1. A novel system for quasi-continuous THz signal transmission and receptionAndrej Sarjaš, Blaž Pongrac, Dušan Gleich, 2022, original scientific article Abstract: This paper presents a novel system for generating and receiving quasi-continuous (QC)
TeraHertz (THz) waves. A system design and theoretical foundation for QC-THz signal generation
are presented. The proposed QC-THz system consists of commercially available photo-conductive
antennas used for transmission and reception of THz waves and a custom-designed QC optical
signal generator, which is based on a fast optical frequency sweep of a single telecom distributedfeedback laser diode and unbalanced optical fiber Michelson interferometer used for a high-frequency
modulation. The theoretical model for the proposed system is presented and experimentally evaluated. The experimental results were compared to the state-of-the-art continuous-wave THz system. The comparison between the continuous-wave THz system and the proposed QC-THz system
showed the ability to transmit and receive QC-THz waves up to 300 GHz. The upper-frequency limit
is bounded by the length of the used Michelson interferometer. The presented design of THz signal
generation has a potential for industrial application because it is cost-efficient and can be built using
commercially available components.
Keywords: quasi-continuous, terahertz, photoconductive antenna, wave emittance, wave detection
Published in DKUM: 01.04.2025; Views: 0; Downloads: 2
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2. Toward embedded system resources relaxation based on the event-triggered feedback control approachAndrej Sarjaš, Dušan Gleich, 2022, original scientific article Abstract: The paper describes an event-triggered nonlinear feedback controller design. Event triggering is a real-time controller implementation technique which reduces embedded system utilization
and relaxes task scheduling of the real-time system. In contrast to classic time implementation
techniques, the event-triggered execution is validated regarding the introduced triggering policy.
The triggering rule is a boundary, where the last task value is preserved until the rule is violated.
In the given paper, two different event-triggered strategies are designed for the class of dynamic
systems with integral behavior. Both methods are based on sliding mode controller design, where the
triggering rule of the first design involves only a partial state vector, which is a direct consequence of
the triggering rule derivation throughout the Lyapunov stability analysis. In the second approach,
the sliding mode controller is designed upon prior stabilized systems with the additional term, which
enables derivation of the triggering rule based on the whole state vector. The second approach offers
better closed-loop performance and higher relaxation of the system utilization. The selection of
triggering boundary is related closely to the derived minimal inter-event time, which impacts the
computational burden of the real-time system and closed-loop performance directly. The derived
controllers are compared with the classic sample and hold implementation techniques. The real-time
results are presented, and system performances are confirmed regarding embedded system task
relaxation, lowering the computational intensity and preserving closed-loop dynamics.
Keywords: sliding mode control, event-triggered control, lowering computational intensity, task relaxation
Published in DKUM: 28.03.2025; Views: 0; Downloads: 7
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3. Modelling and analysis of the ionospheric impact on observables in low earth orbit monitoring systems for gnss : master's thesisDominik Zdelar, 2024, master's thesis Abstract: Ionospheric errors in the ionosphere are a major source of signal delays in Global Navigation Satellite System (GNSS) propagation, particularly in the 250-400 km region of the ionosphere, where high electron density occurs. This thesis develops a model to estimate electron density at 300 km, focusing on improving predictions of ionospheric delays in signal paths between Medium Earth Orbit (MEO) and Low Earth Orbit (LEO) satellites. The model utilizes simulated orbits on specific dates to account for varying solar flux strengths and compares results with data from the Swarm mission. The findings aim to enhance GNSS delay estimation and navigation accuracy regarding ionospheric errors.
Keywords: ionosphere, GNSS, model, MEO, LEO
Published in DKUM: 06.02.2025; Views: 0; Downloads: 21
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4. Comparative Study of GPR Acquisition Methods for Shallow Buried Object DetectionPrimož Smogavec, Blaž Pongrac, Andrej Sarjaš, Venceslav Kafedziski, Nabojša Dončov, Dušan Gleich, 2024, original scientific article Abstract: This paper investigates the use of ground-penetrating radar (GPR) technology for detecting shallow buried objects, utilizing an air-coupled stepped frequency continuous wave (SFCW) radar system that operates within a 2 GHz bandwidth starting at 500 MHz. Different GPR data acquisition methods for air-coupled systems are compared, specifically down-looking, side-looking, and circular acquisition strategies, employing the back projection algorithm to provide focusing of the acquired GPR data. Experimental results showed that the GPR can penetrate up to 0.6 m below the surface in a down-looking mode. The developed radar and the back projection focusing algorithm were used to acquire data in the side-looking and circular mode, providing focused images with a resolution of 0.1 m and detecting subsurface objects up to 0.3 m below the surface. The proposed approach transforms B-scans of the GPR-based data into 2D images. The provided approach has significant potential for advancing shallow object detection capabilities by transforming hyperbola-based features into point-like features.
Keywords: GPR, UAV, SFCW radar, acquisition methods
Published in DKUM: 04.12.2024; Views: 0; Downloads: 7
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7. Cross-Hole GPR for Soil Moisture Estimation Using Deep LearningBlaž Pongrac, Dušan Gleich, Marko Malajner, Andrej Sarjaš, 2023, original scientific article Abstract: This paper presents the design of a high-voltage pulse-based radar and a supervised data processing method for soil moisture estimation. The goal of this research was to design a pulse-based radar to detect changes in soil moisture using a cross-hole approach. The pulse-based radar with three transmitting antennas was placed into a 12 m deep hole, and a receiver with three receive antennas was placed into a different hole separated by 100 m from the transmitter. The pulse generator was based on a Marx generator with an LC filter, and for the receiver, the high-frequency data acquisition card was used, which can acquire signals using 3 Gigabytes per second. Used borehole antennas were designed to operate in the wide frequency band to ensure signal propagation through the soil. A deep regression convolutional network is proposed in this paper to estimate volumetric soil moisture using time-sampled signals. A regression convolutional network is extended to three dimensions to model changes in wave propagation between the transmitted and received signals. The training dataset was acquired during the period of 73 days of acquisition between two boreholes separated by 100 m. The soil moisture measurements were acquired at three points 25 m apart to provide ground truth data. Additionally, water was poured into several specially prepared boreholes between transmitter and receiver antennas to acquire additional dataset for training, validation, and testing of convolutional neural networks. Experimental results showed that the proposed system is able to detect changes in the volumetric soil moisture using Tx and Rx antennas.
Keywords: ground penetrating radar, cross-hole, L-band, deep learning, convolutional neural network, soil moisture estimation
Published in DKUM: 03.04.2024; Views: 448; Downloads: 26
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8. Despeckling of SAR Images Using Residual Twin CNN and Multi-Resolution Attention MechanismBlaž Pongrac, Dušan Gleich, 2023, original scientific article Abstract: The despeckling of synthetic aperture radar images using two different convolutional neural network architectures is presented in this paper. The first method presents a novel Siamese convolutional neural network with a dilated convolutional network in each branch. Recently, attention mechanisms have been introduced to convolutional networks to better model and recognize features. Therefore, we propose a novel design for a convolutional neural network using an attention mechanism for an encoder–decoder-type network. The framework consists of a multiscale spatial attention network to improve the modeling of semantic information at different spatial levels and an additional attention mechanism to optimize feature propagation. Both proposed methods are different in design but they provide comparable despeckling results in subjective and objective measurements in terms of correlated speckle noise. The experimental results are evaluated on both synthetically generated speckled images and real SAR images. The methods proposed in this paper are able to despeckle SAR images and preserve SAR features.
Keywords: synthetic aperture radar, speckle, speckle suppression, despeckling, deep learning, convolutional neural network
Published in DKUM: 21.02.2024; Views: 280; Downloads: 30
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9. Odstranjevanje pegastega šuma iz slik SAR z uporabo globokega učenja : magistrsko deloTadej Habjanič, 2023, master's thesis Abstract: Postopek odstranjevanja pegastega šuma je neizogiben pri obdelavi slik z radarjem s sintetično odprtino (SAR). Obstaja več različnih metod za odstranjevanje pegastega šuma, vendar se je postopek s konvolucijsko nevronsko mrežo (CNN) izkazal kot zelo učinkovita metoda.
Pri preprosti strukturi CNN se še vedno izgubi precejšnje število podrobnosti na sliki. Za rešitev tega problema je bila uporabljena arhitektura kodirnika – dekoderja. Model se uči s pristopom, ki temelji na veliki količini podatkov, z uporabo algoritma gradientnega spuščanja s kombinacijo spreminjanja ojačanja pri odstranjevanju šuma in funkcije izgube celotne variacije. Poskusi, izvedeni na realnih slikah, kažejo, da ta metoda dosega pomembne izboljšave v primerjavi z ostalimi metodami.
Keywords: pegasti šum, radar s sintetično odprtino, konvolucijska nevronska mreža, arhitektura kodirnik – dekodirnik
Published in DKUM: 06.02.2024; Views: 274; Downloads: 39
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10. Načrtovanje sistema vodenja termoelektričnega hladilnika : diplomsko deloAlen Merčnik, 2023, undergraduate thesis Abstract: V diplomskemu delu smo načrtali sistem vodenja termoelektričnega hladilnika. Termoelektrični hladilniki so naprave, ki uporabljajo Peltierjev pojav za hlajenje manjših naprav in zagotavljajo njihovo učinkovito delovanje. V načrtanem sistemu smo uporabili termoelektrični hladilnik manjših dimenzij in omejitvijo napajelne napetosti 3V oz. omejitvijo maksimalnega napajalnega toka 3A. Za učinkovito hlajenje se zahteva konstanten napjalni tok. Iz tega razloga smo uporabili namensko integrirano vezje ADN8831 in digitalno vodenje s pomočjo MAX5715 kot DAC pretvornik. Opravljen je bil preizkus vodenja izbranega termoelektričnega hladilnika, ki je pokazal dobro regulacijo temperature.
Keywords: termoelektrični hladilnik, Matlab, regulacija temperature, Peltierjev pojav, regulacija
Published in DKUM: 06.02.2024; Views: 592; Downloads: 67
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