scholarly journals A low-cost IMU/GPS position accuracy experimental study using extended kalman filter data fusion in real environments

2021 ◽  
Vol 297 ◽  
pp. 01040
Author(s):  
Aziz El Fatimi ◽  
Adnane Addaim ◽  
Zouhair Guennoun
Keyword(s):  
Experimental Study ◽  
Data Fusion ◽  
Low Cost ◽  
Three Dimensional ◽  
Measurement Unit ◽  
Circular Path ◽  
Positioning System ◽  
Fusion Algorithm ◽  
Position Accuracy ◽  
The Stability

In a three-dimensional environment, the navigation of a vehicle in airspace, terrestrial space, or maritime space presents complex aspects concerning the determination of its position, its orientation, and the stability of the processing of the asynchronous data coming from the various sensors during navigation. In this context, this paper presents an experimental analysis of the position accuracy estimated by a low-cost inertial measurement unit coupled, by the extended Kalman data fusion algorithm, with a system of absolute measurements of a positioning system received from a GPS which designates the global positioning system. The different scenarios of the experimental study carried out during this work concerned three tests in a real environment, such as the navigation in a course inside the city of Rabat/Morocco with a moderate speed, a section on the highway at a speed of 120 Km/h and a circular path around a roundabout. The experimental results proved that the low-cost sensors studied are a good candidate for civil navigation applications.

scholarly journals Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6292
Author(s):  
Vincenzo Di Pietra ◽  
Paolo Dabove ◽  
Marco Piras
Keyword(s):  
Data Fusion ◽  
Low Cost ◽  
Ground Truth ◽  
Location Based Services ◽  
Global Navigation Satellite Systems ◽  
Ultra Wideband ◽  
Portable Devices ◽  
Positioning System ◽  
Fusion Algorithm ◽  
Satellite Systems

The growth of location-based services (LBS) has increased rapidly in last years, mainly due to the possibility to exploit low-cost sensors installed in portable devices, such as smartphones and tablets. This work aims to show a low-cost multi-sensor platform developed by the authors in which an ultra-wideband (UWB) indoor positioning system is added to a classical global navigation satellite systems–inertial navigation system (GNSS-INS) integration, in order to acquire different synchronized data for further data fusion analysis in order to exploit seamless positioning. The data fusion is based on an extended Kalman filter (EKF) and on a geo-fencing approach which allows the navigation solution to be provided continuously. In particular, the proposed algorithm aims to solve a navigation task of a pedestrian user moving from an outdoor space to an indoor environment. The methodology and the system setup is presented with more details in the paper. The data acquired and the real-time positioning estimation are analysed in depth and compared with ground truth measurements. Particular attention is given to the UWB positioning system and its behaviour with respect to the environment. The proposed data fusion algorithm provides an overall horizontal and 3D accuracy of 35 cm and 45 cm, respectively, obtained considering 5 different measurement campaigns.

scholarly journals Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2480
Author(s):  
Isidoro Ruiz-García ◽  
Ismael Navarro-Marchal ◽  
Javier Ocaña-Wilhelmi ◽  
Alberto J. Palma ◽  
Pablo J. Gómez-López ◽  
...  
Keyword(s):  
Data Fusion ◽  
Reference System ◽  
Inertial Sensor ◽  
Low Cost ◽  
Sampling Rate ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Improve Technique ◽  
Worst Case ◽  
Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

A Low-Cost, High Rate Motion Software Sensor System Based on Novel Data Fusion for Unmanned Surface Vehicle Navigation and Oceanographic Instrumentation Motion Correction

2011 ◽  
Author(s):  
Chrystel R. Gelin ◽  
Nikolaos I. Xiros
Keyword(s):  
Data Fusion ◽  
Low Cost ◽  
Underwater Vehicles ◽  
High Rate ◽  
Measurement Unit ◽  
Vehicle Navigation ◽  
Gps Receiver ◽  
Unmanned Surface Vehicle ◽  
Flux Gate ◽  
Tilt Sensor

One of the major challenges in the navigation of underwater vehicles is obtaining precise and reliable positioning updates. Dead-Reckoning aided with Doppler velocity measurement has been, and remains, the most common method for underwater navigation for small vehicles. DR uses a set of navigation instruments to estimate the position of the vehicle by integrating the body-fixed velocity, accelerations, and angular rates with respect to time. Instrument error and bias lead to position error that increases exponentially with time. Thus, current DR systems require frequent position recalibrations. The Global Positioning System (GPS) provides measurements of geodetic coordinates for air and surface vehicles and it is often used to correct positioning error. However, underwater vehicles cannot use GPS for inflight navigation because GPS signals only penetrate a few centimeters past the air-sea interface. Thus, underwater vehicle navigation systems are limited to periodic position update from the GPS when they surface and extend an antenna through the air-sea interface. Standard GPS receivers are unable to provide the rate or precision required when used on a small vessel such as an Unmanned Surface Vehicle (USV). To overcome this, a low cost high rate motion measurement system for an USV with underwater and oceanographic purposes is proposed. The proposed onboard system for the USV consists of an Inertial Measurement Unit (IMU) with accelerometers and rate gyros, a GPS receiver, a flux-gate compass, a roll and tilt sensor and an ADCP. Interfacing all the sensors proved rather challenging because of their different characteristics. Some of the instruments have digital output (Compass/ADCP/GPS) while others have an analog output (IMU/tilt sensor). The proposed data fusion technique integrates the IMU, GPS receiver, flux-gate compass as well as tilt sensor and develops an embeddable software package, using real time data fusion methods, for a USV to aid in navigation and control as well as controlling an onboard Acoustic Doppler Current Profiler (ADCP). While ADCPs non-intrusively measure water flow, they suffer from the inability to distinguish between motions in the water column and self-motion. Thus, the vessel motion contamination needs to be removed to analyze the data and the system developed in this text provides the motion measurements and processing to accomplish this task.

Sensor Data Fusion Algorithm for Indoor Environment Mapping Using Low-Cost Sensors

2013 ◽  
Vol 24 (3) ◽  
pp. 199-211 ◽  
Author(s):  
Luciano Buonocore ◽  
Cairo Lúcio Nascimento Júnior ◽  
Areolino de Almeida Neto
Keyword(s):  
Data Fusion ◽  
Indoor Environment ◽  
Low Cost ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Sensor Data Fusion

scholarly journals An Unconventional Multiple Low-Cost IMU and GPS-Integrated Kinematic Positioning and Navigation Method Based on Singer Model

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4274
Author(s):  
Zhu ◽  
Yu ◽  
Xiao
Keyword(s):  
Low Cost ◽  
A Priori ◽  
Strong Dependence ◽  
Kinematic Model ◽  
Three Dimensional ◽  
Measurement Unit ◽  
Trajectory Model ◽  
The Road ◽  
Integration Strategy ◽  
Smooth Transitions

To release the strong dependence of the conventional inertial navigation mechanization on the a priori low-cost inertial measurement unit (IMU) error model, this research applies an unconventional multi-sensor integration strategy to integrate multiple low-cost IMUs and a global positioning system (GPS) for mass-market automotive applications. The unconventional integration strategy utilizes a basic three-dimensional (3D) kinematic trajectory model as the system model to directly estimate navigational parameters, and it allows the measurements from all of the sensors independently participating in measurement updates. However, the less complex kinematic model cannot realize smooth transitions between different motion statuses for the road vehicle with acceleration maneuvers. In this manuscript, we establish a more practical 3D kinematic trajectory model based on a “current” statistical Singer acceleration model to realize smooth transitions for the maneuvering vehicle. In addition, taking advantage of the unconventional strategy, we individually model the systematic errors of each IMU and the measurements of all sensors, in contrast to most existing approaches that adopt the common-mode errors for different sensors of the same design. A real dataset involving a GPS and multiple IMUs is processed to validate the success of the proposed algorithm model under the unconventional integration strategy.

scholarly journals Attitude Determination Method by Fusing Single Antenna GPS and Low Cost MEMS Sensors Using Intelligent Kalman Filter Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Lei Wang ◽  
Bo Song ◽  
Xueshuai Han ◽  
Yongping Hao
Keyword(s):  
Kalman Filter ◽  
Attitude Determination ◽  
Fuzzy Controller ◽  
Low Cost ◽  
Transition Process ◽  
Measurement Unit ◽  
Accurate Estimation ◽  
Mems Sensors ◽  
Fusion Algorithm ◽  
Single Antenna

For meeting the demands of cost and size for micronavigation system, a combined attitude determination approach with sensor fusion algorithm and intelligent Kalman filter (IKF) on low cost Micro-Electro-Mechanical System (MEMS) gyroscope, accelerometer, and magnetometer and single antenna Global Positioning System (GPS) is proposed. The effective calibration method is performed to compensate the effect of errors in low cost MEMS Inertial Measurement Unit (IMU). The different control strategies fusing the MEMS multisensors are designed. The yaw angle fusing gyroscope, accelerometer, and magnetometer algorithm is estimated accurately under GPS failure and unavailable sideslip situations. For resolving robust control and characters of the uncertain noise statistics influence, the high gain scale of IKF is adjusted by fuzzy controller in the transition process and steady state to achieve faster convergence and accurate estimation. The experiments comparing different MEMS sensors and fusion algorithms are implemented to verify the validity of the proposed approach.

A low-cost integrated positioning system for autonomous off-highway vehicles

2008 ◽  
Vol 222 (11) ◽  
pp. 1997-2009 ◽  
Author(s):  
L-S Guo ◽  
Q Zhang
Keyword(s):  
Inertial Sensor ◽  
Low Cost ◽  
Maximum Error ◽  
Positioning System ◽  
Differential Gps ◽  
Fusion Algorithm ◽  
Position Information ◽  
Mems Accelerometer ◽  
Sensor Unit ◽  
Update Rate

This article reports a method for integrating a low-cost positioning system, constructed using a Garmin N17 global positioning system (GPS) and an integrated inertial sensor unit, consisting of three single-axis microelectromechanical system (MEMS) gyros and one triaxial MEMS accelerometer, for autonomous off-highway vehicle use. Based on a vehicle position—velocity—attitude (PVA) model, a data fusion algorithm was formulated to extract more accurate and reliable positioning information from the raw data sensed by the GPS and inertial sensor unit. The developed integrated positioning system (IPS) was evaluated on an agricultural utility vehicle on three different sites. A real-time kinematic (RTK) differential GPS unit, capable of providing 2–3cm dynamic positioning accuracy while the position dilution of precision is low enough, was installed on the test vehicle to provide accurate positioning references in those evaluation tests. Results obtained from those tests showed that, when the vehicle was travelling on paved roads near buildings and/or under the trees, the maximum positioning error of the developed IPS was 0.50m, and that this maximum error level was reduced to 0.30m when the vehicle was travelling in open fields. The IPS could provide a position update rate at 50Hz; even the GPS could provide only a 1Hz update rate. Test results also revealed that this system could continuously provide accurate position signals when the GPS signal is lost for up to 30s. This research verified that a low-cost IPS could provide satisfactory position information for autonomous off-highway vehicle uses.

Stability Experimental Study on High Temperature and Oxygen-Containing Flue Gas

2012 ◽  
Vol 512-515 ◽  
pp. 1307-1310
Author(s):  
Wu Qi Wen ◽  
Shi Ping Jin ◽  
Su Yi Huang ◽  
Shun Li Fang ◽  
Xi Lai Zhang ◽  
...  
Keyword(s):  
Experimental Study ◽  
High Temperature ◽  
Flue Gas ◽  
Low Cost ◽  
Calorific Value ◽  
Marginal Effect ◽  
Pyrolysis Process ◽  
Key Technology ◽  
The Stability ◽  
Generation Rule

During lignite pyrolysis process, there will produce large amounts of gas which is low calorific value, combustion difficult. This paper creatively put forward a program: high temperature and oxygen-containing flue gas of coal-fired mix combustion with low calorific value gas. Compared to mixing high calorific value fuel, the distinguishing feature of this program is ultra-low cost, and technically feasible. In this scheme, the stability of high-temperature and oxygen-containing flue gas is key technology. Through coal-fired experiments, we obtained generation rule of high-temperature and oxygen-containing flue gas, and summed up a diminishing marginal effect.

scholarly journals Design and Implementation of a 3-Dimensional Attitudes Estimator Device using Low Cost Accelerometer & Gyroscope with Microcontroller IDE

2020 ◽  
Vol 12 (2) ◽  
pp. 151-161
Author(s):  
M. RAJA ◽  
Ugur GUVEN ◽  
Kartikay SINGH
Keyword(s):  
Dimensional Space ◽  
Low Cost ◽  
Three Dimensional ◽  
3 Dimensional ◽  
Aerospace Applications ◽  
Vector Quantity ◽  
Measurement Units ◽  
Fixed Axis ◽  
The Stability ◽  
Three Dimensional Space

Navigation and guidance systems for most automobile as well as aerospace applications require a coupled chip setup known as Inertial Measurement Units (IMU) which, depending on the degree of freedoms, contains a Gyroscope (for maintaining orientation and angular velocity), Accelerometers (to determine acceleration in the respective direction) and a Magnetometer (to determine the respective magnetic fields). In the three-dimensional space, any required rotation analysis is limited to the coordinate systems and all subtended angles in either direction must be defined by a fixed axis to effectively estimate the stability and to define all the attitude estimates needed to compile different rotations and orientations. The Quaternions are mathematical notations used for defining rotations and orientation in three-dimensional space. The simplest terms Quaternions are impossible to visualize in a three-dimensional space; the first three terms will be identical to the coordinate system, but through Quaternions another vector quantity is added into the equations, which may in fact underline how we can account for all rotational quantities. The fundamental analysis of these components different applications for various fields is proposed.

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