INCORPORATIONS

The following materials are incorporated by reference for all purposes as if fully set forth herein:Contemporaneously filed U.S. application Ser. No. 17/374,885, titled “Architecture for Providing Forecasts of GNSS Obscuration and Multipath,” filed 13 Jul. 2021, now U.S. Pat. No. 11,287,531, issued 29 Mar. 2022; andContemporaneously filed U.S. application Ser. No. 17/374,882, titled “Improving Accuracy of a GNSS Receiver That Has a Non-Directional Antenna,” filed 13 Jul. 2021; andRecommandation ITU-R P.681-11 (August 2019), Propagation data required for the design systems in the land mobile-satellite service; andReport ITU-R P.2145-2, (September 2017), Model parameters for the physical-statistical wideband model in Recommendation ITU-R P.681; andRecommendation ITU-R P.1407-7, (August 2019), Multipath propagation and parameterization of its characteristics; andGB Application No. 1111305.7, titled Recording, Storage and Playback of GNSS Signals, filed 4 Jul. 2011, now GB Patent No. 2492547, issued 7 Nov. 2018; andU.S. application Ser. No. 13/786,020, titled System and Method for Testing Real World A-GNSS Performance Of A Device, filed 5 Mar. 2013, now U.S. Pat. No. 9,519,063, issued 13 Dec. 2016; andFederal Aviation Administration (FAA) Technical Standard Order (TSO)-C199 for Traffic Awareness Beacon System (TABS)

FIELD OF THE TECHNOLOGY DISCLOSED

The technology disclosed relates to data processing, vehicles, navigation and relative location. The technology disclosed provides for electrical computers, digital data processing systems, and data processing processes for transferring data between a plurality of computers or processes wherein the computers or processes employ the data before or after transferring and the employing affects the transfer of data therebetween.

In particular, the technology disclosed relates to path planning and route planning for rolling autonomous or automated vehicles and for flying autonomous or automated vehicles using a GNSS Forecast that specifies satellite obscurations based on position, time, environmental data and maps. Also disclosed is use by a flight control system with GNSS Forecasts and planned paths for flying vehicles to plan a path or route that has GNSS signals available over the path, and to accommodate real-time changes in flight paths without leaving space.

BACKGROUND

The subject matter discussed in this section should not be assumed to be prior art merely as a result of its mention in this section. Similarly, a problem mentioned in this section or associated with the subject matter provided as background should not be assumed to have been previously recognized in the prior art. The subject matter in this section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.

Connected Autonomous Vehicles (CAV) and vehicles with Advanced Driver-Assisted Systems (ADAS) require reliable GPS sensor information. In one example, an autonomous vehicle needs to have reliable positioning information for safety. The absence of good GPS signal coverage can cause malfunctions in the decision-making logic of an automated or self-driving car, causing it to navigate incorrectly and potentially collide with traffic. In another example, for an Unmanned Aerial System (UAS/drone) being used for package delivery or survey relies upon consistent highly accurate GPS positioning. The result of encountering an area of poor GPS coverage can be the failure of a package delivery, non-compliance with Remote Identification requirements, non-conformance to the approved operational airspace, or even increased risk of collision with other aircraft.

Simulations can be performed before equipment is used in a live setting, in order to minimize risks involved in component or system failure. Testing for receiver equipment exists and is widely used in the industry. Simulation and testing in a design environment ensures that the system has a known performance given a range of signal qualities and types. Modeling and simulation of a signal environment specific to an area of operation is less prevalent.

An opportunity arises for providing dilution of precision (DOP) forecasts for GNSS navigation for routing of vehicles or alerting humans in vehicles, distributing forecasts with more information than a device can estimate from its sensing of the environment that it is in. Moreover, the forecast is done in advance of a vehicle being in the environment and hence can be used for planning and improving integrity. The disclosed technology can improve both real time and route planning for both terrestrial and airborne vehicles, providing improved information about the reliability of the signals being processed by GNSS receivers, and providing the predictions over an Internet cloud architecture to millions of users.

SUMMARY

The technology disclosed addresses path planning using a GNSS Forecast. This includes requesting the GNSS Forecast of signal obscuration on behalf of a vehicle travelling in a region, receiving the requested GNSS Forecast, and using the GNSS Forecast to plan a path or route that has GNSS signals available over the path or route that satisfy a predetermined criterium. Also addressed is using a flight control system with GNSS Forecasts and planned paths or routes for a plurality of flying vehicles, requesting and receiving the GNSS Forecast of signal obscuration on behalf of a flying autonomous or automated vehicle travelling in a region, and using the GNSS Forecast to plan a path or route that has GNSS signals available over the path or route that satisfy predetermined criteria including accommodating real-time changes in flight paths, without leaving space, that satisfies the predetermined criteria, whereby at least some real-time changes in flight paths that would not compromise a diverted flying vehicle's ability meet the requirements of flight control in an airspace.

Particular aspects of the technology disclosed are described in the claims, specification and drawings.

