{"http:\/\/lib.itenas.ac.id\/kti\/?p=5215":{"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#type":[{"type":"uri","value":"http:\/\/rdfs.org\/sioc\/ns#Post"},{"type":"uri","value":"http:\/\/rdfs.org\/sioc\/types#BlogPost"}],"http:\/\/purl.org\/dc\/elements\/1.1\/title":[{"type":"literal","value":"Practical considerations on partial ambiguity resolution for attitude  determination"}],"http:\/\/purl.org\/dc\/terms\/identifier":[{"type":"literal","value":"5215","datatype":"http:\/\/www.w3.org\/2001\/XMLSchema#integer"}],"http:\/\/purl.org\/dc\/elements\/1.1\/modified":[{"type":"literal","value":"2017-09-25","datatype":"http:\/\/www.w3.org\/2001\/XMLSchema#date"}],"http:\/\/purl.org\/dc\/elements\/1.1\/created":[{"type":"literal","value":"2017-09-25","datatype":"http:\/\/www.w3.org\/2001\/XMLSchema#date"}],"http:\/\/rdfs.org\/sioc\/ns#link":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?p=5215"}],"http:\/\/rdfs.org\/sioc\/ns#has_creator":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?author=6#account"}],"http:\/\/rdfs.org\/sioc\/ns#has_container":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/#posts"}],"http:\/\/purl.org\/dc\/elements\/1.1\/abstract":[{"type":"literal","value":""}],"http:\/\/purl.org\/rss\/1.0\/modules\/content\/encoded":[{"type":"literal","value":"<![CDATA[The GNSS carrier phase observation allows for high precision positioning and attitude determination, as long as its integer ambiguity is correctly resolved. Solving integer ambiguities in attitude determination, using multiple antennae installed on the moving body, has some advantages: antennae are separated by relatively short distances, and their geometry is fixed, thus allowing precise baseline lengths in the body reference frame to be known beforehand. From the mathematical point of view, the predefined precise baseline lengths will lead to strong functional and stochastic models, which in turn, will allow for a higher success rate for the integer ambiguity resolution. However, solving several integer ambiguities may also be computationally demanding, especially for real-time applications. The usage of the partial ambiguity resolution method solves this drawback. It was reported that this strategy not only gives higher ambiguity success rate compared to the full ambiguity resolution approach, but also decreases the computational cost. [1]\u2013[5]. Besides that, [6] suggested the so-called affine constrained least squares method, which avoids the complexity of the (multi-) constrained least-squares problem as well as the complexity of the ambiguity search space. This contribution examines the partial ambiguity resolution method for two different search models: the affine constrained least squares model and the gradient iterative least squares model. The two methods are compared by means of the ambiguity dilution of precision, the success rate, and the number of fixed ambiguities. We show that each method has benefit for a particular purpose.\r\n\r\n<strong>Dibuat oleh : <\/strong>Hendy F. Suhandri, Eugenio Realini\r\n<strong> Alamat e-mail: <\/strong>suhandri@nav.uni-stuttgart.de, eugenio.realini@g-red.eu\r\n<strong> Kata kunci : <\/strong>Baseline constraint, Partial ambiguity search strategy, Affine constrained least squares model, Iterative baseline-constrained least squares model, Success rate, Number of fixed ambiguities\r\n<strong>Keterangan: <\/strong>Karya ilmiah ini di sampaikan pada <span id=\"yui_3_14_1_1_1506304855920_125\" data-reactid=\"25\">European Navigation Conference, At Rotterdam, The Netherland, <span id=\"yui_3_14_1_1_1506304855920_140\" class=\"publication-meta-date\" data-reactid=\"11\"><span id=\"yui_3_14_1_1_1506304855920_139\" data-reactid=\"12\">\u00a0April 2014<\/span><\/span><\/span>\r\n\r\n<a href=\"https:\/\/www.researchgate.net\/publication\/316662713_Practical_considerations_on_partial_ambiguity_resolution_for_attitude_determination\"><strong>Practical considerations on partial ambiguity resolution for attitude\u00a0 determination<\/strong><\/a>]]>","datatype":"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#XMLLiteral"}],"http:\/\/rdfs.org\/sioc\/ns#content":[{"type":"literal","value":"The GNSS carrier phase observation allows for high precision positioning and attitude determination, as long as its integer ambiguity is correctly resolved. Solving integer ambiguities in attitude determination, using multiple antennae installed on the moving body, has some advantages: antennae are separated by relatively short distances, and their geometry is fixed, thus allowing precise baseline lengths in the body reference frame to be known beforehand. From the mathematical point of view, the predefined precise baseline lengths will lead to strong functional and stochastic models, which in turn, will allow for a higher success rate for the integer ambiguity resolution. However, solving several integer ambiguities may also be computationally demanding, especially for real-time applications. The usage of the partial ambiguity resolution method solves this drawback. It was reported that this strategy not only gives higher ambiguity success rate compared to the full ambiguity resolution approach, but also decreases the computational cost. [1]\u2013[5]. Besides that, [6] suggested the so-called affine constrained least squares method, which avoids the complexity of the (multi-) constrained least-squares problem as well as the complexity of the ambiguity search space. This contribution examines the partial ambiguity resolution method for two different search models: the affine constrained least squares model and the gradient iterative least squares model. The two methods are compared by means of the ambiguity dilution of precision, the success rate, and the number of fixed ambiguities. We show that each method has benefit for a particular purpose.\r\n\r\nDibuat oleh : Hendy F. Suhandri, Eugenio Realini\r\n Alamat e-mail: suhandri@nav.uni-stuttgart.de, eugenio.realini@g-red.eu\r\n Kata kunci : Baseline constraint, Partial ambiguity search strategy, Affine constrained least squares model, Iterative baseline-constrained least squares model, Success rate, Number of fixed ambiguities\r\nKeterangan: Karya ilmiah ini di sampaikan pada European Navigation Conference, At Rotterdam, The Netherland, \u00a0April 2014\r\n\r\nPractical considerations on partial ambiguity resolution for attitude\u00a0 determination"}],"http:\/\/rdfs.org\/sioc\/ns#topic":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?cat=118"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?cat=147"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=affine-constrained-least-squares-model"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=baseline-constraint"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=iterative-baseline-constrained-least-squares-model"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=number-of-fixed-ambiguities"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=partial-ambiguity-search-strategy"},{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=success-rate"}],"http:\/\/rdfs.org\/sioc\/ns#attachment":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/wp-content\/uploads\/2017\/09\/Practical-considerations-on-partial-ambiguity-resolution-for-attitude-determination.pdf"}]},"http:\/\/lib.itenas.ac.id\/kti\/?author=6#account":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?author=6&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?cat=118":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?cat=118&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?cat=147":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?cat=147&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?tag=affine-constrained-least-squares-model":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=affine-constrained-least-squares-model&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?tag=baseline-constraint":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=baseline-constraint&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?tag=iterative-baseline-constrained-least-squares-model":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=iterative-baseline-constrained-least-squares-model&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?tag=number-of-fixed-ambiguities":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=number-of-fixed-ambiguities&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?tag=partial-ambiguity-search-strategy":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=partial-ambiguity-search-strategy&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/?tag=success-rate":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?tag=success-rate&feed=lhrdf&format=json"}]},"http:\/\/lib.itenas.ac.id\/kti\/wp-content\/uploads\/2017\/09\/Practical-considerations-on-partial-ambiguity-resolution-for-attitude-determination.pdf":{"http:\/\/www.w3.org\/2000\/01\/rdf-schema#seeAlso":[{"type":"uri","value":"http:\/\/lib.itenas.ac.id\/kti\/?attachment_id=5216&feed=lhrdf&format=json"}]}}