Implementation and performance of a GPS/INS integrated navigation using MEMS inertial sensors

Songyue Chen; Liang Wang; Weixiu Yang

Implementation and performance of a GPS/INS integrated navigation using MEMS inertial sensors

Songyue Chen
, Liang Wang
, Weixiu Yang

School of Automation Science and Electrical Engineering

Beihang University

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, an integrated navigation system based on MEMS-IMU/GPS is implemented through optimization of GPS information processing and Kalman filter algorithm. Low-cost IMU and GPS receivers are used with STEM32 as the core of information processing. An improved speed/position combination is adopted in this paper. Test results are presented showing the performance of the integrated MEMS GPS/inertial navigation system: This measure improves aircraft navigation accuracy and corrects the divergence more quickly. This allows integration with less errors characteristic, which is more suitable for aircrafts with low-cost, low-power, lightweight GPS chip receivers and navigation sensors.

Original language	English
State	Published - 2018
Event	CSAA/IET International Conference on Aircraft Utility Systems, AUS 2018 - Guiyang, China Duration: 19 Jun 2018 → 22 Jun 2018

Conference

Conference	CSAA/IET International Conference on Aircraft Utility Systems, AUS 2018
Country/Territory	China
City	Guiyang
Period	19/06/18 → 22/06/18

Keywords

GPS
INS
Kalman filter
MEMS inertial sensor
Navigation

Cite this

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title = "Implementation and performance of a GPS/INS integrated navigation using MEMS inertial sensors",

abstract = "In this paper, an integrated navigation system based on MEMS-IMU/GPS is implemented through optimization of GPS information processing and Kalman filter algorithm. Low-cost IMU and GPS receivers are used with STEM32 as the core of information processing. An improved speed/position combination is adopted in this paper. Test results are presented showing the performance of the integrated MEMS GPS/inertial navigation system: This measure improves aircraft navigation accuracy and corrects the divergence more quickly. This allows integration with less errors characteristic, which is more suitable for aircrafts with low-cost, low-power, lightweight GPS chip receivers and navigation sensors.",

keywords = "GPS, INS, Kalman filter, MEMS inertial sensor, Navigation",

author = "Songyue Chen and Liang Wang and Weixiu Yang",

note = "Publisher Copyright: {\textcopyright} 2018 IET Conference Publications. All rights reserved.; CSAA/IET International Conference on Aircraft Utility Systems, AUS 2018 ; Conference date: 19-06-2018 Through 22-06-2018",

year = "2018",

language = "英语",

}

TY - CONF

T1 - Implementation and performance of a GPS/INS integrated navigation using MEMS inertial sensors

AU - Chen, Songyue

AU - Wang, Liang

AU - Yang, Weixiu

PY - 2018

Y1 - 2018

N2 - In this paper, an integrated navigation system based on MEMS-IMU/GPS is implemented through optimization of GPS information processing and Kalman filter algorithm. Low-cost IMU and GPS receivers are used with STEM32 as the core of information processing. An improved speed/position combination is adopted in this paper. Test results are presented showing the performance of the integrated MEMS GPS/inertial navigation system: This measure improves aircraft navigation accuracy and corrects the divergence more quickly. This allows integration with less errors characteristic, which is more suitable for aircrafts with low-cost, low-power, lightweight GPS chip receivers and navigation sensors.

AB - In this paper, an integrated navigation system based on MEMS-IMU/GPS is implemented through optimization of GPS information processing and Kalman filter algorithm. Low-cost IMU and GPS receivers are used with STEM32 as the core of information processing. An improved speed/position combination is adopted in this paper. Test results are presented showing the performance of the integrated MEMS GPS/inertial navigation system: This measure improves aircraft navigation accuracy and corrects the divergence more quickly. This allows integration with less errors characteristic, which is more suitable for aircrafts with low-cost, low-power, lightweight GPS chip receivers and navigation sensors.

KW - GPS

KW - INS

KW - Kalman filter

KW - MEMS inertial sensor

KW - Navigation

UR - https://www.scopus.com/pages/publications/85054698807

M3 - 论文

AN - SCOPUS:85054698807

T2 - CSAA/IET International Conference on Aircraft Utility Systems, AUS 2018

Y2 - 19 June 2018 through 22 June 2018

ER -

Implementation and performance of a GPS/INS integrated navigation using MEMS inertial sensors

Abstract

Conference

Keywords

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