Systems and methods for sharing convergence data between GNSS receivers are disclosed. Convergence data received at a GNSS receiver via a communication connection may be utilized to determine a position of the GNSS receiver.

Systems and methods for sharing convergence data between GNSS receivers are disclosed. Convergence data received at a GNSS receiver via a communication connection may be utilized to determine a position of the GNSS receiver.

A system and for determining precision navigation solutions decorrelates GPS carrier-phase ambiguities derived from multiple-source GPS information via Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) algorithms. The set of decorrelated floating-point ambiguities is used to compute protection levels and the probability of almost fix (PAF), or the probability that the partial almost-fix solution corresponding to the decorrelated ambiguities is within the region of correctly-fixed or low-error almost-fixed ambiguities. While the PAF remains below threshold and the protection levels remain below alert levels, the optimal navigation solution (floating-point, partial almost-fix, or fully fixed) is generated by fixing the decorrelated ambiguities are one at a time in the LAMBDA domain and replacing the appropriate carrier-phase ambiguities with the corresponding fixed ambiguities, reverting to the last solution if PAF reaches the threshold or if protection levels reach the alert levels.

A system and for determining precision navigation solutions decorrelates GPS carrier-phase ambiguities derived from multiple-source GPS information via Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) algorithms. The set of decorrelated floating-point ambiguities is used to compute protection levels and the probability of almost fix (PAF), or the probability that the partial almost-fix solution corresponding to the decorrelated ambiguities is within the region of correctly-fixed or low-error almost-fixed ambiguities. While the PAF remains below threshold and the protection levels remain below alert levels, the optimal navigation solution (floating-point, partial almost-fix, or fully fixed) is generated by fixing the decorrelated ambiguities are one at a time in the LAMBDA domain and replacing the appropriate carrier-phase ambiguities with the corresponding fixed ambiguities, reverting to the last solution if PAF reaches the threshold or if protection levels reach the alert levels.

A probabilistic system for tracking a state of a vehicle using unsynchronized cooperation of information includes a probabilistic multi-head measurement model relating incoming measurements with the state of the vehicle. The first head of the model relates measurements of the satellite signals subject to measurement noise with a belief on the state of the vehicle, and a second head relates an estimation of the state of the vehicle subject to estimation noise with the belief on the state of the vehicle. A probabilistic filter of the system updates recursively the belief on the state of the vehicle based on the multi-head measurement model accepting one or a combination of the measurements of the satellite signals subject to the measurement noise and the estimation of the state of the vehicle subject to the estimation noise.

A position measuring apparatus for positioning a mobile object includes a positioning control unit that determines a candidate area type of a position of the mobile object in accordance with an attribute of the mobile object and geospatial information, divides a candidate area corresponding to the candidate area type into a plurality of grids, specifies a grid in which the mobile object is estimated to be located from among the plurality of grids, and outputs a positioning solution of a carrier-phase based positioning calculation by an absolute position positioning unit, the positioning solution being obtained by using the grid specified.

A method of determining a posterior error probability distribution for a parameter measured by a Global Navigation Satellite System (GNSS) receiver. The method comprises receiving a value for each of one or more GNSS measurement quality indicators associated with the GNSS measurement of the parameter. The or each received measurement quality indicator value is provided as an input into a multivariate probability distribution model to determine the posterior error probability distribution for the GNSS measurement, wherein the variates of the multivariate probability distribution model comprise error for said parameter, and the or each measurement quality indicator.

A method for determining assistance data to facilitate processing of radio-navigation signals from a set of radio-navigational satellites of a reference network, each radio-navigational satellite broadcasting at least a first radio-navigation signal on a first frequency and a second radio-navigation signal on a second frequency, the second frequency being distinct from the first frequency, is provided.

A method for determining assistance data to facilitate processing of radio-navigation signals from a set of radio-navigational satellites of a reference network, each radio-navigational satellite broadcasting at least a first radio-navigation signal on a first frequency and a second radio-navigation signal on a second frequency, the second frequency being distinct from the first frequency, is provided.

The present disclosure discloses a method for quickly acquiring a highly reliable integer solution for satellite positioning. The method includes: acquiring observation data by a data computing platform from a GNSS receiver; establishing a GNSS carrier observation equation; solving a real solution for ambiguity and the corresponding variance matrix, a real solution for other unknown parameters including positioning parameters and the corresponding variance matrix, and a covariance matrix of the and by using the least squares method; determining integer vectors with the same dimension as the ambiguity according to a given reliability probability; computing a posterior weighted probability with the integer vectors being the true value of the ambiguity; computing an integer solution for other unknown parameters including positioning parameters by using the posterior weighted probability; computing a variance matrix of the integer solution for other unknown parameters; and outputting a computed result by the data computing platform.