Research On UAV Communication Signal Detection And Parameter Estimation

With the continuous development of UAV(Unmanned Aerial Vehicle)technology,the cost of UAV is getting lower and lower,and its operation is simple.It has become a common tool in people's daily life,such as street photography,monitoring and patrol,fire rescue and so on.In addition to the above legitimate uses,nowadays UAV are increasingly used as new means of committing crimes,such as transporting drugs,spying on other people's privacy,interfering with public services and so on.These actions have seriously threatened the personal safety of citizens.Therefore,how to realize the detection and effective supervision of UAV has become an urgent problem at home and abroad.In complex electromagnetic environment,the interception and parameter estimation of small UAV signal is a hot research topic of UAV countermeasure technology,which has important theoretical significance and application value.In this paper,the research on the detection and parameter estimation methods of UAV flight control signals and image transmission signals is carried out.The main contents and achievements of this paper are as follows:1.Aiming at the problem that the detection performance of traditional signal detection methods declines sharply at low SNR,a blind signal detection algorithm based on the combination of incoherent accumulation and power spectrum cancellation(IA-PSC)is proposed.This algorithm effectively improves the signal-to-noise ratio through incoherent accumulation,thus improving the detection probability.The experimental results show that the proposed IA-PSC blind detection algorithm can achieve higher detection performance at lower signal-to-noise ratio than the traditional blind detection algorithm.2.A frequency hopping signal recognition algorithm suitable for complex electromagnetic environment is proposed.By analyzing the time-frequency characteristics of frequency-hopping signal and other modulation communication signals,the unique time-frequency characteristics of frequency-hopping signal are extracted,which can effectively distinguish frequency-hopping signal from fixed frequency signal,frequency shift keying signal,phase shift keying signal,quadrature amplitude modulation signal and so on.3.Aiming at the problem that the computational efficiency and estimation accuracy of traditional blind estimation algorithm of frequency hopping parameters can not be combined at the same time,a new blind estimation algorithm of frequency hopping signal parameters based on STFT-LS-CZT is proposed.The algorithm use STFT to perform time-frequency analysis to reduce the computational complexity.The parameters are optimized by the least square method and Chirip_Z algorithm.To improve the accuracy of parameter estimation.The experimental results show that the proposed blind estimation algorithm based on STFT-LS-CZT has lower computational complexity and can improve the estimation accuracy at low signal-to-noise ratio(SNR)compared with the traditional estimation method of frequency hopping parameters.4.A method of UAV image-transmitted signal detection and parameter estimation is proposed.The blind carrier frequency estimation algorithm is studied in detail.Aiming at the problem of low estimation accuracy of traditional spectral center-of-gravity carrier frequency estimation algorithm under low signal-to-noise ratio,an improved algorithm is proposed.The experimental results show that the improved spectral center of gravity algorithm can improve the carrier frequency estimation accuracy at low signal-to-noise ratio.