  Radio source localization can benefit many fields, including wireless
communications, radar, radio astronomy, wireless sensor networks, positioning
systems, and surveillance systems. However, accurately estimating the position
of a radio transmitter using a remote sensor is not an easy task, as many
factors contribute to the highly dynamic behavior of radio signals. In this
study, we investigate techniques to use a mobile robot to explore an outdoor
area and localize the radio source using sparse Received Signal Strength
Indicator (RSSI) measurements. We propose a novel radio source localization
method with fast turnaround times and reduced complexity compared to the
state-of-the-art. Our technique uses RSSI measurements collected while the
robot completed a sparse trajectory using a coverage path planning map. The
mean RSSI within each grid cell was used to find the most likely cell
containing the source. Three techniques were analyzed with the data from eight
field tests using a mobile robot. The proposed method can localize a gas source
in a basketball field with a 1.2 m accuracy and within three minutes of
convergence time, whereas the state-of-the-art active sensing technique took
more than 30 minutes to reach a source estimation accuracy below 1 m.
