Trimble Inc.

Trimble Navigation Limited

Ralf Drescher

Xiaoming Chen

Rodrigo Leandro

Some embodiments of the present invention derive an ionospheric phase bias and an ionospheric differential code bias (DCB) using an absolute ionosphere model, which can be estimated from data obtained from a network of reference stations or obtained from an external source such as WAAS, GAIM, IONEX or other. Fully synthetic reference station data is generated using the ionospheric phase bias and/or the differential code bias together with the phase leveled clock and ionospheric-free code bias and/or MW bias.

GNSS signal processing with ionosphere model for synthetic reference data

The invention relates to generating correction information to be used to correct observations coming from a navigation satellite system (NSS) receiver in a region of interest. For each of a plurality of reference stations in said region, raw observations obtained by the reference station observing NSS multiple-frequency signals from a plurality of satellites over multiple epochs are received. Then, precise satellite information on the orbit position, clock offset, and biases of each satellite is obtained. For each reference station, ambiguities in the carrier phase of the received raw observations are estimated, using the precise satellite information and the position coordinates of the reference station. Geometric-free phase linear combination values are then computed based on the received raw observations together with the estimated ambiguities. The correction information is generated based on the computed geometric-free phase linear combination values. The correction information comprises, for each NSS satellite, a regional ionospheric delay function and its coefficients, those representing, per NSS satellite, the ionospheric delay in said region. The correction information is sent, for example to facilitate position determination, to the NSS receiver or to a server in charge of processing observations from the NSS receiver.

Navigation satellite system positioning involving the generation of correction information

The invention relates to generating regional tropospheric correction information for correcting observations useful for estimating phase ambiguities and/or a position of global or regional navigation satellite systems (NSS) receiver(s). For each of a plurality of reference stations, at least one troposphere correction parameter is estimated by evaluating NSS observation equations using i) precise satellite information or the information derived from the precise satellite information, and ii) received multiple-frequency-signals-based raw observations or a linear combination thereof. The regional tropospheric correction information is then generated based on the estimated troposphere correction parameter(s) per reference station, the tropospheric correction information comprising a regional tropospheric delay function(s) and coefficients representing a tropospheric delay affecting a NSS signal passing through the troposphere in a region of interest. The generated tropospheric correction information may then be sent to NSS receiver(s) and used by the receiver(s) for example to facilitate position determination.

Navigation satellite system positioning involving the generation of advanced correction information

Accuracy information for an ionosphere model is generated. Phase residual information of a parameter estimation procedure is obtained and coordinates of pierce points are computed on a sphere around the earth. The coordinates indicate where signals pierce the sphere. Phase residual information is mapped for each pierce point. A grid of equidistant points is put on the sphere and the pierce points are identified. For each selected grid point, vertical accuracy information is computed based on vertical residual information, and a scale factor is computed based on the vertical accuracy information. The accuracy information for the ionosphere model is generated based on the vertical accuracy information computed for the selected grid points and an overall scale factor computed based on computed scale factors.

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Hoehenkirchen, Germany

Ralf Drescher