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State-of-the-Art Navigation, Control Science and Engineering in Celebrating the 70th...
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State-of-the-Art Navigation, Control Science and Engineering in Celebrating the 70th Anniversary of Harbin Engineering University

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 6791

Special Issue Editors

Prof. Dr. Liang Li

E-Mail Website
Guest Editor
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Interests: GNSS-based high-precision navigation
Prof. Dr. Lanyong Zhang

E-Mail Website
Guest Editor
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Interests: intelligent control theory; multi-agent control

Special Issue Information

Dear Colleagues,

High-precision navigation and control technologies have been widely and deeply utilized in the fields of automatic applications—for instance, automatic transportation, automated landing, autonomous departing and berthing, in which the utilization of integrated navigation and intelligent control for the required performance of safety-of-life applications is a hot topic. 2023 marks the 70th anniversary of Harbin Engineering University. Within the university, the College of Intelligent Systems Science and Engineering, also known as the College of Automation prior to 2019, has top-class navigation and control discipline in China and excellent researchers in the field of shipborne navigational and control-related applications. The purpose of this session is to present and share new ideas and achievements in high-precision navigation and intelligent control in multiple automatic applications with relevant experts, scholars and engineers around the world, with a secondary purpose of to celebrating the 70th anniversary of Harbin Engineering University. The topics of this session include, but are not limited to:

(1) Classic GNSS/INS-based high-precision navigation and positioning modelling; multi-GNSS navigation and positioning modelling; GNSS/INS, GNSS/MEMS integrated navigation modelling; GNSS/LiDAR/vision SLAM integrated navigation modelling and filtering algorithm.

(2) Integrity monitoring for multi-sources integrated navigation system; receiver autonomous integrity monitoring (RAIM); aircraft autonomous integrity monitoring (AAIM); advanced RAIM; space-based augmentation system (SBAS); ground-based augmentation system (GBAS).

(3) The state-of-the-art unmanned navigational applications and new trends of research; automatic transportation; automated landing; autonomous departing and berthing; joint precision approach and landing system (JPALS).

(4) Interactive intelligent technologies; manned–unmanned cooperation and coordination; 

(5) Multi-agent reinforcement learning and its applications; intelligent perception and navigation for unmanned systems.

(6) Intelligent perception and decision making in unmanned systems; autonomous planning and intelligent control of unmanned systems; cooperative control of heterogeneous unmanned systems; interactive control of manned/unmanned systems; intelligent control of unmanned cluster systems; multi-agent reinforcement learning and its applications.

Prof. Dr. Liang Li
Prof. Dr. Lanyong Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • GNSS
  • INS
  • SLAM
  • high-precision navigation
  • intelligent control
  • autonomous planning
  • unmanned systems

Published Papers (4 papers)

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17 pages, 20245 KiB  
Article
A Lightweight Model for Real-Time Monitoring of Ships
by Bowen Xing, Wei Wang, Jingyi Qian, Chengwu Pan and Qibo Le
Electronics 2023, 12(18), 3804; https://doi.org/10.3390/electronics12183804 - 8 Sep 2023
Cited by 6 | Viewed by 2119
Abstract
Real-time monitoring of ships is crucial for inland navigation management. Under complex conditions, it is difficult to balance accuracy, real-time performance, and practicality in ship detection and tracking. We propose a lightweight model, YOLOv8-FAS, to address this issue for real-time ship detection and [...] Read more.
Real-time monitoring of ships is crucial for inland navigation management. Under complex conditions, it is difficult to balance accuracy, real-time performance, and practicality in ship detection and tracking. We propose a lightweight model, YOLOv8-FAS, to address this issue for real-time ship detection and tracking. First, FasterNet and the attention mechanism are integrated and introduced to achieve feature extraction simply and efficiently. Second, the lightweight GSConv convolution method and a one-shot aggregation module are introduced to construct an efficient network neck to enhance feature extraction and fusion. Furthermore, the loss function is improved based on ship characteristics to make the model more suitable for ship datasets. Finally, the advanced Bytetrack tracke is added to achieve the real-time detection and tracking of ship targets. Compared to the YOLOv8 model, YOLOv8-FAS reduces computational complexity by 0.8×109 terms of FLOPs and reduces model parameters by 20%, resulting in only 2.4×106 parameters. The mAP-0.5 is improved by 0.9%, reaching 98.50%, and the real-time object tracking precision of the model surpasses 88%. The YOLOv8-FAS model combines light weight with high precision, and can accurately perform ship detection and tracking tasks in real time. Moreover, it is suitable for deployment on hardware resource-limited devices such as unmanned surface ships. Full article
(This article belongs to the Special Issue State-of-the-Art Navigation, Control Science and Engineering in Celebrating the 70th Anniversary of Harbin Engineering University)
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18 pages, 6466 KiB  
Article
An Image Enhancement Method for Side-Scan Sonar Images Based on Multi-Stage Repairing Image Fusion
by Ziwei Lu, Tongwei Zhu, Huiyu Zhou, Lanyong Zhang and Chun Jia
Electronics 2023, 12(17), 3553; https://doi.org/10.3390/electronics12173553 - 22 Aug 2023
Cited by 3 | Viewed by 1516
Abstract
The noise interference of side-scan sonar images is stronger than that of optical images, and the gray level is uneven. To solve this problem, we propose a side-scan sonar image enhancement method based on multi-stage repairing image fusion. Firstly, to remove the environmental [...] Read more.
The noise interference of side-scan sonar images is stronger than that of optical images, and the gray level is uneven. To solve this problem, we propose a side-scan sonar image enhancement method based on multi-stage repairing image fusion. Firstly, to remove the environmental noise in the sonar image, we perform adaptive Gaussian smoothing on the original image and the weighted average grayscale image. Then, the smoothed images are all processed through multi-stage image repair. The multi-stage repair network consists of three stages. The first two stages consist of a novel encoder–decoder architecture to extract multi-scale contextual features, and the third stage uses a network based on the resolution of the original inputs to generate spatially accurate outputs. Each phase is not a simple stack. Between each phase, the supervised attention module (SAM) improves the repair results of the previous phase and passes them to the next phase. At the same time, the multi-scale cross-stage feature fusion mechanism (MCFF) is used to complete the information lost in the repair process. Finally, to correct the gray level, we propose a pixel-weighted fusion method based on the unsupervised color correction method (UCM), which performs weighted pixel fusion between the RGB image processed by the UCM algorithm and the gray-level image. Compared with the algorithm with the SOTA methods on datasets, our method shows that the peak signal-to-noise ratio (PSNR) is increased by 26.58%, the structural similarity (SSIM) is increased by 0.68%, and the mean square error (MSE) is decreased by 65.02% on average. In addition, the processed image is balanced in terms of image chromaticity, image contrast, and saturation, and the grayscale is balanced to match human visual perception. Full article
(This article belongs to the Special Issue State-of-the-Art Navigation, Control Science and Engineering in Celebrating the 70th Anniversary of Harbin Engineering University)
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20 pages, 5197 KiB  
Article
Trajectory Tracking Control of Unmanned Surface Vehicles Based on a Fixed-Time Disturbance Observer
by Xiaosong Li, Xiaochen Li, Dianguang Ma and Xianwei Kong
Electronics 2023, 12(13), 2896; https://doi.org/10.3390/electronics12132896 - 30 Jun 2023
Cited by 2 | Viewed by 1346
Abstract
In ocean environments with unknown complex disturbances, the control accuracy for an unmanned surface vehicle (USV) is severely challenged with an increase in task complexity. As the foundation for executing complex tasks, it is particularly important to control a USV to navigate along [...] Read more.
In ocean environments with unknown complex disturbances, the control accuracy for an unmanned surface vehicle (USV) is severely challenged with an increase in task complexity. As the foundation for executing complex tasks, it is particularly important to control a USV to navigate along a safe trajectory that has been set. In order to effectively handle the trajectory tracking problem, an innovative USV tracking control strategy with high accuracy is proposed by combining the integral sliding-mode and disturbance observer technologies, and these are effectively extended to a scenario with the cooperative trajectory tracking of multiple USVs in this study. Specifically, unknown disturbances are treated as lumped uncertainties, and a novel fixed-time stable-convergence disturbance observer (FT-DO) is proposed to effectively observe and approximate the lumped uncertainties. Then, in order to quickly reach and steadily navigate along the desired trajectory, an effective fixed-time stable-convergence fast integral sliding mode is modified, and on this basis, an accurate trajectory tracking controller (FTFISM-TTC) for a single USV and a cooperative trajectory tracking controller for multiple USVs are meaningfully proposed. Finally, the stability of FT-DO and FTFISM-TTC was rigorously proven by using the Lyapunov approach, and a comprehensive simulation of current advanced tracking control methods was conducted by using Matlab, which proved the reliability of the proposed trajectory tracking control strategy and further eliminated the impact of the initial state on the tracking accuracy. Full article
(This article belongs to the Special Issue State-of-the-Art Navigation, Control Science and Engineering in Celebrating the 70th Anniversary of Harbin Engineering University)
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22 pages, 4797 KiB  
Article
A Polar Moving Base Alignment Based on Backtracking Scheme
by Jianhua Cheng, Jiaxin Liu, Yu Wang and Jing Cai
Electronics 2023, 12(9), 2037; https://doi.org/10.3390/electronics12092037 - 27 Apr 2023
Viewed by 981
Abstract
In the polar region, the gravity vector and Earth’s rotation vector tend to be in the same direction, leading to a slower convergence speed and longer alignment time of the moving base alignment. When the alignment time is short, the alignment cannot converge, [...] Read more.
In the polar region, the gravity vector and Earth’s rotation vector tend to be in the same direction, leading to a slower convergence speed and longer alignment time of the moving base alignment. When the alignment time is short, the alignment cannot converge, resulting in low azimuth accuracy. To address this issue, we propose a polar moving base alignment method based on a backtracking scheme. Notably, this work first derives a polar coarse alignment method with the inertial frame based on the transverse Earth model. On this basis, we designed a polar coarse alignment method based on a backtracking scheme and optimized the data storage scheme. Then, a backward navigation algorithm based on the transverse inertial navigation mechanical arrangement scheme was derived, and a polar fine alignment method based on a backtracking scheme was designed. Semi-physical simulation experiments showed that the alignment algorithm based on a backtracking scheme could converge in the 180 s with high alignment accuracy, which is 70% faster than the current polar moving base alignment method. Full article
(This article belongs to the Special Issue State-of-the-Art Navigation, Control Science and Engineering in Celebrating the 70th Anniversary of Harbin Engineering University)
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