Rx Networks Inc.

Guylain Roy-Machabee

Mohamed Youssef

Ashkan Izadpanah

James W LaMance

Maria Eagen

Eric Derbez

Dave Cayer

James W Lamance

A method of determining a location of a mobile device includes: detecting, at the mobile device, at least one Radio Frequency transmitter; receiving information associated with a number of Radio Frequency transmitters located within a geographical area, the number of Radio Frequency transmitters being a subset of all Radio Frequency transmitters located within the geographical area, the information being decodable to provide global locations and identifiers of the number of Radio Frequency transmitters; comparing an identifier associated with the at least one detected Radio Frequency transmitter with the global locations and identifiers of the number of Radio Frequency transmitters; and determining the location of the mobile device within the geographical area; wherein the information is received in a reduced format.

Geo-reference based positioning of a mobile device

A method of determining a location of a mobile device includes: detecting, at the mobile device, at least one Radio Frequency transmitter; receiving information associated with a number of Radio Frequency transmitters located within a geographical, area, the number of Radio Frequency transmitters being a subset of all Radio Frequency transmitters located within the geographical area, the information being decodable to provide global locations and identifiers of the number of Radio Frequency transmitters; comparing an identifier associated with the at least one detected Radio Frequency transmitter with the global locations and identifiers of the number of Radio Frequency transmitters; and determining the location of the mobile device within the geographical area; wherein the information is received in a reduced format.

A method of predicting a location of a satellite is provided wherein the GPS device, based on previously received information about the position of a satellite, such as an ephemeris, generates a correction acceleration of the satellite that can be used to predict the position of the satellite outside of the time frame in which the previously received information was valid. The calculations can be performed entirely on the GPS device, and do not require assistance from a server. However, if assistance from a server is available to the GPS device, the assistance information can be used to increase the accuracy of the predicted position.

Autonomous orbit propagation system and method

A mobile device includes a processor for generating a predicted orbital state vector using an initial satellite position and velocity and force model parameters received from a server, the predicted orbital state vector being used to generate satellite navigation data; and a GNSS receiver in communication with the processor for receiving the satellite navigation data; wherein the satellite navigation data is valid for a time period.

Distributed orbit modeling and propagation method for a predicted and real-time assisted GPS system

A distributed orbit and propagation method for use in a predicted GPS or GNSS system, which includes a predicted GPS server (PGPS Server), a source of high accuracy orbit predictions (Orbit Server), a global reference network (GRN Server) providing real-time GPS or GNSS assistance data to the PGPS Server, a predicted GPS client (PGPS Client) running on a device equipped with a GPS or AGPS chipset. In response to requests from the PGPS Client, the PGPS Server produces and disseminates an initial seed dataset consisting of current satellite orbit state vectors and orbit propagation model coefficients. This seed dataset enables the PGPS Client to locally predict and propagate satellite orbits to a desired future time. This predictive assistance in turn helps accelerate Time To First Fix (TTFF), optimize position solution calculations and improve the sensitivity of the GPS chip present on, or coupled with, the device. In contrast with other conventional predicted GPS systems that forward large volumes of predicted orbits, synthetic ephemeris or synthetic almanac data, this method optimally reduces data transfer requirements to the client, and enables the client to locally synthesize its own predicted assistance data as needed. This method also supports seamless notification of real-time satellite integrity events and seamless integration of predicted assistance data with industry standard real-time assistance data.

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Vancouver, Canada

Guylain Roy-Machabee