| Target identification and localization technologies play an important role in the field of radio monitoring.With the rapid development of communication technology and the popularization of communication devices,the electromagnetic environment is becoming more and more complex,and the optimization of radio monitoring technology is becoming more and more urgent.As the important components target location parameter estimation,TDE(Time Delay Estimation)has been widely concerned.And in TDE,most of the existing algorithms were based on the assumption of impulsive noise,which do not consider the complex electromagnetic environment where co-channel interference and strong impulsive noise coexist,or mostly for narrowband signals and Gaussian noise,which does not eliminate the impact of impulsive noise and multipath environment on the performance.In addition,due to the characteristics of large profits and difficult to deal with,unauthorized broadcast signals have been banned repeatedly,seriously interfering with the broadcasting order and electromagnetic environment.However,the existing identification algorithms have low accuracy and poor applicability.To address the above issues,this dissertation focuses on TDE in complicated electromagnetic environment,the super-resolution TDE performance in impulsive noise and multipath environments,and unauthorized broadcasting identification,which aims to break through the limitations of the existing algorithms,and improve the theoretical system of the existing radio monitoring technologies.The detailed contents are as follows:(1)In complex electromagnetic environment,due to the impact of co-channel interference and impulsive noise,the performance of existing TDE algorithms degrade severely.In this paper,an improved Generalized Cyclic Correntropy time delay Estimation(HTGCCE)algorithm is proposed by using the Hyperbolic Tangent function to address this degradation problem.Firstly,the performance degradation of generalized cyclic correntropy method is thoroughly analyzed and explained in impulsive noise.Then,HTGCCE algorithm is proposed to improve the delay estimation performance under impulsive noise.Finally,Simulation results illustrate that HTGCCE has an outstanding performance in impulsive noise,even with small characteristic component and low GSNR(Generalized Signal-to-Noise Ratio).(2)To address the performance degradation of existing algorithms in impulsive noise and multipath environment,we combine MUSIC algorithms with kernel functions to achieve superresolution time delay estimation while suppressing impulsive noise.Firstly,correlation method based on kernel function is proposed.Then,a pseudo-signal model similar to the MUSIC algorithm is obtained.And finally,the TDE of multipath components are estimated through constructing the covariance matrix,decomposing the eigenvalues and searching for the spectral peaks.Simulation experiments reveal that our algorithm maintains great performance even when the characteristic exponent of impulsive noise is small,the GSNR is low and the normalized bandwidth of the signal is small.(3)To solve the problem that unauthorized broadcast signals interfere with broadcast communication and affects electromagnetic environment,this paper proposes a LabVIEW +deep learning system for unauthorized broadcast signals identification.Firstly,the broadcast signals received from LabVIEW + USRP are used for the training data.Then the identification system designed by LabVIEW receives the broadcast signals and sends them to the testing model.Finally,mapping the model output and judging whether they are unauthorized broadcast signals or not.Several experiments have proved that the proposed system has good identification performance. |
