# Drone and Controller Detection and Localization: Trends and Challenges
## 3 UAV Detection Methods
### Radar
In [55], the authors proposed research and experiments for evaluating the data acquisition and signal processing algorithm in a CW radar system that supports C and X frequency bands operations. The radar system uses the micro-Doppler principle. The extracted signatures in the frequency and time domains are used in UAV classification for calculating the propeller blades' length and determining the rotation propellers' speed. For performance evaluation, the number of UAV propellers varies during the experiments while fixing the propellers' rotational speed and a maximum distance of 25 m between the radar and UAV. The classification and measurement of UAVs become complex with the increase in propellers. In another work [56], simulation and analysis of continuous wave radar's echo signals are studied and presented in different conditions at an operating frequency of 35 GHz. Mainly UAV detection is based on the time-frequency characteristics of the Micro Doppler signal produced by the rotor rotation using singular value decomposition. Discrete wavelet transform is also used to remove environmental clutter from the radar echo signal, whereas the support vector machine (SVM) is used as a classifier. The detection accuracy of the developed system achieved 85%. Another type of radar-based UAV detection mechanism, cylindrical phased array radar, was discussed in [27]. The system performs better for UAV detection when comparing the omnidirectional scanning to planner array radar due to the flexibility of changing the direction of the beam and illumination time to the target after the phased array was used. As for the operational norms, the system's hardware structure and signal processing flow are designed to get a strong clutter suppression specified in the investigation, and the result of the experiment shows potential for UAV detection. Authors in [27] developed a cylindrical phased array radar system and explored signal optimization by specifying signal processing flow with the moving target detection (MTD) based on the maximum signal-to-clutter ratio (SCR) criterion. [PERSON] et al. [24] explained the type x-band, a small phased array radar based on AD9361, an RF Agile Transceiver. The AD9361 is a highly integrated RF module with a high-performance agile transceiver for 3G and 4G base station applications. The reported radar system consists of a control module controlling the antenna beam pointing through the transmitter/receiver (T/R) module. The signal processor also sends waveforms as transmitted RF signals to AD9361 within the timing sequence. Then the corresponding  
Figure 3: Architecture design of FMCW radar [21]. waveform is generated and established by AD9361. The radar simulation detects a drone with a radar cross section (RCS) of 0.01 m\({}^{-2}\) within the range of 5 km. For radar detection, enhanced reflected signals are necessary to minimize the effect of noise. An SNR value greater than 14 dB indicates a highly accurate detection. In the case of a reliable RCS, the chosen wavelength should not reach half of the detected object's dimension. It is critical to use a higher frequency while using Doppler-based detection. As illustrated in [22], radar is used to detect smaller drones; however, it has an ill-prepared standard for UAV detection based on low air-velocity aircraft and weak radar signature. During target detection, the radars would receive reflections from clutter-like objects, landscapes, and precipitation, posing a challenge in detection. A target can only be detected if system noise due to clutter is minimized. A 30 \(\times\) 30 rectangular phase array used in [22] detects the presence of drones in monostatic radar. It would continuously scan the predefined surveillance region, with the limitation of a 90-degree azimuth sector, to achieve 360 azimuth coverage at a low cost. Doppler estimation discussed in [22] can be described as a spectrum estimation process. The reference [26] illustrates the new method based on 5G millimeter waves with an end-to-end network.