Conventional approaches of localization using GPS may fail to offer reliable information in several obstacle-rich, cluttered environments. The signals may get attenuated, be subject to multipath phenomenon, or suffer multiple scattering effects, making the estimation of direction, technically called Direction of arrival (DoA), extremely challenging. While this may be not of much concern for civilians in day-to-day life where GPS are quire reliable, for militaries this may be a mounting concern. The militaries frequently need to locate their team members in places with complex infrastructure and cluttered environments as inside a building. To address these concerns, a team of four researchers from U.S. Army Research Laboratory claims to have developed a novel algorithm for determining DoA from a radio frequency signal source, quite accurately. The algorithm is based on received signal strength (RSS) gradient and is robust to statistically detect and correct spatial outliers and even reliably determine the case of DoA not being available.
The researchers tested their approach with full-wave, high-fidelity simulations and experiments with 40MHz and 2.4GHz bands. The findings are published officially on 24 September 2018 in IEEE Xplore.
Proposed Technique determines and corrects Spatial Outliers to Determine Location with Accuracy
Current methods to locate DoA rely on techniques that determine the phase or time of arrival of the wireless signal. This causes RSS samples to suffer correlated shadowing causing DoA to be biased, thus leading to incorrect estimation of the source direction. The method essentially called Bayesian DoA estimation algorithm to rectify correlated shadowing. In case where this is not possible, as in the case of extremely cluttered signals, the algorithm decides the uncertainly and establishes that no DoA is present.
For validating the results, the researchers looked at data from high fidelity simulations and analyzed data sets related to several in-house location measurements. The innovative technique has advantages over traditional GPS-based techniques excludes the need any fixed infrastructure or multiple antennas, or prior knowledge of the environment.