Honeywell International Inc.

Jan Lukas

Ondrej Kotaba

David C Vacanti

Yunqian Ma

Michal Dobes

Tomas Beda

Ondrej Koukol

Pavel Badin

Jindrich Dunik

Kailash Krishnaswamy

Sara Susca

Ondrej Pokorny

Milos Vesely

Brennan Kilty

Milan Sopata

In some examples, a system includes a weather radar device configured to transmit radar signals, receive first reflected radar signals at a first time, and receive second reflected radar signals at a second time. In some examples, the system also includes processing circuitry configured to determine a first magnitude of reflectivity based on the first reflected radar signals and determine a second magnitude of reflectivity based on the second reflected radar signals. In some examples, the processing circuitry is also configured to determine a temporal variance in reflectivity magnitudes based on determining a difference in reflectivity between the first magnitude and the second magnitude. In some examples, the processing circuitry is further configured to determine a presence of ice crystals based on the first magnitude of reflectivity, the second magnitude of reflectivity, and the temporal variance in reflectivity magnitudes.

Ice crystal detection by weather radar

In some examples, a system is configured for determining an estimated altitude of a melting layer, and the system includes a weather radar device configured to transmit radar signals and receive reflected radar signals. In some examples, the system also includes processing circuitry configured to determine the estimated altitude of the melting layer based on the reflected radar signals.

Melting layer estimation by weather radar device

In some examples, a processor is configured to predict the presence of ice crystals (e.g., high altitude ice crystals) in a volume of airspace based on radar reflectivity values and one or more other types of information indicative of weather conditions in the volume of airspace, such as one or more of: ambient air temperature and altitude. For example, the processor may predict the ice crystals presence by at least estimating the iced water content level within a volume of airspace of interest based on radar reflectivity values for the volume of airspace (e.g., stored as in a three-dimensional buffer) and other information indicative of weather conditions of the volume of airspace. The processor may estimate the iced water content level using a model that relates the information indicative of weather conditions in and around the volume of interest to iced water content in the atmosphere.

Prediction of ice crystal presence in a volume of airspace

Embodiments of the present invention provide improved systems and methods for matching scenes. In one embodiment, a processor for implementing robust feature matching between images comprises: a first process for extracting a first feature set from a first image projection and extracting a second feature set from a second image projection; a memory for storing the first feature set and the second feature set; and a second process for feature matching using invariant mutual relations between features of the first feature set and the second feature set; wherein the second feature set is selected from the second image projection based on the identification of similar descriptive subsets between the second image projection and the first image projection.

Systems and methods for matching scenes using mutual relations between features

A vehicle display system displays approach lights acquired by a vision system overlaid on, and aligned with, a stored synthetic approach light symbol. A stored approach light type that corresponds to the target runway may be verified to match the acquired approach lights. A synthetic approach light symbol that corresponds to the approach light type is chosen and aligned with the approach lights for display.

System and method for detecting and displaying airport approach lights

Systems and methods for 3D data based navigation using descriptor vectors are provided. In at least one embodiment, a method for identifying corresponding segments in different frames of data comprises identifying a first segment set in a first frame in multiple frames acquired by at least one sensor, and identifying a second segment set in a second frame in the multiple frames. The method also comprises calculating a first and second set of descriptor vectors, wherein the first and second sets of descriptor vectors comprise a descriptor vector for each segment in the respective first and second segment set, wherein a descriptor vector describes an indexed plurality of characteristics; and identifying corresponding segments by comparing the first set of descriptor vectors against the second set of descriptor vectors, wherein the corresponding segments describe characteristics of the same feature in the environment.

Systems and methods for 3D data based navigation using descriptor vectors

Systems and methods for 3D data based navigation using a watershed method are provided. In at least one embodiment, a method for segmenting three-dimensional frames of data comprises acquiring at least one frame from at least one sensor, wherein the at least one frame provides a three-dimensional description of an environment containing the at least one sensor; and identifying a surface in the at least one frame. The method further comprises computing at least one residual map for the at least one frame based on the orthogonal distance from data points on the surface to at least one polynomial surface fitted to the surface; and segmenting the at least one residual map by performing a watershed algorithm on the residual map.

Systems and methods for 3D data based navigation using a watershed method

Systems and methods for airborne object detection using monocular sensors are provided. In one embodiment, a system for detecting moving objects from a mobile vehicle comprises: an imaging camera; a navigation unit including at least an inertial measurement unit; and a computer system coupled to the image camera and the navigation unit. The computer system executes an airborne object detection process algorithm, and calculates a transformation between two or more image frames captured by the imaging camera using navigation information associated with each of the two or more image frames to generate a motion compensated background image sequence. The computer system detects moving objects from the motion compensated background image sequence.

Systems and methods for monocular airborne object detection

An aircraft system and method provide visual input to a pilot during takeoff roll. A runway centerline line vector is determined from a captured image, a displacement of the aircraft from the centerline line vector and an aircraft line vector are determined from the image based on the knowledge of sensor characteristics. The runway centerline line vector and the aircraft line vector are displayed to indicate a direction in which the pilot may change heading to maintain the aircraft on the runway.

System and method for aligning aircraft and runway headings during takeoff roll

Systems and methods for processing extracted plane features are provided. In one embodiment, a method for processing extracted plane features includes: estimating an area of each plane of a plurality of planes extracted from data collected by an imaging sensor; generating a list of detected planes including the area of each plane; filtering the list of detected planes to produce a list of candidates for merger, filtering the list of detected planes discarding any plane not satisfying an actual points received criteria; applying a primary merge algorithm to the list of candidates for merger that iteratively produces a list of merged planes by testing hypothetical merged planes against a merging criteria, the hypothetical merged planes each comprising a plane from the list of merged planes and a plane from the list of candidates for merger; and outputting a final list of planes.

Systems and methods for processing extracted plane features

An example embodiment includes a method including receiving a three-dimensional set of range data including a plurality of points from one or more range finders. The method also includes extracting one or more surface features. Extracting includes segmenting the set of range data into a plurality of surfaces based on one or more edges, selecting one or more of the plurality of surfaces as the one or more surface features, and describing the one or more surface features based on a generic descriptor that can describe both planar and non-planar surface features.

Generic surface feature extraction from a set of range data

A method of controlling an actuator based on a set of three-dimensional (3D) data points is provided. The method includes obtaining a first set of 3D data points for a scene and a second set of 3D data points for a scene with a sensor. At least a first set of planar features is extracted from the first set of 3D data point. At least a second set of planar features is extracted from the second set of 3D data points. A motion is determined between the first set of 3D data points and the second set of 3D data points based on a rotation and a translation from the at least a first set to the at least a second set. At least one actuator is controlled based on the motion.

Systems and methods for extracting planar features, matching the planar features, and estimating motion from the planar features

A method of extracting a feature from a point cloud comprises receiving a three-dimensional (3-D) point cloud representing objects in a scene, the 3-D point cloud containing a plurality of data points; generating a plurality of hypothetical features based on data points in the 3-D point cloud, wherein the data points corresponding to each hypothetical feature are inlier data points for the respective hypothetical feature; and selecting the hypothetical feature having the most inlier data points as representative of an object in the scene.

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Melnik, Czechia

Jan Lukas