Bayesian terrain-based underwater navigation using an improved state-space model

被引：15
|
作者：
Anonsen, Kjetil Bergh [1 ]
Hallingstad, Oddvar [1 ]
Hagen, Ove Kent [2 ]
机构：
[1] Norwegian Univ Sci & Technol, Dept Engn Cybernet, NO-7491 Trondheim, Norway
[2] Norwegian Def Res Estab FFI, NO-2027 Kjeller, Norway
来源：
2007 SYMPOSIUM ON UNDERWATER TECHNOLOGY AND WORKSHOP ON SCIENTIFIC USE OF SUBMARINE CABLES AND RELATED TECHNOLOGIES, VOLS 1 AND 2 | 2007年
关键词：
D O I：
10.1109/UT.2007.370773
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
This paper focuses on terrain aided underwater navigation as a means of aiding an inertial navigation system. It is assumed that a prior map is present and Bayesian methods are used to estimate the position of the vehicle. Traditionally this has been done using a crude low-dimensional model in the Bayesian filters. An improved state-space model is introduced, implemented in a particle filter/sequential Monte Carlo filter and tested on real AUV (autonomous underwater vehicle) data. Compared to conventional filter models, the new model yields smoother, slightly more accurate results, though problems with overconfidence occur.
引用
收藏
页码：499 / +
页数：2
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