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Automatic aircraft recognition using convolutional neural Network

100%

Adamiak D. , Ślesicka A.

2024

tom No. 29

90--99

The paper presents the possibility of utilisation convolutional neural network for aircraft classification by their type. Main purpose of the study was to use a common deep learning network and modify it to correctly classify three types of general aviation aircraft. Differentiation is made based on their low quality picture with black outline on white background. Database utilized in this study is small compared to common CNN databases and results ought to be taken only as a trend. Research consisted of choosing right parameters of network to make the recognition as accurate as possible. 20 samples have been produced to evaluate accuracy of the software and eliminate deviations. Conclusions and issues have also been described.

Improve the safety of air transport, especially in militarized terrain, by use of side looking airborne radar and space time adaptive processing

80%

Ślesicki B. , Ślesicka A. , Kawalec A.

tom z. 123

335--346

The paper explores the potential to enhance aviation safety, particularly in militarized regions, by outfitting aircraft with Side Looking Airborne Radar (SLAR) and employing space-time adaptive processing (STAP) algorithms. The research objective revolves around implementing a model of side-looking airborne radar and the corresponding STAP algorithms. This technology enables the detection of slow-moving targets amidst strong interference, encompassing both passive (clutter) and active (jammer) elements. Slow-moving targets relative to the aircraft's speed include tanks, combat vehicles, command vehicles, artillery, and logistical assets of enemy forces. The theoretical framework of space-time adaptive processing is presented, elucidating the sequential steps of the classical Sample Matrix Inversion Space-Time Adaptive Processing (SMI STAP) algorithm. The paper underscores the significance of characteristic parameters delineating a linear STAP processor. The proposed solution facilitates the detection of enemy combat measures and enhances aviation safety. It outlines a radar model installed beneath the aircraft's fuselage and elucidates algorithms for space-time adaptive processing of radar signals. The simulations conducted within the article were executed using the MATLAB environment. The simulation results indeed suggest that the proposed solution holds promise for deployment in equipping aircraft of one's own military and those engaged in operations within conflict zones. This paper stands as one of the few contributions in the literature addressing the augmentation of aircraft safety through radar and space-time adaptive processing.

The Study of the Possibility of Applying Parallel Programming to the Algorithms of Space-Time Adaptive Processing

80%

Ślesicki B. , Kawalec A. , Ślesicka A.

tom Vol. 13, Nr 3 (49)

27--42

The article presents the description, assumptions and subsequent steps of the space-time adaptive processing (STAP) algorithms used as a signal processing tool in radars. The possibilities of object detection using the Sample Matrix Inversion (SMI) and Data Domain Least Squares (DDLS) algorithms were compared and showned. The article shows the impact of the use of parallel programming on the computation time of both algorithms. The main aim of this study was to propose an efficient method for the real-time implementation of the STAP algorithm in airborne radar systems. The idea of using parallel programming in STAP, supported only by the preliminary research results presented above, gives a real chance for the casual implementation of the STAP algorithm in a radar operating in close to real time mode.

W artykule przedstawiono opis, założenia i kolejne kroki algorytmów przestrzenno-czasowego przetwarzania adaptacyjnego (STAP) stosowanych jako narzędzie przetwarzania sygnałów w radarach. Porównano i pokazano możliwości wykrywania obiektów za pomocą algorytmów Sample Matrix Inversion (SMI) i Data Domain Least Squares (DDLS). W artykule przedstawiono wpływ zastosowania programowania równoległego na czas obliczeń obu algorytmów. Głównym celem pracy było zaproponowanie efektywnej metody implementacji algorytmu STAP w czasie rzeczywistym w pokładowych systemach radarowych