Real-time Estimation Method for GLONASS Phase Inter-frequency Bias Based on Particle Swarm Optimization

被引：0
|
作者：
Sui X. [1 ]
Xu A. [1 ]
Hao Y. [1 ]
Wang C. [1 ]
机构：
[1] School of Geomatics, Liaoning Technical University, Fuxin
来源：
Xu, Aigong (xu_ag@126.com) | 2018年 / SinoMaps Press卷 / 47期
关键词：
Ambiguity resolution; GLONASS; Particle swarm optimization; Phase inter-frequency bias; Real time;
D O I：
10.11947/j.AGCS.2018.20170244
中图分类号：
学科分类号：
摘要：
GLONASS phase inter-frequency bias (IFB) is linearly correlated to ambiguity, so it is difficult to separate phase IFB and ambiguity quickly. To solve this problem, a real-time estimate method for GLONASS phase IFB is proposed. By analyzing the relationship between the phase IFB parameter and the RATIO value, the phase IFB estimation problem comes down to solve the optimization problem. The particle swarm optimization (PSO) algorithm is one of the optimization methods, which is used to estimate the phase IFB parameters. This method can search the IFB rate parameter in an effective and reliable way without increasing the number of estimated parameters and prior information, and GLONASS ambiguities can be real-time fixed. The experimental results show that the average number of searching per epoch is 32 for single-epoch solution, which is far below what particle filter-based estimation of phase IFB needs, the number of searching per epoch is always 200 by using particle filter-based estimation. The average number of searching per epoch is only 9 by using PSO for filtering solution. The ambiguity-fixing success rate is above 96.2% whether for single-epoch solution or filtering solution, and maximal position differences of fixed solution are all below 4 cm. © 2018, Surveying and Mapping Press. All right reserved.
引用
收藏
页码：584 / 591
页数：7
相关论文
共 20 条
  • [1] Pratt M., Burke B., Misra P., Single-Epoch Integer Ambiguity Resolution with GPS-GLONASS L1-L2 Data[C, Proceedings of the 11th International Technical Meeting of the Satellite Division of the Institute of Navigation, 11, pp. 389-398, (1998)
  • [2] Wang J., Rizos C., Stewart M.P., Et al., GPS and GLONASS Integration: Modeling and Ambiguity Resolution Issues, GPS Solutions, 5, 1, pp. 55-64, (2001)
  • [3] Wanninger L., Wallstab-Freitag S., Combined Processing of GPS, GLONASS, and SBAS Code Phase and Carrier Phase Measurements, Proceedings of the 20th International Technical Meeting of the Satellite Division of the Institute of Navigation, pp. 866-875, (2007)
  • [4] Wanninger L., Carrier-phase Inter-frequency Biases of GLONASS Receivers, Journal of Geodesy, 86, 2, pp. 139-148, (2012)
  • [5] Takzc F., GLONASS Inter-frequency Biases and Ambiguity Resolution, Inside GNSS, 4, 2, pp. 24-28, (2009)
  • [6] Chen J., Xiao P., Zhang Y., Et al., GPS/GLONASS System Bias Estimation and Application in GPS/GLONASS Combined Positioning, China Satellite Navigation Conference (CSNC) 2013 Proceedings, pp. 323-333, (2013)
  • [7] Zinoviev A.E., Veitsel A.V., Dolgin D.A., Renovated GLONASS: Improved Performances of GNSS Receivers, Proceedings of the 22nd International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS 2009), pp. 3271-3277, (2001)
  • [8] Al-Shaery A., Zhang S., Rizos C., An Enhanced Calibration Method of GLONASS Inter-channel Bias for GNSS RTK, GPS Solutions, 17, 2, pp. 165-173, (2013)
  • [9] Tian Y., Ge M., Neitzel F., Particle Filter-based Estimation of Inter-frequency Phase Bias for Real-time GLONASS Integer Ambiguity Resolution, Journal of Geodesy, 89, 11, pp. 1145-1158, (2015)
  • [10] Kennedy J., Particle Swarm Optimization, Encyclopedia of Machine Learning, pp. 760-766, (2011)
12