<p>This thesis aims the problem of underwater vehicle positioning. The vehicle usedwas a Saab Seaeye Falcon which was equipped with a Doppler Velocity Log(DVL)manufactured by RD Instruments and an inertial measurement unit (IMU) fromXsense. During the work several different Extended Kalman Filter (EKF) havebeen tested both with a hydrodynamic model of the vehicle and a model withconstant acceleration and constant angular velocity. The filters were tested withdata from test runs in lake Vättern. The EKF with constant acceleration andconstant angular velocity appeared to be the better one. The misalignment of thesensors were also tried to be estimated but with poor result.</p>

A method is proposed to fuse the information from two navigation systems whose relative position is unknown, but where there exists an upper limit on how far apart the two systems can be. The proposed information fusion method is applied to a scenario in which a pedestrian is equipped with two foot-mounted zero-velocity-aided inertial navigation systems; one system on each foot. The performance of the method is studied using experimental data. The results show that the method has the capability to significantly improve the navigation performance when compared to using two uncoupled foot-mounted systems. / <p>QC 20121221</p>

This thesis aims the problem of underwater vehicle positioning. The vehicle usedwas a Saab Seaeye Falcon which was equipped with a Doppler Velocity Log(DVL)manufactured by RD Instruments and an inertial measurement unit (IMU) fromXsense. During the work several different Extended Kalman Filter (EKF) havebeen tested both with a hydrodynamic model of the vehicle and a model withconstant acceleration and constant angular velocity. The filters were tested withdata from test runs in lake Vättern. The EKF with constant acceleration andconstant angular velocity appeared to be the better one. The misalignment of thesensors were also tried to be estimated but with poor result.

A general automotive navigation system is a satellite navigation system designed for use inautomobiles. It typically uses GPS to acquire position data to locate the user on a road in the unit's map database. However, due to recent improvements in the performance of small and lightweight micro-machined electromechanical systems (MEMS) inertial sensors have made the application of inertial techniques to such problems, possible. This has resulted in an increased interest in the topic of inertial navigation. In location tracking system, sensors are used either individually or in conjunction like in data fusion. However, still they remain noisy, and so there is a need to measure maximum data and then make an efficient system that can remove the noise from data and provide a better estimate. The task of this thesis work was to take data from two sensors, and use an estimation technique toprovide an accurate estimate of the true location. The proposed sensors were an accelerometer and a GPS device. This thesis however deals with using accelerometer sensor and using estimation scheme, Kalman filter. The thesis report presents an insight to both the proposed sensors and different estimation techniques. Within the scope of the work, the task was performed using simulation software Matlab. Kalman filter’s efficiency was examined using different noise levels.

One important part of inertial navigation is the estimation of the direction relative to the Earth’s geographic North Pole, the so called heading. In this project, a gyroscope and an accelerometer were used together in an Extended Kalman Filter with a quaternion as the state space variable, representing the attitude. Given the attitude of the system, measurements from a magnetometer were rotated to a horizontal coordinate frame in order to calculate the direction toward Earth’s magnetic North Pole. Comparing this direction with the angle toward the Geographic North Pole given by a GPS, the local magnetic declination was estimated with the purpose of correcting the heading in the future. Different methods for detecting disturbances on the magnetometer in order to automatically decide when it is to be trusted was discussed and evaluated. Routines for easily performing sensor calibration was created. The outcome of the project was a well working attitude estimation, simply performed calibration routines and a set of methods working together to detect magnetometer disturbances. / En viktig del av ett tröghetsnavigeringssystem är skattningen av riktningen relativt jordens geografiska nordpol, den så kallade bäringen. I detta projekt användes ett gyroskop och en accelerometer tillsammans i ett Extended Kalman filter med en quaternion som tillståndsvariabel för att representera attityden. Givet systemets attityd roterades mätningar från en magnetometer till ett horisontellt koordinatsystem för att beräkna riktningen mot magnetiska nordpolen. Genom att jämföra denna riktning med vinkeln mot geografiska nordpolen kunde den lokala magnetiska deklinationen skattas för att sedan användas i framtiden för att korrigera bäringen. Olika metoder för att detektera störningar på magnetometern för att automatiskt bestämma när den är störd diskuteras och utvärderas. Rutiner för att enkelt kalibrera sensorerna skapades. Projektets resultat var en väl fungerande attitydestimering, enkla kalibreringsmetoder samt ett par metoder för att detektera störningar på magnetometern.

Thesis (Ph. D.)--Ohio University, 2002. / Title from PDF t.p.

Thesis (M.S.)--Ohio University, June, 2000. / Title from PDF t.p.

Thesis (M.S.)--Ohio University, August, 2003. / Title from PDF t.p. Includes bibliographical references (leaves 33-34).

Thesis (M.S.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains xii, 108, [9] p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 104-108).

Thesis (M. Eng.)--Carleton University, 2001. / Includes bibliographical references p. (115-117). Also available in electronic format on the Internet.