摘要
针对高精度GNSS/INS组合定位中,伪距多路径误差严重影响模糊度固定效率及系统定位精度的问题,引入抗差估计函数,建立INS辅助GPS/BDS模糊度快速固定抗差模型。首先建立了单频GPS/BDS/INS紧组合动力学模型以及观测模型,继而研究了紧组合系统INS辅助下GNSS模糊度快速分解模型,分析了伪距观测值粗差对于模糊度参数估值的影响。为减弱异常观测值对于模糊度固定成功率的影响,提出了附有INS定位约束的模糊度解算抗差算法。最后利用实测导航定位数据验证了算法的有效性。结果表明:对比不考虑观测值粗差影响的模糊度固定算法,模糊度固定抗差算法显著提高了模糊度固定的可靠性,抗差算法的模糊度固定效率不受粗差值大小的影响;对于模拟的伪距多粗差情形,抗差算法对GPS/INS、BDS/INS和GPS/BDS/INS三种组合方案的模糊度固定Ratio均值分别提高了100.8%、47.7%以及19.5%;在INS定位松约束条件下,抗差算法提高了模糊度固定成功率。
In view that the ambiguity resolution and positioning performance of GNSS/INS integrated system would be dramatically degraded in the presence of highly multipath-contaminated measurements, a robust INS aided GPS/BDS ambiguity resolution model was introduced. Firstly, the dynamic and measurement models for the single-frequency GPS/BDS/INS tightly coupled navigation system were developed. Then an effective INS aided GNSS ambiguity resolution algorithm was presented, the impact of biased code observations on ambiguity resolution was analyzed, and a robust ambiguity resolution algorithm with INS constraint was developed to improve the ambiguity fixing rate in the presence of measurement outliers. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm. It is shown that the proposed robust ambiguity resolution scheme can significantly improve the reliability of the resolved ambiguities compared with the ambiguity resolution scheme without considering measurements outliers. The ratio values of the robust algorithm are not affected by the magnitude of outliers. The mean ratio values of the robust scheme for GPS/INS, BDS/INS, GPS/BDS/INS integrated system are improved by 100.8%, 47.7% and 19.5% respectively under the multiple outliers conditions, and the ambiguity fixing rates are also improved with loose INS constraint.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2015年第4期493-499,共7页
Journal of Chinese Inertial Technology
基金
国家科技支撑计划课题(2012BAJ22B01)
关键词
GPS
BDS
INS
紧组合
模糊度
抗差
GPS
Bei Dou navigation satellite system
inertial navigation system
tightly coupled
ambiguity
robust
