# A Study on Various Types of Beamforming Algorithms

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4 Capon Beamformer Fig. 5.1: Beam pattern plot for conventional Beam forming with desired signal at 40 degrees. For a uniform linear array with 32 number of antennas, inter-element spacing (d) = 0.5λ, the plot of Beampattern vs array look angle for a single source for capon beamforming is shown in figure 7.5 here our desired signal direction is at 40 degrees and interference at 60 degrees. Desired signal direction=40degrees, Interference direction=60 degrees, Signal Power=1dB, Noise Power=5dB, Interference power=1000db. Fig. 5.2: Beampattern plot for Capon Beamforming with desired signal at 40 degrees and interference at 60 degrees. For a uniform linear array with 32 number of antennas, inter-element spacing (d) = 0.5λ, the plot of Beampattern vs array look angle for a single source for capon beamforming with interferences at directions at 0,10,30,60 and 80 degrees and desired signal at 40 degrees is shown in figure 5.3. Fig. 5.3: Beampattern plot for Capon Beamforming with desired signal at 40 degrees and interference at 0,10,30,60 and 80 degrees. All rights reserved by 58

5 Adaptive Beamforming A Study on Various Types of Beamforming Algorithms For a uniform linear array with 32 number of antennas, inter-element spacing (d) = 0.5λ, the plot of Beampattern vs array look angle for a single source for Adaptive Beamforming with interferences at directions at 11 degrees and source at 0 degrees.here the interference signal magnitude is & times the signal power.here we have simulated it with the help of Generalized Side Lobe Canceller Structure. Fig. 5.4: Input desired signal, Input Interference Signal, Real Input Received at Beam former Fig. 5.5: Output from the Conventional Beamformer Fig. 5.6: Output from the Adaptive Beamformer in which LMS algorithm is used for correction. VI. CONCLUSION Beamforming or spatial filtering combines signals from an array of sensors, to achieve directionality. Each signal is weighted and summed to form a single strong signal from a desired direction of arrival, while suppressing interference. This concept could be useful in various terrestrial radar application scenarios of open cast mining of metallic mineral core. The goal is to optimize the output such that it contains minimum noise. For the simulation purposes Matlab R2013a would be used. LMS algorithm is used here due to its simplicity, low computational complexity and better performance in different running environments. It performs really well in terms of number of iterations required for convergence and the results showed that LMS algorithm is the best algorithm to be implemented in FPGA. All rights reserved by 59

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