Publication Type:

Conference Paper


Communications and Signal Processing (ICCSP), 2014 International Conference on, IEEE, Melmaruvathur (2014)



Accession Number:




adaptive beamforming algorithm, array signal processing, Artificial neural networks, Beamforming, direction-of-arrival, direction-of-arrival estimation, Field programmable gate arrays, filtering theory, FPGA implementation, gain adjustment, Interference suppression, iterations, Iterative methods, Jamming, Jamming signal, least mean square algorithm, least mean squares methods, Least squares approximations, LMS, Mean square error, metallic mineral core, open cast mining, phase adjustment, radar antennas, radar interference, radar signal processing, sensor array, Signal resolution, Spatial filtering, spatial filters, step size, Table lookup, terrestrial radar application, Vectors, Xilinx, Xilinx X power analyzer


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. Without mechanical structures the antenna can be steered electronically by adjusting gain and phase. This concept can be used in terrestrial radar application scenarios like open cast mining of metallic mineral core. FPGAs offer higher levels of performance; therefore they are especially appropriate for beamforming applications. Here focus, is to implement adaptive beamforming algorithm known Least Mean Square Algorithm in FPGA. Therefore the relation between Mean Square Error and Iterations and different Step Size are found out. Power Analysis of LMS is presented using Xilinx X Power Analyzer.

Cite this Research Publication

A. D and Sundaram, G. A. Shanmugha, “FPGA Implementation Of Beamforming Algorithm For Terrestrial Radar Application”, in Communications and Signal Processing (ICCSP), 2014 International Conference on, Melmaruvathur, 2014.