# US 10,871,579 B2 · System and method for satellite positioning > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,871,579 B2 - Document ID: US10871579B2 - Status: Granted - Kind: B2 - Application number: 16/685,927 - Filed: 2019-11-15 - Published: 2020-05-21 - Granted: 2020-12-22 - Earliest claimed: 2018-11-16 - Assignees: Swift Navigation, Inc. - Applicants: Swift Navigation, Inc. - Inventors: Benjamin Lipeles Segal; Alexander Thomas Kleeman; Anthony Mark Cole; Matthew Peddie - Web page: https://patentgrep.com/patent/US10871579B2 ## CPC - G01S 19/44: Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method - G01S 5/0054: {of actual mobile position, i.e. position calculation on base station} - G01S 19/04: providing carrier phase data - G01S 19/07: providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections - G01S 19/09: providing processing capability normally carried out by the receiver - G01S 19/258: {relating to the satellite constellation, e.g. almanac, ephemeris data, lists of satellites in view} - G01S 19/37: Hardware or software details of the signal processing chain - G01S 19/393: {Trajectory determination or predictive tracking, e.g. Kalman filtering} - G01S 19/51: Relative positioning - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES ## Abstract A system and method for determining a position of a mobile receiver including receiving a set of satellite observations, the set of satellite observations corresponding to a set of satellites; determining a state vector at each of a plurality of filters, wherein each filter determines the respective state vector based on a unique subset of the set of satellite observations; after a convergence criterion is satisfied, determining a converged state vector based on the respective integer ambiguity hypotheses; and determining the position of the mobile resolver based on the converged state vector. ## Claims ### Claim 1 A method for determining a position of a mobile receiver comprising: receiving, at the mobile receiver, a set of satellite observations, the set of satellite observations comprising code data and carrier phase data, the set of satellite observations corresponding to a set of satellites, wherein the set of satellites correspond to a plurality of satellite constellations, wherein the set of satellite observations are measured during a time period; correcting the set of satellite observations based on a location correction received from a set of reference stations; while a residual value of each of a plurality of Kalman filters remains below an intermediate residual threshold, independently determining an integer ambiguity hypothesis at each of the plurality of Kalman filters, wherein each Kalman filter determines the respective integer ambiguity hypothesis based on a unique subset of the set of satellite observations, wherein the intermediate residual threshold is greater than a mutual residual threshold; determining that the residual value associated with each Kalman filter of the plurality of Kalman filters is less than the mutual residual threshold, wherein the mutual residual threshold is a threshold for differences between the Kalman filters; after each residual value falls below the mutual residual threshold, determining a converged integer ambiguity based on the respective integer ambiguity hypotheses; and determining the position of the mobile receiver based on the converged integer ambiguity. ### Claim 2 (depends on 1) The method of claim 1, wherein each unique subset of the satellite observations comprises nonconsecutive satellite observations from the set of satellite observations. ### Claim 3 (depends on 1) The method of claim 1, further comprising stopping a Kalman filter from the plurality of Kalman filters when the continuing criterion is not satisfied for the respective Kalman filter. ### Claim 4 (depends on 1) The method of claim 1 further comprising: measuring a set of sensor data associated with the time period, wherein the sensor data is associated with an inertial measurement unit (IMU); and wherein each of the set of Kalman filters uses at least a subset of the sensor data to determine the respective integer ambiguity hypothesis. ### Claim 5 A method for determining a position of a mobile receiver comprising: receiving, at the mobile receiver, a set of satellite observations, the set of satellite observations comprising code data and carrier phase data, the set of satellite observations corresponding to a set of satellites, wherein the set of satellite observations are associated with a time period; independently determining an integer ambiguity hypothesis at each of a plurality of filters, wherein each filter determines the respective integer ambiguity hypothesis based on a unique subset of the set of satellite observations; determining that the plurality of filters have collectively converged when a residual value from each filter of the plurality of filters falls below a mutual residual threshold, wherein the mutual residual threshold is a threshold for differences between the filters; after the plurality of filters have collectively converged, determining a converged integer ambiguity based on the respective integer ambiguity hypotheses; and determining the position of the mobile receiver based on the converged integer ambiguity. ### Claim 6 (depends on 5) The method of claim 5, further comprising correcting the set of satellite observations before determining the integer ambiguity hypotheses. ### Claim 7 (depends on 6) The method of claim 6, wherein correcting the set of satellite observations is based on a location correction received from a set of reference stations. ### Claim 8 (depends on 6) The method of claim 6, wherein correcting the set of satellite observations comprises calculating a set of double differenced satellite observations. ### Claim 9 (depends on 5) The method of claim 5, wherein the plurality of filters comprises a Kalman filter. ### Claim 10 (depends on 5) The method of claim 5, wherein each unique subset of the satellite observations comprises nonconsecutive satellite observations from the set of satellite observations. ### Claim 11 (depends on 5) The method of claim 5, wherein each unique subset of the satellite observations comprises consecutive satellite observations from the set of satellite observations. ### Claim 12 (depends on 5) The method of claim 5, wherein two or more of the unique subsets of satellite observations comprise a shared satellite observation from the set of satellite observations. ### Claim 13 (depends on 5) The method of claim 5, wherein each satellite of the set of satellites corresponds to a satellite constellation, wherein the satellite constellation is selected from the group comprising global positioning system (GPS), global navigation satellite system (GLONASS), BeiDou navigation satellite system (BDS), and Galileo. ### Claim 14 (depends on 5) The method of claim 5, wherein every unique subset of the satellite observations comprises at least one satellite observation sampled by a common satellite from the set of satellites. ### Claim 15 (depends on 5) The method of claim 5, wherein determining that the plurality of filters have collectively converged comprises each of the integer ambiguity hypotheses having the same value. ### Claim 16 (depends on 5) The method of claim 5, further comprising determining satisfaction of a continuing criterion for each filter before determining that the plurality of filters have collectively converged. ### Claim 17 (depends on 16) The method of claim 16, further comprising stopping a filter when the continuing criterion is not satisfied for the respective filter. ### Claim 18 (depends on 16) The method of claim 16, wherein determining satisfaction of the continuing criterion for each filter comprises determining that the respective residual value for the filter falls below an intermediate residual threshold. ### Claim 19 (depends on 16) The method of claim 16, wherein the continuing criterion comprises a time threshold corresponding to an amount of time each filter operates. ### Claim 20 (depends on 5) The method of claim 5, wherein for a second time period after the time period, the method further comprises: receiving a second set of satellite observations associated with the second time period; at each of a second plurality of filters, determining a second integer ambiguity hypothesis associated with a second unique subset of the satellite observations; and after determining a second convergence criterion has been met, updating the position of the mobile receiver based on the second integer ambiguity hypotheses. ### Claim 21 (depends on 20) The method of claim 20, wherein the second plurality of filters is distinct from the plurality of filters. ### Claim 22 (depends on 5) The method of claim 5, further comprising: measuring a set of sensor data associated with the time period; and wherein each filters of the plurality of filters uses at least a subset of the sensor data to determine the integer ambiguity hypothesis. ### Claim 23 (depends on 5) The method of claim 5, further comprising updating the unique subsets of the satellite observations based on an estimated convergence time for the respective filter, wherein updating a given unique subset of the satellite observations comprises at least one of: adding satellite observations to or removing satellite observations from the unique subset of the satellite observations.