الفهرس 
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Abstract
The high-resolution signal parameter estimation is a problem of significance in many signal processing applications. Such applications include direction-of-arrival (DOA) estimation, system identification and time series analysis. Accurate estimation of signal direction of arrival (DOA) has many applications in communications and radar systems. For example, in defense applications, it is important to identify the direction of possible threat. One example of civilian and commercial applications is to identify the direction of emergency cell phone call such that the rescue team can be dispatched to the proper location.
Array signal processing techniques enhance the resolution of signal DOA and have the ability to identify multiple targets. Model based techniques and eigen-analysis estimation techniques are the most dominant ones in achieving that.
Current researches tend to identify the DOA of the radiating sources under severe fading conditions and various degrees of correlation. The deflation approach is used nowadays to estimate the (DOA) of stationary targets by using symmetric uniform linear arrays (ULAs) under different unknown fading conditions. In this method, the uncorrelated sources are estimated first, and then they are removed by utilizing the symmetric characteristic of array elements or using the oblique projection. The technique manifests significant performance and computational advantages over previous algorithms such as MUSIC.
In this thesis, a new approach for tracking the signal subspace recursively to estimate the DOA of moving sources under multipath fading is presented.
The tracking process is achieved by using an adaptive technique, Least Mean Square (LMS) technique, as a solution of a projection like unconstrained minimization problem. The solution is obtained by making an appropriate projection approximation. The adaptive estimator, for this purpose, uses constrained gradient search procedure. The multipath.