A misalignment angle error calibration method of underwater acoustic array in strapdown inertial navigation system/ultrashort baseline integrated navigation system based on single transponder mode

2019 ◽  
Vol 90 (8) ◽  
pp. 085001 ◽  
Author(s):  
Jinwu Tong ◽  
Xiaosu Xu ◽  
Tao Zhang ◽  
Yao Li ◽  
Yiqing Yao ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Integrated Navigation ◽  
Misalignment Angle ◽  
Angle Error ◽  
Integrated Navigation System ◽  
Error Calibration ◽  
Acoustic Array

scholarly journals Improved Underwater Integrated Navigation System using Unscented Filtering Approach

2015 ◽  
Vol 69 (3) ◽  
pp. 561-581 ◽  
Author(s):  
Mohammad Shabani ◽  
Asghar Gholami
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Doppler Velocity ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Measurement Models ◽  
Error State ◽  
Filtering Approach

In underwater navigation, the conventional Error State Kalman Filter (ESKF) is used for combining navigation data where due to first order linearization of the nonlinear equations of the dynamics and measurements, considerable error is induced in estimated error state and covariance matrices. This paper presents an underwater integrated inertial navigation system using the unscented filter as an improved nonlinear version of the Kalman filter family. The designed system consists of a strap-down inertial navigation system accompanying Doppler velocity log and depth meter. In the proposed approach, to use the nonlinear capabilities of the unscented filtering approach the integrated navigation system is implemented in a direct approach where the nonlinear total state dynamic and and measurement models are utilised without any linearization. To our knowledge, no results have been reported in the literature on the experimental evaluation of the unscented-based integrated navigation system for underwater vehicles. The performance of the designed system is studied using real measurements. The results of the lake test show that the proposed system estimates the vehicle's position more accurately compared with the conventional ESKF structure.

The Design of Vehicle Integrated Navigation System Based on FPGA

2012 ◽  
Vol 442 ◽  
pp. 441-445
Author(s):  
Yong Sen Wei
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Gps Data ◽  
Integrated Navigation ◽  
Good Balance ◽  
Integrated Navigation System ◽  
Navigation Data ◽  
Navigation Algorithms ◽  
The Cost

A GPS/inertial navigation system design scheme is introduced. Combination of DSP and FPGA is used on the navigation board, and micro inertial navigation measuring element --ADIS16405 is used to sample required navigation data. DSP mainly implements navigation calculating based on navigation data, and realizes different navigation algorithms; FPGA in the system plays centeral control role, and not only samples IMU and GPS data, but also synchronize IMU and GPS in the real time, and preprocess and packet the navigation data. This paper also introduces the design of the software on FPGA. Practice proves that the scheme is feasible, and achieves the good balance between the cost, reliability and efficiency.

Application of Extended Kalman Filter Algorithm in SDINS/GPS Integrated Inertial Navigation System

2013 ◽  
Vol 367 ◽  
pp. 528-535
Author(s):  
Otman Ali Awin
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Integrated System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Matlab Package ◽  
Noisy Measurements

This paper deals with the integrated navigation system based on fusion of data from Strap Down Inertial Navigation System (SDINS) and from Global Position System (GPS). In order to increase the accuracy and reliability of navigation algorithms, these two different systems are combined. The navigation system that be analyzed is basically of INS type while GPS corrective data are obtained less frequently and these are treated as noisy measurements in an extended Kalman filter scheme. The simulation of whole system (SDINS/GPS integrated system with Kalman filter) was modeled using MATLAB package, SIMULINK© tool. The proper choice of Kalman filter parameters had taken to minimize navigation errors for a typical medium range flight scenario (Simulated test trajectory and real trajectory of vehicle motion). A prototype of a SDINS installed on a moving platform in the laboratory to collected data by many experiments to verification our SIMULINK models.

scholarly journals Based on Grid Reference Frame for SINS/CNS Integrated Navigation System in the Polar Regions

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Song Lijun ◽  
Zhao Wanliang ◽  
Cheng Yuxiang ◽  
Chen Xiaozhen
Keyword(s):  
Reference Frame ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Polar Regions ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Celestial Navigation ◽  
Low Latitudes ◽  
And Performance

As the inertial navigation system cannot meet the precision requirements of global navigation in the special geographical environment of the Polar Regions, this paper presents Strapdown Inertial Navigation System (SINS)/Celestial Navigation System (CNS) integrated navigation system of airborne based on Grid Reference Frame (GRF) and the simulation is carried out. The result of simulation shows that the SINS/CNS integrated navigation system is superior to the single subsystem in precision and performance, which not only effectively inhibits the error caused by gyro drift but also corrects the navigation parameters of system without delay. Comparing the simulation in the middle and low latitudes and in the Polar Regions, the precision of SINS/CNS integrated navigation system is the same in the middle and low latitudes and in the Polar Regions.

Study on Method of Autonomous Mobile Robot Integrated Navigation Based on SLAM

2012 ◽  
Vol 263-266 ◽  
pp. 1290-1297 ◽  
Author(s):  
Jing Zeng ◽  
Xiao Song Guo ◽  
Guo Liang Zhang
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
The Self ◽  
Autonomous Mobile Robot ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Unknown Environment ◽  
Navigation Scheme

Aiming at the problem of navigation in unknown environment of autonomous mobile robot, the self-made mobile robot was taken as research object. The integrated navigation technology was adapted to integrate the SLAM navigation system, DR navigation system and MEMS micro inertial navigation system possessed by the studied robot to construct the SLAM/DR/MEMS integrated navigation system of mobile robot. The experiments were carried to test the method, and the results show that the precision of navigation and location of mobile robot was developed by the integrated navigation scheme.

INS/Odometer Integration: Positional Approach

2021 ◽  
Vol 29 (2) ◽  
pp. 110-125
Author(s):  
A.A. Golovan ◽  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Strapdown Inertial Navigation System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Zero Velocity ◽  
Strapdown Inertial Navigation

The problem of a strapdown inertial navigation system (SINS) integration with an odometer as part of an integrated navigation system is considered. The odometer raw measurement is considered as an increment of the distance traveled along the odometer ‘measuring’ axis. Models of the integration solution components for the case of threedimensional navigation are presented, among which are the models of inertial autonomous and kinematic odometer dead reckoning (DR), models of relevant error equations, the model of SINS position aiding based on the odometer DR data and using GNSS position and velocity, wherever possible. The models comprise objective components, which do not depend on the type of the inertial sensors used and their accuracy grade, and variable components, which take into account the properties of the navigation sensors used. The integration does not require zero velocity updates, known as ZUPT correction, which are commonly used in navigation application.

DATA PROCESSING OF AN INTEGRATED NAVIGATION SYSTEM BY THE KAUFMAN FILTER

2020 ◽  
Author(s):  
В.В. ДЕМЬЯНОВ ◽  
И.С. ШУСТОВ ◽  
Д.С. ЧИРОВ
Keyword(s):  
Data Processing ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Integrated Navigation ◽  
Integrated Navigation System

Приведены результаты работ, выполненных в рамках исследования вопросов разработки унифицированной навигационной системы робототехнических комплексов. Рассмотрена возможность применения фильтра Кауфмана для обработки данных навигационной системы наземного робототехнического комплекса. Приводится анализ применимости фильтра Кауфмана для решения задачи фильтрации данных инерциальной навигационной системы. This article presents the results of the development of the unified navigation system of robotic complexes. The possibility of using the Kaufman filter for processing of data of a navigation system of a ground robotic complex is considered. An analysis of the applicability of the Kaufman filter for solving the problem of filtering data of the inertial navigation system is presented.

Transfer Alignment for MEMS Integrated Navigation System Based on H∞ Filter

2014 ◽  
Vol 490-491 ◽  
pp. 886-890
Author(s):  
Xing Zhi Zhang ◽  
Kun Peng He ◽  
Chen Yang Wang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Kalman Filters ◽  
Inertial Navigation System ◽  
Digital Simulation ◽  
Integrated Navigation ◽  
Misalignment Angle ◽  
Transfer Alignment ◽  
Integrated Navigation System ◽  
Simulation Results

The transfer alignment of strapdown inertial units were proposed that use the H filter to estimate the misalignment of the slave INS (inertial navigation system) relative to the master INS. Characteristics of the H filter in transfer alignment were studied in detail by checking digital simulation results obtained by using the H and Kalman filters. The results shows that the misalignment angle obtained with the H filter converge faster and closer to the exact values than do those obtained with the Kalman filter. The H filter is more robust than the Kalman filter in transfer alignment for MEMS integrated navigation system.

INS/GPS/MNS Integrated Navigation System with Federated Kalman Filtering

2013 ◽  
Vol 718-720 ◽  
pp. 1207-1212
Author(s):  
De Ning Jiang ◽  
Tulu Muluneh Mekonnen
Keyword(s):  
Global Positioning System ◽  
Kalman Filtering ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Global Positioning ◽  
Heading Angle ◽  
Adaptive Extended Kalman Filter

A multi-sensor integrated solution that combine complementary features of the Global Positioning System (GPS), inertial navigation system (INS), and magnetometer is presented due to GPS-aided inertial navigation system (INS) provides poor observability of heading angle. In addition, Based on the principle of federated Kalman filtering and Adaptive Extended Kalman Filter, the algorithm is presented also for accuracy of positioning and attitude, rapidity, and error tolerance of the navigation system. The algorithm is implemented in the integrated navigation system. Experimental results show that the observability issue is solved and improvement in accuracy.

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