scholarly journals Invariant observers for attitude and heading estimation from low-cost inertial and magnetic sensors

2007 ◽  
Author(s):  
Philippe Martin ◽  
Erwan Salaun
Keyword(s):  
Low Cost ◽  
Magnetic Sensors ◽  
Heading Estimation

Deep Fusion of a Skewed Redundant Magnetic and Inertial Sensor for Heading State Estimation in a Saturated Indoor Environment

2021 ◽  
Vol 15 (03) ◽  
pp. 313-335
Author(s):  
Mojtaba Karimi ◽  
Edwin Babaians ◽  
Martin Oelsch ◽  
Eckehard Steinbach
Keyword(s):  
Magnetic Field ◽  
Indoor Environment ◽  
Inertial Sensor ◽  
Low Cost ◽  
Magnetic Sensors ◽  
Filter Model ◽  
Novel Approach ◽  
Essential Components ◽  
Heading Estimation

Robust attitude and heading estimation in an indoor environment with respect to a known reference are essential components for various robotic applications. Affordable Attitude and Heading Reference Systems (AHRS) are typically using low-cost solid-state MEMS-based sensors. The precision of heading estimation on such a system is typically degraded due to the encountered drift from the gyro measurements and distortions of the Earth’s magnetic field sensing. This paper presents a novel approach for robust indoor heading estimation based on skewed redundant inertial and magnetic sensors. Recurrent Neural Network-based (RNN) fusion is used to perform robust heading estimation with the ability to compensate for the external magnetic field anomalies. We use our previously described correlation-based filter model for preprocessing the data and for empowering perturbation mitigation. Our experimental results show that the proposed scheme is able to successfully mitigate the anomalies in the saturated indoor environment and achieve a Root-Mean-Square Error of less than [Formula: see text] for long-term use.

scholarly journals Gravity-Based Methods for Heading Computation in Pedestrian Dead Reckoning

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1170 ◽  
Author(s):  
Adi Manos ◽  
Itzik Klein ◽  
Tamir Hazan
Keyword(s):  
Field Experiments ◽  
Dead Reckoning ◽  
Vertical Direction ◽  
Indoor Navigation ◽  
Magnetic Sensors ◽  
Dominant Factor ◽  
Heading Estimation ◽  
Using Data ◽  
Pedestrian Dead Reckoning ◽  
Gravity Direction

One of the common ways for solving indoor navigation is known as Pedestrian Dead Reckoning (PDR), which employs inertial and magnetic sensors typically embedded in a smartphone carried by a user. Estimation of the pedestrian’s heading is a crucial step in PDR algorithms, since it is a dominant factor in the positioning accuracy. In this paper, rather than assuming the device to be fixed in a certain orientation on the pedestrian, we focus on estimating the vertical direction in the sensor frame of an unconstrained smartphone. To that end, we establish a framework for gravity direction estimation and highlight the important role it has for solving the heading in the horizontal plane. Furthermore, we provide detailed derivation of several approaches for calculating the heading angle, based on either the gyroscope or the magnetic sensor, all of which employ the estimated vertical direction. These various methods—both for gravity direction and for heading estimation—are demonstrated, analyzed and compared using data recorded from field experiments with commercial smartphones.

Design of a New Non-Contact Torque Sensor for Rotating Stepped Shaft by Monitoring Magnetic Field

2010 ◽  
Vol 44-47 ◽  
pp. 547-551 ◽  
Author(s):  
Gang Shi ◽  
Na Wang ◽  
Chong Du Cho
Keyword(s):  
Magnetic Field ◽  
Power Transmission ◽  
Low Cost ◽  
Time Algorithm ◽  
Magnetic Sensors ◽  
Torque Sensor ◽  
Rotating Shaft ◽  
Stepped Shaft ◽  
New Development ◽  
Contact Sensor

In this paper, a new non-contact sensor is presented for detecting torque of a rotating stepped shaft which is frequently employed in power transmission system. This sensor doesn’t require cutting or lengthening the rotating shaft. Torque value is obtained by using two magnetic sensors to sense magnetic field intensity of two permanent rubber magnets fixed at the outer surface of the shaft. The phase difference between these two induction signals is used to determine torque of the stepped shaft. A real-time algorithm based on LabVIEW is employed to obtain the measured torque value. The present work has demonstrated that non-contact torque measurement for rotating stepped shaft by monitoring magnetic field is feasible. It seems like that further development will result in low-cost torque sensor. It is hoped that this kind of sensor can lead to a new development direction of torque sensor for rotating shaft.

scholarly journals Investigation of a low-cost magneto-inductive magnetometer for space science applications

2017 ◽  
Author(s):  
Leonardo H. Regoli ◽  
Mark B. Moldwin ◽  
Matthew Pellioni ◽  
Bret Bronner ◽  
Kelsey Hite ◽  
...  
Keyword(s):  
Power Consumption ◽  
Linear Response ◽  
Low Cost ◽  
Magnetic Sensors ◽  
Low Power Consumption ◽  
The Novel ◽  
Noise Floor ◽  
Recent Developments ◽  
Measurement Principle ◽  
Low Amplitude

Abstract. A new sensor for measuring low-amplitude magnetic fields that is ideal for small spacecraft is presented. The novel measurement principle enables the fabrication of a low-cost sensor with low power consumption and with measuring capabilities that are comparable to recent developments for CubeSat applications. The current magnetometer, a software-modified version of a commercial sensor, is capable of detecting fields with amplitudes as low as 8.7 nT at 40 Hz and 2.7 nT at 1 Hz, with a noise floor of 500 pT/√(Hz) @ 1 Hz. The sensor has a linear response to less than 3 % over a range of ±100 000 nT. All of these features make the magneto-inductive principle a promising technology for the development of magnetic sensors for both space-borne and ground-based applications to study geomagnetic activity.

scholarly journals ULTRASONIC BASED HEADING ESTIMATION FOR AIDING LAND VEHICLE NAVIGATION IN GNSS DENIED ENVIRONMENT

2018 ◽  
Vol XLII-1 ◽  
pp. 315-322 ◽  
Author(s):  
M. Moussa ◽  
A. Moussa ◽  
N. El-Sheimy
Keyword(s):  
Low Cost ◽  
Ultrasonic Sensor ◽  
The Body ◽  
Navigation Solution ◽  
Land Vehicles ◽  
Land Vehicle Navigation ◽  
Novel Approach ◽  
Constant Distance ◽  
Heading Estimation ◽  
Wooden Surface

<p><strong>Abstract.</strong> This paper introduces a novel approach for land vehicles navigation in GNSS denied environment by aiding the Inertial Navigation System (INS) with a very low-cost ultrasonic sensor using Extended Kalman Filter (EKF) to bound its drift during GNSS blockage through a heading change update to enhance the navigation estimation.</p><p>The ultrasonic sensor is mounted on the body of the car facing the direction of the car motion and behind the front right wheel, a wooden surface is mounted on the car body on the other side of this wheel with a constant distance between the sensor and this surface. The ultrasonic sensor measures this range as long as the car moving straight. When orientation changes, the ultrasonic sensor senses the range to the front right wheel. The relation between the range and the estimated GNSS/INS change of heading during GNSS availability is estimated through a linear regression model. During GNSS signal outage, the ultrasonic sensor provides heading change update to the INS standalone navigation solution.</p><p>Experimental road tests were performed, and the results show that the navigation states estimation using the proposed aiding is improved compared with INS standalone navigation solution during GNSS signal outage. For multiple GNSS outages of 60<span class="thinspace"></span>seconds, the inclusion of the proposed update reduced the position RMSE to around 80<span class="thinspace"></span>% of its value when using the non-holonomic constraints and velocity update only.</p>

scholarly journals Circular Array of Magnetic Sensors for Current Measurement: Analysis for Error Caused by Position of Conductor

2018 ◽  
Author(s):  
Hao Yu ◽  
Qian Zheng ◽  
Huayi Liu ◽  
Jiaqi Qu
Keyword(s):  
Mathematical Model ◽  
Relative Error ◽  
Low Cost ◽  
Low Noise ◽  
Current Measurement ◽  
Magnetic Sensors ◽  
Circular Array ◽  
Measurement Analysis ◽  
Offset Distance ◽  
Earth Magnetic Field

This paper analyzes the measurement error, caused by the position of the current-carrying conductor, of circular array of magnetic sensors for current measurement. The circular array of magnetic sensors is an effective approach for AC or DC non-contact measurement, as its low cost, large linear range, wide bandwidth, light weight and low noise. Especially it has claimed that such structure has the excellent reduction ability for the errors caused by the position of the current-carrying conductor, crosstalk current interference, shape of the conduction cross section and the earth magnetic field. However, the positions of the current-carrying conductor, including un-center and un-perpendicularity, has not analyzed in detail until now. In this paper, the theoretical analysis has been proposed based on vector inner and exterior product. In the presented mathematical model of relative error, the un-center offset distance, the un-perpendicular angle, the radius of the circle and the number of the magnetic sensor are expressed in one equation. The comparison of the relative error caused by the position of the current-carrying conductor between four and eight sensors is conducted. The Tunnel Magnetoresistance (TMR) sensors are used in the experimental prototype to verify the mathematical model. The analysis results can be the reference to design the detail of circular array of magnetic sensors for current measurement in practical situation.

A Low Cost Attitude and Heading Reference System Based on a MEMS IMU for a T-Quadrotor

2011 ◽  
Author(s):  
Yangbo Long ◽  
Shi Bai ◽  
Paras Patel ◽  
David J. Cappelleri
Keyword(s):  
Kalman Filter ◽  
Reference System ◽  
Low Cost ◽  
Magnetic Sensors ◽  
Estimation Errors ◽  
Highly Nonlinear ◽  
Mems Gyroscopes ◽  
Vector Algorithms ◽  
Mems Imu ◽  
Acquisition Method

Combining signals from accelerometers and gyroscopes is a widely used way to estimate robot attitude. However, when using a Kalman filter in this case, the measurements are vulnerable to dynamic accelerations which will result in substantial attitude estimation errors. The attitude acquisition method presented in this paper takes an attitude quaternion as system measurements and uses a Kalman filter to fuse signals from MEMS gyroscopes, accelerometers and magnetic sensors. In order to remove the influence of dynamic accelerations, when dynamic accelerations are found to be significant, a Quaternion-based Strapdown Navigation System (Q-SINS) algorithm is only applied without the Kalman filtering. When the dynamic accelerations are not significant, both the Q-SINS and the Bi-vector algorithms are utilized and fused using the Kalman filter for improved system performance. Compared with some other highly nonlinear and complicated attitude algorithms, the Attitude and Heading Reference System (AHRS) proposed in this paper is computationally less expensive and more suitable for real-time applications.

scholarly journals Enhanced Drone Navigation in GNSS Denied Environment Using VDM and Hall Effect Sensor

2019 ◽  
Vol 8 (4) ◽  
pp. 169 ◽  
Author(s):  
Shady Zahran ◽  
Adel Moussa ◽  
Naser El-Sheimy
Keyword(s):  
Hall Effect ◽  
Low Cost ◽  
Integrated System ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Hall Effect Sensor ◽  
Aerial Vehicle ◽  
Heading Estimation ◽  
Global Navigation Satellite ◽  
Vehicle Dynamic Model

The last decade has witnessed a wide spread of small drones in many civil and military applications. With the massive advancement in the manufacture of small and lightweight Inertial Navigation System (INS), navigation in challenging environments became feasible. Navigation of these small drones mainly depends on the integration of Global Navigation Satellite Systems (GNSS) and INS. However, the navigation performance of these small drones deteriorates quickly when the GNSS signals are lost, due to accumulated errors of the low-cost INS that is typically used in these drones. During GNSS signal outages, another aiding sensor is required to bound the drift exhibited by the INS. Before adding any additional sensor on-board the drones, there are some limitations that must be taken into considerations. These limitations include limited availability of power, space, weight, and size. This paper presents a novel unconventional method, to enhance the navigation of autonomous drones in GNSS denied environment, through a new utilization of hall effect sensor to act as flying odometer “Air-Odo” and vehicle dynamic model (VDM) for heading estimation. The proposed approach enhances the navigational solution by estimating the unmanned aerial vehicle (UAV) velocity, and heading and fusing these measurements in the Extended Kalman Filter (EKF) of the integrated system.

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