METHOD AND APPARATUS FOR AUTONOMOUS, IN-RECEIVER PREDICTION OF GNSS EPHEMERIDES

• US 20100060518A1
• Filed: 09/11/2008
• Published: 03/11/2010
• Est. Priority Date: 09/11/2008
• Status: Active Grant

• Current Assignee: California Institute of Technology
• Original Assignee: California Institute of Technology
• Inventors: Bertiger, William I., Bar-Sever, Yoaz E.
• Granted Patent: US 8,120,529 B2
• Time in Patent Office: Days
• US Class Current: 342/357.640
• CPC Class Codes: G01S 19/27 creating, predicting or correcting ephemeris or almanac data within the receiver

Abstract

Methods and apparatus for autonomous in-receiver prediction of orbit and clock states of Global Navigation Satellite Systems (GNSS) are described. Only the GNSS broadcast message is used, without need for periodic externally-communicated information. Earth orientation information is extracted from the GNSS broadcast ephemeris. With the accurate estimation of the Earth orientation parameters it is possible to propagate the best-fit GNSS orbits forward in time in an inertial reference frame. Using the estimated Earth orientation parameters, the predicted orbits are then transformed into Earth-Centered-Earth-Fixed (ECEF) coordinates to be used to assist the GNSS receiver in the acquision of the signals. GNSS satellite clock states are also extracted from the broadcast ephemeris and a parametrized model of clock behavior is fit to that data. The estimated modeled clocks are then propagated forward in time to enable, together with the predicted orbits, quicker GNSS signal acquision.

Claims

1. A method to autonomously predict satellite orbit information in Earth-centered-Earth-fixed (ECEF) coordinates for aiding a satellite receiver, comprising:

i) obtaining a broadcast orbital ephemeris of the satellite;

ii) iteratively estimating orbital position, velocity, and dynamic parameters of the satellite based on a satellite dynamics model, and iteratively estimating Earth orientation parameters (EOP) based on an Earth orientation model, until convergence is obtained;

iii) propagating the estimated orbital position, velocity and dynamic parameters forward in time through the satellite dynamics model, thus obtaining predicted orbits;

iv) converting the predicted orbits to Earth-centered-Earth-fixed (ECEF) coordinates through the Earth orientation model; and

v) storing the converted predicted orbits.

2. The method of claim 1, wherein orbit information of a plurality of satellites is autonomously predicted by applying steps i), ii), iii), iv and v) to the plurality of satellites.

3. The method of claim 1, wherein EOP values and their covariance matrix estimated from one satellite data, are optimally combined with estimates of EOP and covariance from other satellites data.

4. The method of claim 1, wherein the EOP comprise X polar motion, Y polar motion, and length of day (LOD).

5. The method of claim 1, further comprising converting the obtained broadcast orbital ephemeris of the satellite from a first coordinate system to a second coordinate system.

6. The method of claim 5, further comprising, during the iterative estimation, calculating sensitivities of the converted broadcast orbital ephemeris to EOP.

7. The method of claim 5, wherein the first coordinate system is an Earth-centered-Earth-fixed (ECEF) Cartesian coordinate system and the second coordinate system is an Earth-centered-inertial (ECI) coordinate system.

8. The method of claim 1, wherein the satellite and the receiver are part of a Global Navigation Satellite System (GNSS).

9. The method of claim 2, wherein the plurality of satellites and the receiver are part of a Global Navigation Satellite System (GNSS).

10. The method of claim 1, wherein the broadcast ephemeris of the satellite is obtained through a sampling process.

11. The method of claim 10, wherein the sampling process occurs at least three times a day.

12. The method of claim 10, wherein the sampling process occurs with a daily periodicity-avoiding sampling frequency.

13. The method of claim 12, wherein the sampling frequency is selected from the group consisting of a 7-hour interval sampling frequency, and a 10-hour interval sampling frequency.

14. The method of claim 3, wherein the Earth orientation model is based on a parametric fit to historic time series of measured EOP values.

15. The method of claim 1, wherein step ii) is performed through a least squares fit to satellite states.

16. The method of claim 15, wherein the satellite states are Earth-centered-Earth-fixed (ECEF) satellite states.

17. The method of claim 16, wherein the least squares fit is solved through a square root information filter (SRIF) factorization approach.

18. The method of claim 1, wherein convergence of step ii) is obtained a) when currently estimated orbital position, velocity, and orbital dynamic parameters are sufficiently close to the broadcast ephemeris for that satellite or b) when the currently estimated orbital position, velocity condition and orbital dynamic parameters are sufficiently close to their preceding values.

19. The method of claim 1, wherein the predicted orbits are stored in the satellite receiver.

23. A method for autonomous prediction of satellite orbit information and satellite clock states, comprising:

autonomously predicting satellite orbit information according to the method of claim 1; and

autonomously predicting satellite clock states according to the method of claim 20.

25. The GNSS receiver of claim 24, wherein the software code for satellite orbit prediction operates according to the method of claim 1, and the software code for satellite clock states prediction operates according to the method of claim 20.

20. A method to autonomously predict satellite clock states, comprising:

i) obtaining broadcast clock records for the satellite;

ii) iteratively estimating future clock states of the satellite based on a prediction model, until convergence is obtained; and

iii) storing the estimated clock states for autonomous prediction of the satellite clock states.

21. The method of claim 20, wherein clock states of a plurality of satellites are autonomously predicted by applying steps i), ii) and iii) to the plurality of satellites.

22. The method of claim 20, wherein the prediction model is quadratic in time plus a once-per revolution harmonic, resulting in five model parameters per satellite.

24. A Global Navigation Satellite System (GNSS) receiver comprising:

a processing unit; and

a memory unit,

wherein the memory unit is configured to comprise;

a first memory section storing software code for satellite orbit prediction and satellite clock states prediction;

a second memory section storing recorded satellite broadcast orbit and satellite clock states;

a third memory section storing Earth orientation parameter (EOP) values and orbital dynamic parameters; and

a fourth memory section storing predicted satellite orbits and satellite clock states calculated in accordance with the software code stored in the first memory section.

26. A personal navigation device comprising the GNSS receiver of claim 24.

27. The personal navigation device of claim 26, said device being a cell phone or a car navigation device.