<p><strong>G1 &#8211; Geodetic Theory and Algorithms</strong></p><p><strong>G1.3 High-precision GNSS: methods, open problems and Geoscience applications</strong></p><p><strong>&#160;</strong></p><p><strong>Instantaneous Ambiguity Resolved GLONASS FDMA Attitude Determination</strong></p><p><strong>&#160;</strong></p><p>PJG Teunissen<sup>1,2</sup>, A. Khodabandeh<sup>3</sup>, S. Zaminpardaz<sup>4</sup></p><p><sup>1</sup>GNSS Research Centre, Curtin University, Perth, Australia</p><p><sup>2</sup>Geoscience and Remote Sensing, Delft University of Technology, The Netherlands</p><p><sup>3</sup>University of Melbourne, Melbourne, Australia</p><p><sup>4</sup>RMIT University, Melbourne, Australia</p><p>&#160;</p><p>In [1] a new formulation of the double-differenced (DD) GLONASS FDMA model was introduced. It closely resembles that of CDMA-based systems and it guarantees the estimability of the newly defined GLONASS ambiguities. The close resemblance between the new GLONASS FDMA model and the standard CDMA-models implies that available CDMA-based GNSS software is easily modified [2] and that existing methods of integer ambiguity resolution can be directly applied. Due to its general applicability, we believe that the new model opens up a whole variety of carrier-phase based GNSS applications that have hitherto been a challenge for GLONASS ambiguity resolution [3]</p><p>We provide insight into the ambiguity resolution capabilities of the new GLONASS FDMA model, combine it with next-generation GLONASS CDMA signals [4] and demonstrate it for remote sensing platforms that require single-epoch, high-precision direction finding. This demonstration will be done with four different, instantaneous baseline estimators: (a) unconstrained, ambiguity-float baseline, (b) length-constrained, ambiguity-float baseline, (c) unconstrained, ambiguity-fixed baseline, and (d) length-constrained, ambiguity-fixed baseline. The unconstrained solutions are computed with the LAMBDA method, while the constrained ambiguity solutions with the C-LAMBDA method, thereby using the numerically efficient bounding-function formulation of [5]. The results will demonstrate that with the new model, GLONASS-only direction finding is instantaneously possible and that the model and associated method therefore holds great potential for array-based attitude determination and array-based precise point positioning.</p><p>&#160;</p><p>[1] P.J.G. Teunissen (2019): A New GLONASS FDMA Model, GPS Solutions, 2019, Art 100.</p><p>[2] A. Khodabandeh and P.J.G. Teunissen (2019): GLONASS-L. MATLAB code archived in GPSTOOLBOX:</p><p>https://www.ngs.noaa.gov/gps-toolbox/GLONASS-L.htm</p><p>[3] R. Langley (2017): GLONASS: Past, present and future. GPS World November 2017, 44-48.</p><p>[4] S. Zaminpardaz, P.J.G. Teunissen and N. Nadarajah (2017): GLONASS CDMA L3 ambiguity resolution</p><p>and positioning, GPS Solutions, 2017, 21(2), 535-549.</p><p>[5] P.J.G. Teunissen PJG (2010): Integer least-squares theory for the GNSS compass. Journal of Geodesy, 84:433&#8211;447</p><p>&#160;</p><p><strong>Keywords: </strong>GNSS, GLONASS, FDMA, CDMA model, Instantaneous Attitude Determination, Integer Ambiguity Resolution</p>
Research on Tightly Coupled Multi-Antenna GNSS/MEMS Single-Frequency Single-Epoch Attitude Determination in Urban Environment
