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http://dx.doi.org/10.7471/ikeee.2020.24.4.921

Classification Type of Weapon Using Artificial Intelligence for Counter-battery RadarPaper Title  

Park, Sung-Jin (LIGnex1)
Jin, Hyung-Seuk (LIGnex1)
Publication Information
Journal of IKEEE / v.24, no.4, 2020 , pp. 921-930 More about this Journal
Abstract
The Counter-battery radar estimates the origin and impact point of the artillery by tracking the trajectory of the shell. In addition, it has the ability of identifying the type of weapon. Depending on the position between the shell and the radar, the detected signals appear differently. This has ambiguity to distinguish the type of shells. This paper compares fuzzy logic and artificial intelligence, which classifies type of shell using the parameter of signal processing step. According to the research result, artificial intelligence can improve identification rate of type of shell. The data used in the experiment was obtained from a live fire detection test.
Keywords
Artificial Intelligence; Neural Network; Weapon Classification; Fuzzy Logic; Counter-battery Radar;
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