# UAV Detection Using Thrust Engine Electromagnetic Spectra
### Features of UAV Detection Methods  
* **Analysis of the acoustic signal characteristics:** Compatible with a variety of other UAV detection techniques. The combination of different techniques effectively improves the accuracy of an optical detection [19]. For example, a microphone array that is easy to deploy for building or perimeter security is presented in [20; 21]. These kinds of systems are economical and easy to install in urban places, stadium security, large gatherings, airports, and locations close to noise sources. These kinds of systems are not ideal due to noise interference. The reliability of detection can be affected by rain, wind, and noise. Additionally, there is no capability to track objects. * **Analysis of optical signatures:** The capability to track objects quickly and precisely. Can be combined with a variety of additional detecting techniques [22]. Possibilities to interact with methods of the artificial intelligence [23; 24]. The technology is ineffective in low-light situations, mist, fog, rain, and snow. The problems with low light are not resolved by infrared light. Flying UAVs can be difficult to distinguish from gliders and can cause false alerts [25]. * **Heat signatures:** The study of heat signatures can be combined with a variety of different UAV detection techniques in order to increase the accuracy. However, weather conditions have a significant impact on the accuracy of detection. The thermal signature of birds causes erroneous warnings of UAV detection. As a defense against thermal signature detection, UAVs can utilize thermal shielding and ventilation. * **Analysis of a radar signature:** This technique allows reaching a high detection range. Passive radar may be used when using another source of sent signals, for example, a TV broadcast signal. Characteristics of digital broadcast signals are successfully used to detect high-altitude UAVs [26]. With the aid of conventional radar devices, huge winged drones can be located [27]. Small drones can be detected using solid-state marine radars in the range of more than half a km [28]. However, UAVs with active RF emitting systems can be set up to fly over detecting zones or close to the surface. Small UAVs with unique construction and materials are difficult to find. It is difficult to identify small birds from UAVs. Due to the impact of radiation on human health and building protection, metropolitan locations are not ideal [29]. The cost of operations and equipment is substantial. * **Analysis of radio frequency communication signatures:** Software defined radio (SDR) technology is combined with methods of artificial intelligence in order to better accommodate urban reception [30]. High-altitude mobile UAV communication sources can be used for the future development of detection systems with object-tracking capabilities that enable the detection of swarming UAVs [31]. However, early detection methods were only used to detect communications in known frequency ranges. UAV'scontrol data frequencies are typically low power and can be used on WI-FI, GSM, DVB, or public frequency ranges that are nearly impossible to detect in urban areas. New UAV models were not detected by such systems unless they were uploaded to the system, but only the detection of pre-stored pattern data packets was available. Advances in UAV autopilots have made it possible to complete pre-programmed flight missions in complete radio silence and without RF transmissions. * **Combined detection methods:** Any known method that is combined by integrating a variety of different sensor types can be used to provide more reliable detection capabilities. Detection reliability is greatly improved when used in conjunction with a voice-assisted video camera array [19; 32]. However, the methods require complex coordination between different UAV detection systems of different manufacturers. There is no common interface standard for connecting multiple systems from different manufacturers.