In an example, a method is described. The method includes causing one or more sensors arranged on an aircraft to acquire, over a window of time, first data associated with a first object that is within an environment of the aircraft, where the one or more sensors include one or more of a light detection and ranging (LIDAR) sensor, a radar sensor, or a camera, causing an array of microphones arranged on the aircraft to acquire, over approximately the same window of time as the first data is acquired, first acoustic data associated with the first object, and training a machine learning model by using the first acoustic data as an input value to the machine learning model and by using an azimuth, a range, an elevation, and a type of the first object identified from the first data as ground truth output labels for the machine learning model.

Tracking aircraft in and near a ramp area is described herein. One method includes receiving camera image data of an aircraft while the aircraft is approaching or in the ramp area, receiving LIDAR/Radar sensor data of an aircraft while the aircraft is approaching or in the ramp area, merging the camera image data and the LIDAR/Radar sensor data into a merged data set, and wherein the merged data set includes at least one of: data for determining the position and orientation of the aircraft relative to the position and orientation of the ramp area, data for determining speed of the aircraft, data for determining direction of the aircraft, data for determining proximity of the aircraft to a particular object within the ramp area, and data for forming a three dimensional virtual model of at least a portion of the aircraft from the merged data.

Devices, systems, and methods for determining aircraft orientation are described herein. One device includes instructions executable to determine a subsection of a rendering of a portion of an airport, wherein the subsection is associated with a particular stand of the airport, and wherein the subsection includes a plurality of ground travel pathways, determine a first subset of the plurality of pathways, a second subset of the plurality of pathways, and a third subset of the plurality of pathways, track a location of an outbound aircraft within the subsection of the rendering, determine an orientation of the aircraft according to a first set of rules responsive to a determination that the location of the aircraft is within the first or second subset of the plurality of pathways, and determine the orientation of the aircraft according to a second set of rules responsive to a determination that the location of the aircraft is within the third subset of the plurality of pathways.

Tracking aircraft in and near a ramp area is described herein. One method includes receiving camera image data of an aircraft while the aircraft is approaching or in the ramp area, receiving LIDAR/Radar sensor data of an aircraft while the aircraft is approaching or in the ramp area, merging the camera image data and the LIDAR/Radar sensor data into a merged data set, and wherein the merged data set includes at least one of: data for determining the position and orientation of the aircraft relative to the position and orientation of the ramp area, data for determining speed of the aircraft, data for determining direction of the aircraft, data for determining proximity of the aircraft to a particular object within the ramp area, and data for forming a three dimensional virtual model of at least a portion of the aircraft from the merged data.

To provide a foreign-object system which uses a plurality of radars, and which can detect a foreign object that is present on a runway or the like and which can suppress interference between radars. A foreign-object detection system including a first radar 11, a second radar 21 connected to the first radar via a network 33, and a signal source 31 for transmitting a synchronization signal to the first radar and the second radar via the network, said foreign-object detection system wherein interference generated due to a radar signal outputted from the second radar being reflected by a reflective body and inputted to the first radar is prevented by controlling a delay time that corresponds to |τ.sub.1i−τ.sub.2j|, where τ.sub.1i is the time taken for the synchronization signal to be transmitted from the signal source to the first radar, and τ.sub.2j is the time taken for the synchronization signal to be transmitted from the signal source to the second radar.

To provide a foreign-object system which uses a plurality of radars, and which can detect a foreign object that is present on a runway or the like and which can suppress interference between radars. A foreign-object detection system including a first radar 11, a second radar 21 connected to the first radar via a network 33, and a signal source 31 for transmitting a synchronization signal to the first radar and the second radar via the network, said foreign-object detection system wherein interference generated due to a radar signal outputted from the second radar being reflected by a reflective body and inputted to the first radar is prevented by controlling a delay time that corresponds to |τ.sub.1i−τ.sub.2j|, where τ.sub.1i is the time taken for the synchronization signal to be transmitted from the signal source to the first radar, and τ.sub.2j is the time taken for the synchronization signal to be transmitted from the signal source to the second radar.

Methods, devices, and systems for false target detection for airport traffic control are described herein. One device includes a user interface, a memory, and a processor configured to execute executable instructions stored in the memory to receive one or more sensor reports from one or more sensors, aggregate data that corresponds to a particular target from the one or more sensor reports, determine the particular target is a false target responsive to only one of the sensor reports including data that corresponds to the particular target, and display the particular target as a false target on the user interface responsive to determining the particular target is a false target.

A sensor assembly for use in association with non-integrated, ground-based collision avoidance systems for aircraft, including (a) a sensor; and (b) a frame sub-assembly, wherein the sensor is releasably securable to the frame sub-assembly.

Embodiments of the present disclosure provide a system, device and method for collecting, processing, correcting and employing positional vehicle data broadcast by aircraft and/or other vehicles to improve airport and related vehicle operations and tracking. In various embodiments, an IOT sensor subsystem comprising a detection unit is secured at or near an airport and includes one or more antennae, one or more sensors and a processing unit for analyzing the data and producing beneficial output.

Devices, systems, and methods for determining aircraft orientation are described herein. One device includes instructions executable to determine a subsection of a rendering of a portion of an airport, wherein the subsection is associated with a particular stand of the airport, and wherein the subsection includes a plurality of ground travel pathways, determine a first subset of the plurality of pathways, a second subset of the plurality of pathways, and a third subset of the plurality of pathways, track a location of an outbound aircraft within the subsection of the rendering, determine an orientation of the aircraft according to a first set of rules responsive to a determination that the location of the aircraft is within the first or second subset of the plurality of pathways, and determine the orientation of the aircraft according to a second set of rules responsive to a determination that the location of the aircraft is within the third subset of the plurality of pathways.