Share Email Print

Proceedings Paper

Improving fundamental factors among correlation matching algorithms in underwater TANS
Author(s): Yi Lin; Lei Yan; Qingxi Tong
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 8 August 2007
PDF: 9 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 675216 (8 August 2007); doi: 10.1117/12.760669
Show Author Affiliations
Yi Lin, Peking Univ. (China)
Lei Yan, Peking Univ. (China)
Qingxi Tong, Institute of Remote Sensing Applications (China)

Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information

© SPIE. Terms of Use
Back to Top