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In recent years, Mini/Micro UAVs have started to become a major concern and threat to the public, which made the need of detection and classification of them inevitable. Among all known detection techniques, one of the best reassuring and promising approach is utilizing the passive RF detection method. One of the major problems in this technique is detecting the threats in the presence of the other wireless interference signals like ISM Band Based or Spurious Signals. Proposed study handles this task using hybrid discrimination techniques both utilizing Signal Analysis/Decoding and Overlapping Signal Removal methods. In the first part of the technique, the captured signals are decoded to detect and get RF parameters of Wi-Fi signals and therefore the detected ones are removed from the corresponding spectrums in the time domain which prevents the miscalculation of the center frequency and bandwidth caused by overlapping Wi-Fi signals. In the second part of the technique, developed pulse on pulse (PoP) algorithms are employed in order to calculate more precisely the center frequency and bandwidth of the threat. Both methods developed on an SDR are experimented on both laboratory and field. By means of PoP Algorithms, the calculated deviation center frequency of the one of the Mini/Micro UAVs’ signal is improved from 103 ppm to 61.2 ppm in the presence of wideband overlapping spurious signals. The bandwidth correction is also achieved and makes the bandwidth to be calculated precisely. When Wi-Fi signals are decoded corresponding technique is applied additionally, in frequency domain, the center frequency estimation improved from 61.2 ppm to 28.5 ppm. These results show that the proposed method outperforms the results given in laboratory and field tests.
Özkaner et al. (Fri,) studied this question.