Navigation à l'estime | EPFL Graph Search

La navigation à l'estime est une méthode de navigation qui consiste à déduire la position d'un véhicule (terrestre, maritime, aérien ou spatial ; piloté ou automatique) de sa route et de la distance parcourue depuis sa dernière position connue. Traditionnellement, cette méthode repose sur les instruments mesurant son cap (compas), sa vitesse (loch, tachymètre, badin...) et le temps (chronomètre) ainsi qu'avec l'estimation éventuelle (ou le calcul) de l'influence de l'environnement (courant, vent) sur sa marche. Elle est incertaine, car dépendante de la précision de la mesure de la route vraie (ou route sur le fond pour un navire) et de sa vitesse réelle. En pratique, en navigation maritime, on adopte une incertitude égale à 2 à 3 % de la distance parcourue, mais qui peut atteindre 5 % si les conditions météorologiques sont mauvaises. Avec un contrôle de la position au moins une fois par jour, on peut admettre en permanence un rayon d'incertitude toujours inférieur à 15 milles mari

Terrain-based Navigation for Underwater Vehicles Using Side Scan Sonar Images

Hannes Bleuler, Severin Stalder

Underwater navigation challenges the research community as a reliable navigation system is unavailable. Correctly matched landmarks could compensate the drift of dead reckoning navigation systems. Furthermore, they could be useful in side scan sonar image registration. We propose to integrate both applications to form one landmark detection and matching system. Our approach detects disruptions in the local texture field using level set evolution on Haralick feature maps. During evolution the landmarks are continuously tried to be matched. An energy term which has been used for supervised image registration is used to verify the hypothesized matches. If the energy term based on pixel-wise similarity and hard landmark constraints is minimum, the landmark matches are considered as correct.

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GPS/INS integration for pedestrian navigation

This research has been sponsored by the Centre Suisse d'Electronique et de Microtechnique (CSEM) in Neuchâtel, Switzerland. It introduces a system and the algorithms for Pedestrian Navigation using a combination of sensors. The main objective is to localise a pedestrian anywhere and at any moment. The equipments utilised to fulfill this requirement are a Global Navigation Satellite System (GNSS) receiver and inertial sensors, which are attached to the person and as such need to be portable. An overview of Pedestrian Navigation constitutes the first part of the document. This new domain is examined from four different views: applications, tools (or sensors), architecture of the system and finally environment in which the pedestrian is travelling. As part of this process, the "state of the art" situation is presented. The approach followed in order to aid pedestrian to navigate is based on the Dead Reckoning technique coupled with GNSS. Consequently, the resolution of the travelled "distance" is separated from the resolution of the orientation of the walk. For the computation of the distance, a new technique based upon accelerometers and GNSS has been developed and demonstrated. The accelerometers are not used as a classical pedometer (counter of the number of steps) and the technique is not based on the double integration to obtain successively speed and distance. Instead, signal processing allows, considering individual parameters, the walking speed to be obtained directly from the signal of the accelerometers. This process, as well as the manner to determine the individual parameters, is presented in detail. The development of the algorithms is based on research performed in both the navigation and the medical domains (mainly in physiology). The computation of the orientation is more classical. It is based on the measurements made by a gyroscope and a GNSS receiver. The particularity of this study is the use of a single gyroscope to determine the orientation of the walk instead of three for the classical technique of inertial navigation. The influence of body movement on the gyroscope output has been deeply examined to determine the most appropriate way to process the signal of the gyroscope. The feasibility of the use of a single gyro, in the context of pedestrian navigation, is demonstrated. The potential added value for introducing a magnetic compass in the system is also evaluated. Finally a centralised Kalman filter has been designed and tested to merge all the sensors outputs, to combine the distance and the orientation, to integrate the Dead Reckoning solution and the GNSS solutions and to estimate all the parameters in a close to real-time process. The efficiency of this filter is demonstrated through different tests.

EPFL2003

GPS/INS integration for pedestrian navigation

EPFL2003