| The passive bistatic radar(PBR)does not actively transmit signals but uses the existing signal in the space to detect targets,so that the passive bistatic radar can deal with electronic interference,low-altitude target detection,anti-radiation missiles and stealth aircraft.Therefore,the passive bistatic radar has great research and application value.As a new generation of mobile communication technology,5G has the characteristics of high carrier frequency and large bandwidth,which can improve the range and speed resolution of radar.Moreover,the coverage density of 5G base stations is higher,so there are fewer blind areas for detection.Therefore,passive bistatic radar that use 5G as a new illuminator of opportunity are worthy of study.This paper discusses the physical layer structure of the 5G downlink channel,and analyzes its characteristics that are beneficial to radar,and proposes two indoor application scenarios of 5G that multipath detection and target recognition.The research contents of this dissertation can be summarized as follows:1.The physical layer structure of the 5G downlink channel and its characteristics that are beneficial to radar are analyzed.First,this paper introduces the physical layer structures of the 5G,such as variable subcarrier spacing,frame structure,bandwidth part,synchronization signal block,demodulation reference signal,etc,including the coding methods and working methods of these structures.In addition to the physical layer structure of 5G,this paper also analyzes the radar characteristics of 5G,including simulates the self-ambiguity function of5 G,and analyzes the reasons for the generation of periodic side peaks,and discusses whether side peak suppression is required in the application scenario of this paper.Finally,the effect of different physical layer settings on the detection performance is analyzed.2.The multipath detection scenarios and methods of 5G are analyzed.This paper proposes diffraction-only path scenario and scenario in which both diffraction and reflection paths exist.Then,considering the positioning requirement,the second scenario is analyzed.In this scenario,take into account the characteristics of the passive bistatic radar,the situation where the target is located in the line-of-sight area and the non-line-of-sight area of the receiver is discussed.Then,combined with geometry,this paper quantitatively analyzes the multipath effects in the two cases,and proposes the formula of the two-dimensional coordinates of the target.Moreover,the signal processing of clutter suppression,R-D processing,and CFAR are introduced.Finally,the effectiveness of the proposed method is verified by simulation.3.The method of target recognition that using 5G millimeter wave is proposed.Firstly,this paper introduces the motion equations of various parts of the human body,and verifies the correctness of the human motion model by simulation.After obtaining the human motion model,the echo of target is constructed,and the short-time Fourier transform is used to analyze the echo.Then,the time-frequency characteristic of different targets are simulated.Finally,this paper introduces the basic components of the convolutional neural network and the working methods of each layer,and proposes the basic structure of the network used in the paper.The confusion matrix of results proves the feasibility of identifying human targets using 5G. |
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