<p>Automated radio telemetry systems (ARTS) consisting of animal-borne radio transmitters and networks of fixed radio receivers are frequently used to continuously track wildlife movements over time. The low weight of available radio transmitters and the ability of these systems to collect data with high temporal resolution make ARTS an attractive alternative to other wildlife tracking technologies. However, the research questions that can be addressed with ARTS are often limited by the spatial accuracy of location data produced by the system. One of the primary methods used to produce location estimates with ARTS involves comparing the received signal strength (RSS) of radio transmissions detected by multiple receivers in a network. The accuracy of the resulting locations is highly dependent on the algorithm used to process the raw RSS data generated by the ARTS into location estimates. In this work, we have developed a grid search algorithm for producing location estimates from RSS data generated by networks of receivers. In an experiment conducted with a radio transmitter and receiver network, we demonstrate that the grid search method produces location estimates that are greater than 2 times more accurate than the commonly used method of multilateration. A simulation was developed to compare the accuracy of the two methods over a large range of receiver spacings and with varying levels of measurement noise in the system. The simulation showed that the grid search method and multilateration perform similarly for receiver networks with relatively close receivers; however, as the distance between receivers in the array increases, the mean error of location estimates increases much more rapidly for multilateration than for grid search. The improvement in spatial accuracy realized through the use of grid search enables the design of wildlife tracking studies utilizing ARTS to address research questions that were previously inaccessible.</p>