Advanced Signal Processing for Position, Navigation and Timing of Autonomous and Cyber-Physical Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 1445

Special Issue Editors

School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK
Interests: position; navigation and timing (PNT); cognitive communications; radar systems; multi-sensor navigation; autonomous systems; multi-sensor fusion; damage diagnostics; vibration NDT; acoustic and ultras
School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK
Interests: autonomous systems; advanced flight controls; human–autonomy interaction; urban air mobility; explainable AI for trustworthy autonomous systems
Special Issues, Collections and Topics in MDPI journals
School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK
Interests: Position, Navigation and Timing (PNT); Digital Signal Processing (DSP); Software Defined Radio (SDR); counter-drone systems; Internet of Things (IoT)

Special Issue Information

Dear Colleagues,

The present-day requirements for high levels of performance, intelligence and robustness in the operation of autonomous and cyber-physical systems often demands that the system have access to accurate, relevant and reliable position and time information through the utilization of new high-performance Position, Navigation and Timing (PNT) technologies. Advanced signal processing techniques play a crucial role in ensuring the quality of PNT information, especially in multi-sensor solutions, thus underpinning improvements in the accuracy, robustness and security of autonomous and cyber-physical systems, while maintaining the cost and complexity of the system at lower levels.

The main challenges of new PNT technologies include quality control and integrity analysis, the detection and correction of errors and failures, as well as its ability to work effectively with large amounts of data for resource-constrained systems. Recent research has focused on improving methods for processing PNT signals and observables, the detection and correction of errors due to sensor imperfections or environmental effects, fusing PNT information, and predicting and assessing its quality.

Multiple advanced signal processing methods, which range from statistical analysis and conventional signal processing to fully AI-driven solutions, have been proposed to solve elements of these problems. However, growing demands for higher levels of quality and reliability in the PNT information, fueled by new emerging applications of autonomous and cyber-physical systems, requires further advances in this field.

To facilitate these advances, in this Special Issue, we welcome review and research papers that present novel and advanced methods for PNT-related Signal Processing, including, but not limited to, the enhancement of the PNT sensor information, such as inertial measurement unit and visual odometry error prediction, and the correction and processing of Signals of Opportunity (SOOP); the detection and mitigation of interferences in GNSS-based solutions (e.g. multipath, jamming and spoofing); sensor and information fusion; integrity monitoring and uncertainty prediction; the quantification of PNT information, and time dissemination and synchronization for autonomous and cyber-physical systems.

Dr. Ivan Petrunin
Prof. Dr. Gokhan Inalhan
Dr. Zhengjia Xu
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

  • signal processing
  • sensors
  • sensor fusion
  • autonomous systems
  • AI
  • machine learning
  • GNSS
  • PNT
  • SOOP

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

15 pages, 6365 KiB  
Article
Adaptive Satellite Navigation Anti-Interference Algorithm Based on Inverse Cosine Function
by Pingping Qu, Zibo Yuan, Ershen Wang, Song Xu and Tianfeng Liu
Electronics 2023, 12(21), 4437; https://doi.org/10.3390/electronics12214437 - 28 Oct 2023
Viewed by 840
Abstract
Contrasting the dilemma that the traditional time-domain least mean square (LMS) algorithm in the existing satellite navigation receiver anti-interference system cannot satisfy the convergence time is short and maintain a low level of steady-state error at the same time, an inverse cosine variable [...] Read more.
Contrasting the dilemma that the traditional time-domain least mean square (LMS) algorithm in the existing satellite navigation receiver anti-interference system cannot satisfy the convergence time is short and maintain a low level of steady-state error at the same time, an inverse cosine variable step size LMS algorithm (ICVS-LMS) is proposed. To begin with, the LMS algorithm, with a fixed step size focuses on its effectiveness in attenuating and suppressing interference signals, is analyzed, and then the proposed ICVS-LMS algorithm is analyzed. In conclusion, both the ICVS-LMS algorithm and the traditional algorithm are simulated and compared in terms of their effectiveness in suppressing interference in satellite navigation signals. The experimental results demonstrate that the improved algorithm significantly reduces convergence time while maintaining a small steady-state error. The improved algorithm demonstrates high robustness and an obvious suppression effect on interference signals. The anti-interference performance is 8.41–12.22% higher than that of the proposed algorithm. Full article
Show Figures

Figure 1

Back to TopTop