Self-discovery and orientation of a randomly distributed cognitive beamforming array

This paper introduces the MARCO POLO Algorithm (MPA) that uses wireless discovery and control signals from a Master Control Node (MCN) with a cognitive engine to learn the relative location and orientation of a randomly distributed set of array elements. The elements are then synchronized and instructed to apply appropriate magnitude and phase offsets to collectively radiate as an array with beamforming capability. Unlike conventional discovery algorithms, MARCO POLO does not assume any a priori information about the array elements, does not rely on reference beacons, and works without GPS. With this algorithm, sensor nodes can be placed around the periphery of a complex enclosure, such as a vehicle, aircraft, or building and then self-organize into a distributed array with no wired connectivity.