The present disclosure generally pertains to systems and methods for providing position information to aircraft using radio-frequency signals. By providing a ground-based solution entirely independent of GPS, systems of the present disclosure can make navigation systems more accurate and robust, enhancing their effectiveness and safety. More precisely, systems of the present disclosure may employ a series of ground-based beacon transmitters to provide coverage across a defined geographic region. Primary beacon transmitters may be used to generate a radio-frequency (RF) signal pulse with a highly regular frequency. A larger number of secondary beacon transmitters may be used to re-transmit these RF signal pulses with a tightly controlled turnaround time. A locating receiver can detect the arrival times of these pulses and use this information, along with stored information about the relative positions of the beacon transmitters, to determine its location.

A device generates a first plurality of aerial vehicle (AV) constellations about a geographic area and determines respective positioning scores for each AV constellation. The respective positioning score is determined based at least in part on a measure of positioning accuracy for positioning enabled by the AV constellation at position(s) of interest within the geographic area. The device generates a second plurality of AV constellations based on the first plurality and the respective positioning scores by modifying one or more of the AV constellations of the first plurality using random location perturbations. The device determines respective positioning scores for each AV constellation of the second plurality. The device selects a preferred AV constellation from a group of selectable constellations based on the respective positioning score of the preferred AV constellation, the group of selectable constellations generated based at least in part on the first and/or second plurality of AV constellations.

Disclosed herein A UAV and/or UAV operator detector (1) configured to be mounted to an aircraft (2). The detector comprises an array of multiple Directional Radio Frequency (RF) antennae spaced apart from one another over two or three dimensions.

A computer implemented method in a communications network for determining location information about an actual location of a drone comprises obtaining (302) a reported location of the drone at a first time point and obtaining (304) a measurement of radio conditions between the drone and a node in the telecommunications network, at the first time point. The method then comprises predicting (306) radio conditions at one or more locations related to the reported location of the drone, and determining (308) the location information about the actual location of the drone based on the measured radio conditions and the predicted radio conditions.

A correlation and track system identifies whether a Radar warning (RW) Track contains one or more emitters by receiving a set of initial Short and Long Baseline Interferometer (SBI) (LBI) detections; receiving inertial navigational data; receiving subsequent LBI detections; determining whether the LBI detections represent one or multiple emitter(s) by designating an initial SBI conic with a multiple of its one sigma conic Direction Finding (DF) accuracy window as containing the emitter; laying down a set of grid points within the SBI conic window as possible emitters' locations; summing real and imaginary values of a residual phase in the form of a unit vector at each grid point for each LBI update; identifying whether there are one or more emitters in RW track based on whether the magnitude of a peak vector is above or below a defined threshold; and invoking geolocation algorithms based on the vector's magnitude.

A method for positioning a target in a building based on the assistance of two aircraft includes the following steps: allowing two aircraft with respective direction-finding devices to fly around a building, and sending a signal by a positioning tag carried by an indoor target; measuring projections of directions of the signal source on a horizontal plane respectively by the two aircraft, and indicating a position of the indoor target on the horizontal plane by an intersection of the two projections; and according to a difference between barometric pressures of the indoor target and the aircraft, obtaining an altitude of the target to further obtain position coordinates of the target. The method avoids deploying an indoor positioning base station, and improves the positioning accuracy, stability and anti-interference performance.

Method of detecting and tracking an unmanned aerial vehicle, the method comprising, at a detector unit (300a) comprising a first microphone and a second microphone: monitoring for a sound associated with the presence of the unmanned aerial vehicle (505) in the vicinity of the detector unit; in response to the monitoring indicating the presence of the unmanned aerial vehicle, determining, at the detector unit, a phase delay between the sound as received at the first microphone and the sound as received at the second microphone; on the basis of the determined phase delay and a known separation of the first microphone and the second microphone, determining, at the detector unit, an azimuth angle (507a) to the unmanned aerial vehicle from the detector unit; and transmitting, to a computing node (501), the determined azimuth angle for use in determining a location of the unmanned aerial vehicle.

The detection and identification of unmanned aerial vehicles (UAVs) from a radio wave measurement result based on artificial intelligence (AI) are provided. A method of operating an apparatus to detect unmanned aerial vehicles (UAVs) includes generating a spectrogram, determining a first region to find a direction of the UAVs in the spectrogram, determining a direction of a first UAV of the UAVs based on signal values in the first region, determining a second region to identify a type of the first UAV in the spectrogram, and identifying the type of the first UAV based on signal values in the second region.

Some embodiments include methods performed by a processor associated with a wireless communication device for enabling an unmanned autonomous vehicle (UAV) to operate in an automatic user tracking mode. Such embodiments may include capturing image data of surroundings by a camera while the UAV is operating in the automatic user tracking mode, calculating estimated position information for the wireless communication device based on captured image data, and transmitting estimated position information to the UAV for use in tracking a user of the wireless communication device. Some embodiments include methods performed by a processor of a UAV for enabling the UAV to automatically follow a user. Such embodiments may include calculating a current position of the UAV, receiving from a user's wireless communication device estimated position information derived from image data captured by a camera of the wireless communication device, and determining whether an update to the UAV motion is required.

Provided are an airway setting device for signaling an airway to an aerial vehicle and an automatic navigation system for controlling the aerial vehicle to fly the airway. The airway setting device transmits radio frequency (RF) signals through two antennas spaced apart from each other. The transmitted RF signals are encoded with phase difference information intended for an aerial vehicle receiving the transmitted RF signals. An automatic navigation system of the aerial vehicle receives the RF signals from the two antennas spaced apart from each other, measures a phase difference between the RF signals, decodes encoded phase difference information, and compares the measured phase difference with the decoded phase difference to identify and maintain an airway.