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Improving ARGOS Doppler Location Using Kalman Filtering

The ARGOS service was launched in 1978 as a joint US-French initiative and is geared towards environmental applications, including oceanography, wildlife tracking, fishing vessel monitoring and maritime safety. The system allows for worldwide, near real-time data collection and positioning of Platform Terminal Transmitters (PTTs). The current ARGOS positioning algorithm is based on a classical non-linear Least Squares estimation technique. We present here a new positioning algorithm that relies on Kalman filtering of the ARGOS frequency measurements. The performance of this new location algorithm are compared to those of the existing algorithm using a large dataset coming from mobiles carrying both an ARGOS transmitter and a GPS receiver. The results show that the new algorithm provides more estimated positions and significantly improves the positioning accuracy. Improvements are most significant for locations obtained in difficult conditions (class A and B locations).