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Support vector regression based sensor localization using UAV

In this work, we focus on localization of a beacon which is a source of radio frequency (RF) signal using a single unmanned aerial vehicle (UAV). We propose to use the Support Vector Regression (SVR) technique to directly localize the sensor by using the received signal strength (RSS) of the RF signal as the input. A systematic method to collect the samples of the RSS values followed by the filtering techniques to process the noise in the RSS measurements as well as the estimate of the sensor position are presented. Pure pursuit guidance law is used to guide the UAV to the estimated sensor location. The algorithm is tested by means of simulations, where it was shown to estimate the position within 2 m accuracy.