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8 August 2007 Improving fundamental factors among correlation matching algorithms in underwater TANS
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Abstract
TERCOM, ICP and TIEM algorithms, which mathematically all apply correlation matching mode, have been developed for positioning in underwater Terrain-aided Navigation System (TANS), but how to virtually improve their performance is still research puzzle now. Analyzing the characters of terrain reference data's distribution and vehicles prowling underwater, we find that grid spacing and accumulation sequence are two decisional elements of underwater TANS. Then the modified Maximum a Posteriori (MAP) estimation algorithm (M-MAP) from super-resolution images reconstruction is creatively explored for implementing interpolation to enhance the accuracy of non-surveyed points' deep-determination, and basic error mechanism model (EMM) based on Mean Absolute Difference (MAD) algorithm is deduced which can reflect the relationship of underwater TANS's inner factors. Simulation experiments indicate that adopting appropriate fundamental factors can effectively boost up underwater TANS's navigation competence based on the algorithms listed above.
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Yi Lin, Lei Yan, and Qingxi Tong "Improving fundamental factors among correlation matching algorithms in underwater TANS", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 675216 (8 August 2007); https://doi.org/10.1117/12.760669
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