The challenge of knowing one's position in a precise and reliable way, at any time, with and without reception of satellite signals, represents an area fairly explored for the navigation of vehicles. To widen this service to the pedestrians requires a different approach that adapts to the dynamics, to the speed and especially to the total freedom of movement of the people. The traditional approach implements a triad of accelerometers and gyroscopes, which signals are integrated to obtain the relative displacement. This concept is unfortunately not judicious for a low-cost system. The principal reason is that the speed of displacement of a person is lost in the sensor noise level. In order to take into account all these specificities, an occurential approach was developed, based upon a subset of sensors as well as physiological and biomechanical parameters of the walk. This research is divided into three main directions. The first area of interest consists in the determination of the physiological parameters necessary to quantify the speed of walk and the step length. While the agitation of the accelerometer signals is a good speedometer, the frequency of the steps improves the robustness of the models. The influence of the gender added to the great human diversity imply the normalisation of the various relations deduced. Many tests carried out under conditions of everyday life reveal that the variation of the stride length, especially with the slope, strongly depends on the physical training of the person as well as on the duration of the climb or descent. Characteristic pattern were identified to differentiate between the forward, backward and lateral movements. The various suggested models were then favourably tested with some blind people, whose walking rhythm strongly varies according to the degree of confidence they have towards the course. The second part directly relates to the multiple technologies integrated to build an autonomous three-dimensional Pedestrian Navigation Module (PNM). The knowledge of the terrestrial magnetic field and its orientation makes it possible to determine the azimuth of displacement of a person. The use of a gyroscope improves the reliability of the system and facilitates the detection of magnetic disturbances. More stable in the short term than the compass, it is therefore the optimal complement under such circumstances. The altimetric information is obtained by barometric measurements which, according to the required precision, can be differential. The implementation of a GPS receiver allows the absolute positioning simultaneously to the calibration of the different sensor parameters and physiological models. The third part describes the integration of the models and measurements as well as the characteristics and treatments specific to pedestrian navigation. An initialisation phase is presented to individualize the parameters of the walk and adapt them from the general model. Hence, thanks to the compass-gyroscope integration together with the detection of any movement, this allows an optimal determination and filtering of the azimuth that has little or no temporal degradation. The consideration of several phenomena specific to the displacements of the humans brings artificial intelligence in pedestrian navigation. The coupling of the various sources of measurements, the influence of their precision on the computed position as well as their implication on the PNM reliability are described and illustrated. More than 550 km covered in various circumstances by 31 people allowed to validate the presented approach while fixing its limits.