Presented herein are embodiments of signal detection and location finding directed to a “Signature Detector and Direction Finder” (SDDF) add-on module. The SDDF is an add-on module to any Signal Detection System (SDS) that detects, locates, and/or tracks any type(s) of Radio Frequency (RF) signals. Even though the presented embodiments can be used with any RF signal type, the preferred targets are Uncrewed Aerial Vehicles (UAV) or drones, and their controllers. A goal of the SDDF add-on module is to recognize the reported signal of interest and identify its direction. The machine-learning feature enables the system (i.e. SDDF add-on module with SDS) to be deployable in various environments with flexibility in choosing the antenna type(s). The Signature Detector component of the SDDF add-on module uniquely filters drone/controller signals, hence, more accurate direction estimation of the detected signal by SDDF add-on module.

A terrestrial acoustic sensor array for detecting and preventing airspace collision with an unmanned aerial vehicle (UAV) includes a plurality of ground-based acoustic sensor installations, each of the acoustic sensor installations including a sub-array of microphones. The terrestrial acoustic sensor array may further include a processor for detecting an aircraft based on sensor data collected from the microphones of at least one of the plurality of acoustic sensor installations and a network link for transmitting a signal based on the detection of the aircraft to a control system of the UAV.

Systems and methods for detecting radio frequency (“RF”) signals and corresponding origination locations are disclosed. An RF sensor device includes a software-defined radio and an antenna pair for receiving RF signals. Furthermore the RF sensor device may include a processing unit for processing/analyzing the RF signals, or the processing unit may be remote. The system calculates a phase difference between an RF signal received at two separate antennas of an antenna pair. The phase difference, the distance between the antennas, and the frequency of the RF signal are used for determining the origination direction of the RF signal. In various embodiments, the origination direction may indicate the location of a UAV controller or base station. The software-defined radio may include more than one antenna pair, connected to multiplexers, for efficiently scanning different frequencies by alternating active antenna pairs. Moreover, the system may execute packet-based processing on the RF signal data.

A method of measuring positioning signals at a user equipment (UE) includes: obtaining, at the UE, one or more transmission characteristics corresponding to each of a plurality of positioning signals; obtaining, at the UE, topographic information regarding physical features of a region associated with the UE and the plurality of positioning signals; determining, at the UE, one or more selected positioning signals, of the plurality of positioning signals, to measure based on the one or more transmission characteristics and the topographic information; and measuring, at the UE, the one or more selected positioning signals to produce one or more measurements.

A method of monitoring a kinematic state of an unmanned aerial vehicle (UAV) is provided. The method comprises obtaining one or more predicted pathlosses between a UAV and one or more base stations at a first time instance, wherein the predicted pathlosses are determined using an estimate of a kinematic state of the UAV at the first time instance and one or more pathloss models developed using a machine-learning process. The method further comprises obtaining one or more measurements of a pathloss between each of the one or more base stations and the UAV at the first time instance, and re-determining the estimate of the kinematic state of the UAV at the first time instance based on the one or more predicted pathlosses and the one or more measurements of the pathloss.

Co-channel beacon transmissions are provided with at least one of spectral redundancy and temporal redundancy. A receiver produces a snapshot of a superposition of received co-channel beacon transmissions. Subcarrier demodulation, code nulling, or a Class-C linear minimum-mean-square error (MMSE) operation separates multiples ones of the co-channel beacon transmissions or eliminates inter-symbol interference and inter-subcarrier interference in the snapshot. Receiver operations can be performed at a network user, a network node, or a network operations center.

An image reconstruction algorithm system for hazardous source mapping. The algorithm system can be used to automate and optimize the search path of a movable vehicle (such as a UAV), equipped with detection capability. The algorithm allows the vehicle to localize hazardous sources in multiple scenarios effectively. Hazard mapping is formulated as an inverse problem and solved either with a deconvolution or a reconstruction algorithm, according to the problem complexity. The algorithms can use the Maximum a Posteriori (MAP) and the least square regression algorithm, respectively. However, alternative algorithms can be used as set forth herein. The source mapping algorithms are able to provide a quantitative estimation of the hazard source magnitude. A non-negative version of the least square algorithm is used to reconstruct the map at each step of the navigation algorithm of the vehicle. The navigation algorithm correctly located single and multiples simulated hazardous sources.

A method and system to determine the position of a moveable platform relative to an object is disclosed. The method can include storing one or more synthetic models each trained by one of the one or more synthetic model datasets corresponding to one or more objects in a database; capturing an image of the object by one or more sensors associated with the moveable platform; identifying the object by comparing the captured image of the object to the one or more synthetic model datasets; generating a first model output using a first synthetic model of the one or more synthetic models, the first model output including a first relative coordinate position and a first spatial orientation of the moveable platform; and generating a platform coordinate output and a platform spatial orientation output of the moveable platform at the first position based on the first model output.

A method and system for locating a high-intensity target light source (26) from an elevated observation location (Po), for instance in an aircraft. The target light source is located at/near an earth surface portion (30) and amongst reference light sources (16, 24, 25) arranged along the surface portion. This target light source emits light (28) with a peak radiant intensity that exceeds the intensity of the reference light sources by at least one order of magnitude. The method includes: acquiring, with an image recording device located at the observation location, images of the light and light emitted the reference light sources; comparing the images and a digital ground map (50) that includes representations of the surface portion and of structures (20, 22) associated with the reference light sources, and estimating a location (Pt) of the target light source relative to the reference light sources, based on the comparison.

Systems and methods for detecting radio frequency (“RF”) signals and corresponding origination locations are disclosed. An RF sensor device includes a software-defined radio and an antenna pair for receiving RF signals. Furthermore the RF sensor device may include a processing unit for processing/analyzing the RF signals, or the processing unit may be remote. The system calculates a phase difference between an RF signal received at two separate antennas of an antenna pair. The phase difference, the distance between the antennas, and the frequency of the RF signal are used for determining the origination direction of the RF signal. In various embodiments, the origination direction may indicate the location of a UAV controller or base station. The software-defined radio may include more than one antenna pair, connected to multiplexers, for efficiently scanning different frequencies by alternating active antenna pairs. Moreover, the system may execute packet-based processing on the RF signal data.