An inertial navigation system for small autonomous underwater vehicles (original) (raw)
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The Institute of Ocean and Systems Engineering at Florida Atlantic University is currently developing a new generation of autonomous underwater vehicle (AUV), the MiniAUV. One major objective in its development is to provide a higher degree of navigation accuracy than the former generation of vehicle, the Ocean Explorer could achieve. To this end an embedded, real-time inertial navigation system has been developed for the past two years. It integrates high-precision navigation sensors while performing high frequency filtering and extensive data fusion methods, including a standard and an extended Kalman filter. This paper presents both the hardware and software architectures of the navigation system. Although the system is not fully operational yet, preliminary results were produced and are presented to illustrate the different features of the system
Small inertial sensors for a miniature autonomous underwater vehicle
Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204)
Testing and algorithm development are addressed for the guidance system of a low-cost (disposable) miniature autonomous underwater vehicle. The requirements for low-cost and small size systems typically necessitate the use of low-performance sensors. In this work, we address the limitations of low-performance inertial sensors. Mechanized calibration routines are developed to compensate for high drift rates in gyro calibration coefficients, and compassjgyro stabiliiation methods are investigated to address susceptibility of the compass to magnetic interference.
The need to successfully navigate in an underwater environment is rapidly becoming an important concern in the 1990's. This paper presents the development of an integrated navigation system for autonomous underwater vehicles (AUV) using GPS, INS and sonar. This paper discusses the existing problems with sub-sea navigation, the motivation for an integrated system, the mathematical derivation for an integrated GPS/INS/sonar system, and the results obtained from extensive testing.
Enhancement of the inertial navigation system for the Morpheus autonomous underwater vehicles
IEEE Journal of Oceanic Engineering, 2001
This paper presents the design and development of an enhanced inertial navigation system that is to be integrated into the Morpheus autonomous underwater vehicle at Florida Atlantic University. The inertial measurement unit is based on the off-the-shelf Honeywell HG1700-AG25 3-axis ring-laser gyros and three-axis accelerometers and is aided with ground speed measurements obtained using an RDI Doppler-velocity-log sonar. An extended Kalman filter has been developed, which fuses together asynchronously the inertial and Doppler data, as well as the differential global positioning system positional fixes whenever they are available. A complementary filter was implemented to provide a much smoother and stable attitude estimate. Thus far, preliminary study has been made on characterizing the inertial navigation system-based navigation system performance, and the corresponding results and analyzes are provided in this paper.
Inertial Sensor Self-Calibration Module for Autonomous Underwater Vehicle Navigation
Evolution in Electrical and Electronic Engineering, 2021
The Autonomous Underwater Vehicles (AUV) industry is growing dramatically with the increase in the reliability and technical abilities of these vehicles. The vehicles require autonomous guidance and control system in order to perform underwater tasks. The Inertial Sensor Self-Calibration Navigation module is the important mission module that can be implemented into the navigation target, it permits the vehicle to follow preprogrammed trajectories wherever and whenever required. Without this module, the vehicle will not be able to achieve the desired mission. In this work, the Mission module need to be able to identify the task, detect the target, coordinate the state of AUV (attain desired height and yaw angle) and makes decision on path based on mission time elapsed. To navigate this Autonomous Underwater Vehicle (AUV), the navigation module selects Inertial Navigation System (INS). This navigation system used computers, accelerometers, gyroscopes, and sometimes magnetic sensors to calculate the dead reckoning, orientation and velocity (movement direction and speed) moving objects without external reference requirements. The AUV was able to navigate underwater and track underwater object without the need of operator assistance.
Integration of inertial sensors and GPS system data for underwater navigation
2012
The Inertial Navigation System (INS) is usually employed to determine the position of an underwater vehicles, like Remotely Operated Vehicles (ROV) and, more recently, Autonomous Underwater Vehicle (AUV). The accuracy of the position provided by the INS, which uses accelerometers and gyroscopes, deteriorates with time. An external aiding sources such as the Global Positioning System (GPS) can be employed to reduce the error growth in the INS. The GPS aided INS system provides enhance positioning accuracy of the underwater vehicles compared to that of a stand-alone INS technique. In the paper integration algorithm of inertial sensors (accelerometers and gyroscopes) and GPS system data for underwater navigation is presented. For data integration algorithm External Kalman Filter (EKF) is proposed.
Underwater Navigation System Solution using MEMS-Mobile Sensors during the GPS Outage
Journal of Communications, 2019
These position of Unmanned Surface Vehicle (USV) is very important in most navigation applications. The Global Position System (GPS) can be used for navigation system for most applications on the earth's surface, but its signal is not available underwater and indoor areas. Inertial Navigation System (INS) can be used for navigation system in such environments, but it has errors increase over time. This paper presents a method based on the integrated GPS with MEMS (Micro-Electro Mechanical System) INS mobile sensors to enhance the navigation system of USV and provide a continuous navigation solution during GPS outage. In this study, real-time data from GPS, MEMS-INS mobile sensors are fused and integrated by Kalman Filtering (KF); to estimate and correct errors of navigation system when GPS is available. When GPS becomes outage, the MEMS-INS system can provide acceptable navigation system within a not long of time until the GPS system is available. The performance of navigation system based on GPS/MEMS-INS cell phone is tested to a reference path when GPS is available and during its outage on parts of the path. Index Terms-Global Position System (GPS), Micro-Electro Mechanical System with Inertial Navigation System (MEMS-INS) mobile sensors, Kalman Filtering (KF), experimental test. I. INTRODUCTION On earth surface, Global position system (GPS) is popular navigation system, that developed by United States Department of Defense (DOD). It can provide acceptable position information anywhere when there is direct line of sight to four or more satellites. However, it suffer from signal outage in urban area and underwater, where signals from satellite can be blocked. [1]. In literature, Inertial Navigation System (INS) is a method of navigation, which determines the status of moving vehicle using motion sensors without depending on external source (satellite). States of the vehicle refer to position, velocity, and orientation of the vehicle. INS is used in aircrafts, ships, guided missiles and UAVs [2]. INS is an autonomous system that comprises of threeaxis accelerometers and gyroscopes; placed along the
Recent Advances in Navigation of Underwater Remotely Operated Vehicles
2013
A review of the most significant technical papers related to the navigation of underwater remotely operated vehicles is presented, with special interest in aided inertial navigation. Sensors used for implementation, fusion algorithms and models that describe the navigation systems are presented. From this review, it was concluded that the implementation of an estimator, based on the vehicle kinematic and dynamic models, limits the growth of the estimated error, even in case that the only available information is that provided by an inertial measurement unit.
IEEE Journal of Oceanic Engineering, 2007
This paper presents an integrated navigation system for underwater vehicles to improve the performance of a conventional inertial acoustic navigation system by introducing range measurement. The integrated navigation system is based on a strapdown inertial navigation system (SDINS) accompanying range sensor, Doppler velocity log (DVL), magnetic compass, and depth sensor. Two measurement models of the range sensor are derived and augmented to the inertial acoustic navigation system, respectively. A multirate extended Kalman filter (EKF) is adopted to propagate the error covariance with the inertial sensors, where the filter updates the measurement errors and the error covariance and corrects the system states when the external measurements are available. This paper demonstrates the improvement on the robustness and convergence of the integrated navigation system with range aiding (RA). This paper used experimental data obtained from a rotating arm test with a fish model to simulate the navigational performance. Strong points of the navigation system are the elimination of initial position errors and the robustness on the dropout of acoustic signals. The convergence speed and conditions of the initial error removal are examined with Monte Carlo simulation. In addition, numerical simulations are conducted with the six-degrees-of-freedom (6-DOF) equations of motion of an autonomous underwater vehicle (AUV) in a boustrophedon survey mode to illustrate the effectiveness of the integrated navigation system.
Journal of Field Robotics, 2012
This paper presents a new ultrashort baseline (USBL) tightly coupled integration technique to enhance error estimation in low‐cost strapdown inertial navigation systems (INSs), with application to underwater vehicles. In the proposed strategy, the acoustic array spatial information is directly exploited in an extended Kalman filter (EKF) implemented in a direct feedback structure. Instead of using the USBL position fixes or computed range and elevation/bearing angles to correct the INS error drifts, as in classical loosely coupled strategies, the novel tightly coupled strategy directly embeds in the EKF the round‐trip‐time and time‐difference‐of‐arrival of the acoustic signals arriving at the onboard receivers. The enhanced performance of the proposed filtering technique is evidenced both through extensive numerical simulations and with experimental data obtained in field tests at sea. The tightly coupled filter is also shown to be able to operate closer to theoretical performance l...