# Review and Simulation of Counter-UAS Sensors for Unmanned Traffic Management
## 2 Review of the State-of-the-Art Technology
### Active Detection Radars  
Radars have several advantages in detecting aircraft compared with other sensors in terms of weather independency, day and night operation capability, technology development, and capacity to measure range and velocity simultaneously. A big challenge with UAVs is that they have very small radar cross sections (RCS), and they fly at lower altitudes and lower speeds compared to larger aircrafts [4]. Regular radar systems typically aim to detect air targets of medium and large size (RCS larger than 1 m\({}^{2}\)). In addition, due to its low speed, Doppler processing (Moving Target Indication/Detection) is not so effective. In the literature [5], there are several types of radar used for detection, tracking and classification of drones, such as mmWave Radar or Ultrawide-Band Radar, which can be classified in two main categories: active detection and passive detection radars. In this section, we focus on active detection radars, while the next section describes passive radars. Conventionally, there are two possible ways to increase the distance and azimuth resolution of active radar detection systems in the case of UAVs operations: using higher frequency carriers or utilizing multiple input multiple output (MIMO) beamforming antennas. To use shorter a wavelength, K-band, X-band and W-band frequency modulated continuous wave (FMCW) radars are specifically designed for UAV detection. The selection of carrier frequency for UAV detection radar should be higher than 6 GHz (K-band), as in [6], where it is verified the ability of radars to detect small, slow, and low-flying targets. There are two important factors to be considered for the use of radars to detect airborne threats: the target to be detected and the radar itself. When a radar is used to detect small and slow targets, the limiting factor is the RCS, so in that work, \"mini-UAVs\" were treated as a Medium of Airborne Attack (MoAA), and it was concluded that radars working in the K-band are the ones that best detect \"mini-UAVs\" due to their dimensions and radar sections. These radars offer optimal accuracy for measuring the coordinates of the targets being detected and small antenna dimensions. Other approaches use multiple antennas following a MIMO approach. The advantage of this approach is in its applicability to a radar system with lower carrier frequencies, as in [7; 8]. A Holographic RadarTM (HR) with a 2D antenna array and an appropriate signal processing is used in [7]. This signal processing can create a multibeam, 3D, wide-area, staring surveillance sensor, which is able to achieve high detection sensitivity, and provide fine Doppler resolution, with update rates of fractions of a second. The ability to remain continuously on targets throughout the entire search volume enables the detection of small targets, such as UAVs, against a moving background. The system uses a 32-by-8 element L-Band receiver array. As the radar has a high detection sensitivity, it can detect small drones and other small moving targets as birds. Thus, it is necessary to have a stage of processing to discriminate the UAV from other objects. In this case, a machine learning decision tree classifier is used to reject small objects while maintaining a high probability of detection for the drone. A similar study is presented in [8], where a ubiquitous frequency modulated continuous wave (FMCW) radar system working at 8.75 GHz (X-band) with PC-based signal processor can detect a micro-UAV at a range of 2 km with an excellent range-speed resolution. The advances in computation enable another type of radar described in the literature for this application, the software-defined radar (SDR) [9]. This radar is a multiband, multi-mode, software-defined radar that consists of a hardware-based platform and software-based platform. It is multiband because the module allows the selection of S-, X- and K-bands, while it is multimode because of the capacity of selecting waveforms of CW, Pulse, FMCW and LFM Chirp.