An unmanned aerial vehicle (UAV) for detecting, identifying, and locating a source emitting an interfering signal is described herein. The UAV can detect wireless network site interference within a given frequency spectrum band and locate the source of the interference based on one or more signals received by one or more antennas, such as directional antennas. The one or more antennas are located on or within a main body or one or more booms of the UAV. The UAV can be flown manually (e.g., by an operator) or automatically (e.g., by a processor or preset routine).

Iterative methods for direction of arrival estimation of a signal at a receiver with a plurality of spatially separated sensor elements are described. A quantized estimate of the angle of arrival is obtained from a compressive sensing solution of a set of equations. The estimate is refined in a subsequent iteration by a computed error based a quantized estimate of the direction of arrival in relation to quantization points offset from the quantization points for the first quantized estimate of the angle of arrival. The iterations converge on an estimated direction of arrival.

A two-dimensional direction-of-arrival estimation method for a coprime planar array based on structured coarray tensor processing, the method includes: deploying a coprime planar array; modeling a tensor of the received signals; deriving the second-order equivalent signals of an augmented virtual array based on cross-correlation tensor transformation; deploying a three-dimensional coarray tensor of the virtual array; deploying a five-dimensional coarray tensor based on a coarray tensor dimension extension strategy; forming a structured coarray tensor including three-dimensional spatial information; and achieving two-dimensional direction-of-arrival estimation through CANDECOMP/PARACFAC decomposition. The present disclosure constructs a processing framework of a structured coarray tensor based on statistical analysis of coprime planar array tensor signals, to achieve multi-source two-dimensional direction-of-arrival estimation in the underdetermined case on the basis of ensuring the performance such as resolution and estimation accuracy, and can be used for multi-target positioning.

A system is disclosed and includes a plurality of antennas. Each antenna includes a plurality of conductive elements and is circularly polarized. The plurality of conductive elements is configured to receive radio frequency (RF) signals. A first end of each of the plurality of conductive elements is electrically coupled to a printed circuit board, which includes a plurality of coupler circuits and a switching circuit. The plurality of coupler circuits is configured to combine the RF signals and output a signal to the switching circuit based on the combined RF signals. The switching circuit is configured to selectively output one of the signals based on at least one control port of the switching circuit being selectively activated by a control signal. The system also includes a microcontroller configured to determine, based on at least one of the signals, an angle of arrival associated with the plurality of antennas.

An RFID system includes multiple antennas and uses amplitude and phase information of the RFID signals received by each antenna to determine the position of RFID tags in the vicinity. More than one antenna can receive the RFID signals during a single read cycle, enabling the RFID system to operate more quickly than a system that energizes antennas separately.

A communication device comprising: a plurality of wireless communication sections; and a control section configured to control a repetition process of repeatedly performing a measurement process, on a basis of a reliability parameter calculated through the measurement process, and control a selection process of selecting a representative wireless communication section each time the measurement process is repeated in the repetition process, the measurement process including transmission of a signal from the representative wireless communication section, reception of the signal by the plurality of wireless communication sections, and calculation of the reliability parameter with regard to at least any of the wireless communication sections.

A method for determining an angle of arrival at a communication device is described. The method comprises performing a message exchange between the communication device and a further communication device. The message exchange comprises receiving at least one first message associated with a first frequency at the communication device by means of a first antenna and a second antenna and receiving at least one second message associated with a second frequency at the communication device by means of the first antenna and the second antenna. The method further comprises determining the angle of arrival defined by an orientation of the communication device and a transmission direction of the message exchange, wherein the angle of arrival is determined based on the received first message and the received second message. Furthermore, a corresponding communication device is described.

A method for determining an angel includes: sending a control message to a target device on a first channel. The control message carries at least channel switch information configured to instruct the target device to transmit signals on a second channel. The method further includes determining an angle from the target device to the terminal according to a first signal and a second signal. The first signal transmitted by the target device is received on the first channel. The second signal transmitted by the target device is received on the second channel.

Techniques are disclosed for determining a true bearing angle from an airborne platform to a source of a radar signal. In an embodiment, a grid is generated based on a coarse range to, and angle-of-arrival of, an electromagnetic signal. The grid represents a geographic area thought to contain the emission source. A measured spatial angle is computed for each pulse of the signal received during a data collection interval. Hypothesized spatial angles are computed for a point in each grid box in the grid. A score is generated for each grid point based on the computed hypothesized spatial angles for the grid point and the measured spatial angles. The grid point having the lowest score is identified as a seed location and is used to launch a Nelder-Mead algorithm that converges on a point in the grid. A true bearing angle to the source of a radar angle is computed to the point provided by the Nelder-Mead algorithm.

Systems and methods for automated unmanned aerial vehicle recognition. A multiplicity of receivers captures RF data and transmits the RF data to at least one node device. The at least one node device comprises a signal processing engine, a detection engine, a classification engine, and a direction finding engine. The at least one node device is configured with an artificial intelligence algorithm. The detection engine and classification engine are trained to detect and classify signals from unmanned vehicles and their controllers based on processed data from the signal processing engine. The direction finding engine is operable to provide lines of bearing for detected unmanned vehicles.