Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2003-06-17
2004-09-14
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C701S002000
Reexamination Certificate
active
06792363
ABSTRACT:
BACKGROUND
1. Field of the Invention
The present invention relates generally to trajectory optimization of vehicles, such as airborne vehicles. More specifically, the present invention relates to routing optimization using adaptive navigation performance estimation.
2. Background of the Invention
Uninhabited autonomous vehicles (UAV) are utilized for various purposes in industries such as in the defense industry. These vehicles often travel according to predetermined routes that are often planned in advance using optimization routines that check the potential route for success or failure based on various criteria. UAVs rely mainly on an integrated navigation system for an estimate of their navigation state. When traveling unobstructed, the UAV processes information from global positioning satellites (GPS) and inertial sensors to determine if it is traveling along its prescribed route. If GPS access is lost, for example due to an obstruction, the UAV's navigation system begins operating in the free-inertial navigation solution for guidance.
Unlike the GPS-aided navigation mode, the GPS/Inertial Navigation Systems (INS) in the free-inertial mode can develop unbounded errors over time. GPS errors may increase due to poor satellite visibility. The INS error growth rate is dependent on previous maneuvers while GPS is available and also on maneuvers made after GPS is lost. For example, error growth rate on a straight trajectory is less than error growth rate on a trajectory that includes turns or rapid changes in elevation. The UAV can be directed to make certain maneuvers prior to the loss of GPS to calibrate the inertial sensors, resulting in enhanced performance in areas where GPS is obstructed. In addition, information from a Kalman filter may be used before the flight to predict error bounds, or during the flight in real-time to determine whether or not the UAV is flying within its planned flight corridor.
Traditionally air traffic has been controlled using predetermined routes and flight procedures to ensure sufficient separation between various aircraft as well as to ensure sufficient distance from structures and other obstacles. Today's practices often result in planes moving along a tortuous route from point to point along predetermined corridors.
Recently, the Federal Aviation Administration (FAA) has put forth a concept called free flight that will serve as the operating paradigm for future air traffic control. This change will require new concepts of shared responsibility between controllers and aircraft operators. Currently, controllers assign routes, altitudes, and speeds. Under the new system, aircraft operators can change these parameters in real time. Controllers would only intervene to ensure that aircraft remain at safe distances from one another. The free flight environment will also enable individual aircraft to minimize operating costs. One key to the success of free flight is the detection of conflicts and determination of appropriate strategies for resolving conflict among aircraft.
In addition to free flight used in commercial aviation, route planning systems are in place that plan predetermined routes for UAVs or vehicles with automated piloting systems that may travel low to the ground and thus encounter many obstacles. In this application, route planning is specifically described in regard to airborne vehicles. The route planning process described herein, however, may be applicable to any vehicle capable of traveling along a predetermined route and is not limited solely to aircraft.
Current systems develop a flight plan and utilize a fixed estimated error that estimates errors due to factors such as, for example flight technical error, wind, and navigation error, to determine if the proposed route will be a success. All errors may be specified statistically. For example, the expected position error is often set at 10 m (Spherical Error Probable (SEP)). As used in this application, fixed estimated error denotes a single error factor estimated in advance and used throughout a route performance evaluation to determine success or failure of the route. Estimated error, or error factor, in general denotes potential deviation from the predetermined route. For example, a specific error factor would provide a buffer zone around the predetermined route. If an obstacle were to fall within that buffer, the route would be deemed a failure. The smaller the error factor, the smaller the buffer.
If the route fails, that is an obstacle falls within the fixed estimated error or buffer zone, the route is recalculated to ensure that all obstacles will be avoided. Because the error factors used in these calculations are merely estimations, it may be possible that a craft could actually navigate a route that does not pass the failure analysis, but because the perceived likelihood of a collision is too high, that route is not chosen. This results in a recalculation of the route and often means a longer and more costly flight path. Thus, there is a need for a trajectory planning system capable of determining flight paths for free flight as well as optimizing predetermined routes for unmanned aircraft that minimizes the error used. In the invention this is achieved by dynamically estimating the error.
BRIEF SUMMARY OF THE INVENTION
According to one aspect of the invention, a method for optimizing a route of a vehicle includes planning an initial route using rules to estimate navigation system performance, wind error, flight technical error, and to enhance accuracy of the navigation system and then utilizing a navigation performance prediction tool to evaluate possible success of the initial route. The error may be calculated by dynamically estimating the error and utilizing the dynamic error estimate to evaluate possible success of alternate routes. If the initial route is deemed a failure, the rules may be used to designate at least one error correcting maneuver to be added to the initial route to reduce error and then the error of the initial route including the error correcting maneuver may then be recalculated using the navigation prediction process to compute the dynamic estimated error. The possible success of the initial route including the error correcting maneuver is therefore evaluated. The methods of alternate routes and error correcting maneuvers may be repeated in whole or in part until a satisfactory route is obtained. Alternately, the dynamic error estimate could be computed concurrently with the computation of the initial route with the rules rather than computing the dynamic error estimate after the initial route has been completely defined
Additionally, during an actual mission, the navigation system may, in real-time, dynamically compute its estimate of the system's navigation error. The estimated error may be compared to the allowed navigation, flight technical, and wind errors for each segment of the mission. If the estimate of the real-time dynamic estimated error exceeds the allowed error then the route is dynamically re-planned to ensure that the vehicle travels through a flight corridor that is wide enough to allow for the estimated navigation, flight technical, and wind errors that will occur in that corridor. Alternatively, the system may add error correcting maneuvers to calibrate the navigation system so that the error does not exceed the allowed error for that corridor.
REFERENCES:
patent: 5340056 (1994-08-01), Guelman et al.
patent: 5502638 (1996-03-01), Takenaka
patent: 6122572 (2000-09-01), Yavanai
patent: 6377875 (2002-04-01), Schwaerzler
patent: 6498968 (2002-12-01), Bush
patent: 6615135 (2003-09-01), Davis
patent: 2002/0055819 (2002-05-01), Shimizu
patent: 2003/0025038 (2003-02-01), Nicolai et al.
Raghunathan et al. “Dynamic Optimazation Strategies for 3D Conflict Resolution of Multiple Aircraft”, Aug. 29, 2002, pp. 1-27.
Honeywell International , Inc.
Shaw Pittman LLP
Taylor Victor J.
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