Research On Method Of Direction-of-arrival Based On Cyclostationarity Of Signals

Spatial spectrum estimation techniques own an outstanding position inelectronic warfare. By exploiting the cyclostationarity of incoming signals, spatialspectrum estimation techniques have a capability of signal selection, an increase ofthe number of detectable signals and noise robustness. Therefore, this technique isparticularly suitable for the complex electromagnetic environment. This paperstudies spatial spectrum estimation techniques based on the cyclostationarityproperty, and the main contents are as follows:(a) Introduction of the basis of spatial spectrum estimation, such as its systemmodel, signal model, as well as classic subspace classification algorithms. Then, thecyclostationarity property and its performance in various types of man-made signalsis presented. And through analysis and simulation, this paper indicates thehigh-resolution capability of the subspace classification algorithms, and thedifferent cyclostationarity between real modulation and complex modulation for asame signal.(b) Introduction of three1-D DOA algorithms in the case of independentincoming signals: Generalized spectral correlation subspace fitting (GSC-SSF),Cyclic multiple signal classification (CMUSIC), Extended cyclic multiple signalclassification (ECM) algorithm. The latter two methods are based on real array, andthe GSC-SSF algorithm is based on the virtual array. A problem of the virtual arrayis that if the statistics of incoming signals are the same, these signals are equivalentto coherent signals for a virtual array. Then, by utilizing ULA, fast rooting methodsfor various algorithms are introduced. Finally, the performance of differentalgorithms is compared by a large number of Monte Carlo simulations using rootingalgorithms.(c) Introduction of a variety of cyclostationarity2-D DOA algorithms. Thesealgorithms can be divided into two categories, one is based on peak searching, andthe other is based on DOA matrix algorithm. A gradient-based peak searchingmethod is proposed in this paper to substitute the traditional peak searching method,which is of significantly lower computational complexity than the traditional one. On the other hand, DOA matrix algorithm avoids the procedure of peak searchingand angle matching, on the basis of which an Extended DOA matrix(EDM)algorithm is studied, which can be applied to two parallel arrays with arbitrarysub-array geometries. Finally, based on the EDM algorithm, two cyclostationarity2-D DOA algorithms are studied: Generalized cyclic DOA matrix algorithm andVirtual array-based cyclic DOA matrix algorithm. These two algorithms have somesimilarities, and the reason is analyzed in the paper.(d) Introduction of cyclostationarity2-D DOA algorithms in coherent case.Firstly, as a traditional2-D spatial smoothing algorithm, Spatial smoothing DOAMatrix algorithm is introduced. Spatial smoothing algorithm is utilized to solve theproblem of statistical coherent signal estimation in virtual array. Finally, based onthe analysis of clostationarity array model in the coherent case, a coherent solutionfor VA-CDM algorithms is presented.