Array Signal processing is a wide area of research in signal processing which can be extended from a simplest form of one-dimension to a complex form of M-dimension multivariate.Spatial spectrum from an array of multiple passive sensors plays vital role in estimating the signal parameters and the location of the signal source with high resolution and high accuracy.It is applied in the field of radio signal detection and ranging,communication,sonar,earthquake,astronomy,biomedicine,exploration and navigation.For outdoor satellite based global positioning system（GPS）are available for accurate source positioning,but indoors where GPS signal fades,and presence of multipath,non-line-of-sight,and dense scattering environment,yields unreliable position estimation.Classical subspace based indoor positioning has been long objective of the research community,and several source estimation and positioning methods were proposed for localization of wireless device in the indoor environment.Spatial spectrum estimation plays an important role in array signal processing to achieve high resolution and high accuracy,while fusion is the technology which can process data comprehensively,particularly in the field of wireless network at cost of limited data resources.In indoor,most of the studied and used wireless systems have uniform linear antenna array（ULA）structure.The previous research has focused on sensor fusion,time-of-arrival（TOA）fusion,or direction of arrival（DOA）fusion,where one-dimensional information of the direction of arrival of incoming signal relative to the array axis was estimated for localization.However,the positioning of user equipment in three dimensions is expected nowadays,where two-dimensional angular domain estimation is required along with use of planar arrays.Moreover,Massive Multiple-input-multiple-output（MIMO）with orthogonal-frequency division multiplexing（OFDM）is most probable candidate to be used in upcoming fifth generation（5G）communication system due to its high angular resolution,energy efficient high data throughput,increased robustness to delay spread for multipath and link reliability properties.It also has sparse channel property from uplink to perform downlink beamforming at base-stations which is exploited here for localization of user as an integral part of the network at reduced cost of user’s power.In OFDM system one wideband channel is divided to narrowband sub channels where user serial data are mapped to parallel path of allocated number of subcarriers for transmission.These serial data are OFDM symbols,containing pilot sequences along with user data.In this thesis,a direction of arrival（DOA）related novel two-dimensional spatial spectrum fusion estimation and localization（SSFEAL）scheme is proposed,which can be used to localize user by fusion of narrowband uplink pilot signal observed at distributed uniform circular array（UCA）massive MIMO base stations for channel estimation to avoid user identification complexity.Massive-MIMO channels sparse characteristics at individual base stations are used to synthesize the covariance matrices of received signal to form fused spatial spectrum pursuit at central fusion center to reduce the computation complexity.Then localization of user is performed by maximum sum of orthogonal projection of spatial spectrum function in minimum noise subspace.Additionally,our method uses two-dimensional spatial information fusion to generate informative spatial spectrum followed by grid refinement to reduce localization error.We minimize the searching area by making a coarse grid based on time of arrival estimation on deconvolution approach with l₁ norm of pulse shaping reconstruction function.The SSFEAL technique does not need larger signal bandwidth and is independent of cyclic prefix.Multiple signal classification algorithm like method is used for spectrum generation to suitably project the estimated directional data into the fused noise subspace for localization of user with minimum error and is compared with other algorithm to advocate the accuracy of proposed method.Simulation models for different cases were run using MATLAB to analyze the performance of the proposed localization scheme.The simulation results shows that the proposed localization scheme provides high accuracy and outperforms in indoor environment in presence of severe multipath and NLOS signals compared to different antenna geometry.The proposed scheme also estimates accurate NLOS-only source location when the LOS paths are not available.