Enhancing the accuracy of position and speed parameter determination for carrying devices through artificial neural networks
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https://doi.org/10.54939/1859-1043.j.mst.CAPITI.2024.182-188Keywords:
GPS/INS integrated system; Artificial intelligence; GPS outages.Abstract
This paper presents a method of applying an extended nonlinear Kalman filter to combine measured information from angular rate gyroscopes with magnetometers and accelerometers and satellite positioning information to estimate Rodrig - Hamilton parameters, position and speed of the carrier. In addition, the article also presents a method to improve the performance of the integrated global positioning system and inertial navigation system (GPS/INS) during GPS downtime, a new combined algorithm is proposed to provide virtual position and speed information to support an integrated positioning system, which is the application of ANN artificial neural network to improve accuracy when GPS is lost. The article focuses on improving the position accuracy and speed of carrier ships when GPS is lost. This issue is still new in Vietnam, and little has been published. The authors propose a solution to place a micromechanical gyroscope to measure angular speed, an accelerometer to measure apparent acceleration, and a magnetometer on the device to combine algorithms to solve the problem just mentioned above.
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