一种无须变换参考星的GNSS单基线卡尔曼滤波算法

doi:10.11947/j.AGCS.2015.20140430

测绘学报 ›› 2015, Vol. 44 ›› Issue (9): 958-964.doi: 10.11947/j.AGCS.2015.20140430

一种无须变换参考星的GNSS单基线卡尔曼滤波算法

张宝成¹, 袁运斌¹, 蒋振伟²

1. 中国科学院测量与地球物理研究所动力大地测量学国家重点实验室, 湖北武汉 430077;
2. 北京空间信息中继传输技术研究中心, 北京 100094

收稿日期:2014-03-24 修回日期:2014-12-04 出版日期:2015-09-24 发布日期:2015-09-24
作者简介:张宝成(1985—),男,博士后,研究方向为精密单点定位算法和应用。E-mail:b.zhang@whigg.ac.cn
基金资助:
国家自然科学基金重点项目(41231064);国家973计划(2012CB825604);国家863计划(2012AA121803);大地测量与地球动力学国家重点实验室开放基金(SKLGED2013-1-6-E;SKLGED2014-3-7-E)

Kalman Filter-based Single-baseline GNSS Data Processing without Pivot Satellite Changing

ZHANG Baocheng¹, YUAN Yunbin¹, JIANG Zhenwei²

1. State Key Laboratory of Dynamic Geodesy, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China;
2. Beijing Space Information Relay and Transmission Technology Research Centre, Beijing 100094, China

Received:2014-03-24 Revised:2014-12-04 Online:2015-09-24 Published:2015-09-24
Contact: 袁运斌,yybgps@whigg.ac.cn E-mail:yybgps@whigg.ac.cn
Supported by:
The State Key Program of National Natural Science Foundation of China (No.41231064) The National Basic Research Program of China(973 Program)(No.2012CB825604) The National High-tech Research and Development Program of China (No.2012AA121803) Open Foundation of State Key Laboratory of Geodesy and Earth's Dynamics (Nos. SKLGED 2013-1-6-E; SKLGED 2014-3-7-E)

摘要/Abstract

摘要： 处理单基线全球导航卫星系统观测数据可获取位置、时间、大气延迟等信息,其应用包括相对定位、时频传递等。为实现实时性,常采用卡尔曼滤波递归地估计各类参数;为确保可靠性,还需形成一组独立的双差模糊度,并将其正确地固定为整数。实践中,滤波函数模型较常采用双差观测方程(即双差滤波模型)。若在当前历元原先的参考星不再可视时,双差滤波模型则需要定义新的参考星,并“映射”双差模糊度预报值以确保滤波连续。此外,双差滤波模型所计算的接收机相位钟差估值吸收了对应于参考星的站间单差模糊度,因此当参考星变换后可能会发生“整周跳跃”。在仍将双差模糊度作为一类可估参数的前提下,本文推导出以站间单差观测方程为滤波函数模型的算法(单差滤波模型),并证明了其与双差滤波模型具备理论上的等价性和实施上的差异性。与双差滤波模型相比,单差滤波模型不再需要“映射”双差模糊度预报值等运算,从而具备了更高的计算效率和灵活性;单差滤波模型所提供的接收机相位钟差估值也不受“整周跳跃”的影响,因此特别有利于频率传递应用。

关键词: GNSS单基线, 卡尔曼滤波, 站间单差, 双差模糊度, 参考星, 频率传递

Abstract: Single-baseline global navigation satellite system (GNSS) data are able to be processed into a batch of parameters such as positions, timing information as well as atmospheric delays. The applications of relevance, therefore, consist of relative positioning, time and frequency transfer and so forth. To achieve real-time capability, these parameters are usually estimated by means of Kalman-filter. Moreover, the reliability of these parameters can be further strengthened by forming and then successfully fixing a set of independent double-differenced (DD) integer ambiguities. For this purpose, the filter function model is commonly set up based on the DD observation equations (DD filter model). In order to preserve the continuity of the filter, DD filter model needs to explicitly refer to another pivot satellite once the previous one becomes invisible. This thereby implies that, before being predicted to the next epoch, the former filtered DD ambiguity vector has to be “mapped” with respect to the newly-defined pivot satellite. In addition to that, the estimated receiver phase clocks using DD filter model may soak up distinct between-receiver single-differenced (SD) ambiguities belonging to different pivot satellites and would thereby be subject to apparent “integer jumps”. In this contribution, SD observation equations involving estimable DD ambiguity parameters are alternatively selected as the filter function model (SD filter model). Our analyses suggest that, both DD and SD filter models are equivalent in theory, but differ from each other as far as their implementations are concerned. Typically, for SD filter model, no effort should be made to map DD ambiguities, thus implying less intensive computational burden and better flexibility than DD filter model. At the same time, receiver phase clocks determined by SD filter model are free from “integer jumps” and thus are particularly beneficial for frequency transfer.

Key words: GNSS single-baseline, Kalman-filter, between-receiver single-difference, double-difference ambiguity, pivot satellite, frequency transfer

中图分类号:

P228

张宝成, 袁运斌, 蒋振伟. 一种无须变换参考星的GNSS单基线卡尔曼滤波算法[J]. 测绘学报, 2015, 44(9): 958-964.

ZHANG Baocheng, YUAN Yunbin, JIANG Zhenwei. Kalman Filter-based Single-baseline GNSS Data Processing without Pivot Satellite Changing[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(9): 958-964.

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一种无须变换参考星的GNSS单基线卡尔曼滤波算法

Kalman Filter-based Single-baseline GNSS Data Processing without Pivot Satellite Changing

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