Mathematical Model of a Radiobeam Detection System Signal
DOI:
https://doi.org/10.64915/RADAP.2025.102.%25pKeywords:
detection, radiobeam, perimeter security means, mathematical modelAbstract
This paper presents the development of a mathematical model of the information signal of a radiobeam detection system for studying the factors influencing its parameters. The model is based on the Huygens–Fresnel principle. The intruder is represented by an equivalent rectangle, which sequentially occludes certain regions of the wave phase front during movement. The information signal is defined as the normalized difference between the field strength in the absence of the intruder model and the field strength in its presence and motion. The mathematical model of the information signal was verified by physical simulation at a frequency of 9.3 GHz using a R2-61 panoramic VSWR meter, standard horn antennas, and metal plates of various sizes that were moved across the detection zone.
The model demonstrated good agreement with experimental data, allowing its application for predicting the waveform of information signals. A series of computational experiments was performed for frequencies of 10.5 GHz, 5.8 GHz, 2.5 GHz, and 1.0 GHz for a 50 m security perimeter. Three intruder movement scenarios were analyzed: upright, bent over, and crawling. It was shown that at higher frequencies (10.5 GHz), the signal during crawling exhibits a positive increment, creating a risk of undetected intruder crossing in systems configured to trigger on negative increments. Lowering the frequency to 5.8 GHz and 2.5 GHz provides more stable negative increments at slightly reduced signal amplitude. At 1.0 GHz, a significant reduction in the signal level is observed. The proposed mathematical model of the information signal accounts for the operating frequency, antenna spacing, intruder geometry, its position, and movement method. This makes it possible to create a database of signals for a specific security perimeter, enabling the use of correlation-based signal processing methods. The obtained results allow selecting the optimal frequency range for a given security perimeter, reducing the volume of experimental testing on a security perimeter, and improving information signal processing algorithms, which will enhance detection reliability and reduce the number of false alarms.
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Copyright (c) 2025 В. Г. Сторож, С. Є. Фабіровський, І. Н. Прудиус, Ю. М. Матієшин, В. І. Оборжицький, Р. М. Гурмач
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