Abstract
Abstract
Since the last decade, stealth technology has been developing at a much higher speed with much research going on to evaluate the properties of radar absorbing structures (RASs) and scattering parameters of the developed stealth structures at different phases of practical use. A vector network analyzer plays an important role in RAS performance evaluation of stealth structures. Different scientists have used closed cell measurement techniques utilizing coaxial cables and waveguides to evaluate RAS materials at high accuracy, while others have used free-space measurement techniques utilizing radiating antennas to evaluate the RAS performance of larger stealth structures without damaging the specimen. All these conventional evaluation systems can scan a single point at a time. A scanning free-space measurement (SFM) system was an initial step toward automated scanning of large stealth structures. This system was capable of scanning 1000 mm × 1000 mm flat structures using raster scanning with two linear stages. However, the two-dimensional SFM was not applicable to leading-edge and cylindrical structures, and the signal-to-noise ratio (SNR) is highly affected by the specimen curvature. In this paper, a 3-axis scanning free-space measurement (3-axis SFM) system was developed. The system has two linear stages and a rotational stage for raster scanning of the specimen. The system performance was checked by scanning cylindrical RAS specimens with a radius of 100 mm. The results were then compared to the SFM system, which showed that the SNR of the 3-axis SFM is quite high compared to the SFM system. A coordinate-based scanning algorithm was also developed for 3-axis SFM to ensure a fixed interval scan of complex geometrically shaped specimens, such as wing leading edges, at lower incident angles. The algorithm achieved a zero-degree incident angle scan with ±1 degree of accuracy for the NACA-M3 symmetrical leading-edge specimen. Different scan parameters and results are visualized in the developed graphical user interface software. Finally, the inspected results were curvature-compensated to obtain the actual RAS performance of the specimen. The accuracy of the geometry-based perfect electric conductor (PEC) reflection-loss prediction algorithm was further improved by adding a stand-off distance effect and more specimen curvature data to the algorithm. The accuracy of the algorithm was verified by comparing the predicted PEC results to the measured PEC results of the corresponding specimen.
Funder
National Research Foundation of Korea
Korean government
Ministry of Science and ICT, the Republic of Korea
Unmanned Vehicle Advanced Research Center
NRF
Subject
Applied Mathematics,Instrumentation,Engineering (miscellaneous)
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