UAV Electromagnetic Sensors for Spectrum Sensing and Propagation Environment Assessment [video]

Abstract

Electromagnetic (EM) sensors onboard small UAVs can be used for the critical functions of: (1) monitoring the electromagnetic (EM) spectrum, (2) collecting data to evaluate the EM propagation environment, (3) determining EM emissions by fleet assets (ship’s radiating systems), and (4) estimating ship’s emitter detectability by non-cooperative intercept receivers. Assessment of real-time propagation conditions is needed to accurately perform these radar, communication and electronic warfare functions. Anomalous propagation mechanisms, such as ducting, have a strong influence on the directional distribution and strength of EM waves. Many techniques have been employed to estimate the propagation environment, such as (1) using radar clutter return, (2) point to point transmission loss and phase measurements, (3) collection of meteorological data (temperature, humidity, etc.), and (4) GPS signal occultation. Rather than sensing the meteorological properties of the environment, signal transmission to and from a number of sources and receivers are used to build a picture of the electromagnetic environment and the propagation conditions. The sources and receivers can be distributed on UAVs to obtain a detailed EM “map” over large distances and a wide frequency band. The EM data can be used in parallel with meteorological data to enhance the real-time propagation model. Recent developments in commercially available small transmitters and receivers make the concept of outfitting large numbers of UAVs with EM sensors feasible and affordable. Propagation simulations were conducted using state-of-the-art commercial computational EM software. Various meteorological conditions were reproduced, and the loss characteristics for transmissions between networks of UAVs and ships simulated. Using the loss data, the gross real-time propagation conditions are estimated. It is shown that the presence of surface and elevated ducts can be identified using this method. Several operational issues (e.g., number of UAVs required, flight patterns, altitudes, data collection times, etc.) are also discussed.