There is a strong need for an accurate pedestrian navigation system, functional also in GNSS challenging environments, namely urban areas and indoors, for improved safety and to enhance everyday life. Pedestrian navigation is mainly needed in these environments that are challenging for GNSS but also for other RF positioning systems and some non-RF systems such as the magnetometry used for heading due to the presence of ferrous material. Indoor and urban navigation has been an active research area for years. There is no individual system at this time that can address all needs set for pedestrian navigation in these environments, but a fused solution of different sensors can provide better accuracy, availability and continuity. Self-contained sensors, namely digital compasses for measuring heading, gyroscopes for heading changes and accelerometers for the user speed, constitute a good option for pedestrian navigation. However, their performance suffers from noise and biases that result in large position errors increasing with time. Such errors can however be mitigated using information about the user motion obtained from consecutive images taken by a camera carried by the user, provided that its position and orientation with respect to the user’s body are known. The motion of the features in the images may then be transformed into information about the user’s motion. Due to its distinctive characteristics, this vision-aiding complements other positioning technologies in order to provide better pedestrian navigation accuracy and reliability. This thesis discusses the concepts of a visual gyroscope that provides the relative user heading and a visual odometer that provides the translation of the user between the consecutive images. Both methods use a monocular camera carried by the user. The visual gyroscope monitors the motion of virtual features, called vanishing points, arising from parallel straight lines in the scene, and from the change of their location that resolves heading, roll and pitch. The method is applicable to the human environments as the straight lines in the structures enable the vanishing point perception. For the visual odometer, the ambiguous scale arising when using the homography between consecutive images to observe the translation is solved using two different methods. First, the scale is computed using a special configuration intended for indoors. Secondly, the scale is resolved using differenced GNSS carrier phase measurements of the camera in a method aimed at urban environments, where GNSS can’t perform alone due to tall buildings blocking the required line-of-sight to four satellites. However, the use of visual perception provides position information by exploiting a minimum of two satellites and therefore the availability of navigation solution is substantially increased. Both methods are sufficiently tolerant for the challenges of visual perception in indoor and urban environments, namely low lighting and dynamic objects hindering the view. The heading and translation are further integrated with other positioning systems and a navigation solution is obtained. The performance of the proposed vision-aided navigation was tested in various environments, indoors and urban canyon environments to demonstrate its effectiveness. These experiments, although of limited durations, show that visual processing efficiently complements other positioning technologies in order to provide better pedestrian navigation accuracy and reliability
