Novel Super Resolution Coprime Array Configurations And A Low Complexity 2D RARE Algorithm Design

Accurate source identification in far field situation needs to deal with lot of challenges especially when we have to estimate more sources than number of sensors,In order to analyze the performance of any source localization system,there are some challenges which determines their ultimate performance.These challenges are computational complexity,robustness to noise,pairing of different parameters,joint estimation of unknown sources,source separation,array perturbation,management of undetermined scenario,and direction of arrival(DOA)estimation under multi-dimensional scenario.In our thesis,we tried to triumph above mentioned challenges as much as possibleDirection of arrival(DOA)estimation in array signal processing is of paramount importance in order to pinpoint the sources precisely.Accurate estimation is an indispensable part of many real world applications like radar,microphone array systems,sonar and speech processing.The key objective of this thesis is to design array configurations which can grip undetermined cases(when one has to estimate more sources than number of sensors)and can solve different multi-dimensional sources with optimal complexity.The main contributions of our work focused on to solve the above challenges like we want to estimate more sources than sensors,this one is achieved by designing super resolution coprime array configurations and secondly aimed to design an algorithm which can solve 2-D DOA estimation with less complexity,can separate different sources and by default can solve pairing problem.The main contributions of the dissertation can be summarized briefly as followsThe first segment of the thesis deals with the study of non-circular quasi stationary signals(QSS)far field sources impinging on a coprime array.The array is designed using translational and displacements properties so that we can achieve high resolution/lags.In this part,we focused on to enterprise an extended covariance matrix exploiting the non-circular property of QSS signals and then subspace-based techniques like multiple signal classification(MUSIC)was used to articulate DOA.In order to further achieve better enhanced lags,Khatri-Rao(KR)technique was implemented after exploiting non-circular property.The proposed algorithm has the competency to uniquely estimate DOA's more than twice the number of sensors.Statistical analysis is performed considering large number of Monte-Carlo simulations.Simulation results showed that the proposed algorithm can succeed better performance as compared to Khatri-Rao(KR)subspace,coprime array with displaced subarray(CADiS)and nested array based techniques under various situations.The second segment deals with the design of high resolution coprime array configurations design in order to accomplish better lags in terms of unique lags and most importantly consecutive lags.This objective is achieved by designing coprime arrays'configurations based on displacements and suppression which gave us enhanced lags especially in term of consecutive lags.The 1st composition known as CASDiS stands for Coprime Arrays with Suppressed and Displaced Subarrays.It can achieve 4MN+1 number of consecutive lags considering only 2M+N number of sensors.However,still there are some holes,which leads us to craft another configuration.In order to accomplish hole free lags,a novel nested inspired "Nested Displaced CoPrime subarrays"(NesDCoP)structure was designed.This configuration performs remarkable in term of generating consecutive lags and can triumph hole free 4MN+2M+ 1 lags.The key contributions of this work are:Firstly,both array configurations can achieve longer consecutive lags as compared to previously proposed arrays.Secondly,NesDCoP structure can accomplish consecutive lags almost equivalent to nested arrays.Lastly,both structures are less complex because there is no need to use interpolation techniques.The practicality of these configurations are demonstrated using MUSIC algorithm and then simulation results are equated with other methods which shows the effectiveness of both the proposed array configurations.The third segment deals with the multi-dimensional mixed sources impinging on a three parallel uniform linear array(ULA).The mixed sources are a combination of circular and non-circular sources,since,in real communications different sources emit different types of signals like in adaptive modulation,the sources far from antenna array emit binary phase shift keying(BPSK)whereas the remaining other may send different signals like quadrature phase shift keying(QPSK).To tackle this problem,a low complexity algorithm was designed which can estimate different two-dimensional sources efficiently and can solve pairing problem without adding any additional complexity.Furthermore,a RARE based 2-D DOA estimation algorithm was proposed for a mixture of circular and non circular sources.The RARE technique decomposes 2-D observation space into two successive 1-D peak search functions which reduces the complexity of the algorithm drastically.The algorithm designs unique steering vectors separately for both sources exploiting the circular/non-circular nature of the sources.The proposed method has some distinctive advantages;it can enhance the array aperture utilization,it can provide better estimation accuracy when mixed sources are greater than sensors,it can also estimate more number of sources than the number of sensors and finally it can automatically pair 2-D DOAs without any complicated pairing formulation.Extensive simulation results are provided to demonstrate the effectiveness of the proposed method.