Adaptive Algorithms in Radar Signal Processing

Fulltext (.pdf 1,24 MB)

https://doi.org/10.52651/sam.a.2024.1.15-25

Autor: Jana Ľoncová, Ján Ochodnický

In: Science & Military

ISSN: 2453-7632

Ročník: 19

Číslo: 1

Strany: 15 - 25

Rok vydania: 2024

Vydavateľ: Akadémia ozbrojených síl generála Milana Rastislava Štefánika, Liptovský Mikuláš

Abstrakt: The development of modern technologies has fundamentally transformed the field of radar signal and data processing. With the use of advanced algorithms and computational power, radars are now capable of extracting crucial information from received signals, facilitating improved target identification and tracking. This article presents some of the advanced technologies employed in radar signal and data processing and their impact on adaptability of radar systems. It traces the evolution of radar technology from old systems to the present, emphasizing the benefits of adaptive radar signal processing, which includes algorithms such as adaptive beamforming, Space-Time Adaptive Processing, and the integration of Machine Learning and Artificial Intelligence. In conclusion, challenges, and future prospects in the field of radar systems are discussed, with a focus on the potential integration of Artificial Intelligence methods, Cognitive radars, and Multiple Input Multiple Output technologies. Despite technical obstacles, opportunities emerge to enhance the performance of radar systems and achieve new levels of efficiency.

Kľúčové slová: Radar signal processing; Radar data processing; Adaptive radar; Adaptive algorithm.

Citácia:

ĽONCOVÁ, Jana a OCHODNICKÝ, Ján. Adaptive Algorithms in Radar Signal Processing. In: Science & Military [online]. Liptovský Mikuláš: Akadémia ozbrojených síl generála Milana Rastislava Štefánika, 2024, 19 (1), s. 15-25. ISSN: 1336-8885 (print). ISSN: 2453-7632 (online). Dostupné na internete: https://doi.org/10.52651/sam.a.2024.1.15-25

Object Recognition System for the Spinbotics Robotic Arm

Fulltext (.pdf 1,24 MB)

https://doi.org/10.52651/sam.a.2024.1.39-44

Autor: Patrik Štefka, Peter Pásztó, Marian Kľúčik, Martin Smoľák, Matej Vargovčík, Jakub Lenner

In: Science & Military

ISSN: 2453-7632

Ročník: 19

Číslo: 1

Strany: 39 - 44

Rok vydania: 2024

Vydavateľ: Akadémia ozbrojených síl generála Milana Rastislava Štefánika, Liptovský Mikuláš

Abstrakt: This study focuses on the development of a visual system designed to facilitate object detection for the Spinbotics robotic arm in spatial environments. The primary objective is to enable accurate detection and classification of diverse objects, enhancing the arm's capability to grasp and manipulate items effectively. The system employs the YOLOv7 deep neural network, fine-tuned using transfer learning on a local computing infrastructure. Compared to traditional methods like R-CNN and SSD, YOLOv7 offers superior real-time processing capabilities and efficiency, making it well-suited for dynamic environments. Through extensive training and testing, the system demonstrates robust performance in detecting objects across
varied scenes and identifying optimal grasp points. This research underscores the effectiveness of integrating advanced computer vision techniques to enhance the operational efficiency and versatility of robotic manipulators in real-world applications.

Kľúčové slová: Robot arm; Visual system; YOLO; Object detection.

Citácia:

ŠTEFKA, Patrik; PÁSZTÓ, Peter; KĽÚČIK, Marian; SMOĽÁK, Martin; VARGOVČÍK, Matej et al. Object Recognition System for the Spinbotics Robotic Arm. In: Science & Military [online]. Liptovský Mikuláš: Akadémia ozbrojených síl generála Milana Rastislava Štefánika, 2024, 19 (1), s. 39-44. ISSN: 1336-8885 (print). ISSN: 2453-7632 (online). Dostupné na internete: https://doi.org/10.52651/sam.a.2024.1.39-44

Tribotechnical Diagnostics – Degradation of Engine Oil Properties SAE 10W-40 in Iveco Crossway During Long Journeys

Fulltext (.pdf 1,24 MB)

https://doi.org/10.52651/sam.a.2024.1.26-38

Autor: Radovan Stephany, Vladimír Kadlub, Miroslav Marko

In: Science & Military

ISSN: 2453-7632

Ročník: 19

Číslo: 1

Strany: 26 - 38

Rok vydania: 2024

Vydavateľ: Akadémia ozbrojených síl generála Milana Rastislava Štefánika, Liptovský Mikuláš

Abstrakt: This paper addresses tribotechnical diagnostics, specifically by examining the properties of the engine oil (MO) type i-Sigma top MS; SAE 10W-40 used in the IVECO CROSSWAY bus with a higher number of total mileage from the inter-vehicle standard. In the abstract of the paper, the characteristics of the measured technique, tribodiagnostic instruments of measurement and a more detailed specification of the oil properties and the monitoring of its gradual degradation during long-term operation are presented. Long-term operation in the sense of the article means a continuous mileage run of more than 200 km (one race without stop) and a MO temperature in the range of 80 ºC to 130 ºC. All measurements were carried out in the tribodiagnostic laboratory of the Department of Mechanical Engineering of the Armed Forces Academy of General M. R. Štefánik (hereinafter referred to as „AOS") in Liptovský Mikuláš.

Kľúčové slová: Motor oil; ACEA; API; SAE; VW 501 01; 505 00; 504.00; 507.00/MB-Approval 229.31/229.51; Kinematic viscosity; Motor oil condition; Motor oil degradation.

Citácia:

STEPHANY, Radovan; KADLUB, Vladimír a Marko, Miroslav. Tribotechnical Diagnostics – Degradation of Engine Oil Properties SAE 10W-40 in Iveco Crossway During Long Journeys. In: Science & Military [online]. Liptovský Mikuláš: Akadémia ozbrojených síl generála Milana Rastislava Štefánika, 2024, 19 (1), s. 26-38. ISSN: 1336-8885 (print). ISSN: 2453-7632 (online). Dostupné na internete: https://doi.org/10.52651/sam.a.2024.1.26-38