| With advances in sensor technology and the inclusion of low cost consumer grade sensors in portable systems like smart-phones, pedestrian navigation using such devices has become a reality. With consumer grade sensors comes a Pandora's Box full of errors rendering the unaided navigation solution with these sensors of limited use. A significant contribution to the overall navigation error budget associated with pedestrian navigation is accurate attitude/orientation estimation. This research develops different sensor fusion techniques to utilize the Earth's magnetic field for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that GNSS is denied.;First, a Multiple Magnetometer Platform (MMP) based perturbation detection and mitigation scheme is developed, which estimates the perturbation free local magnetic field. Second, a Single Magnetometer (SM) based orientation estimator is developed that uses different magnetic field parameters for assessing the accuracy of the estimated heading. Finally a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. All of these schemes are used as input measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator.;Results indicate that the combination of QSF and SM is capable of effectively estimating attitude and gyroscope errors, reducing the overall navigation error budget by over 80% in the urban canyons and indoor environments tested.;As the Earth's magnetic field undergoes severe degradation in pedestrian navigation environments, detailed surveys are conducted for characterizing the magnetic field perturbations. A mathematical model of the Earth's magnetic field in presence of perturbation sources is then developed and used for developing different schemes for detecting, mitigating as well as directly using the magnetic perturbations for attitude and gyroscope error estimation. |
