JOURNAL ARTICLE

Combinational Seabed Terrain Matching Algorithm Basing on Probability Data Associate Filtering and Iterative Closest Contour Point

Abstract

This paper is committed to solve some key technique of seabed terrain matching. After introduced the specificity of seabed terrain matching, we analyzed the advantage and disadvantage of TERCOM, PDAF (Probabilistic Data Association Filtering) and ICCP (Iterative Closest Contour Point), then a combinational seabed terrain matching algorithm was proposed to improve the accuracy and practicability of seabed terrain matching which is based and ICCP. By using this combinational algorithm, underwater vehicle is allowed for mobile navigation in the period of terrain matching. Theoretical analysis and simulation results both show that the performance of this combinational algorithm is satisfactory.

Keywords:
Terrain Matching (statistics) Seabed Algorithm Computer science Probabilistic logic Iterative closest point Computer vision Blossom algorithm Point (geometry) Artificial intelligence Iterative method Geology Mathematics Geography Point cloud Geometry

Metrics

1
Cited By
0.38
FWCI (Field Weighted Citation Impact)
6
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Computational Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering
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