Route taken and distance travelled are important parameters for studies of animal locomotion. They are often measured using a collar equipped with GPS. Collar weight restrictions limit battery size, which leads to a compromise between collar operating life and GPS fix rate. In studies that rely on linear interpolation between intermittent GPS fixes, path tortuosity will often lead to inaccurate path and distance travelled estimates. Here, we investigate whether GPS‐corrected dead reckoning can improve the accuracy of localization and distance travelled estimates while maximizing collar operating life. Custom‐built tracking collars were deployed on nine freely exercising domestic dogs to collect high fix rate GPS data. Simulations were carried out to measure the extent to which combining accelerometer‐based speed and magnetometer heading estimates (dead reckoning) with low fix rate GPS drift correction could improve the accuracy of path and distance travelled estimates. In our study, median 2‐dimensional root‐mean‐squared (2D‐RMS) position error was between 158 and 463 m (median path length 16.43 km) and distance travelled was underestimated by between 30% and 64% when a GPS position fix was taken every 5 min. Dead reckoning with GPS drift correction (1 GPS fix every 5 min) reduced 2D‐RMS position error to between 15 and 38 m and distance travelled to between an underestimation of 2% and an overestimation of 5%. Achieving this accuracy from GPS alone would require approximately 12 fixes every minute and result in a battery life of approximately 11 days; dead reckoning reduces the number of fixes required, enabling a collar life of approximately 10 months. Our results are generally applicable to GPS‐based tracking studies of quadrupedal animals and could be applied to studies of energetics, behavioral ecology, and locomotion. This low‐cost approach overcomes the limitation of low fix rate GPS and enables the long‐term deployment of lightweight GPS collars.

Unmanned aerial systems (UASs), frequently referred to as 'drones', have become more common and affordable and are a promising tool for collecting data on free-ranging wild animals. We used a Phantom-2 UAS equipped with a gimbal-mounted camera to estimate position, velocity and acceleration of a subject on the ground moving through a grid of GPS surveyed ground control points (area ∼1200 m 2 ). We validated the accuracy of the system against a dual frequency survey grade GPS system attached to the subject. When compared with GPS survey data, the estimations of position, velocity and acceleration had a root mean square error of 0.13 m, 0.11 m s , respectively. The system can be used to collect locomotion and localisation data on multiple free-ranging animals simultaneously. It does not require specialist skills to operate, is easily transported to field locations, and is rapidly and easily deployed. It is therefore a useful addition to the range of methods available for field data collection on free-ranging animal locomotion.