On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors

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On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors

The integration of the Inertial Navigation System (INS) and the Global Positioning System (GPS) is widely applied to seamlessly determine the time-variable position and orientation parameters of a system for navigation and mobile mapping applications. For optimal data fusion, the Kalman filter (KF) is often used for real-time applications. Backward smoothing is considered an optimal post-proces...

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Based on a small, lightweight, low-cost high performance inertial Measurement Units(IMU), an effective calibration method is implemented to evaluate the performance of Micro-Electro-Mechanical Systems(MEMS) sensors suffering from various errors to get acceptable navigation results. A prototype development board based on FPGA, dual core processor’s configuration for INS/GPS integrated navigation...

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Calibration of a Low Cost Mems Ins Sensor for an Integrated Navigation System

The method, the procedure and the results of the calibration of a low cost MEMS INS sensor are described and discussed. The reduced cost of the MEMSs sensors is very advantageous, but these sensors are characterized by much large errors. The accurate calibration of the sensors is very important for the determination of the systematic errors, like bias, scale factor and misalignment of the axes....

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Test Results of a Gps/inertial Navigation System Using a Low Cost Mems Imu

This paper describes the design, operation, and test results of a miniature, low cost integrated GPS/inertial navigation system that uses commercial off-the-shelf Micro-Electro-Mechanical System (MEMS) accelerometers and gyroscopes. The MEMS inertial measurement unit (IMU) is packaged in a small size and provides the raw IMU data through a serial interface to a processor board where the inertia...

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ژورنال

عنوان ژورنال: Sensors

سال: 2012

ISSN: 1424-8220

DOI: 10.3390/s121217372