Pedestrian navigation with hand-held sensors is still particularly complex. Pedestrian Dead Reckoning method is generally used but the estimation of the walking direction remains problematic because the device's pointing direction does not always correspond to the walking direction. To overcome this difficulty, it is possible to use gait modeling based approaches. But, these methods suffers from sporadic erroneous estimates and their accumulation over time. The HEAD (smootH Estimation of wAlking Direction) filter usesWAISS andMAGYQ angular estimates as observations to correct the walking direction and to obtain more robust and smooth results. TDCP updates are apply to constrain the walking direction estimation error while pseudo-ranges directly updates the position. HEAD is tested by 5 subjects over 21 indoor/outdoor acquisitions (between 720m and 1.3km). A 54% improvement is achieved thanks to the fusion in texting mode. The median obtained angular error is 5.5ý in texting mode and 12ý in pocket mode.