Spatially resolved and spatially aware antenna for radio navigation
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G01C-021/00
H01R-003/00
출원번호
US-0315872
(2002-12-10)
발명자
/ 주소
Challoner, A. Dorian
Bornholdt, James M.
출원인 / 주소
The Boeing Company
대리인 / 주소
Gates & Cooper LLP
인용정보
피인용 횟수 :
5인용 특허 :
4
초록▼
A method and apparatus for radio navigation and location is disclosed. The method uses an autonomous, on-board micro-inertial navigation system to propagate the state of a station, and an angularly resolvable antenna to measure relative orientation and relative range and to receive estimated state i
A method and apparatus for radio navigation and location is disclosed. The method uses an autonomous, on-board micro-inertial navigation system to propagate the state of a station, and an angularly resolvable antenna to measure relative orientation and relative range and to receive estimated state information from one or more companion stations. Optimally estimated state information is used to permit operation in environments that are otherwise hostile to communications between stations.
대표청구항▼
A method and apparatus for radio navigation and location is disclosed. The method uses an autonomous, on-board micro-inertial navigation system to propagate the state of a station, and an angularly resolvable antenna to measure relative orientation and relative range and to receive estimated state i
A method and apparatus for radio navigation and location is disclosed. The method uses an autonomous, on-board micro-inertial navigation system to propagate the state of a station, and an angularly resolvable antenna to measure relative orientation and relative range and to receive estimated state information from one or more companion stations. Optimally estimated state information is used to permit operation in environments that are otherwise hostile to communications between stations. and (g) injecting said simulated GPS measurement data and said generated IMU simulated electronic signals into said integrated GPS/INS system, wherein when said integrated GPS/INS system is excited in dynamic operation, a performance and reliability of said integrated GPS/INS system are able to be tested and evaluated as if experiencing a real transportation test. 2. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claim 1, in the step (c), wherein said estimator comprises a differential filter for calculating said rover position and said rover velocity by using said simulated rover and reference GPS measurement data, wherein a plurality of Kalman filters are running in parallel in an estimator bank, each of said Kalman filter having a GPS carrier phase integer ambiguity set and a corresponding weight being calculated in a weight bank, wherein a total sum of weights in said weight bank is equal to 1.3. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claim 2, wherein said differential filter is contributed by said estimator bank and said corresponding weight bank, an IASS which is an intermediate ambiguity search strategy, and a search window having a plurality of time epochs, wherein the step (c) further comprises the steps of: (c.1) setting up said search window having said plurality of time epochs; (c.2) searching an integer ambiguity set at said first time epoch of said search window by using said IASS, wherein said integer ambiguity set becomes a member of said estimator bank while there is no member in said estimator bank before said first time epoch, wherein based on said integer ambiguity set and phase measurements, said rover position is estimated in said estimator bank, and then a corresponding weight is calculated in said weight bank, as a result, an optimal rover position for said time epoch is equal to said rover position multiplied by said corresponding weight, and based on said optimal rover position and said Doppler shifts, said rover velocity is estimated; (c.3) following the step (b) first at said second time epoch, searching said integer ambiguity set at said second time epoch of said search window by using said IASS; (c.4) following the step (c.3) for said other time epochs of said search window, wherein at said last time epoch N of said search window, after said search of said IASS, said estimator bank and said corresponding weight bank are completely established; (c.5) following the step (b) first at said (N+1) thtime epoch, inputting said phase measurements into each of said Kalman filters of said differential filter, wherein based on each of said integer ambiguity sets and said phase measurements, an individual rover position is estimated in said estimator bank and each corresponding weight is calculated accumulatively in said weight bank to an associated weight, therefore said optimal rover position is equal to a sum of said individual rover position multiplied by said associated weight, and further based on said optimal rover position and Doppler shifts, said rover velocity is estimated; (c.6) following the step (c.5) after said (N+1) thtime epoch until a criterion is met, wherein after said criterion is met, said estimator bank and said weight bank stop functioning, and during a confirmation period, that is from said first time epoch of said search window to said last time epoch when said estimator bank and said weight bank stop functioning, said estimator bank and said weight bank continuously identify a correct integer ambiguity set and estimate said rover position in real-time, wherein said weight corresponding to said correct integer ambiguity is approaching to one while said other integer ambiguity sets are converging to zero; and (c.7) estimating said rover position and velocity by using said least-squares estimated method after fixing integer ambiguities; as new satellites or cycle slips occur, the process (i.e. steps (c.1)-(c.7)) will be initiated. 4. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claim 3, in the step (c.3), wherein when said integer ambiguity set is same as one of said previous time epoch, said number of said Kalman filter remains, wherein based on said integer ambiguity set and said phase measurements, said rover position is estimated in said estimator bank and said corresponding weight is accumulatively calculated in said weight bank, as a result, said optimal rover position is equal to said rover position multiplied by said associated weight and based on said optimal rover position and said Doppler shifts, said rover velocity is estimated.5. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claim 3, in the step (c.3), wherein when said integer ambiguity set is different from one of said previous time epoch, said current integer ambiguity set becomes a new member of said estimator bank, that is a number of said Kalman filters increases by one, wherein based on each of said integer ambiguity sets and said same phase measurements, an individual rover position is estimated in said estimator bank and a calculation of each corresponding weight is recalculated from scratch in said weight bank, and therefore said optimal rover position is equal to a sum of said individual rover position multiplied by said associated weight, wherein based on said optimal rover position and said Doppler shifts, said rover velocity is estimated.6. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claims 3,4 or5, wherein said IASS comprises the steps of: resolving primary double difference wide lane ambiguities in a primary double difference wide lane ambiguity resolution module, wherein a priori information of said rover position obtained from ionosphere-free pseudorange measurements and an approximated double difference wide lane ambiguities are combined with said primary double difference wide lane phase measurements to estimate said rover position and said primary double difference wide lane ambiguities; establishing an ambiguity search domain based on said estimated primary double difference wide lane ambiguities and said corresponding cofactor matrix; searching for an ambiguity set by using a “simplified” least-squares search estimator; computing said rover position based on said fixed primary double difference wide lane ambiguities in a position calculation module; fixing secondary double difference wide lane ambiguities by applying said primary wide-lane-ambiguity-fixed rover position solution into said secondary double difference wide lane phase measurements; calculating approximated double difference narrow lane ambiguities and then using said extrawidelaning technique module to resolve double difference narrow lane ambiguities; and calculating a L 1 and L2 ambiguities in a L1 and L2 ambiguity resolution module from said combination of said double difference wide lane ambiguities and said double difference narrow lane ambiguities.7. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claim 6, after the above step (g), further comprises an additional step of collecting test data from s aid integrated GPS/INS system by a data acquisition and performance evaluation system connected between said 6DOF trajectory generator and said integrated GPS/INS system, so as to compare said real-time trajectory data from said 6DOF trajectory generator with integrated GPS/INS estimated vehicle trajectory data output from said integrated GPS/INS system in order to evaluate whether said integrated GPS/INS system works properly.8. A process of coupled real-time GPS/IMU simulation with differential GPS, as recited in claims 1,2,3,4 or5, after the above step (g), further comprises an additional step of collecting test data from said integrated GPS/INS system by a data ac quisition and performance evaluation system connected between said 6DOF trajectory generator and said integrated GPS/INS system, so as to compare said real-time trajectory data from said 6DOF trajectory generator with integrated GPS/INS estimated vehicle trajectory data output from said integrated GPS/INS system in order to evaluate whether said integrated GPS/INS system works properly.9. A coupled real-time GPS/IMU simulation system, adapted to connect between a 6DOF trajectory generator and an integrated GPS/INS system, comprising: an IMU signal generator which includes a GPS simulation input/output interface and an IMU simulation input/output interface; a simulation computer which comprises a GPS simulation module for performing GPS simulation and an IMU simulation module for performing IMU simulation, wherein said GPS simulation module receives real-time trajectory data from said 6DOF trajectory generator and generates dynamic and static GPS measurements including pseudoranges, carrier phases, and Doppler shifts, and positioning information including location information and velocity information, said dynamic and static GPS measurements being formatted to simulated GPS measurement data which are sent through said GPS simulation input/output interface to said GPS simulation module for GPS tracking loop aiding to facilitate said integrated GPS/INS system, said IMU simulation module receiving said real-time trajectory data from said 6DOF trajectory generator and producing IMU simulated measurements, said IMU simulation input/output interface projecting said IMU measurements into specific simulated electronic signals; and a signal regulator and connector board for converting electronic signals from said IMU simulation input/output interface into said simulated electronic signals, wherein said simulated electronic signals, coupled with said simulated GPS measurement data, are injected into said integrated GPS/INS system which causes an on-board GPS/INS navigation computer installed therein into working as if experiencing a real transportation test. 10. A coupled real-time GPS/IMU simulation system, as recited in claim 9, wherein said GPS simulation module comprises: a GPS satellite constellation simulation which is triggered by said real-time trajectory data from said 6DOF trajectory generator for reading orbit parameters, satellite clock parameters, and atmospheric parameters from ephemeris data, which are stored in said GPS/IMU simulation computer of said coupled real-time GPS/IMU simulation system, and calculating a position and velocity vector for GPS satellites in an Earth-Centered-Earth-Fixed coordinate system which is connected between said 6DOF trajectory generator and said simulation computer; user positions which are given by and based on said 6DOF trajectory data respectively; a GPS satellite prediction using an information from said GPS satellite constellation simulation and said user positions to determine visible GPS satellites and elevation, azimuth, and Doppler shifts thereof; a GPS Error Models for using said information from said GPS satellite constellation simulation and a user initial position of said user positions to calculate error correction terms, including satellite clock correction, relativistic, ionospheric delay, tropospheric delay, and group delay; a jamming model and effect simulation for simulating an impact of jamming on GPS signal reception, wherein an array of jammers defined by location, type, and effective radiating power is constructed and input to said jamming model and effect simulation; a raw data generation using information from said user positions, said GPS satellite prediction, said GPS error models, and said jamming model and effect simulation to calculate simulated pseudorange, carrier phase, and delta range for said visible satellites; an estimator for calculating the GPS rover position and velocity using simulated raw data from said raw data generation ; and a data formatting means for formatting said position and velocity information and said simulated raw data along with said ephemeris data according to a specific protocol, wherein said data formatting means is an integral part which allows said simulated GPS measurement data having a format identical to a real GPS receiver used in said integrated GPS/INS system. 11. A coupled real-time GPS/IMU simulation system, as recited in claim 10, wherein said estimator comprises a Kalman filter which calculates said rover position and velocity by using said simulated rover GPS measurement data.12. A coupled real-time GPS/IMU simulation system, as recited in claim 11, wherein said estimator further comprises a differential filter which calculates said rover position and velocity by using said simulated rover and reference GPS measurement data.13. A coupled real-time GPS/IMU simulation system, as recited in claim 10, wherein said estimator comprises a differential filter which calculates said rover position and velocity by using said simulated rover and reference GPS measurement data.14. A coupled real-time GPS/IMU simulation system, as recited in claim 9, wherein said GPS simulation module comprises: a GPS satellite constellation simulation which is triggered by said 6DOF trajectory data from said 6DOF trajectory generator for reading orbit parameters, satellite clock parameters, and atmospheric parameters from ephemeris data, which are stored in said GPS/IMU simulation computer of said coupled real-time GPS/IMU simulation system, and calculating a position and velocity vector for GPS satellites in an Earth-Centered-Earth-Fixed coordinate system which is connected between said 6DOF trajectory generator and said simulation computer; user positions which are given by and based on said 6DOF trajectory data respectively; a GPS satellite prediction using information from said GPS satellite constellation simulation and a user initial position to determine visible GPS satellites and the elevation, azimuth, and Doppler shifts thereof; a GPS Error Models for using said information from said GPS satellite constellation simulation and said user initial position to calculate error correction terms, including satellite clock correction, relativistic, ionospheric delay, tropospheric delay, and group delay; a jamming model and effect simulation for simulating an impact of jamming on GPS signal reception, wherein an array of jammers defined by location, type, and effective radiating power is constructed and input to said jamming model and effect simulation; an input signal simulation for generating a GPS spread spectrum signal at an intermediate frequency (IF), which comprises a noise generation for generating a white noise using a random number method, a carrier generation for creating a sine wave at a defined intermediate frequency, a code generation adapted for selectively generating a coarse acquisition (C/A) code and a precision (P) code, a first multiplier for multiplying said white noise from said noise generation and said sine signal from said carrier generation and a second multiplier for multiplying an output of said first multiplier by said C/A code or P code generated by said code generation; a tracking loop and signal processing simulation for accurately representing characteristics and performance of a real GPS receiver, wherein a modulated IF signal coming from said input signal simulation is an input signal of said tracking loop and signal processing simulation, said tracking loop and signal processing simulation comprising a carrier phase correction for driving a carrier DCO to generate said sine wave at said tracked frequency that is close to said intermediate frequency (IF), a deviation between said tracked frequency of said generated sine wave and said input IF being called frequency tracking error, and a code phase correction for driving a code generation to produce said C/A code or P code same as said cod
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이 특허에 인용된 특허 (4)
Johnson William M. (Sudbury MA) Musoff Howard (Brookline MA), Apparatus and method for autonomous satellite attitude sensing.
Challoner A. Dorian (Manhattan Beach CA) von der Embse U. A. (Westchester CA) Mitchell Mark P. (Playa del Rey CA) Chang Donald C. D. (Thousand Oaks CA) Fowell Richard A. (Palos Verdes Estates CA) Hua, Satellite attitude determination and control system with agile beam sensing.
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