A Modeling of gradient algorithm of antenna array adaptation in MATLAB environment
Abstract
In many radio engineering systems at the input of the receiving antenna arrays simultaneously there are several useful signals, different directions of arrival, and, for example, the structure of the signal at code division, on a background of interference. Carry out the processing of multiple signals in the receiving AR can be achieved by creating a separate device for spatial-temporal signal processing for each of the correspondents (individual spatial-temporal signal processing) or by synthesizing algorithms for joint processing of all signals (group spatial-temporal signal processing). In this work, the problem of synthesis of adaptive algorithms for signal processing in antenna arrays to improve the quality of reception of multiple signals in radio engineering systems is considered. Algorithms of individual and group processing by a criterion of the minimum mean square error in the form of practically realizable gradient algorithms providing practical realization of optimum spatial and temporal signal processing have been offered. Based on these results, an analysis of their effectiveness in the MATLAB environment was conducted. Simulation of gradient Widrow algorithms in the MATLAB environment was conducted. As a result of modeling, the sensitivity of gradient algorithms to changes in the initial conditions of the system, such as the number of elements of the antenna array, the step of convergence of the adaptation algorithm, signal to noise ratio was analyzed. An analysis of the convergence rate of the algorithms at different values of the algorithm convergence step was also carried out. Based on the carried out researches the optimum parameters of gradient Widrow algorithms have been received proceeding from a minimum of a root-mean-square error at the maximum possible speed of convergence of algorithms. In conclusion, an example of the synthesis of the antenna array directional diagram, which provides spatial and temporal signal processing, taking into account the optimal parameters of the system, is given.
