A method of determining the position of a moving unmanned aerial vehicle (UAV) is provided. The method comprises obtaining, for each of three or more base stations, one or more measurements of a carrier frequency offset (CFO) for one or more signals sent between a moving UAV and the respective base station. The method further comprises inputting the CFO measurements into a model to determine a position of the UAV, in which inputs to the model do not include range measurements of the UAV with respect to the three or more base stations.

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.

Search points in a search space may be projected onto images from cameras imaging different parts of the search space. Subimages, corresponding to the projected search points, may be selected and processed to determine if a target object has been detected. Based on subimages in which target objects are detected, as well as orientation data from cameras capturing images from which the subimages were selected, positions of the target objects in the search space may be determined.

Systems and methods for autonomous location of “Emergency Personal Locator Beacons” and other emergency Radio Frequency communication devices; providing navigation between Robotic systems such as a UAS, and the asset which is carrying a Personal Locator Beacon, EPIRB or signaling device which transmits a digital, ASCII or similar embedded data stream, intended for tracking and emergency location, within its RF broadcast. This method for navigating a robotic system or UAS relative to a defined target comprises detecting, on an Emergency Radio Frequency (RF) receiver an Emergency Radio Frequency signal generated by a Transmitter carried on the target, such as an Automatic Identification System Transmitter, As such there may be GPS enabled embedded data messages in these VHF radio transmissions, which is the focus of this invention. The invention decodes and parses the data contained in these messages, using proprietary software, converting them into motion commands for an autonomous robotic system.

Search points in a search space may be projected onto images from cameras imaging different parts of the search space. Subimages, corresponding to the projected search points, may be selected and processed to determine if a target object has been detected. Based on subimages in which target objects are detected, as well as orientation data from cameras capturing images from which the subimages were selected, positions of the target objects in the search space may be determined.

Provided is a technology for increasing accuracy of position estimation by estimating a position of a signal source based on an error due to altitudes of a sensor and a signal source and an error due to a pitch of an aircraft as well as an error due to curvature of the earth. At this time, a position estimation method may include receiving measurement data from a plurality of sensors, estimating first position data of the signal source based on the measurement data, identifying an altitude error of the first position data, and estimating second position data that is data obtained by correcting the first position data based on the altitude error.

Methods and apparatuses are provided for estimating a path of an aerial vehicle engaged in attacking network devices in a wireless communication network. A distance function corresponding to the aerial vehicle and a boundary node is determined based on an initial coordinate location of the aerial vehicle and an initial coordinate location of the boundary node. A function of jamming power received at the boundary node from the aerial vehicle is determined based at least on the first distance function and a transmission power of the boundary node. The function of jamming power represents a power associated with a jamming signal received from the aerial vehicle at the boundary node. A trajectory of the aerial vehicle at a plurality of time periods is estimated by the boundary node with an extended Kalman filter. The extended Kalman filter is determined based on the function of jamming power.

Embodiments described herein provide for an electronic device comprising a set of classifiers that can determine whether the electronic device is likely on an airplane. Upon a determination that the electronic device is likely on an airplane, one or more wireless radios on the electronic device (e.g., an ultra-wideband ranging radio, a cellular radio, etc.) may be disabled or a prompt can be displayed to enable a user to place the device into airplane mode.

A control terminal includes a memory storing program instructions, a communication interface configured to communicate with an unmanned aerial vehicle (UAV), receive position information outputted by a positioning device of the UAV and sent by the UAV, and receive flight state information of a plurality of aircrafts detected by an aircraft detection device of the UAV and sent by the UAV, and a processor configured to execute the program instructions to detect an operation state of the positioning device based on the position information and the flight state information.

An unmanned aircraft includes: a sensor that includes at least a microphone that generates sound data; and a processor. The processor determines quality of a target sound using the sound data generated by the microphone, obtains a positional relationship between the unmanned aircraft and a sound source of the target sound using data generated by the sensor, and controls movement of the unmanned aircraft to control a distance between the unmanned aircraft and the sound source of the target sound, in accordance with the quality of the target sound and the positional relationship.