Bayesian Direct Position Estimation (BDPE) is a novel and promising positioning method, where the Position, Velocity and Time (PVT) is estimated directly from the correlation values of a Global Navigation Satellite System (GNSS) receiver. A natural approach for this method is the usage of Bayesian filtering techniques, such as a particle filter, which also allow for non-linearities in the system and observation model and being able to cope with non-Gaussian multi-modal distributions. One essential step within Bayesian filters it the measurement update (particle weight update), which updates the current state of the filter with a new set of measurements. Therefore, an optimal measurement update equation exists in literature, which considers a numerically stable evaluation of the weight update equation and accounting for residual user range errors (orbit, satellite clock, atmosphere or multipath) by introducing a nuisance parameter for the range measurement. This work discusses the problems with the optimal but plain measurement update and extends the existing framework by introducing an additional nuisance parameter for the Doppler. Similar to the range measurement also the Doppler can be biased e.g. by clock drift errors or multipath. The results of the extended approach are shown on a real-world dataset.    «

Bayesian Direct Position Estimation (BDPE) is a novel and promising positioning method, where the Position, Velocity and Time (PVT) is estimated directly from the correlation values of a Global Navigation Satellite System (GNSS) receiver. A natural approach for this method is the usage of Bayesian filtering techniques, such as a particle filter, which also allow for non-linearities in the system and observation model and being able to cope with non-Gaussian multi-modal distributions. One essenti...    »