实时GLONASS相位频间偏差粒子群优化估计方法

doi:10.11947/j.AGCS.2018.20170244

测绘学报 ›› 2018, Vol. 47 ›› Issue (5): 584-591.doi: 10.11947/j.AGCS.2018.20170244

实时GLONASS相位频间偏差粒子群优化估计方法

隋心, 徐爱功, 郝雨时, 王长强

辽宁工程技术大学测绘与地理科学学院, 辽宁阜新 123000

收稿日期:2017-05-08 修回日期:2018-02-26 出版日期:2018-05-20 发布日期:2018-06-01
通讯作者: 徐爱功 E-mail:xu_ag@126.com
作者简介:隋心(1981-),男,博士,讲师,研究方向为GNSS精密数据处理与应用研究。E-mail:survey_suixin@163.com
基金资助:
国家重点研发计划（2016YFC0803102）；辽宁省教育厅创新团队项目（LT2015013）；辽宁省教育厅辽宁省高等学校基本科研项目（LJ2017QL007）；辽宁省科技厅博士启动基金（201501126）

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

SUI Xin, XU Aigong, HAO Yushi, WANG Changqiang

School of Geomatics, Liaoning Technical University, Fuxin 123000, China

Received:2017-05-08 Revised:2018-02-26 Online:2018-05-20 Published:2018-06-01
Supported by:
The National Key Research and Development Program (No.2016YFC0803102);The Innovation Team Project of Education Bureau of Liaoning Province (No.LT2015013);The General Science Research Project of Education Bureau of Liaoning Province (No.LJ2017QL007);The Doctoral Scientific Research Foundation of Liaoning Province (No.201501126)

摘要/Abstract

摘要： 针对GLONASS相位频间偏差与模糊度线性相关所导致的难以对两者进行快速分离的问题，提出了一种实时GLONASS相位频间偏差估计方法。通过分析相位IFB与RATIO值之间的关系，将相位IFB估计问题归结为求解最优化问题，并将优化方法中的粒子群优化算法引入相位IFB估计中，该方法可在不增加待估参数数量以及先验信息的条件下，高效可靠地搜索出IFB变化率参数，实现GLONASS模糊度实时固定。测试结果表明，该方法在单历元解算条件下每历元平均搜索次数为32次，远低于基于粒子滤波的相位频间偏差估计方法的200次；在采用Kalman滤波方法进行解算条件下，每历元平均搜索次数仅为9次。无论采用单历元解还是滤波解，模糊度固定成功率均高于96.2%，模糊度固定解的最大坐标偏差均小于4 cm。

关键词: GLONASS, 相位频间偏差, 粒子群优化算法, 整周模糊度解, 实时

Abstract: 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.

Key words: GLONASS, phase inter-frequency bias, particle swarm optimization, ambiguity resolution, real time

中图分类号:

P228.4

隋心, 徐爱功, 郝雨时, 王长强. 实时GLONASS相位频间偏差粒子群优化估计方法[J]. 测绘学报, 2018, 47(5): 584-591.

SUI Xin, XU Aigong, HAO Yushi, WANG Changqiang. Real-time Estimation Method for GLONASS Phase Inter-frequency Bias Based on Particle Swarm Optimization[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(5): 584-591.

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实时GLONASS相位频间偏差粒子群优化估计方法

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

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