Honeywell International Inc.

Zuowei He

Gang He

Zhong Hai Chen

Zhiguo Ren

Rakshit R

Haidong Huang

Methods and systems are provided for propagating a free-form user input across different displays. One method involves receiving a free-form user input on a navigational map display, assigning a geographic location to the free-form user input based on a position of the free-form user input on the navigational map display, and generating a graphical indication influenced by the free-form user input on a second display at a respective position on the second display corresponding to the geographic location assigned to the free-form user input.

Methods and systems for propagating user inputs to different displays

Systems and methods are disclosed that receiving ground traffic data from a traffic computer, and enhanced vision system, EVS, imaging data from at least one EVS camera. A target area is determined in the EVS imaging data based on position data of the ground traffic data. Graphics processing is performed that is confined to the target area to enhance visibility of ground traffic in the EVS imaging data in the target area, thereby generating enhanced EVS imaging data. The graphics processing is selected from at least one of contrast enhancement, edge detection and template matching and highlighting of an outline of the ground traffic. A display is generated that is to be displayed on the display device based on the enhanced EVS imaging data and the EVS imaging data.

Methods and systems for highlighting ground traffic on cockpit displays

Systems and methods for calibrating a synthetic image on an avionic display. The method includes receiving a synthetic image frame generated by an avionic display system and a sensor image frame from a forward-facing onboard sensor system. Object recognition is performed on the sensor image frame to generate a first search region for a first Federal Aviation Administration (FAA) marking, defined as a first search region-FAA marking pair. The sensor image frame and the first search region-FAA marking pair are processed using a deep learning method (DLM) to determine for the first FAA marking of the first search region-FAA marking pair, each of: a position deviation calculation, an orientation deviation calculation, and a synthetic image distortion factor. The synthetic image frame is then updated and rendered in accordance with the position deviation calculation, the orientation deviation calculation, and the synthetic image distortion factor, thereby calibrating the synthetic image frame.

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Shanghai, China

Zuowei He