<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>The basis of high precision relative positioning is the use of carrier phase measurements. Data differencing techniques are one of the keys to achieving high precision positioning results as they can significantly reduce a variety of errors or biases in the observations and models. Since GPS observations are usually contaminated by many errors such as the atmospheric biases, the receiver clock bias, the satellite clock bias, and so on, it is impossible to model all systematic errors in the functional model. Although the data differencing techniques are widely used for constructing the functional model, some un-modeled systematic biases still remain in the GPS observations following such differencing. Another key to achieving high precision positioning results is to fix the initial carrier phase ambiguities to their theoretical integer values. To obtain a high percentage of successful ambiguity-fixed rates, noisy GPS satellites have to be identified and removed from the data processing step. This paper introduces a new method using genetic algorithm (GA) to optimize the best combination of GPS satellites which yields the highest number of successful ambiguity-fixed solutions in kinematic positioning mode. The results indicate that the use of GA can produce higher number of ambiguity-fixed solutions than the standard data processing technique.</p></abstract>

The basis of high precision relative positioning is the use of carrier phase measurements. Data differencing techniques are one of the keys to achieving high precision positioning results as they can significantly reduce a variety of errors or biases in the observations and models. Since GPS observations are usually contaminated by many errors such as the atmospheric biases, the receiver clock bias, the satellite clock bias, and so on, it is impossible to model all systematic errors in the functional model. Although the data differencing techniques are widely used for constructing the functional model, some un-modeled systematic biases still remain in the GPS observations following such differencing. Another key to achieving high precision positioning results is to fix the initial carrier phase ambiguities to their theoretical integer values. To obtain a high percentage of successful ambiguity-fixed rates, noisy GPS satellites have to be identified and removed from the data processing step. This paper introduces a new method using genetic algorithm (GA) to optimize the best combination of GPS satellites which yields the highest number of successful ambiguity-fixed solutions in kinematic positioning mode. The results indicate that the use of GA can produce higher number of ambiguity-fixed solutions than the standard data processing technique.

Optimization of Satellite Combination in Kinematic Positioning Mode with the Aid of Genetic Algorithm

Department of Survey Engineering, Faculty of Engineering, Chulalongkorn University, Thailand

Department of Civil & Geomatics Engineering, California State University, Fresno, California, U.S.A.

Department of Civil Engineering, Changwon National University, Rep. of Korea

Artificial Satellites

The basis of high precision relative positioning is the use of carrier phase measurements. Data differencing techniques are one of the keys to achieving high...

Optimization of Satellite Combination in Kinematic Positioning Mode with the Aid of Genetic Algorithm

Published Online: Jun 14, 2012

Page range: 35 - 46

DOI: https://doi.org/10.2478/v10018-012-0012-z

Keywords
Global Positioning System, Kinematic Positioning, Genetic Algorithm

This content is open access.

Optimization of Satellite Combination in Kinematic Positioning Mode with the Aid of Genetic Algorithm

Published Online: Jun 14, 2012

Page range: 35 - 46

DOI: https://doi.org/10.2478/v10018-012-0012-z

KeywordsGlobal Positioning System, Kinematic Positioning, Genetic Algorithm

This content is open access.

Keywords
Global Positioning System, Kinematic Positioning, Genetic Algorithm