Using the integer decorrelation procedure to increase of the efficiency of the MAFA method

• Autorzy: Cellmer S.

Identyfikatory

DOI

10.2478/v10018-012-0002-1

• Konferencja: Proceedings of the Conference on "Satelitarne metody wyznaczania pozycji we wspólczesnej geodezji i nawigacji", Wroclaw, Poland, June 2-4, 2011 - Part 1
• Języki publikacji: EN

Abstrakty

EN

The Modified Ambiguity Function Approach (MAFA) is a method of GNSS carrier phase processing. In this method, the functional model of the adjustment problem contains the conditions ensuring the "integerness" of the ambiguities. These conditions are expressed in the form of differentiable function. A prerequisite for obtaining the correct solution is a mechanism ensuring not only the "integerness" of the ambiguity but also appropriate localization of the search space in the place where the ambiguities have correct values. One of such mechanisms is cascade adjustment, applying the linear combinations of the signals L1 and L2 with the integer coefficients and various wavelengths. This paper presents another, independent from the previous, approach to increase the efficiency of the MAFA method. It is based on the application of the integer decorrelation matrix to transform observation equations into equivalent, but better conditioned, observation equations. The transformation matrix is obtained in the well-known ambiguity variance-covariance matrix integer decorrelation process.

Słowa kluczowe

EN

GNSS data processing; ambiguity function; MAFA method

• Wydawca: Centrum Badań Kosmicznych PAN ; De Gruyter
• Czasopismo: Artificial Satellites : Journal of Planetary Geodesy
• Rocznik: 2011
• Tom: Vol. 46, No. 3
• Strony: 103--110
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Cellmer S.

• Institute of Geodesy University of Warmia and Mazury in Olsztyn, Olsztyn

Bibliografia

• Cellmer S., Wielgosz P., Rzepecka Z. (2010) Modified ambiguity function approach for GPS carrier phase positioning. Journal of Geodesy, vol. 84, 264-275.
• Cellmer S. (2011a) The real time precise positioning using MAFA method, The 8th International Conference ENVIRONMENTAL ENGINEERING, selected papers, vol . III, Vilnius, s.1310-1314.
• Cellmer S. (2011b), A Graphic Representation of the Necessary Condition for the MAFA Method. Transactions on Geoscience and Remote Sensing, vol. PP Isssue: 99, 1-7.
• Cellmer S. and Wielgosz P. (2011) “GNSS Carrier Phase Processing Using Modified Ambiguity Function Approach”, Florence, Italy, May 27-30 2009, EUREF Publication, Mitteilungen des Bundesamtes für Kartographie und Geodäsie (Submitted for publication), on line available http://www.epncb.oma.be/_newsmails/papers/eurefsymposium2009/gnss_carrier_phase_processing_using_modified_ambiguity_function.pdf
• Chang X-W, Yang X, Zhou T. (2005) MLAMBDA: a modified LAMBDA method for integer least-squares estimation, Journal of Geodesy 79, 552-565.
• Cocard M., Bourgon S. Kamali O., Collins P. (2008) A systematic investigation of optimal carrier-phase combinations for modernized triple-frequency GPS”, Journal of Geodesy vol. 82, 555-564.
• Dach R, Hugentobler U, Fridez P, Meindl M (2007) BERNESE GPS Software Version 5.0. Astronomical Institute, University of Berne.
• Glenn J., Svedensen G. 2006. Some properties of decorrelation techniques in the ambiguity space GPS Solution vol. 10, 40-44.
• Hassibi A. and Boyd S. (1998) Integer parameter estimation in linear models with application to GPS. IEEE Trans SignallProc 46, 2938-2952.
• Hofmann-Wellenhof B, Lichtenegger H, Wasle E. (2008) GNSS-Global Navigation Satellite Systems - GPS, GLONASS, Galileo & more. Springer-Verlag Wien.
• Han S, Rizos C. (1996) Improving the computational efficiency of the ambiguity function algorithm. Journal of Geodesy 70, 330-341.
• Jonge P. de., Tiberius Ch. (1996) The LAMBDA method for integer ambiguity estimation: implementation aspects Delft Geodetic Computing Centre LGR Series.
• Jung J. and Enge P. (2000) Optimization of Cascade Integer Resolution with Three Civil GPS Frequencies In Proc. ION GPS’2000, Salt Lake City, September.
• Leick A. (2004) GPS Satellite Surveying. 3rd edition,John Wiley and Sons, Inc.
• Liu L.T., Hsu H.T., Zhu Y.Z., Ou J.K. (1999) A new approach to GPS ambiguity decorrelation Journal of Geodesy vol. 73,478-490.
• Teunissen P J G. (1995) The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation Journal of Geodesy 70, 65-82.
• Teunissen P J G, and Kleusberg A. (1998) GPS for Geodesy, Springer - Verlag, Berlin Heidelberg New York.
• Urquhart, L. (2009) An Analysis of Multi-Frequency Carrier Phase Linear Combinations for GNSS. Senior technical report, Department of Geodesy and Geomatics Engineering Technical Report No. 263, University of New Brunswick, Fredericton, New Brunswick, Canada.
• Xu PL (2001) Random simulation and GPS decorrelation. Journal of Geodesy 75:408-423.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).