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Switched beamforming using electronic phase shifters is commonplace. Digital switched beamformers offer a premise of better performance than electronic phase shift switched beamformers. It is also worth noting that current unknown signal Direction of Arrival (DoA) estimation methods (commonly MUltiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT)) are generally computationally intensive. In this paper, signal DoA estimation and digital switched beamforming using aptly designed Artificial Neural Network (ANN) classifiers are looked into. Initially, signals detected at a rectangular receiving array are mapped onto a DoA through an ANN classifier. A second ANN classifier maps the selected DoA onto an optimal set of beamforming weights leading to an optimal switched beamforming reception pattern. The ANN classifiers' performance in DoA estimation and beamforming is tested over a variety of trials, yielding good results. The designed ANN beamformer premises to yield high-speed and accurate switched beamforming performance, most notably in large array systems. The ANN DoA estimator/beamformer can be easily adapted to nonuniform arrays wherein closed form DoA estimation/beamforming solutions are impractical. MATLAB software environment has been used as the main analysis tool.

A typical outcome of Collaborative Beamforming (CB) in Wireless Sensor Networks (WSNs) is the presence of relatively high radiation in undesired directions, an aspect attributed to the usual random arrangement of collaborating sensor nodes. High radiation in undesired directions and prominent sidelobes are bound to result in interference in adjacent co-channel networks. Research towards suppression of radiation in undesired directions in CB is active with a number of proposals already in place. Most of the proposals are in the domain/perspective of 2-dimension WSN configuration with a focus on suppressing the highest-leveled (peak) sidelobe only. Commonly, peak sidelobe suppression is achieved through nodes' transmission amplitude perturbation after a conventional phase steering based beamsteering procedure. In this paper, concurrent amplitude and phase perturbation at collaborating nodes has been utilized towards achieving concurrent beamsteering and suppression of radiation in an elaborate set of undesired directions. A variant of the Particle Swarm Optimization (PSO) algorithm has been applied in the node transmit amplitude and phase perturbation process. Selection of radiation suppression directions is done uniformly from the set of all possible undesired radiation directions. A WSN featuring planar node arrangement with the sink at an elevated plane has been used as the analysis platform. The proposed scheme outperforms the peak sidelobe suppression approach in terms of observed radiation in undesired directions and average sidelobe levels. It has also been established that increasing the number of collaborating nodes and/or the number of selected undesired radiation directions in the proposed CB scheme leads to undesired radiation performance improvement although at an exponentially decaying rate.

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