| Compared with traditional illuminators of opportunity(Io O)such as FM radio,mobile communication signals have the characteristics of high carrier frequency,large bandwidth,and wide distribution.The use of mobile communication signals as Io O for low-altitude,slow-speed,and small target detection has higher anti-ground clutter ability and target estimation accuracy and has become a research hotspot in recent years.However,the mobile communication base station has a cellular layout,and the transmission signal adopts the mode of frequency multiplexing,which leads to the serious co-channel interference problem for passive radar that uses mobile communication signals as the Io O.This seriously affects the accuracy of detecting the target and the accuracy of estimating the direction of arrival(DOA)of the target.In order to solve the problems of direct signal spatial spectrum estimation and weak target DOA estimation in the environment of strong co-channel interference,this paper eliminates the influence of co-channel interference on target detection and DOA estimation by two aspects: time domain co-channel interference suppression and space domain target separation.The main contents are as follows:(1)First,the basic detection principle and signal processing flow of passive radar are introduced.Then combined with the principles of traditional direct signal spatial spectrum estimation and target direction of arrival estimation and simulation experiments,the reasons for the failure of traditional direct signal spatial spectrum estimation method and target direction of arrival estimation method in passive radar that uses mobile communication signals as the Io O are analyzed.(2)In order to solve the problem of insufficient degrees of freedom,poor resolution accuracy,and large array size in traditional spatial spectrum estimation methods due to the large number of co-channel interferences in mobile communication-based passive radars.This paper proposes a method for estimating the spatial spectrum of strong direct signal in passive radar by fusing coprime arrays and compressed sensing.In this method,the coprime array is used as the receiving antenna of the passive radar that uses mobile communication signals as the Io O.First,the signal received by the coprime array antenna is extended to the virtual domain,and the virtual array extension is performed to improve the array degree of freedom and azimuth resolution.Then,the compressed sensing sparse reconstruction algorithm is used to realize the spatial spectrum estimation of strong co-channel interference.Finally,the proposed method is verified by simulation analysis and measured data.(3)In order to solve the problem that the passive radar that uses mobile communication signals as the Io O is faced with a large number of co-channel interference,the time-domain suppression algorithm is difficult to fully eliminate the interference,and the remaining co-channel interference will seriously affect the target detection.In this paper,we propose a method for weak target detection and DOA estimation based on spatial spectrum sparse reconstruction.After interference cancellation and range-Doppler correlation,the signal model in the range-Doppler unit where the target is located can be regarded as a linear combination of the main lobe of the target and the strong interference side lobe in the airspace.The proposed method combines the advantages of the large aperture in the virtual domain of the coprime array,and performs azimuth sparse rough reconstruction based on compressed sensing for the virtual domain signals of each range-Doppler unit,so as to separate the target echo from the strong interference in the space domain.Rearrange the sparse reconstruction results to obtain the range-Doppler two-dimensional data matrix of all amplitude data in the same direction,then the constant false alarm probability detection is performed on the data matrix to realize target detection and DOA estimation.The validity and superiority of the proposed method are verified by simulation analysis. |
