Context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU / GNSS gains significant benefits from context information in terms of improvement of filter ’s adaptive capability. A context-aware algorithm using differential carrier phase was proposed to recognize a mobile MEMS IMU / GNSS equipped vehicle’s stationary,slow moving or fast moving status. The corresponding context error in awarding was analyzed and consequently conducted two fading factors based on the analysis. The factors were applied in the system’s adaptive filter with targeting applications in deep urban where severe multipath presents. The dense urban field test shows that the false alarm of proposed context-aware algorithm is less than 5% and the adaptive filtering can achieve around 15% improvement in terms of 1σ in two-dimension position accuracy. Context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU / GNSS gains significant benefits from context information in terms of improvement of filter ’s adaptive capability. A context-aware algorithm using differential carrier phase was reconstituted a mobile MEMS IMU / GNSS equipped vehicle’s stationary, slow moving or fast moving status. The corresponding context error in awarding was analyzed and stressed two fading factors based on the analysis. The factors were applied in the system’s adaptive filter with targeting applications in deep The dense urban field test shows that the false alarm of proposed context-aware algorithm is less than 5% and the adaptive filtering can achieve around 15% improvement in terms of 1σ in two-dimension position accuracy.