This paper presents a real time pedestrian navigation system that combines different type of GPS receivers (namely High Sensitivity GPS and Assisted GPS) with several low-cost inertial sensors to face GPS outages and provide a reliable and continuous position solution. The off-the-shelf inertial module from Xsens is made of several low-cost MEMS type sensors contained in a very small package (58×58×22 mm W×L×H). This unit is composed of a triad of gyroscopes, a triad of accelerometers and a triad of magnetometers as well as a temperature sensor. The measurements of the different sensors are combined to provide an autonomous Pedestrian Navigation System that does not rely on GPS measurements. This navigation method is based on the analysis of the dynamic of the pedestrian, as performed in [1], in order to limit the impact of accelerometer biases that systematically degrades the position accuracy. The remaining gyro drifts are estimated and compensated dynamically through the implementation of an attitude filter that combines the different sensors data. The magnetic interference issue is also addressed with a mitigation technique based on gyros measurements. The Assisted GPS or High Sensitivity GPS receiver and the Pedestrian Navigation System are combined in real time to provide more reliable position solutions and also augment the overall availability especially in deep urban canyons and indoor environments. The coupling methodology follows a loose integration scheme. The Integrated Navigation System is software implemented on an ultra portable PC. The inertial unit is connected to the ultra Portable PC using the serial RS-232 link through the USB serial port. Results show that the real time combination of both navigation systems improves tremendously the availability of the position solution, especially in harsh environments. The accuracy of the position solution during GPS outages is also augmented, and stays within acceptable limits according the trials that are exercised during long GPS outages. It is also shown that the analysis of the coefficients used to model the velocity of the pedestrian allows the detection of bad GPS measurements that prevent the Pedestrian Navigation System from being inaccurately initialized for further standalone navigation.