2012Unpublished venueRequires access

Research on Micro SINS/GPS Integrated Navigation System Based on MEMS Sensors

Yonghao Hu, Yangzhu Wang, Qibing Zhao

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Abstract

In this paper we describe a micro SINS/GPS Integrated Navigation System based on MEMS sensors. According to the special characters of micro navigation sensors, the navigation errors of Microminiaturized Inertial Measurement(MIMU), micro GPS receivers were analyzed and modeled using the time-sequence analysis from the random series respectively in order to achieve high-precision navigation. In order to obtain the precise information by the navigation information of multi-sensors, a Kalman filter is applied to combine the inertial solutions with the GPS position and velocity output to estimate errors in the inertial navigation solutions and the IMU measurements. Estimates of the inertial error states are fed back to the SINS algorithm to improve inertial navigation accuracy. Test results are presented showing the performance of the integrated MEMS SINS/GPS. Data is provided showing the position, velocity, and attitude accuracy when operating with GPS aiding.

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What this paper is about

In this paper we describe a micro SINS/GPS Integrated Navigation System based on MEMS sensors. According to the special characters of micro navigation sensors, the navigation errors of Microminiaturized Inertial Measurement(MIMU), micro GPS receivers were analyzed and modeled using the time-sequence analysis from the random series respectively in order to achieve high-precision navigation. In order to obtain the precise information by the navigation information of multi-sensors, a Kalman filter is applied to combine the inertial solutions with the GPS position and velocity output to estimate errors in the inertial navigation solutions and the IMU measurements. Estimates of the inertial error states are fed back to the SINS algorithm to improve inertial navigation accuracy. Test results are presented showing the performance of the integrated MEMS SINS/GPS. Data is provided showing the position, velocity, and attitude accuracy when operating with GPS aiding.

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Available abstract

In this paper we describe a micro SINS/GPS Integrated Navigation System based on MEMS sensors. According to the special characters of micro navigation sensors, the navigation errors of Microminiaturized Inertial Measurement(MIMU), micro GPS receivers were analyzed and modeled using the time-sequence analysis from the random series respectively in order to achieve high-precision navigation. In order to obtain the precise information by the navigation information of multi-sensors, a Kalman filter is applied to combine the inertial solutions with the GPS position and velocity output to estimate errors in the inertial navigation solutions and the IMU measurements. Estimates of the inertial error states are fed back to the SINS algorithm to improve inertial navigation accuracy. Test results are presented showing the performance of the integrated MEMS SINS/GPS. Data is provided showing the position, velocity, and attitude accuracy when operating with GPS aiding.

Key concepts: Inertial navigation system, Global Positioning System, Inertial measurement unit, GPS/INS, Kalman filter, Computer science, Dead reckoning, Navigation system

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