Assisted Global Navigation Satellite System (AGNSS) with Precise Ionosphere Model Assistance

• US 20130021201A1
• Filed: 09/27/2011
• Published: 01/24/2013
• Est. Priority Date: 07/19/2011
• Status: Abandoned Application

• Current Assignee: Avago Technologies General IP PTE Limited (Broadcom, Inc.)
• Original Assignee: Broadcom Corporation (Broadcom, Inc.)
• Inventors: Lundgren, David Albert, LaMance, James, del CASTILLO, Manuel
• Application Number:
  US13/246,480
• Publication Number:
  US 20130021201A1
• Time in Patent Office: Days
• US Class Current: 342/357.59
• CPC Class Codes: G01S 19/071 DGPS corrections

Abstract

Embodiments enable higher accuracy GNSS performance by generating local/regional ionosphere models tailored to specific local/regional areas of interest and by using location-based delivery of the local/regional ionosphere models to mobile GPS receivers. Different types and levels of reference locations (e.g., Cell ID (CID), Location Area Code (LAC), Radio Network Controller ID (RNC-ID), Mobile Country Code (MCC)) can be used to estimate the location of mobile GPS receivers and to deliver the appropriate local/regional ionosphere models to the mobile GPS receivers. According to embodiments, the local/regional ionosphere models are fit into the same 8-parameter set as the broadcast global ionosphere model, therefore being compatible with existing GPS receivers that accept the broadcast global ionosphere model.

Claims

1. A method of providing precise ionosphere model assistance to a mobile Global Positioning System (GPS) receiver, comprising:

selecting a region of interest;

retrieving historical ionosphere data for the selected region of interest;

generating predictions of ionospheric delays for the selected region based on the historical ionosphere data;

fitting the predictions of ionospheric delays to a standard GPS ionosphere model to generate a predictive ionosphere model for the selected region; and

storing the predictive ionosphere model in a database.

2. The method of claim 1, wherein the region of interest represents a geographical area represented by a latitude range and a longitude range.

3. The method of claim 1, wherein the historical ionosphere data includes localized ionospheric delays generated by a reference network.

4. The method of claim 1, wherein the historical ionosphere data includes broadcast ionospheric delays sent by a Wide Area Augmentation System (WAAS).

5. The method of claim 1, wherein the historical ionosphere data includes historical ionospheric delays stored in a database.

6. The method of claim 5, wherein the database includes a Crustal Dynamics Data Information System (CDDIS) database.

7. The method of claim 1, wherein the historical ionosphere data includes ionospheric delays for the selected region of interest over a K-day period, wherein K is any integer number.

8. The method of claim 1, wherein the historical ionosphere data includes a plurality of grid maps, each grid map having a respective time tag that indicates a validity time-of-day for the grid map.

9. The method of claim 8, wherein each grid map includes a plurality of grid lines, each grid line including ionospheric delays for a respective sub-region within the selected region of interest.

10. The method of claim 1, further comprising:

augmenting the historical ionosphere data prior to said generating step.

11. The method of claim 1, wherein said generating step comprises:

generating predicted ionospheric delays for a future N-day period based on historical ionospheric delays for a past K-day period, where N and K are integer numbers.

12. The method of claim 11, wherein the predicted ionospheric delays for the future N-day period are generated by averaging the historical ionospheric delays for the past K-day period.

13. The method of claim 11, wherein N is equal to 10 and K is equal to 5.

14. The method of claim 1, wherein said fitting step comprises:

applying one or more of a least mean squares error (LMSE), Kalman filtering, linear search, and non-linear search algorithm to the predictions of ionospheric delays to generate a plurality of model parameters of the standard GPS ionosphere model.

15. The method of claim 14, wherein the plurality of model parameters include 8 Klobuchar parameters.

16. The method of claim 1, wherein the method is performed by an Assisted GPS (AGPS) processing site.

17. The method of claim 1, further comprising:

retrieving the predictive ionosphere model from the database; and

sending the predictive ionosphere model to a mobile GPS receiver determined to be within the selected region.

18. The method of claim 17, wherein the predictive ionosphere model is sent to the mobile GPS receiver using Assisted GPS (AGPS).

19. The method of claim 17, further comprising:

determining a reference location associated with the mobile GPS receiver, wherein the reference location estimates a current position of the mobile GPS receiver.

20. The method of claim 19, wherein the reference location associated with the mobile GPS receiver includes one of a wireless network cell ID (CID), a Location Area Code (LAC), a Radio Network Controller ID (RNC-ID), and a Mobile Country Code (MCC).

21. The method of claim 1, wherein the region of interest is defined by a wireless network cell ID (CID) associated with a mobile GPS receiver.