Underwater Terrain Positioning Method Using Maximum a Posteriori Estimation and PCNN Model

被引：9

作者：

Chen, Pengyun ^{[1
]}

Zhang, Pengfei ^{[1
]}

Ma, Teng ^{[2
]}

Shen, Peng ^{[3
]}

Li, Ye ^{[2
]}

Wang, Rupeng ^{[2
]}

Han, Yue ^{[4
]}

Li, Lizhou ^{[1
]}

机构：

[1] North Univ China, Coll Mechatron Engn, Taiyuan 030051, Shanxi, Peoples R China

[2] Harbin Engn Univ, Sci & Technol Underwater Vehicle Lab, Harbin 150001, Heilongjiang, Peoples R China

[3] Natl Deep Sea Ctr, Qingdao 266237, Shandong, Peoples R China

[4] Taiyuan Tourism Coll, Modern Educ Informat Ctr, Taiyuan 030032, Shanxi, Peoples R China

来源：

JOURNAL OF NAVIGATION | 2019年 / 72卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Autonomous Underwater Vehicle; Terrain Matching Positioning; Maximum a Posteriori estimation; Pulse Coupled Neural Network; BASE-LINE; NAVIGATION; VEHICLES;

D O I：

10.1017/S0373463319000067

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

Conventional underwater navigation and positioning methods for Autonomous Underwater Vehicles (AUVs) either require the installation of acoustic arrays, which make AUVs less independent, or result in cumulative errors. This paper proposes an Underwater Terrain Positioning Method (UTPM) using Maximum a Posteriori (MAP) estimation and a Pulse Coupled Neural Network (PCNN) model for highly accurate navigation by AUVs. The PCNN model is used as a secondary discriminant to effectively identify pseudo-anchor points in flat terrain feature areas and to find the true positioning point, which significantly improves the matching positioning accuracy in these areas. Simulation results show that the proposed method effectively corrects Inertial Navigation System (INS) cumulative errors and has high matching positioning accuracy, which satisfy the requirements of AUV underwater navigation and positioning.

引用

页码：1233 / 1253

页数：21