This beam formation device includes: a Doppler bin detection unit that detects a target Doppler bin which is a Doppler bin in which a target signal is present, from a correlation matrix calculated by a correlation matrix calculation unit and a reception signal vector calculated by a Doppler analysis unit; a target signal removal unit that removes, from the correlation matrix calculated by the correlation matrix calculation unit, the target signal in the target Doppler bin detected by the Doppler bin detection unit and thereby calculates a target-signal-removed correlation matrix from which the target signal has been removed; and a weighting calculation unit that calculates an adaptive weighting of the reception signal vector from the target-signal-removed correlation matrix calculated by the target signal removal unit. A beam formation unit forms an adaptive beam from the reception signal vector calculated by the Doppler analysis unit and the adaptive weighting calculated by the weighting calculation unit.

Systems and methods for determining a timing offset of a plurality of emitter antennas in a wireless network. The methods include deploying a network synchronization calibration unit at a location within receiving range of a plurality of direct path reference signals transmitted by the plurality of emitter antennas. The synchronization calibration unit receives the plurality of direct path reference signals and one or more reflected reference signals, which are then separated from one another to identify the direct path reference signals when a signal strength of one direct path reference signal is less than a signal strength of a reflected reference signal. A set of data is collected from the reflected reference signals that is indicative of the timing offset and that set of data is analyzed to estimate the timing offset.

Systems and methods for determining a timing offset of a plurality of emitter antennas in a wireless network. The methods include deploying a network synchronization calibration unit at a location within receiving range of a plurality of direct path reference signals transmitted by the plurality of emitter antennas. The synchronization calibration unit receives the plurality of direct path reference signals and one or more reflected reference signals, which are then separated from one another to identify the direct path reference signals when a signal strength of one direct path reference signal is less than a signal strength of a reflected reference signal. A set of data is collected from the reflected reference signals that is indicative of the timing offset and that set of data is analyzed to estimate the timing offset.

Two antennas receive three kinds of radio waves with different frequencies. A computation unit determines the arrival direction of the three kinds of radio waves arriving at the two antennas after propagating along two mutually different paths from a single transmit point in accordance with receive signals of the three kinds of radio waves with different frequencies received individually by the two antennas.

Two antennas receive three kinds of radio waves with different frequencies. A computation unit determines the arrival direction of the three kinds of radio waves arriving at the two antennas after propagating along two mutually different paths from a single transmit point in accordance with receive signals of the three kinds of radio waves with different frequencies received individually by the two antennas.

This disclosure relates generally to field agnostic source localization. Conventional state-of-the-art methods perform source localization for near-field scenario by estimating carrier frequency and direction of arrival (DOA) at or above Nyquist sampling rate. Embodiments of the present disclosure provide a method for source localization at sub Nyquist sampling rate. The method estimates parameters such as range, carrier frequency and DOA of source signals from data sources in a mixed field scenario. i.e., the data sources may reside in far-field as well as near-field. The method considers a delay channel to a sensor receiver architecture for estimating the parameters. The disclosed method can be used in applications like cognitive radio to determine the carrier frequency, DOA and range of various source signals from data sources in mixed field.

A method and a radio access device for performing the method for positioning of a target station (STA) by a radio access device. The method receives sounding feedback, from a target station (STA), for each of a plurality of subbands in response to sending a sounding signal, the sounding feedback comprising channel quality information for each subband of the plurality of subbands. The method calculates an angle-of-arrival (AoA) characteristic from the sounding feedback for at least a subset of the plurality of subbands and maps the AoA characteristics of the at least the subset of the plurality of subbands to a fingerprint in a fingerprint reference map. The method then determines the location of the target STA based on at least the fingerprint.

A wireless communication apparatus includes a first antenna circuit that forms a beam selected from among a plurality of first beams through a beamforming process performed for communication using a millimeter wave band and a monitor that displays a first pattern indicating a radiation direction of the selected beam.

A wireless communication apparatus includes a first antenna circuit that forms a beam selected from among a plurality of first beams through a beamforming process performed for communication using a millimeter wave band and a monitor that displays a first pattern indicating a radiation direction of the selected beam.

A method for estimating angle of arrival (AoA) of signals in a wireless communication system applied in an apparatus can estimate multiple AOAs of multiple paths on one channel tap using a transmitting scheme of beamformed multiple transmissions at the transmitting side. In the transmitting scheme, the equivalent channels for paths with multiple AoAs can be viewed as random, and a subspace-based algorithm is applied for AoA estimation.