Current Issue : July-September
Volume : 2022
Issue Number : 3
Articles : 5 Articles
Based on the theory of atmospheric refraction, combined with the atmospheric parameter data of NCEP (National Centers for
environmental prediction), the Fourier interpolation fitting algorithm is used to model and analyze the parameters affecting
atmospheric refraction on a global scale. The atmospheric temperature and density model with space-time variation is constructed.
The spacecraft state equation and the measurement equation with the starlight apparent height as the observation
quantity are established. Moreover, the Unscented Kalman filter is applied to the indirect sensitive horizon autonomous astronomical
navigation of starlight refraction. The relative error of fitting the measured data with the spatiotemporal atmospheric
temperature model established in this paper is less than 2%.The position estimation error of the navigation system is 94 m, and the
velocity estimation error is 0.16 m/s. Compared with the traditional model, the navigation and positioning considering complex
atmospheric changes are more accurate....
An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of
the Informed-RRT∗ algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning
procedure. When a new node is obtained, it will be judged whether it can directly reach the target point. Second, the search scope
of the potential optimal parent node becomes the constructed path, instead of the node tree, which reduces the number of nodes to
be searched and improves the navigation efficiency. Combined with the dynamic window approach (DWA), the improved
algorithm is utilized to simulate the autonomous navigation process of the robot based on the Robot Operating System (ROS)
platform. Thesimulation results show that compared with the original algorithm, the length of the global path is reduced by 5.15%,
and the time of planning path and autonomous navigation is shortened by 78.34% and 21.67%, respectively....
The development of autonomous ships has begun. Artificial intelligence (AI) is expected
to be partially responsible for navigation; nevertheless, the importance of human intervention is
higher than ever. Human intervention in the control of an autonomous ship via the remote operator
requires navigation proficiency. The education method for the remote operators that is presently
considered is simulation training. However, the simulation training does not take long enough time
for enabling trainees to develop their navigation proficiency equivalent to that of conventional ships
navigators. In addition, the simulation training should contain various navigation scenarios to train
the trainee properly. Therefore, this paper suggests the methods to generate the massive and practical
navigation scenarios by extracting navigation elements’ distribution from actual ship trajectory
data and applying them to the permutation of navigation elements. The results demonstrated the
advantages of the proposed methods by comparing the sample navigation scenario and an example
of an impractical navigation scenario. In conclusion, it is expected that the massive generation
of practical navigation scenarios using the proposed permutation model will positively affect the
simulation training of the maritime autonomous surface ship remote operators....
This study addresses the problem of controlling series active power filters for voltage sag compensation. Indeed, we can control
this kind of filter to generate a voltage series that compensates the grid voltage sag in order to protect the sensitive loads
against this perturbation. This study is aimed at seeking a control strategy that meets the main control objective, which is the
compensation of grid voltage sags and this by considering the following technical constraints: (i) the nonlinearity of the system
dynamics, (ii) the high dimension of the system model, and (iii) the inaccessibility of some system variables to measurements.
To meet the main control objective, we propose a nonlinear controller that is designed based on the system nonlinear model,
using the backstepping technique. This controller involves a nonlinear regulator and a grid observer. The former copes with
the compensation issue. The observer provides online the grid voltage estimations. In addition to a theoretical analysis of the
control system, the performances of the proposed controller are evaluated by simulation using MATLAB/Simulink....
A Pseudo-satellite system that transmits signals similar to GNSS can provide positioning
services in places where GNSS signals are not captured and have enormous potential for indoor
machine system and airports. Different paths of the device have different carrier phase initial solution
positioning accuracy. Existing methods rely on measuring instruments or use many coordinate points
for solving ambiguity resolution (AR), which creates inconvenience for real-time ground positioning.
This study aims to find a new on-the-fly (OTF) method to achieve high accuracy and convenient
positioning. A new method is proposed based on a two-difference observation model for groundbased
high-precision point positioning. We used an adaptive particle swarm algorithm to solve the
initial solution, followed by a nonlinear least-squares method to optimize the localization solution. It
is free of priori information or measuring instruments. We designed several different paths, such as
circular trajectory and square trajectory, to study the positioning accuracy of the solution. Simulation
experiments with different trajectories showed that geometric changes significantly impact solutions.
In addition, it does not require precise time synchronization of the base stations, making the whole
system much easier to deploy. We built a real-world pseudo-satellite system and used a multi-sensor
crewless vehicle as a receiver. Real-world experiments showed that our approach could achieve
centimeter-level positioning accuracy in applications....
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