METHOD FOR FUSING MULTIPLE GPS MEASUREMENT TYPES INTO A WEIGHTED LEAST SQUARES SOLUTION
First Claim
1. A method of calculating position data for an airborne aircraft using a GPS-based airborne navigation system, comprising processing a position component of a relative state function by fusing a plurality of different types of measurement data axailable in the GPS-based system into a weighted least squares algorithm to determine an appropriate covariance matrix for the plurality of different types of measurement data.
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Accused Products
Abstract
A method of calculating position data for an airborne aircraft using a GPS-based airborne navigation system includes the processing of a position component of a relative state function by fusing a plurality of different types of measurement data available in the GPS-based system into a weighted least squares algorithm to determine an appropriate covariance matrix for the plurality of different types of measurement data.
27 Citations
36 Claims
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1. A method of calculating position data for an airborne aircraft using a GPS-based airborne navigation system, comprising processing a position component of a relative state function by fusing a plurality of different types of measurement data axailable in the GPS-based system into a weighted least squares algorithm to determine an appropriate covariance matrix for the plurality of different types of measurement data.
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2. A method for calculating position. velocity, and acceleration data for an airborne craft using a GPS based navigation system. comprising:
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processing position. velocity, and acceleration components of a relative state function by fusing a plurality of measurement data types into a weighted least squares algorithm; and determining an appropriate covariance matrix for the plurality of measurement data types, wherein errors in the position, velocity and acceleration data are minimized. - View Dependent Claims (3, 4, 5, 6, 7, 8, 27)
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9. An apparatus for calculating position velocity and acceleration data for an airborne aircraft using a GPS based navigation system, comprising:
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a data acquisition device operable to acquire a plurality of measured position, velocity and acceleration data types using the GPS based navigation system; and a calculating device operable to fuse the plurality of measured data types in a weighted least squares algorithm, whereby an appropriate covariance matrix is determined for the plurality of data types such that errors in the position, velocity and acceleration data are minimized. - View Dependent Claims (10, 11, 12, 13)
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14. An airborne navigation system for calculating position, velocity and acceleration data for an airborne aircraft using a GPS based navigation system, comprising:
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a plurality of GPS data acquisition devices operable to determine a plurality of position, velocity and acceleration data types of a ship and the airborne aircraft; and a calculating component operable to fuse the plurality of data types in a weighted least squares algorithm, so as to determine an appropriate covariance matrix for the plurality of data type such that errors in the position, velocity and acceleration data are minimized. - View Dependent Claims (15, 16, 17, 18)
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19. A method of calculating position data of a moving craft by fusing different types of measurement data, comprising:
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transmitting Global Positioning System (GPS) measurement data from a GPS satellite constellation to the moving craft; computing position. velocity, and estimated wide lane phase ambiguity data by a reference location employing a weighted least squares algorithm; transmitting the computed data from the reference location to the moving craft; and combining the measurement data and the computed data by the moving craft to produce a relative vector solution between its own location and the reference location. - View Dependent Claims (20, 21, 32)
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22. A method of calculating a relative position and a velocity vector between a ship and an airborne aircraft and providing this information as basic relative state (BRS) data and precision relative state (PRS) data to the aircraft by employing a weighted least squares algorithm, the method comprising:
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calculating Double-Difference measurements at a ship time; determining Wide Lane Float Ambiguities and a covariance value; determining first and second frequency float ambiguities and a covariance calculation from the Double-Difference measurements, the Wide Lane Float Ambiguities. and the covariance value; calculating a PRS solution of the aircraft from the first and second frequency float ambiguities and the covariance calculation; computing a BRS solution and a BRS covariance value at an aircraft time; and transmitting the BRS and PRS solutions to the aircraft.
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23. A method of calculating a Precision Relative State (PRS) solution for an airborne navigation system by processing a plurality of different types of measurement data, comprising:
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computing code range and phase range values from measurements and variances from satellite data; selecting measurement data values having the smallest variance from the computed code range and phase range values; assembling the selected data for a covariance matrix elements calculation; building the covariance matrix by calculating values for its elements; and calculating the PRS solution and its covariance using the covariance matrix by a weighted least squares (WLS) algorithm - View Dependent Claims (24, 25)
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26. A landing system for an airborne aircraft, comprising:
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a reference location having means for computing and transmitting reference location position, velocity, and estimated wide lane phase ambiguity data using a weighted least squares algorithm; a GPS satellite constellation operable to transmit GPS measurement data; a receiver on the moving craft that is operable to receive the measurement data from the GPS satellite constellation and the computed data from the reference location; and a calculating system associated with the receiver that is operable to calculate position data for the aircraft by ftising the measurement data and the reference data with a weighted least squares (WLS) algorithm. - View Dependent Claims (28, 29)
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30. An Airborne Relative Navigation (RelNav) system for calculating a relative position and a velocity vector between a ship and an airborne aircraft and for providing this information as relative state to the aircraft, comprising:
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a Measurement Management and Validation function that processes and validates incoming measurement data; a Relative Measurements function that calculates Double-Difference measurements and variance components from Single-Difference measurements; a Wide Lane Ambiguities function that determines wide lane float ambiguities and a first covariance value; an ambiguities function that determines first and second frequency float ambiguities and a second covariance value; and a relative state function that computes a relative state and covariance solution from the wide lane float ambiguities, the first covariance value, the firs and second frequency float ambiguities and the second covariance alue. and that provides the solution to an avionic system on the aircraft using a weighted least squares algorithm. - View Dependent Claims (31)
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33. A Precision Relative State (PRS) computational module for calculating a PRS solution for an airborne navigation system, employing a weighted least squares (WLS) algorithm for processing a plurality of different types of measurement data, comprising:
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an input computing module operable to compute code range and phase range values from measurement and covariance data from a satellite; a data selection module operable to select data based on measurement variances; a covariance matrix-building module operable to assemble data for a covariance matrix element calculation; a covariance matrix element calculation module for determining values for the covariance matrix elements; and a PRS solution calculation module operable to calculate the PRS solution and its covariance using the covariance matrix by the WLS algorithm. - View Dependent Claims (34, 35, 36)
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Specification