# UAV Detection Using Thrust Engine Electromagnetic Spectra
## 3 Results and Discussion  
The physical experiments were conducted with three engines from three different sources. First of all, two similar-sized multi-rotor UAVs were used for measuring their generated signature on an electromagnetic spectrum. The equipment was chosen according to the possibilities of performing a static flight with the flight stabilization function in use. The first engine was from a DJI MAVIC 2 Enterprise drone and the second engine was from an ACHINE TYRO 109 multi-rotor UAV drone, respectively. A similar BLDC motor from the widely used DEWALT DCF809 impact drive was selected for the comparison of the obtained ES signatures, which were generated by the engines of multi-rotor UAVs. From Figures 5-10, one can seen that after applying the tunable repositioning of the ferrite rod it is possible to achieve:  
* Smooth (continuous) variation of the resonant frequency. * It is possible to detect both the first and other higher harmonics of the electromagnetic spectrum which are emitted by engines of the drone. * Environmental disturbances are eliminated during measurements. The system is not sensitive to environmental disturbances. There were 100 attempts made with every selected device in order to get the electromagnetic spectrograms. Overall, there were 300 attempts. The three summarizing spectrograms are presented for discussion. The aim of the work was to confirm the concept that the designed and manufactured tunable magnetic antenna allows identifying the appearance of the drone in the research area. Additionally, the magnetic antenna allows identifying different operation modes of the engines of the investigated drones. First of all, the 30 s window of the spectrogram of the engine from the Eachine Tyro multi-rotor UAV is presented in Figure 5. The visible essential areas of the spectrogram are: 1--the UAV's thrust motors are turned off; 2--the UAV's thrust motors are spinning  
Figure 4: Performance of the physical experiments. at minimal idle rotation speed; 3--the UAV's thrust motors are spinning from 40% to 30% of the full power; 4--the UAV's thrust motors are spinning at 40% of full power while forced repetitive body destabilization movements in the pitch, yaw, and spin axes are performed. Each forced movement of the UAV is generating a unique signature in an electromagnetic spectrum which is proportional to the frequency shift of the signal. 5--the UAV's thrust motors are spinning at 50% of full power. Equal repetitive forced body destabilization movements in the pitch axis are performed. Each forced movement is generating a proportional signal's frequency shift in an electromagnetic spectrum. 6--the UAV's thrust motors are spinning at the minimal idle rotation speed. According to the results from the spectrogram, it is visible that the appearance of the working engines of the drones is clearly visible in the spectrogram. The actual mode of operation of the engines of the drone can be also identified by using the spectrum of the obtained signal to the magnetic antenna. The level of the amplitude of the spectrum and the distribution of energy at different frequencies will be different in the different modes of operation. For example, the spectrum of obtained signals to the magnetic antenna from all four engines while working in the 50% power of the engines (fifth mode) is presented in Figure 6. The energy of the signal is more concentrated in the lower frequencies. On the other hand, while the UAV's thrust motors are spinning at a minimal idle rotation speed, peaks of amplitudes and the root mean square (RMS) will have the lower values. Additionally, the energy in percentages will be more spread out in higher frequencies (see Figure 7). A similar situation is obtained in the spectrograms of the engines from the DJI MAVIC 2 Enterprise drone (see Figure 8). Figure 5: Recorded signature of a 24 kHz electromagnetic spectrogram, generated by the thrust engines of the multi-rotor Eachine Pyro UAV.