Rockwell Collins, Inc.

Richard M Rademaker

Richard D Jinkins

Weston James Lahr

Brandon E Wilson

Christopher M Boggs

Robert B Anderson

Julian C Ryde

Aaron Perkins

Charlotte S Ljungkrantz-Lahr

A system and method for high-confidence error overbounding of multiple optical pose solutions receives a set of candidate correspondences between 2D image features captured by an aircraft camera and 3D constellation features including at least one ambiguous correspondence. A candidate estimate of the optical pose of the camera is determined for each of a set of candidate correspondence maps (CMAP), each CMAP resolving the ambiguities differently. Each candidate pose estimate is evaluated for viability and any non-viable estimates eliminated. An individual error bound is determined for each viable candidate pose estimate and CMAP, and based on the set of individual error bounds a multiple-pose containment error bound is determined, bounding with high confidence the set of candidate CMAPs and multiple pose estimates where at least one is correct. The containment error bound may be evaluated for accuracy as required for flight operations performed by aircraft-based instruments and systems.

Vision-based navigation system incorporating high-confidence error overbounding of multiple optical poses

A vision-based navigation system (e.g., for aircraft on approach to a runway) captures via camera 2D images of the runway environment in an image plane. The vision-based navigation system stores a constellation database of runway features and their nominal 3D position information in a constellation plane. Image processors detect within the captured images 2D features potentially corresponding to the constellation features. The vision-based navigation system estimates optical pose of the camera in the constellation plane by aligning the image plane and constellation plane into a common domain, e.g., via orthocorrection of detected image features into the constellation plane or reprojection of constellation features into the image plane. Based on the common-domain plane, the vision-based navigational system generates candidate correspondence maps (CMAP) of constellation features mapped to the image features with high-confidence error bounding, from which optical pose of the camera or aircraft can be estimated.

Vision-based navigation system incorporating model-based correspondence determination with high-confidence ambiguity identification

A system and method utilizing an existing boresighted HUD and a camera to determine the transformational and rotational relationships between the camera image and the boresighted HUD image of an aircraft to properly orient the camera for landing operations. Known boresight features are identified in a HUD image and are related to the same boresight features in a camera image, and transformations are applied to align pixels in the camera image to the pixel locations of the boresight features in the HUD image. Object recognition algorithms may be employed to identify the boresight features in the camera image.

Aircraft camera extrinsic calibration using head-up display

An onboard aircraft landing system includes one or more event-based cameras disposed at known locations to capture the runway and visible surrounding features such as lights and runway markings. The event-based cameras produce a continuous stream of event data that may be quickly processed to identify both light and dark features contemporaneously, and calculate an aircraft pose relative to the runway based on the identified features and the known locations of the event-based cameras. Composite features are identified via the relative location of individual features corresponding to pixel events.

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Cedar Rapids, IA, United States of America

Richard M Rademaker