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In the typical urban environment where the satellite visibility is limited or the satellite signal is weak due to the blockage or signal jamming, the availability of the navigation satellite system would be degraded, resulting in conventional four-satellite positioning method is very hard to satisfy the requirement of continuous positioning. To solve this problem, a combined prediction model based on the improved polynomial model and the improved grey model is proposed, which adopts a time interval coefficient and a dynamic weighting factor to predict the receiver clock bias (RCB), and then a predicted clock value from the proposed model is introduced to aid positioning. The experimental results based on BeiDou Navigation Satellite System (COMPASS/BDS) observation data demonstrate that the model is more suitable for predicting RCB both under unequal and equal conditions. Moreover, for 50 s RCB predictions duration of the short satellite signal shading outages, the threedimensional (3-D) position error using the clock-aided position algorithm is slightly larger than about 2.76% than four-satellite 3-D position error, and thus, the availability of positions can be improved efficiently.

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Frame synchronization time of geostationary Earth orbit (GEO) satellites is faster than that of incline geosynchronous satellite orbit and medium Earth orbit satellites in Beidou navigation satellite system (BDS). So time to first fix can be reduced greatly with GEO satellites (GEOs) to provide emergency positioning service during the cold start process. Meanwhile, GEOs can also be utilized to provide radio determination satellite services. Therefore, it is meaningful to research the emergency positioning algorithm based on GEOs. However, due to the poor geometry of the GEOs, the availability and accuracy degrade distinctly. To solve this problem, a low-cost high resolution MS5534B barometric (baro-) module is applied to BDS. Firstly, the principle of emergency positioning based on a baro-altimeter sensor and its performance such as the accuracy are elaborated. Then the effects of baro-altimeter sensor measurement error on positioning are analyzed. Finally, after analyzing the limitation of the conventional algorithms, a new highaccuracy emergency positioning algorithm with baro-altimeter sensor aiding is proposed, which is not limited by the integration and user's altitude. In comparison to the conventional algorithms, the stimulant and experimental results validate the effectiveness, robustness, and higher performance of the proposed algorithms incorporated with sensors.