Using TDCP Measurements in a low-cost PPP-IMU hybridized filter for real-time applications
Résumé
Much of the focus in current positioning systems is on high accuracy, oriented by developing powerful and computationally
heavy algorithms; however, this approach is not compatible with systems that require real-time capabilities. Furthermore, most
Precise Point Positioning (PPP) algorithms use ambiguity estimation techniques in order to leverage the precision of carrier phase
measurements. We developed a low-cost PPP algorithm fused with an Inertial Measurement Unit that uses Time Differenced
Carrier Phase (TDCP) measurements which remove the need to resolve the ambiguities while still benefiting from the most
accurate Global Navigation Satellite System (GNSS) observables. To maximize the accuracy and continuity of the positioning
solution, we designed a tightly coupled Extended Kalman Filter that is capable of processing triple frequency code, Doppler,
and carrier phase or TDCP measurements. We observed that the filter which uses TDCP measurements performs 52% better
than the solution with solely the code and Doppler measurements in deep urban conditions and 5% in open-sky conditions while
taking 66% less computation time (in MATLAB) than the filter with carrier phase measurements. The results demonstrate
that TDCP measurements are a solid alternative to carrier phase measurements, especially in deep urban conditions, for any
computationally limited applications while maintaining a high level of accuracy.
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