Abstract

The advancements in drone technology has led to increased usage of drones in civil and military which poses significant security related challenges. The small size of drones and birds pose a significant problem for their accurate detection in real time. These aerial targets have reduced RCS and operate at low altitudes with speeds of 40-80kmph making it difficult to accurately detect and classify them. This paper focusses on the design and development of an intelligent system for the detection and classification of these aerial targets by obtaining their micro-Doppler characteristics. The work integrates the signal processing techniques of radar-based detection with neural network classifier model for real time target classification.

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