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 directive direction finding apparatus may comprise: a directivity-enabled antenna array in which a constituent antenna or antenna subarray has directivity in the same direction; an RF/IF receiver connected to the directivity-enabled antenna array; a digital receiver connected to the RF/IF receiver; a direction finder connected to the digital receiver; a directivity control unit to control an operation of the directivity-enabled antenna array; and a transport/control interface connected to the direction finder and to manage control and operation of the directivity-enabled antenna array, the RF/IF receiver, the digital receiver, the direction finder and the directive control unit.

A directive direction finding apparatus may comprise: a directivity-enabled antenna array in which a constituent antenna or antenna subarray has directivity in the same direction; an RF/IF receiver connected to the directivity-enabled antenna array; a digital receiver connected to the RF/IF receiver; a direction finder connected to the digital receiver; a directivity control unit to control an operation of the directivity-enabled antenna array; and a transport/control interface connected to the direction finder and to manage control and operation of the directivity-enabled antenna array, the RF/IF receiver, the digital receiver, the direction finder and the directive control unit.

The present disclosure relates to a user equipment in a wireless communication system, an electronic device, a method and a storage medium. The user equipment in the wireless communication system according to the present disclosure comprises one or more processing circuits, the processing circuits being configured to execute the following operations: acquiring a downlink signal from an electronic device in the wireless communication system; estimating the angle of arrival (AOA) of the downlink signal, wherein at least the AOA and the position of the electronic device are used for estimating the position of the user equipment. By using the user equipment, electronic device, method and storage medium according to the present disclosure, the AOA of a downlink signal may be estimated when the user equipment is in an idle or initial access state, and the AOA may be used for estimating the position of the user equipment.

The present disclosure discloses a three-dimensional co-prime cubic array direction-of-arrival estimation method based on a cross-correlation tensor, mainly solving the problems of multi-dimensional signal structured information loss and Nyquist mismatch in existing methods and comprising the following implementing steps: constructing a three-dimensional co-prime cubic array; carrying out tensor modeling on a receiving signal of the three-dimensional co-prime cubic array; calculating six-dimensional second-order cross-correlation tensor statistics; deducing a three-dimensional virtual uniform cubic array equivalent signal tensor based on cross-correlation tensor dimension merging transformation; constructing a four-dimensional virtual domain signal tensor based on mirror image augmentation of the three-dimensional virtual uniform cubic array; constructing a signal and noise subspace in a Kronecker product form through virtual domain signal tensor decomposition; and acquiring a direction-of-arrival estimation result based on three-dimensional spatial spectrum search.

According to one embodiment, an electronic apparatus includes processing circuitry. The processing circuitry estimates a first AoA of an arrival wave corresponding to a received signal from a receiving element array. The processing circuitry determines whether the estimated first AoA is an outlier or not. The processing circuitry outputs the first AoA as a second AoA, when the first AoA is not to be an outlier. The processing circuitry acquires one or more main-lobe angles assuming that the first AoA is a side-lobe angle of the receiving element array, when the first AoA is to be an outlier. The processing circuitry determines whether the main-lobe angle is an outlier or not. The processing circuitry outputs the main-lobe angle as the second AoA, when the main-lobe angle is not to be an outlier.

A transceiver system includes one or more groups of transceivers. The locations of the transceivers are initially unknown. During deployment, the location of each transceiver in the group is automatically estimated by the remaining transceivers in the group. Once the locations of the transceivers in the group are estimated, deployment of the transceivers is complete. The transceivers may estimate location attributes of mobile transceivers within a vicinity of the transceivers in the group.

The present invention discloses a system and a method for detecting, localizing and categorizing radio frequency (RF) emitting sources. In operation presence of one or more RF sources are determined. Further, movement in the detected one or more RF sources is detected based on at least presence of spread power in spatial harmonics and visibility phase measurement. The frequencies of the radio waves at which the movement of one or more RF sources is detected are identified. A localization antenna subsystem is tuned to the identified frequencies one at a time to localize and identify the RF sources. Furthermore, the RF source is classified as an airborne source or ground-based source using radio interferometry imaging. Finally, on determination that the moving RF source is airborne, the interferometric images are further processed to confirm the type of airborne source.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing angular estimation using machine learning. In particular, a radar system 102 includes an angle-estimation module 504 that employs machine learning to estimate an angular position of one or more objects (e.g., users). By analyzing an irregular shape of the radar system 102's spatial response across a wide field of view, the angle-estimation module 504 can resolve angular ambiguities that may be present based on the angle to the object or based on a design of the radar system 102 to correctly identify the angular position of the object. Using machine-learning techniques, the radar system 102 can achieve a high probability of detection and a low false-alarm rate for a variety of different antenna element spacings and frequencies.