galileo Navigation Satellite System (Galileo) of Europe and the BeiDou Navigation Satellite System (BDS) of China [1]. These navigation systems are usually composed of many navigation satellites. The GNSS receiver can calculate the distance from the satellite to the GNSS receiver by receiving the satellite signal. After receiving the signal of at least four satellites, we can get the absolute positioning of the GNSS receiver. The positioning accuracy of the GNSS system will not diverge over time, but its positioning accuracy is not high, and the positioning output frequency is low, usually 1 Hz. The inertial navigation system (INS) is a relative positioning system, which is based on the output of the inertial measurement unit (IMU) to calculate the position, velocity, attitude, and other information of the carrier. It is not affected by the external environment and is only related to the performance of itself. It has high precision in a short time and high output frequency, usually above 50 Hz. However, because it is based on the information of the previous moment, it is easy to cause cumulative error. Therefore, INS is not suitable for long-term positioning.

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