Temporal Frequency Analysis: Target Isolation and Signal Optimization

• Published in: 2019 53rd Asilomar Conference on Signals, Systems, and Computers pp. 1890 - 1895
• Main Authors: Stubbs, Jaclynn J., Birch, Gabriel C., Woo, Bryana L., Kouhestani, Camron, Novick, David
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-11-2019
• Subjects: Counter unmanned aircraft systems; Fourier transforms; frequency analysis; genetic algorithm; Genetic algorithms; Optimization; Signal processing; Sociology; Statistics; temporal frequency signatures
• ISSN: 2576-2303
• DOI: 10.1109/IEEECONF44664.2019.9048854

Unmanned aircraft systems (UASs) have grown significantly within the private sector with ease of acquisition and platform capabilities far outstretching what previously existed. Where once the operation of these platforms was limited to skilled individuals, increased computational power, manufacturing techniques, and increased autonomy allows inexperienced individuals to skillfully maneuver these devices. With this rise in consumer use of UAS comes an increased security concern regarding their use for malicious intent. The focus area of counter UAS (CUAS) remains a challenging space due to a small cross-sectioned UAS's ability to move in all three dimensions, attain very high speeds, carry payloads of notable weight, and avoid standard delay techniques. We examine frequency analysis of pixel fluctuation over time to exploit the temporal frequency signature present in UAS imagery. This signature allows for lower pixels-on-target detection [1]. The methodology also acts as a method of assessment due to the distinct frequency signatures of UAS when examined against the standard nuisance alarms such as birds. The temporal frequency analysis (TFA) method demonstrates a UAS detection and assessment method. In this paper we discuss signal processing and Fourier filter optimization methodologies that increase UAS contrast.