The Boeing Company

University of California

Sysense, Inc.

Other

United States of America As Represented by the Administrator of Nasa

Jason Lee Speyer

Walton Williamson

Stephen M Stecko

John Ferencz Takacs

Robert H Chen

Ashitosh Swarup

John J Ryan

Laurence H Mutuel

A system for automated control of a refueling boom coupled to a tanker aircraft is provided. The system includes: a first inertial measurement unit (IMU) providing inertial measurements for the tanker aircraft; a first GPS receiver providing a GPS location for a GPS antenna attached to the tanker aircraft; and a processor adapted to calculate a first inertial navigation state for the tanker aircraft through integration of the inertial measurements, the processor being further adapted to calculate a first inertial navigation state error relative to the GPS location and to filter the first inertial navigation state error and the first inertial navigation state based upon noise characteristics of the first IMU and the first GPS receiver to provide an updated inertial navigation state for the tanker aircraft, the processor being further adapted to control the refueling boom relative to a receiver aircraft based upon the first and updated inertial navigation states.

Apparatus for an automated aerial refueling boom using multiple types of sensors

A computerized system and method for peak-seeking-control that uses a unique Kalman filter design to optimize a control loop, in real time, to either maximize or minimize a performance function of a physical object ('plant'). The system and method achieves more accurate and efficient peak-seeking-control by using a time-varying Kalman filter to estimate both the performance function gradient (slope) and Hessian (curvature) based on direct position measurements of the plant, and does not rely upon modeling the plant response to persistent excitation. The system and method can be naturally applied in various applications in which plant performance functions have multiple independent parameters, and it does not depend upon frequency separation to distinguish between system dimensions.

Systems and methods for peak-seeking control

Methods and devices for estimating and controlling the orientation of a drogue relative to air mass motion where method and apparatus embodiments incorporate estimation of angle of attack and sideslip and function to correct the direction of a drogue so as to maintain a desired angle of attack and sideslip. Some of the exemplary estimation techniques apply methods of sensor output fusion.

Methodology for autonomous navigation and control of a tethered drogue

A system for automated control of a refueling boom coupled to a tanker aircraft is provided. The system includes sensors such as electro-optical sensor or GPS sensors that provide measurements used by the system to automatically control the refueling boom so as to mate with a receiver aircraft. The system is configured to monitor the health of the sensors and to reconfigure itself if any of the sensor are faulty.

Fault detection and reconfiguration of an automated refueling boom

A system, processing structure and method for performing vehicle intercept includes target acceleration estimation or blocking via a filter prior to deriving an interceptor acceleration time history via a guidance law. In the processing structure where the unknown target accelerations are blocked from affecting estimates, a guidance law is generated, stored and retrieved accounting for worst case target acceleration. In the processing structure where the target acceleration is presumed constant with a constant bank angle, the guidance law is closed form, exploiting constant heading angular velocity, and thus generated online.

Homing missile guidance and estimation algorithms against advanced maneuvering targets

An apparatus and method for vehicle orientation determination is disclosed. A typical method comprises the steps of receiving position and velocity information data from a global positioning system receiver unit, receiving vehicle dynamics information data from one or more vehicle dynamics sensors and determining a vehicle attitude from the position and velocity information and the vehicle dynamics information data using a Kalman filter.

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Los Angeles, CA, United States of America

Jason Lee Speyer