Astronomical Vessel Position Determination Utilizing the Optical Super Wide Angle Lens Camera

Celestial navigation is an important type of autonomous navigation technology which could be used as an alternative to Global Navigation Satellite Systems (GNSS) when a vessel is at sea. After several centuries of development, a variety of astronomical vessel position (AVP) determination methods have been invented, but the basic concepts of these methods are all based on angular observations with a device such as a sextant, which has disadvantages including low accuracy, manual operation, and a limited period of observation. This paper proposes a new method that utilises a fisheye camera to image the celestial bodies and horizon simultaneously. Then, we calculate the obliquity of the fisheye camera's principal optical axis according to the image coordinates of the horizon. Next, we calculate the altitude of the celestial bodies according to the image coordinates of the celestial bodies and the obliquity. Finally, the AVP is determined by the altitudes according to the robust estimation method. Experimental results indicate that this method not only could realize automation and miniaturization of the AVP determination system, but could also greatly improve the efficiency of celestial navigation.

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Practical Modeling of GNSS for Autonomous Vehicles in Urban Environments

Sensors ◽

10.3390/s19194236 ◽

2019 ◽

Vol 19 (19) ◽

pp. 4236

Author(s):

Woosik Lee ◽

Hyojoo Cho ◽

Seungho Hyeong ◽

Woojin Chung

Keyword(s):

Motion Estimation ◽

Autonomous Vehicles ◽

Autonomous Navigation ◽

Urban Environments ◽

Global Navigation Satellite Systems ◽

Navigation Satellite ◽

Key Technology ◽

Satellite Systems ◽

Agricultural Robots ◽

Global Navigation Satellite

Autonomous navigation technology is used in various applications, such as agricultural robots and autonomous vehicles. The key technology for autonomous navigation is ego-motion estimation, which uses various sensors. Wheel encoders and global navigation satellite systems (GNSSs) are widely used in localization for autonomous vehicles, and there are a few quantitative strategies for handling the information obtained through their sensors. In many cases, the modeling of uncertainty and sensor fusion depends on the experience of the researchers. In this study, we address the problem of quantitatively modeling uncertainty in the accumulated GNSS and in wheel encoder data accumulated in anonymous urban environments, collected using vehicles. We also address the problem of utilizing that data in ego-motion estimation. There are seven factors that determine the magnitude of the uncertainty of a GNSS sensor. Because it is impossible to measure each of these factors, in this study, the uncertainty of the GNSS sensor is expressed through three variables, and the exact uncertainty is calculated. Using the proposed method, the uncertainty of the sensor is quantitatively modeled and robust localization is performed in a real environment. The approach is validated through experiments in urban environments.

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Investigation of Alternative Parameters for Immunity-based UAV Navigation in GNSS-denied Environment

Unmanned Systems ◽

10.1142/s2301385021500059 ◽

2020 ◽

Vol 09 (01) ◽

pp. 65-72

Author(s):

Mohanad Alnuaimi ◽

Mario G. Perhinschi

Keyword(s):

Autonomous Navigation ◽

Dead Reckoning ◽

Global Navigation Satellite Systems ◽

External Information ◽

Artificial Immune ◽

Tracking Errors ◽

Satellite Systems ◽

Vehicle Position ◽

Global Navigation Satellite ◽

Uav Navigation

This paper is focused on analyzing effects of several significant parameters on the performance of an immunity-inspired methodology for autonomous navigation of unmanned air vehicles when measurements from global navigation satellite systems (GNSS) or similar current sources, including external information of opportunity, are not available. An artificial immune system (AIS) provides corrections to a dead reckoning algorithm for adequate estimates of vehicle position and velocity. Parameter effects are assessed and analyzed through simulation in terms of trajectory tracking errors during autonomous flight.

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Application of Robust Estimation Method for Establishing 3D Combined Terrestrial and GNSS Network: A case of a Quarry in Lang Son, Vietnam

Inżynieria Mineralna ◽

10.29227/im-2020-02-09 ◽

2020 ◽

Vol 1 (2) ◽

Author(s):

Luu ANH TUAN ◽

Hoang NGOC HA ◽

La PHU HIEN ◽

Pham VAN CHUNG

Keyword(s):

Data Processing ◽

Robust Estimation ◽

Weighting Function ◽

Estimation Method ◽

Geodetic Network ◽

Global Navigation Satellite Systems ◽

Satellite Systems ◽

Gnss Network ◽

Global Navigation Satellite ◽

Mine Surveying

Recently, in Vietnam, the detection of geodetic measurements that contain rough errors as well as such data processing method has been considered as a key step in geodetic data processing, especially for large geodetic networks with many different types of measurements like 3D - Global Navigation Satellite Systems (GNSS) network. On the other hand, mines in Vietnam often have complex terrains, so it is necessary to apply modern and flexible surveying methods in combination with ground and space measurements to build 3D coordinates control networks for management and exploitation to ensure sustainable development. Therefore, this research developed a Robust estimation method based on empirical weighting function for establishing 3D geodetic network combining terrestrial observation and GNSS vectors. The experiment on processing the combined network in Lang Son limestone quarry, Vietnam showed that the proposed method could be an effective solution for processing 3D terrestrial – GNSS geodetic network for mine surveying in Vietnam.

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Problems of creating autonomous navigation systems on geophysical fields

E3S Web of Conferences ◽

10.1051/e3sconf/202131003008 ◽

2021 ◽

Vol 310 ◽

pp. 03008

Author(s):

Vyacheslav Fateev ◽

Dmitrii Bobrov ◽

Murat Murzabekov ◽

Ruslan Davlatov

Keyword(s):

Autonomous Navigation ◽

Global Navigation Satellite Systems ◽

Navigation Systems ◽

Integrated Navigation ◽

Geophysical Fields ◽

Satellite Systems ◽

Integrated Navigation System ◽

New Methods ◽

The Stability ◽

Global Navigation Satellite

Global navigation satellite systems, which provide high accuracy of navigation, in certain conditions (in tunnels, in closed rooms, in conditions of interference, etc.) have restrictions on their use. In this regard, in order to ensure “seamless” navigation in any conditions of the situation, it becomes necessary to develop new methods and means to increase the stability of navigation definitions. The article is devoted to the consideration of the problems of creating an integrated navigation system using measurements of the parameters of the Earth’s gravitational and magnetic fields. Requirements for meters of parameters of geophysical fields and navigation charts are considered, a number of new navigation meters, new methods and means of preparing navigation charts are proposed. The ways of development of relativistic geodesy and the possibility of using the achievements of gravitational-wave astronomy in gravimetry are considered.

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GNSS/LiDAR-Based Navigation of an Aerial Robot in Sparse Forests

Sensors ◽

10.3390/s19194061 ◽

2019 ◽

Vol 19 (19) ◽

pp. 4061 ◽

Cited By ~ 3

Author(s):

Antonio C. B. Chiella ◽

Henrique N. Machado ◽

Bruno O. S. Teixeira ◽

Guilherme A. S. Pereira

Keyword(s):

Autonomous Navigation ◽

Unscented Kalman Filter ◽

Unmanned Vehicles ◽

Global Navigation Satellite Systems ◽

Fusion Algorithm ◽

Forest Environment ◽

Satellite Systems ◽

Aerial Robot ◽

Robust Adaptive ◽

Global Navigation Satellite

Autonomous navigation of unmanned vehicles in forests is a challenging task. In such environments, due to the canopies of the trees, information from Global Navigation Satellite Systems (GNSS) can be degraded or even unavailable. Also, because of the large number of obstacles, a previous detailed map of the environment is not practical. In this paper, we solve the complete navigation problem of an aerial robot in a sparse forest, where there is enough space for the flight and the GNSS signals can be sporadically detected. For localization, we propose a state estimator that merges information from GNSS, Attitude and Heading Reference Systems (AHRS), and odometry based on Light Detection and Ranging (LiDAR) sensors. In our LiDAR-based odometry solution, the trunks of the trees are used in a feature-based scan matching algorithm to estimate the relative movement of the vehicle. Our method employs a robust adaptive fusion algorithm based on the unscented Kalman filter. For motion control, we adopt a strategy that integrates a vector field, used to impose the main direction of the movement for the robot, with an optimal probabilistic planner, which is responsible for obstacle avoidance. Experiments with a quadrotor equipped with a planar LiDAR in an actual forest environment is used to illustrate the effectiveness of our approach.

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Accuracy Benchmark of Galileo and EGNOS for Inland Waterways

10.24868/issn.2631-8741.2020.009 ◽

2020 ◽

Author(s):

G Yayla ◽

S Van Baelen ◽

G Peeters

Keyword(s):

Sensor Fusion ◽

Autonomous Navigation ◽

Global Navigation Satellite Systems ◽

Navigation Systems ◽

Inland Waterways ◽

Satellite Systems ◽

Coordinate Measurement ◽

Measurement Units ◽

Satellite Navigation Systems ◽

Global Navigation Satellite

While Global Navigation Satellite Systems (GNSS) serve as a fundamental positioning technology for autonomous ships in Inland Waterways (IWW), in order to compensate for unexpected signal outages from constellations due to structures such as bridges and high buildings, it is not uncommon to use a sensor fusion setup with GNSS and Inertial Measurement Units (IMU)/Inertial Navigation Systems (INS). However, the accuracy of this fusion relies on the accuracy of the main localization technology itself. In Europe, Galileo and the European Geostationary Navigation Overlay Service (EGNOS) are two satellite navigation systems under civil control and they provide European users with independent access to a reliable positioning satellite signal, claiming better accuracy than what is offered by other accessible systems. Therefore, considering the potential utilization of these systems for autonomous navigation, in this paper, we discuss the results of a case study for benchmarking the accuracy of Galileo and EGNOS in IWW. We used a Coordinate Measurement Machine (CMM) and a sub-cm Real-Time Kinematic (RTK) service which is available in Flanders to quantify the benchmark reference. The results with and without sensor fusion show that Galileo has a better horizontal accuracy profile than standalone Global Positioning System (GPS), and its augmentation with EGNOS is likely to provide European IWW users more accurate positioning levels in the future.

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A Differential Measurement Method for Solving the Ephemeris Observability Issues in Autonomous Navigation

Journal of Navigation ◽

10.1017/s0373463315000417 ◽

2015 ◽

Vol 68 (6) ◽

pp. 1133-1140 ◽

Cited By ~ 2

Author(s):

Shilong Liao ◽

Zhaoxiang Qi ◽

Zhenghong Tang

Keyword(s):

Autonomous Navigation ◽

Measurement Method ◽

Global Navigation Satellite Systems ◽

Differential Measurement ◽

Positioning Systems ◽

Satellite Systems ◽

Navigation Function ◽

Satellite Links ◽

Global Navigation Satellite ◽

First Time

The autonomous navigation of navigation and positioning systems such as the Global Positioning System (GPS) and other Global Navigation Satellite Systems (GNSS) was motivated to improve accuracy and survivability of the navigation function for 180 days without ground contact. These improvements are accomplished by establishing inter-satellite links in the constellation for pseudo-range observations and communications between satellites. But observability issues arise for both ephemeris and clock since the pseudo-range describes only the relative distance between satellites. A differential measurement method is proposed to measure the rotation of the constellation as a whole for the first time. The feasibility of the proposed method is verified by simulations.

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