Magnetic sensors and gradiometers for detection of objects

Disertační práce popisuje vývoj nových detekčních zařízení s anizotropními magnetorezistoryThis thesis describes development of innovative sensor systems based on anisotropi

Development of cost effective IMU Calibration Procedure

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia de Controle e Automação.A empresa Hexagon Agriculture está trabalhando na digitalização da agricultura. Entre as soluções oferecidas pela Hexagon Agriculture está o Piloto Automático, que utiliza um módulo GNSS em conjunto com sensores inerciais microeletromecânicos para estimar a posição do veículo. Os sensores inerciais são afetados por diversas fontes de erro e vários desses erros são sistemáticos. Os erros sistemáticos influenciam significamente na acurácia dos sensores inerciais. Neste trabalho é apresentado primeiramente um estudo sobre as características dos sensores inerciais montados em uma das placas da Hexagon Agriculture. A partir das conclusões retiradas do estudo inicial são propostos métodos de calibração para os sensores inerciais. As propostas de calibração foram então testadas e a partir do resultado destes testes, foram classificadas em viáveis ou não. O conclusão deste trabalho é que existem métodos de calibração que podem ser aplicados nos sensores inerciais resultando em melhoria significativa na acurácia dos sensores inerciais, apesar de que ainda não foi possível de se obter resultados conclusivos sobre a durabilidade dessa calibração, que depende da estabilidade dos erros sistemáticos com o tempo. Além da melhoria na acurácia dos sensores inerciais, também haverá um ganho muito significativo na confiabilidade nos sensores e na padronização da performance dos sensores inerciais. É importante também ressaltar que em algumas aplicações do piloto automático da Hexagon Agriculture é requisitada alta acurácia, que para isso são usados módulos GNSS de alta performance, acurácia de centímetros, mas caso o terreno no qual o piloto automático seja utilizado for muito acidentado, os sensores inerciais se tornam fundamentais para manter a acurácia da estimação de posição, situação na qual a calibração se torna ainda mais significante.Hexagon Agriculture is working on digitizing agriculture. Among the solutions offered by Hexagon Agriculture there is an Auto Steering System which uses a GNSS module working with a MEMS IMU to estimate the vehicle's position, attitude and speed. An IMU is affected by a wide range of errors, some of those errors are systematic and those systematic errors are very relevant to the IMU accuracy. This work starts with a preliminary study on IMU parts mounted in one of Hexagon Agriculture's board. Using the conclusion of the preliminary studies, solutions are proposed, intending to calibrate the IMU. The proposed solutions, calibration procedures, were tested and classified as feasible or not. The achieved conclusion is that there are calibration methods which may be applied on the studied IMU and promote a relevant improvement on the IMU accuracy, although it has not been possible to conclude about how long will the calibration last, which depends on the systematic errors stability with time. Alongside with the accuracy improvement there is also a significant improvement on the reliability of the IMU as their performance will be more uniform. It is also important to emphasize that some applications of the Auto Steering System requires high accuracy, so high tech GNSS modules are used with centimeter level accuracy, but if the Auto Steering System is used in rough terrain, the IMU becomes fundamental to keep the accuracy on the position estimation. On higher level accuracy application e.g., five centimeter requirement, calibrating the IMU becomes even more relevant

Deterministic and stochastic error modeling of inertial sensors and magnetometers

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2012.Thesis (Master's) -- Bilkent University, 2012.Includes bibliographical refences.This thesis focuses on the deterministic and stochastic modeling and model parameter estimation of two commonly employed inertial measurement units. Each unit comprises a tri-axial accelerometer, a tri-axial gyroscope, and a tri-axial magnetometer. In the first part of the thesis, deterministic modeling and calibration of the units are performed, based on real test data acquired from a flight motion simulator. The deterministic modeling and identification of accelerometers is performed based on a traditional model. A novel technique is proposed for the deterministic modeling of the gyroscopes, relaxing the test bed requirement and enabling their in-use calibration. This is followed by the presentation of a new sensor measurement model for magnetometers that improves the calibration error by modeling the orientation-dependent magnetic disturbances in a gimbaled angular position control machine. Model-based Levenberg-Marquardt and modelfree evolutionary optimization algorithms are adopted to estimate the calibration parameters of sensors. In the second part of the thesis, stochastic error modeling of the two inertial sensor units is addressed. Maximum likelihood estimation is employed for estimating the parameters of the different noise components of the sensors, after the dominant noise components are identified. Evolutionary and gradient-based optimization algorithms are implemented to maximize the likelihood function, namely particle swarm optimization and gradient-ascent optimization. The performance of the proposed algorithm is verified through experiments and the results are compared to the classical Allan variance technique. The results obtained with the proposed approach have higher accuracy and require a smaller sample data size, resulting in calibration experiments of shorter duration. Finally, the two sensor units are compared in terms of repeatability, present measurement noise, and unaided navigation performance.Seçer, GörkemM.S

IMP-I spacecraft magnetic test program

Magnetic test program for IMP-I spacecraf

Range of motion measurements based on depth camera for clinical rehabilitation

Dissertação para obtenção do Grau de Mestre em Engenharia BiomédicaIn clinical rehabilitation, biofeedback increases the patient’s motivation which makes it one of the most effective motor rehabilitation mechanisms. In this field it is very helpful for the patient and even for the therapist to know the level of success and performance of the training process. The human motion tracking study can provide relevant information for this purpose. Existing lab-based Three-Dimensional (3D) motion capture systems are capable to provide this information in real-time. However, these systems still present some limitations when used in rehabilitation processes involving biofeedback. A new depth camera - the Microsoft KinectTM - was recently developed overcoming the limitations associated with the lab-based movement analysis systems. This depth camera is easy to use, inexpensive and portable. The aim of this work is to introduce a system in clinical practice to do Range of Motion(ROM) measurements, using the KinectTM sensor and providing real-time biofeedback. For this purpose, the ROM measurements were computed using the joints spatial coordinates provided by the official Microsoft KinectTM Software Development Kit (SDK)and also using our own developed algorithm. The obtained results were compared with a triaxial accelerometer data, used as reference. The upper movements studied were abduction, flexion/extension and internal/external rotation with the arm at 90 degrees of elevation. With our algorithm the Mean Error (ME) was less than 1.5 degrees for all movements. Only in abduction the KinectTM Sketelon Tracking obtained comparable data. In other movements the ME increased an order of magnitude. Given the potential benefits, our method can be a useful tool for ROM measurements in clinics

Doctor of Philosophy

dissertationThe need for position and orientation information in a wide variety of applications has led to the development of equally varied methods for providing it. Amongst the alternatives, inertial navigation is a solution that o ffers self-contained operation and provides angular rate, orientation, acceleration, velocity, and position information. Until recently, the size, cost, and weight of inertial sensors has limited their use to vehicles with relatively large payload capacities and instrumentation budgets. However, the development of microelectromechanical system (MEMS) inertial sensors now o ers the possibility of using inertial measurement in smaller, even human-scale, applications. Though much progress has been made toward this goal, there are still many obstacles. While operating independently from any outside reference, inertial measurement su ers from unbounded errors that grow at rates up to cubic in time. Since the reduced size and cost of these new miniaturized sensors comes at the expense of accuracy and stability, the problem of error accumulation becomes more acute. Nevertheless, researchers have demonstrated that useful results can be obtained in real-world applications. The research presented herein provides several contributions to the development of human-scale inertial navigation. A calibration technique allowing complex sensor models to be identified using inexpensive hardware and linear solution techniques has been developed. This is shown to provide significant improvements in the accuracy of the calibrated outputs from MEMS inertial sensors. Error correction algorithms based on easily identifiable characteristics of the sensor outputs have also been developed. These are demonstrated in both one- and three-dimensional navigation. The results show significant improvements in the levels of accuracy that can be obtained using these inexpensive sensors. The algorithms also eliminate empirical, application-specific simplifications and heuristics, upon which many existing techniques have depended, and make inertial navigation a more viable solution for tracking the motion around us

The MASCOT Magnetometer

The Mobile Asteroid Scout (MASCOT) is a small lander on board the Hayabusa2 mission of the Japan Aerospace Exploration Agency to the asteroid 162173 Ryugu. Among the instruments on MASCOT is a fluxgate magnetometer, the MASCOT Magnetometer (MasMag). The magnetometer is a lightweight ( ∼280 g∼280 g ) and low power ( ∼0.5 W∼0.5 W ) triaxial fluxgate magnetometer. Magnetic field measurements during the landing period and during the surface operational phase shall provide information about any intrinsic magnetic field of the asteroid and its remanent magnetization. This could provide important constraints on planet formation and the thermal and aqueous evolution of primitive asteroids.Thomas F. PetersonUnited States. National Aeronautics and Space Administration. Emerging Worlds Progra

Towards naturalistic scanning environments for wearable magnetoencephalography

Magnetoencephalography (MEG) is a neuroimaging technique that probes human brain function, by measuring the magnetic fields generated at the scalp by current flow in assemblies of neurons. A direct measure of neural activity, MEG offers high spatiotemporal resolution, but limitations imposed by superconducting sensor technologies impede its clinical utility. Specifically, neuromagnetic fields are up to a billion times smaller than that of the Earth, meaning MEG must be performed inside a magnetically shielded room (MSR), which is typically expensive, heavy, and difficult to site. Furthermore, current MEG systems employ superconducting quantum interference devices (SQUIDs) to detect these tiny magnetic fields, however, these sensors require cryogenic cooling with liquid helium. Consequently, scanners are bulky, expensive, and the SQUIDs must be arranged in a fixed, one-size-fits-all array. Any movement relative to the fixed sensors impacts data quality, meaning participant movement in MEG is severely restricted. The development of technology to enable a wearable MEG system allowing free participant movement would generate a step change for the field. Optically-pumped magnetometers (OPMs) are an alternative magnetic field detector recently developed with sufficient sensitivity for MEG measurements. Operating at body temperature, in a small and lightweight sensor package, OPMs offer the potential for a wearable MEG scanner that allows participant movement, with sensors mounted on the scalp in a helmet or cap. However, OPMs operate around a zero-field resonance, resulting in a narrow dynamic range that may be easily exceeded by movement of the sensor within a background magnetic field. Enabling a full range of participant motion during an OPM-MEG scan therefore presents a significant challenge, requiring precise control of the background magnetic field. This thesis describes the development of techniques to better control the magnetic environment for OPM-MEG. This includes greater reduction of background magnetic fields over a fixed region to minimise motion artefacts and facilitate larger movements, and the application of novel, multi-coil active magnetic shielding systems to enable flexibility in participant positioning within the MSR. We outline a new approach to map background magnetic fields more accurately, reducing the remnant magnetic field to <300 pT and yielding a five-fold reduction in motion artefact, to allow detection of a visual steady-state evoked response during continuous head motion. Employing state-of-the-art, triaxial OPMs alongside this precision magnetic field control technique, we map motor function during a handwriting task involving naturalistic head movements and investigate the advantages of triaxial sensitivity for MEG data analysis. Using multi-coil active magnetic shielding, we map motor function consistently in the same participant when seated and standing, and demonstrate the first OPM-MEG hyperscanning experiments. Finally, we outline how the integration of a multi-coil system into the walls of a lightweight MSR, when coupled with field control over a larger volume, provides an open scanning environment. In sum, these developments represent a significant step towards realising the full potential of OPM-MEG as a wearable functional neuroimaging technology

Wearable inertial sensors for human movement analysis

Introduction: The present review aims to provide an overview of the most common uses of wearable inertial sensors in the field of clinical human movement analysis.Areas covered: Six main areas of application are analysed: gait analysis, stabilometry, instrumented clinical tests, upper body mobility assessment, daily-life activity monitoring and tremor assessment. Each area is analyzed both from a methodological and applicative point of view. The focus on the methodological approaches is meant to provide an idea of the computational complexity behind a variable/parameter/index of interest so that the reader is aware of the reliability of the approach. The focus on the application is meant to provide a practical guide for advising clinicians on how inertial sensors can help them in their clinical practice.Expert commentary: Less expensive and more easy to use than other systems used in human movement analysis, wearable sensors have evolved to the point that they can be considered ready for being part of routine clinical routine