Adaptive beamforming and spectrum sensing for radio-frequency source detection and tracking

Abstract

This study presents a robust adaptive beamforming method dedicated to tracking a single mobile target emitting a radio frequency (RF) signal. Based on an LMS estimation algorithm and an adaptive beamforming architecture, it also introduces a CMAP-CFAR detection structure capable of detecting the presence of a target and estimating its transmission frequency. The hardware implementation, carried out on a multi-channel Kraken SDR platform, produced results demonstrating that the proposed system maintains accurate target tracking while enabling the detection of an RF signal and the estimation of its frequency, highlighting its potential for real-time surveillance and direction-finding applications.