中文摘要：

为了提高中基线实时动态（real-time kinematic,RTK）定位的模糊度解算成功率和定位精度,提出一种基于三频北斗系统（BeiDou navigation satellite system,BDS）和双频全球定位系统的多频模糊度解算算法。该算法结合三频模糊度解算（three carrier ambiguity resolution,TCAR）和最小二乘降相关（least-square ambiguity decorrelation adjustment,LAMBDA）算法通过三级迭代固定模糊度。此外,为了减少电离层延迟等误差对模糊度解算的影响,提出一种组合系数搜索算法。利用自适应扩展卡尔曼滤波实现RTK定位。在中基线实验中,将提出算法与BDS TCAR和单/双系统LAMBDA算法在成功率和定位精度方面进行比较。结果表明,所提算法的成功率最高,可即时固定模糊度,且定位误差在毫米级,精度在3种算法中最优。

英文摘要：

To improve the ambiguity resolution success rate and accuracy of real-time kinematic （RTK） po-sitioning for medium baseline, a multi-frequency ambiguity resolution algorithm on the basis of three-frequency BeiDou navigation satellite system （BDS） and dual-frequency global positioning system is proposed. The three carrier ambiguity resolution （ TCAR ） algorithm and the lea st-square ambiguity decorrelation ad justment （LAMBDA） algorithm are brought together to fix ambiguities in three steps. To reduce the effects of errors such as ionosphere delay on ambiguities, a search algorithm for combination coefficients is presented. In addi-tion, an adaptive extended Kalman filter is utilized for RTK positioning. In the medium baseline experiment, the success rates of the proposed algorithm, BDS TCAR algorithm and single/dual-system LAMBDA algorithm are compared. The proposed ambiguity resolution algorithm has the highest success rate, and could fix ambigui-ties instantaneously. Additionally, it has the best positioning accuracy with the position error at the millimeter level.