(A) study on the K-BAND FMCW RADAR system using threshold detection model for detect small UAV

Abstract

This paper aim to apply the threshold detection model to K-Band RADAR for detection of small drones and to identify drone by utilizing micro Doppler technique. The RADAR used in this thesis is a K-band FMCW RADAR at 24.615- 24.565GHz combined with an antenna having a narrow 3dB beam width of 1$^\circ$. A threshold model was established with the RADAR. The Neyman-Pearson Detection Rule that provides fixed threshold and the CFAR technique that provides flexible reference lines are used for establishing the model. At this time, because the experimental design was to detect one target drone, and although it rained during the experiment, the noise caused by clutter is smaller than the SNR, so the noise was considered as homogenous. And CA-CFAR which works best in homogenous situation was applied. As a result, a model with a probability of detection greater than 99% when the probability of false alarm is fixed as $10^{-4}$% and SNR greater than 30dB was established. So, using this radar, the drones invading at low altimeter can be detected. With detected results, the drone was identified using micro doppler technology. Results of extracting MDS from target location were compared with noise’s MDS, and the difference of result between target and noise was a periodic pattern. These periodic patterns mean periodic movements, which are effective in distinguishing drones from unwanted targets(such as birds). In other words, micro doppler is used to check the detected object is drone or not.