An Accurate Land-Vehicle MEMS IMU/GPS Navigation System Using 3D Auxiliary Velocity Updates

A constrained low-cost SINS/OD filter aided with magnetometer is proposed in this paper. The filter is designed to provide a land vehicle navigation solution by fusing the measurements of the microelectromechanical systems based inertial measurement unit (MEMS IMU), the magnetometer (MAG), and the velocity measurement from odometer (OD). First, accelerometer and magnetometer integrated algorithm is studied to stabilize the attitude angle. Next, a SINS/OD/MAG integrated navigation system is designed and simulated, using an adaptive Kalman filter (AKF). It is shown that the accuracy of the integrated navigation system will be implemented to some extent. The field-test shows that the azimuth misalignment angle will diminish to less than 1°. Finally, an outliers detection algorithm is studied to estimate the velocity measurement bias of the odometer. The experimental results show the enhancement in restraining observation outliers that improves the precision of the integrated navigation system.

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Map-based land vehicle navigation system with DGPS

Intelligent Vehicle Symposium, 2002. IEEE ◽

10.1109/ivs.2002.1187953 ◽

2003 ◽

Cited By ~ 2

Author(s):

S.S. Saab ◽

Z.M. Kassas

Keyword(s):

Navigation System ◽

Vehicle Navigation ◽

Land Vehicle ◽

Land Vehicle Navigation ◽

Vehicle Navigation System

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Study on GPS Navigation Navigation System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.556-562.3313 ◽

2014 ◽

Vol 556-562 ◽

pp. 3313-3316

Author(s):

Hao Ran Song

Keyword(s):

Global Positioning System ◽

Navigation System ◽

Systems Design ◽

Design System ◽

Factors Affecting ◽

Gps Navigation ◽

Communications Technologies ◽

Global Positioning ◽

Depth Study ◽

System Requirements

Currently, GPS global positioning system has been in the areas of precise positioning, navigation, timing has been widely used. By GPS-OEM combined with computer and communications technologies, users are able to easily and independently developed to meet the specific needs of GPS systems. Design system based on GPS navigation navigation system requirements package, in-depth study of the main factors affecting the precision of navigation. Several factors made corresponding solutions, implements navigation navigation system the main functions of the software.

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Performance Enhancement of Pedestrian Navigation Systems Based on Low-Cost Foot-Mounted MEMS-IMU/Ultrasonic Sensor

Sensors ◽

10.3390/s19020364 ◽

2019 ◽

Vol 19 (2) ◽

pp. 364 ◽

Cited By ~ 5

Author(s):

Ming Xia ◽

Chundi Xiu ◽

Dongkai Yang ◽

Li Wang

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Navigation System ◽

Low Cost ◽

Ultrasonic Sensor ◽

Measurement Unit ◽

Positioning Error ◽

Process Noise ◽

Pedestrian Navigation ◽

Mems Imu

The pedestrian navigation system (PNS) based on inertial navigation system-extended Kalman filter-zero velocity update (INS-EKF-ZUPT or IEZ) is widely used in complex environments without external infrastructure owing to its characteristics of autonomy and continuity. IEZ, however, suffers from performance degradation caused by the dynamic change of process noise statistics and heading estimation errors. The main goal of this study is to effectively improve the accuracy and robustness of pedestrian localization based on the integration of the low-cost foot-mounted microelectromechanical system inertial measurement unit (MEMS-IMU) and ultrasonic sensor. The proposed solution has two main components: (1) the fuzzy inference system (FIS) is exploited to generate the adaptive factor for extended Kalman filter (EKF) after addressing the mismatch between statistical sample covariance of innovation and the theoretical one, and the fuzzy adaptive EKF (FAEKF) based on the MEMS-IMU/ultrasonic sensor for pedestrians was proposed. Accordingly, the adaptive factor is applied to correct process noise covariance that accurately reflects previous state estimations. (2) A straight motion heading update (SMHU) algorithm is developed to detect whether a straight walk happens and to revise errors in heading if the ultrasonic sensor detects the distance between the foot and reflection point of the wall. The experimental results show that horizontal positioning error is less than 2% of the total travelled distance (TTD) in different environments, which is the same order of positioning error compared with other works using high-end MEMS-IMU. It is concluded that the proposed approach can achieve high performance for PNS in terms of accuracy and robustness.

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