scholarly journals Concept of AHRS Algorithm Designed for Platform Independent Imu Attitude Alignment

2017 ◽  
Vol 104 (1) ◽  
pp. 33-47 ◽  
Author(s):  
Dariusz Tomaszewski ◽  
Jacek Rapiński ◽  
Renata Pelc-Mieczkowska
Keyword(s):  
Coordinate System ◽  
Inertial Measurement Unit ◽  
Low Cost ◽  
Rapid Development ◽  
Satellite Navigation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Satellite Navigation Systems ◽  
Attitude Alignment

Abstract Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.

Concept of INS/GPS Integration Algorithm Designed for MEMS Based Navigation Platform

2017 ◽  
Author(s):  
Dariusz Tomaszewski
Keyword(s):  
Kalman Filter ◽  
Measurement System ◽  
Low Cost ◽  
Rapid Development ◽  
Satellite Navigation ◽  
Navigation Systems ◽  
Mems Devices ◽  
Integration Algorithm ◽  
Smartphone Sensors ◽  
Satellite Navigation Systems

Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far, the most popular satellite navigation, is now supported by positioning results calculated with the use of other measurement system. The method and manner of integration will depend directly on the destination of developed system. To increase the frequency of readings and improve the operation of outdoor navigation systems, one can support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation (INS/GPS systems). For the last two decades, due to the miniaturization in electronics it is possible to build GPS/INS systems with the use of low cost MEMS devices. The following study presents the concept of Kalman filter based integration algorithm designed for cheap micro – electronic navigation platform. The tests of considered algorithm were made with the use of MEMS smartphone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm.

scholarly journals Performance Assessment of an Ultra Low-Cost Inertial Measurement Unit for Ground Vehicle Navigation

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3865 ◽  
Author(s):  
Rodrigo Gonzalez ◽  
Paolo Dabove
Keyword(s):  
Automotive Industry ◽  
Inertial Measurement Unit ◽  
Microelectromechanical Systems ◽  
Inertial Sensor ◽  
Low Cost ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Mass Market ◽  
Inertial Measurement ◽  
Mems Imu

Nowadays, navigation systems are becoming common in the automotive industry due to advanced driver assistance systems and the development of autonomous vehicles. The MPU-6000 is a popular ultra low-cost Microelectromechanical Systems (MEMS) inertial measurement unit (IMU) used in several applications. Although this mass-market sensor is used extensively in a variety of fields, it has not caught the attention of the automotive industry. Moreover, a detailed performance analysis of this inertial sensor for ground navigation systems is not available in the previous literature. In this work, a deep examination of one MPU-6000 IMU as part of a low-cost navigation system for ground vehicles is provided. The steps to characterize the performance of the MPU-6000 are divided in two phases: static and kinematic analyses. Besides, an additional MEMS IMU of superior quality is also included in all experiments just for the purpose of comparison. After the static analysis, a kinematic test is conducted by generating a real urban trajectory registering an MPU-6000 IMU, the higher-grade MEMS IMU, and two GNSS receivers. The kinematic trajectory is divided in two parts, a normal trajectory with good satellites visibility and a second part where the Global Navigation Satellite System (GNSS) signal is forced to be lost. Evaluating the attitude and position inaccuracies from these two scenarios, it is concluded in this preliminary work that this mass-market IMU can be considered as a convenient inertial sensor for low-cost integrated navigation systems for applications that can tolerate a 3D position error of about 2 m and a heading angle error of about 3 °.

Error Modeling and Analysis of Inertial Measurement Unit Using Stochastic and Deterministic Techniques

2011 ◽  
Vol 403-408 ◽  
pp. 4447-4455
Author(s):  
Zeeshan Ashraf ◽  
Wajeeha Nafees
Keyword(s):  
Inertial Measurement Unit ◽  
Low Cost ◽  
Stochastic Approach ◽  
Error Modeling ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Modeling And Analysis ◽  
Inertial Measurement ◽  
Noise Parameters ◽  
Navigation Algorithm

The measurements provided by inertial measurement unit (IMU) are erroneous due to certain noise parameters which are needed to be taken into account because the corrupted data is of little practical value in inertial navigation systems (INS). By integrating the IMU data in navigation algorithm, these errors are accumulated, leading to significant drift in the attitude, position and velocity outputs. Several techniques have been devised for the error modeling of this error by way of Neural Networks (NNs), PSD, ARMA, etc. In this paper, the deterministic and stochastic approach is followed to model the noise parameters of a low cost IMU. The error parameters thus determined by using the both techniques help in the development of an effective navigation algorithm. Deterministic errors are calculated by the help of Up-Down Test and the Rate Table test. While the stochastic errors, which are more random in nature, are recognized using Power Spectral Density (PSD) Analysis and Allan Variance techniques.

Optimal Processing of Information from Inertial and Satellite Navigation Systems by Analysis after Flight

2001 ◽  
Vol 56 (3) ◽  
pp. 13
Author(s):  
E. G. Kharin ◽  
V. G. Maslennikov ◽  
N. B. Vavilova ◽  
I. A. Kopylov ◽  
A. Ch. Staroverov
Keyword(s):  
Satellite Navigation ◽  
Navigation Systems ◽  
Optimal Processing ◽  
Satellite Navigation Systems

REVIEW OF SATELLITE-FREE NAVIGATION SYSTEMS

2018 ◽  
pp. 20-24
Author(s):  
M. K. Savkin ◽  
A. R. Filatov
Keyword(s):  
Satellite Navigation ◽  
Navigation Systems ◽  
Military Operations ◽  
Advantages And Disadvantages ◽  
Working Principle ◽  
Satellite Signal ◽  
Satellite Navigation Systems ◽  
Insufficient Number

Nowadays majority of navigation methods, used in unmanned flying vehicles, are based on satellite navigation systems, such as GPS or GLONASS, or are amplified with them. But hardware, that uses such systems, can’t work in difficult conditions, for example causes by relief: with insufficient number of satellites or at low satellite signal. Satellite navigation systems are vulnerable for methods of radio defense: satellite signal can be deadened or replaced. That is why such systems usage is unacceptable while critical missions during military operations, emergency or reconnaissance. The article briefly describes components used for building alternative satellite-free navigation systems for flying vehicles. For each component its purpose and brief description of working principle are given, advantages and disadvantages are considered.

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