Research And Implementation On DOA Estimation Algorithms For Coprime Array

In recent years,with the rapid development of 5G communication,unmanned aerial vehicle(UAV),and sensor technology,as an important branch of signal processing,array signal processing has received extensive attention and research in both military and civilian fields.The direction of arrival(DOA)estimation plays an important role in array signal processing and has become a research hotspot in the direction of array signal processing.The traditional uniform linear array DOA estimation algorithm is limited by physical array elements,it can be estimated only when the number of sources is less than the number of array elements,which will increase the cost in practical applications.As a kind of sparse array,the coprime array can obtain a larger array aperture and a higher degree of freedom under the same physical array element,and can deal with the source estimation under underdetermined conditions,which significantly improves the DOA estimation performance.Therefore,the research on coprime arrays and related algorithms has important research significance and practical value for enhancing the application of array signal processing technology in actual engineering.This thesis mainly studies one-dimensional and two-dimensional(2D)DOA estimation algorithms based on coprime arrays.At the same time,combined with actual demand,a radio passive monitoring software was designed.The main work of the thesis is as follows:1.To solve the problem of poor performance and high complexity of traditional onedimensional coprime array DOA estimation algorithm,a coprime array DOA estimation algorithms based on Toeplitz matrix reconstruction estimation signal parameter via rotational invariance techniques(ESPRT)and propagation method(PM)is proposed.First the characteristics of the coprime array are used to form an extended virtual uniform linear array,and then Toeplitz matrix reconstruction is used to form a new DOA estimation matrix.Finally,the corresponding ESPRIT and PM algorithms are derived under the new DOA estimation matrix.Simulation experiments verify that both algorithms can effectively increase the degree of freedom of the array.Compared with the traditional coprime array DOA estimation algorithm,the estimation performance is improved.2.For the problems of high computational complexity and low accuracy of traditional parallel coprime array 2D-DOA estimation algorithm,firstly,the traditional 2D parallel prime array algorithm is improved to greatly reduce the complexity of the algorithm.Then a new low-complexity dual parallel coprime array 2D-DOA estimation algorithm is proposed.The algorithm uses two parallel coprime arrays to generate a virtual array,and constructs a new DOA estimation matrix through the self-covariance matrix and the crosscovariance matrix.Finally,the singular value decomposition(SVD)and ESPRIT methods are used to obtain the automatically matched 2D angle estimation.Simulation experiments prove that the algorithm can effectively increase the degree of freedom of the array,improve the performance of the algorithm,and reduce the complexity.3.In order to promote the engineering application of DOA estimation algorithm,the thesis combined with the hardware system developed by the laboratory,designed a radio passive monitoring software.The software has a simple operation and data visualization interface,which realizes the functions of radio frequency detection,modulation mode identification and direction finding.At the same time,it also provides a platform for further research on the signal and the expansion of related algorithm functions.