The Argos service provider assigns a quality index, or location class (LC), to each position based on its estimated precision. However, most satellite tags record observations at irregular intervals and with considerable error, meaning that movements are observed neither continuously nor with complete accuracy. Of the several technologies available, one of the most popular is that based on satellite tags (platform transmitter terminals, PTTs) using the Argos system. The collection of individual animal movement data has become widely utilized by ecologists in the last decade due to the improvement of the underlying technologies and reduction of operational costs involved in animal telemetry. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates. WhalesвЂ™ behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. Precision of KF locations for whales was generally higher. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. Uncertainty in KF model estimates (5.6В±5.6 km) was nearly half that of LS estimates (11.6в.4 km). 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. Data on 6 fin whales ( Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods.

Tracks from 7 harbour seals ( Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to вЂњtrueвЂќ GPS locations. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.ДЄrgos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. Uncertainty in KF model estimates (5.6 В± 5.6 km) was nearly half that of LS estimates (11.6 В± 8.4 km). Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to 'true' GPS locations. Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF).

Marine mammal satellite tag gps tracks