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| Instructors |
Dr.
Kees de Jong, Fugro
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About This Course |
Resolution of the carrier cycle ambiguities to their correct integer values is a prerequisite for precise positioning using Global Navigation Satellite Systems
(GNSS’s) such as GPS and the future European Galileo system. Since the integer ambiguities are estimated from stochastic observations, the ambiguities are stochastic as well and may contain integer errors. Validation of the estimated integer ambiguities is therefore of utmost importance. This course addresses the fundamental concepts and new developments in integer ambiguity estimation, including multi-frequency techniques, as well as validation methods assuring high confidence levels for the results. Also, a wide variety of implementation aspects and practical considerations are discussed and evaluated relating to integer ambiguity resolution applications.
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| Objectives |
• To provide an understanding of the concept of integer ambiguity estimation and present an overview of ambiguity resolution methods.
• To discuss the concept of the ambiguity success rate as a design tool for the reliability of integer ambiguity estimation and its dependence on satellite configuration and precision of the observations.
• To introduce concepts for the validation of the estimated integer ambiguities.
• To make participants aware of the influence of biases (as multipath, ionosphere) on the estimation of the integer ambiguities.
• To discuss implementation aspects and other practical aspects of integer ambiguity resolution. |
| Who Should Attend? |
• Engineers and technical professionals seeking conceptual explanations, trade-offs among various methods and a presentation of recent developments in the concepts of precise GNSS positioning employing ambiguity estimation techniques.
• System specialists, system engineers, software analysts and developers concerned with the implementation of ambiguity estimation procedures in GNSS processing software.
• Academics interested in obtaining or maintaining a high level of expertise and updating their knowledge base with new developments in this rapidly changing and analytically challenging area. |
| Prerequisites |
• Familiarity with the basic concepts of GNSS positioning, linear algebra, statistics, and least squares estimation.
• An understanding of GPS operational principles; Course 111, Course
122, Course 356, or equivalent experience is recommended. |
| Materials
You Will Keep |
•
A notebook including all materials presented during the course.
• Selected papers on ambiguity estimation by the staff of the
Department of Mathematical Geodesy and Positioning and selected other
papers.
• PDF files of selected papers and slides. Source code of LAMBDA
functions (Matlab, C), in combination with the material on Navtech’s
CD-ROM of references. |
| Course Schedule |
DAY 1
Dr.
Kees de
Jong |
8:30 - Ambiguity
Resolution: The Problem
GNSS processing scenarios
High precision applications9:45 - Introduction to Least Squares Estimation
and Quality Control
Principle of least squares
Measurement and stochastic model
Batch estimation
Recursive estimation
Linearization
Hypothesis testing
Internal and external reliability
11:00 - GNSS Observables
Code and carrier observations
Error sources: troposphere, ionosphere, orbits, multipath
Baseline models: geometry-free and geometry-based (stationary and
roving)
Ionosphere fixed, weighted and float solutions
12:00 - Lunch on your own
1:30 -
The
LAMBDA Method for Ambiguity Resolution
Integer
least squares and ambiguity decorrelation
Analysis of various baseline scenarios on ambiguity resolution
performance
2:45
- The LAMBDA Method for Ambiguity Resolution (cont’d)
4:00 -
Software
Demonstration I
Matlab
2D Visualization of integer mapping regions for different scenarios
(depending on influence of ionosphere) for the geometry-free baseline
model using one pair of satellites
5:00 - Day 1 ends
|
DAY 2
Dr.
de Jong |
8:30 - Overview
and Comparison of Approaches to Ambiguity Resolution
Rounding and integer bootstrapping
Integer least squares
Laning and other ambiguity combinations
Partial ambiguity resolution
9:45 - The
Fixed Baseline and Its Quality
Distribution
of the fixed ambiguities and resulting baseline
Validation of estimated ambiguities
Ambiguity
Success Rates
Success
rate as a design parameter
Current GPS, modernized GPS and Galileo
Multi-carrier ambiguity resolution (MCAR)
12:00 - Lunch on your own
1:30 - Biases
and Ambiguity Resolution
Influence
of biases due to ionosphere and multipath on ambiguity resolution and
the ambiguity success rate
2:45 -
Implementation
Aspects
Single-epoch
ambiguity estimation
Accumulation of normal equations
Integration of LAMBDA functions in GPS processing software
4:00 - Software
Demonstration II
Ambiguity
success rates for GPS,
Galileo and integrated GPS/Galileo for different (ionosphere fixed,
weighted and float) baseline models as a function of stochastic model
Number of frequencies and number of epochs
5:00 - Course ends
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| Continuing
Education Units |
1.2
(12 hours) |
|
