## 1 Introduction  
With the rapid development of automatic driving as well as advanced vehicle control and safety systems in urban environments, the requirements in terms of navigation accuracy, continuity, and availability are increasing. Real-time kinematic (RTK) in surveying and mapping is a precise positioning technique by processing double-differenced carrier-phase measurements of Global Navigation Satellite System (GNSS) signals [1]. The double-difference technique can remove the error sources that are highly correlated over space and time, such as ephemeris errors. Range information with remained multipath and receiver noise can achieve cm-level accuracy only after the integer ambiguities in the carrier-phase measurements have been resolved correctly. Thus, integer ambiguity resolution (AR) becomes a critical part of the RTK technique. The conventional AR techniques are classified into three categories according to the usage of receiver measurements [2]: ambiguity resolution in the measurement domain [3], search technique in the coordinate or position domain [4], and search technique in the ambiguity domain [5,6]. The third class based on the theory of integer least-squares (ILS) is most widely used; it contains abundant techniques, such as the Fast Ambiguity Resolution Approach (FARA) [5], the Least-Squares Ambiguity Decorrelation Adjustment (LAMBDA) [6], the Least-Squares Ambiguity Search Technique (LSAST) [7]. A typical AR procedure in the ambiguity domain comprises two steps. Firstly, the float solution of ambiguities and the corresponding variance-covariance matrices are obtained by real-valued least squares estimation. Secondly, the ambiguity search process is employed to fix the integer values and adjust the baseline solution. The performance of the AR procedure in the ambiguity domain depends on a precise float estimation. Thus, it is susceptible to the number of available satellites and the quality of observations. In harsh urban environments, the surrounding obstacles may bring two representative predicaments to the reception of satellite signals: blockages and multipath. GNSS signal blockages always make the RTK techniques suffer from a poor geometry and a reduction in the number of satellites in view. However, this dilemma has improved with the development of other constellations such as BeiDou Navigation Satellite System (BDS), which has been providing Positioning, Navigation, and Timing (PNT) services in the Asia-Pacific region since December 2012 [8]. Taking into account the use of multi-constellation systems, the number of satellites in view for users has effectively increased. Meanwhile, there is potential for the positioning accuracy and stability of RTK to be improved with the combination of GPS and BDS. In addition to solving the reduction in the total number of satellites, the ideal RTK technology also needs to deal with the frequent satellite visibility changes caused by GNSS signal blockages. For carrier-phase measurements, once the satellite signals need to be reacquired by the receiver due to changes of the availability status, the corresponding integer ambiguities have to go through a period of re-searching and fixing. In the interim, unless the fixed solution can be obtained at the time of cycle-slip occurrence, at best, only the accuracy of the float solution can be provided. For the AR techniques in the ambiguity domain, both the float solution and the success rate impose requirements on the accuracy of the pseudorange. Unfortunately, the second predicament in satellite observations under urban environments is that due to the multipath generated by the reflections on building structures, there exist large correlation errors in pseudorange measurements. Therefore, the standalone GNSS positioning methods such as RTK cannot meet the requirements under GNSS-challenged environments. An alternative way to enhance the system performance is exploiting other sensors that are aiding.