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Aerospace
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Flight Data
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Flight Data

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Aeronautics".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 8939

Special Issue Editor

Prof. Dr. Paweł Rzucidło

E-Mail Website
Guest Editor
Department of Avionics and Control Systems, Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, al. Powstanców Warszawy 8, 35-959 Rzeszow, Poland
Interests: avionics; measurement systems; data bus; CAN; flight data recorders; monitoring; data analysis; wavelet; fourier transform; STFT; pilot-induced oscillations; unmanned air vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern avionics systems enable the registration of hundreds of flight parameters. State-of-the-art on-board research systems record data at frequencies of several kHz or even more. Additionally, the use of data fusion and virtual sensor algorithms enables the enrichment of already powerful datasets. In practice, the use of big data analysis techniques can provide new information on the normal operation of aircraft as well as many benefits related to flight testing.

This Special Issue of Aerospace on “Flight Data” focuses on the broad topic of aircraft and spacecraft parameter monitoring, recording, processing, visualization, and analysis. Theoretical and empirical articles related to the data acquisition and processing by various systems installed on board airplanes, helicopters, sailplanes, balloons, stratospheric probes, and spacecraft are welcome.

The scope of this Special Issue includes (but is not limited to):

  • Flight data recorders;
  • Integrated avionics and data buses;
  • Measurement systems;
  • Signal processing;
  • Data acquisition;
  • Virtual sensors;
  • Data fusion;
  • Big data analysis;
  • Telemetry.

Papers from academics as well as applied researchers are encouraged for this Special Issue.

Prof. Dr. Paweł Rzucidło
Guest Editor

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. Aerospace is an international peer-reviewed open access monthly 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.

Published Papers (2 papers)

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Research

19 pages, 8056 KiB  
Article
The PAPI Lights-Based Vision System for Aircraft Automatic Control during Approach and Landing
by Dariusz Nowak, Grzegorz Kopecki, Damian Kordos and Tomasz Rogalski
Aerospace 2022, 9(6), 285; https://doi.org/10.3390/aerospace9060285 - 25 May 2022
Cited by 4 | Viewed by 5641
Abstract
The paper presents the concept of a component of an aircraft’s automatic flight control system, controlling the airplane when in longitudinal motion (i.e., pitch angle, sink rate, airspeed channels) during automatic landing, from a final approach until a touchdown. It is composed of [...] Read more.
The paper presents the concept of a component of an aircraft’s automatic flight control system, controlling the airplane when in longitudinal motion (i.e., pitch angle, sink rate, airspeed channels) during automatic landing, from a final approach until a touchdown. It is composed of two key parts: a vision system and an automatic landing system. The first part exploits dedicated image-processing algorithms to identify the number of red and white PAPI lights appearing on an onboard video camera. Its output data—information about an aircraft’s position on a vertical profile of a landing trajectory—is used as one of the crucial inputs to the automatic landing system (the second part), which uses them to control the landing. The control algorithms implemented by the automatic landing system are based on the fuzzy logic expert system and were developed to imitate the pilot’s control actions during landing an aircraft. These two parts were teamed together as a component of a laboratory rig, first as pure software algorithms only, then as real hardware modules with downloaded algorithms. In two test campaigns (software in the loop and hardware in the loop) they controlled an aircraft model in a simulation environment. Selected results, presenting both control efficiency and flight precision, are given in the final section of the paper. Full article
(This article belongs to the Special Issue Flight Data)
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20 pages, 2641 KiB  
Article
Joint State and Parameter Estimation for Hypersonic Glide Vehicles Based on Moving Horizon Estimation via Carleman Linearization
by Yudong Hu, Changsheng Gao and Wuxing Jing
Aerospace 2022, 9(4), 217; https://doi.org/10.3390/aerospace9040217 - 14 Apr 2022
Cited by 3 | Viewed by 1844
Abstract
Aimed at joint state and parameter estimation problems in hypersonic glide vehicle defense, a novel moving horizon estimation algorithm via Carleman linearization is developed in this paper. First, the maneuver characteristic parameters that reflect the target maneuver law are extended into the state [...] Read more.
Aimed at joint state and parameter estimation problems in hypersonic glide vehicle defense, a novel moving horizon estimation algorithm via Carleman linearization is developed in this paper. First, the maneuver characteristic parameters that reflect the target maneuver law are extended into the state vector, and a dynamic tracking model applicable to various hypersonic glide vehicles is constructed. To improve the estimation accuracy, constraints such as path and parameter change amplitude constraints in flight are taken into account, and the estimation problem is transformed into a nonlinear constrained optimal estimation problem. Then, to solve the problem of high time cost for solving a nonlinear constrained optimal estimation problem, in the framework of moving horizon estimation, nonlinear constrained optimization problems are transformed into bilinear constrained optimization problems by linearizing the nonlinear system via Carleman linearization. For ensuring the consistency of the linearized system with the original nonlinear system, the linearized model is continuously updated as the window slides forward. Moreover, a CKF-based arrival cost update algorithm is also provided to improve the estimation accuracy. Simulation results demonstrate that the proposed joint state and parameter estimation algorithm greatly improves the estimation accuracy while reducing the time cost significantly. Full article
(This article belongs to the Special Issue Flight Data)
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