15 results about "Virtual antenna array" patented technology

An electronic device may include an integrated circuit (IC) including a switch and a plurality of paths that may include a first transmit (Tx) path, a second Tx path, a first receive (Rx) path, and a second Rx path; a first antenna electrically connected with the first Tx path from among the plurality of paths; a second antenna electrically connectable with the second Tx path or the second Rx path from among the plurality of paths via the switch; a third antenna electrically connected with the first Rx path from among the plurality of paths; and at least one processor operably coupled with the IC.

This invention relates to the field of communication technology, specifically to a method and apparatus for the joint design of a virtual antenna array and beamforming for unmanned aerial vehicles (UAVs). The method includes: constructing a near-field signal transmission model based on the positions of each UAV, the distance between the communication user and the sensing target; determining an integrated sensing beamforming model based on the virtual antenna array; determining the downlink signal transmission model for the communication user and the sensing signal echo model based on the near-field signal transmission model; determining the Fisher information matrix and Cramer-Rhodes bound of the sensing target; constructing an objective function with the goal of minimizing the Cramer-Rhodes bound; and solving the objective function using an inner loop algorithm and an outer loop algorithm to determine the positions of each UAV and the beamforming matrix. This invention combines the coordinated position adjustment of multiple UAVs with cooperative beamforming to improve the communication quality for the communication user and the sensing performance for the sensing target, thereby fully utilizing the flexible deployment characteristics of UAVs.

A method may use hybrid-TDMA / FDMA frames to synchronize participating nodes to an orchestrator node of a virtual antenna array as the virtual antenna array transmits to a target node. The virtual antenna array is formed by the orchestrator node and the participating nodes. The orchestrator node synchronizes the participating nodes periodically using the hybrid-TDMA / FDMA frames. The virtual antenna array directs joint communications toward and receives communication from the target node. The communication from the target node may be used to learn channel state information (CSI) between the virtual antenna array and the target node. The nodes may include software-defined radios which execute the hybrid-TDMA / FDMA frames. The hybrid-TDMA / FDMA frames may include concurrent transmissions of signal data and metadata. The hybrid-TDMA / FDMA frames may decouple the duty-cycle from the number of nodes.

The invention discloses a UWB radar angle measurement method and device based on TDM-MIMO, and belongs to the technical field of radar signal processing. The method comprises the following steps: controlling the radar system to work according to a preset time sequence, switching and controlling the connection and working states of at least two bidirectional channels and at least four physical antennas in different time slices through a switch, and performing time-sharing configuration into a transmitting or receiving mode to obtain echo data; wherein the switching time of the radio frequency switch is less than the difference value between the minimum flight time of the signal and the emission duration time, so as to ensure that the switching does not influence normal transceiving. And recombining the data based on the equivalent spatial positions of the physical antennas in different time slices to form a virtual antenna array, and then estimating the direction of arrival. The device comprises a radar chip, an antenna array, a switching network and a control processing unit. According to the invention, through the optimized TDM-MIMO time sequence and strict time sequence constraint, a large-scale virtual array is formed by using a small amount of hardware resources, and high-precision angle measurement is realized with relatively low system complexity.

A method for designing a sparse MIMO virtual antenna array is disclosed. The method includes determining a size of an equivalent uniform linear array (ULA) based on a target number of sparse elements of the sparse MIMO virtual antenna array, setting a first optimization target to a maximum signal level of one or more sidelobes of the ULA when a beam is pointed to a boresight, setting a second optimization target to a maximum signal level of the one or more sidelobes of the ULA when the beam is pointed to an edge of a field of view, determining a set of spacing distances between antenna array elements of the sparse MIMO virtual antenna array that simultaneously minimizes the first optimization target and the second optimization target or minimizes a sum of the first optimization target and the second optimization target, and constructing the sparse MIMO virtual antenna array based on the determined set of spacing distances.

A system and method is presented for determining a plurality of MIMO virtual antenna arrays. Each virtual antenna array of the plurality of MIMO virtual antenna arrays is associated with a subset of a plurality of transmit antennas and a subset of a plurality of receive antennas. Signals received by the plurality of receive antennas are used to determine signal spectrums for each MIMO virtual antenna array of the plurality of MIMO virtual antenna arrays. Each signal spectrum includes signal magnitude values and has associated angle values, wherein main lobe positions of the signal spectrums of the plurality of MIMO virtual antenna arrays are at a same angle across all signal spectrums and sidelobe positions of the signal spectrums are not at the same angle across all signal spectrums. A first combined MIMO virtual antenna array signal spectrum is determined by combining minimum values of the signal spectrums at each angle value. The first combined MIMO virtual antenna array signal spectrum is used to detect an object.

The invention discloses a radar signal processing method, a circuit, a virtual antenna array, an antenna array and equipment. The radar signal processing method comprises the following steps: acquiring a distance Doppler spectrum of a radar signal; for a range gate, acquiring K Doppler units with targets in the range Doppler spectrum corresponding to the range gate; for a Doppler unit with a target, determining corresponding frequency spectrum estimation by adopting an iterative adaptive IAA spectrum estimation method accelerated by fast Fourier transform (FFT); and selecting one frequency spectrum meeting a set condition from the frequency spectrum estimations corresponding to the K Doppler units with the targets as an angle spectrum of the range gate, wherein the fast Fourier transform FFT is carried out based on the K Doppler units with the target, and K is an integer greater than 0. According to the scheme, the radar signal angle spectrum is determined through FFT accelerated IAA spectrum estimation, the distance angle spectrum calculation speed is remarkably increased, and the real-time requirement of radar signal processing is met.

The invention relates to the technical field of mobile robot platform radar imaging, in particular to a millimeter wave synthetic aperture radar imaging method and system based on a quadruped robot. The method comprises the steps that a traditional horizontal scanning track is adjusted into a vertical scanning path, and the quadruped robot is controlled to execute cyclic vertical and horizontal compound motion so as to construct a virtual antenna array; constructing a pose map by using sensor data of the robot, estimating a motion track through a pose map optimization algorithm, and compensating a phase error; and sequentially applying a frequency domain filtering fringe removing method and a generative adversarial network image restoration method taking an optical image as a reference to the initial SAR image to reconstruct a target contour and restore a missing region. According to the method, the influence of non-rigid motion of the quadruped robot on imaging is overcome, robust high-resolution imaging under shielding and non-line-of-sight scenes is realized, and the complex environment sensing capability of a mobile robot platform is expanded.

Method for determining at least one target information of a target object of a sensor system (2) which has several transmitting antennas (3) and several receiving antennas (4), wherein: - in a transmission process, several frequency-shifted electrical outgoing signals (40 to 43) are simultaneously transmitted from the several transmitting antennas (3) into an environment (18); - electrical receiving signals (54 to 57), which are based on the transmitted electrical outgoing signals (40 to 43), are received by the several receiving antennas; - on the basis of the received electrical receiving signals (54 to 57), the antenna positions of the several transmitting antennas (3) and the antenna positions of the several receiving antennas (4), a virtual antenna array (39) which has several virtual receiving antennas (61) is generated; - an environment reconstruction of the environment (18) is performed based on the virtual antenna array (39) is carried outand- which at least one target information is determined on the basis of the environmental reconstruction, wherein- a respective received electrical receive signal (54 to 57), which is assigned to a respective virtual receiving antenna (61) of the virtual antenna array (39), is mixed with a carrier signal (59) on which the several frequency-shifted electrical transmit signals (40 to 43) are based, and- for each virtual receiving antenna (61) a distance spectrum (62) is determined on the basis of the received signal (54 to 57) belonging to the respective receiving antenna (61) and mixed with the carrier signal, characterized in thatthat a respective distance spectrum (62) of a respective virtual receiving antenna (61) is decomposed into partial spectra (64 to 67) depending on a corresponding electrical outgoing signal (40 to 43) to the received signal (54 to 57) and by the transmitting antenna (3) emitting this electrical outgoing signal (40 to 43).

The application is suitable for the field of satellite communication, and provides a cooperative communication method and system of a vehicle-mounted satellite communication terminal, the method comprising: collecting spatial motion vectors, radio frequency channel nonlinear characteristics and service flow priority characteristics of each vehicle terminal in a cluster in real time; establishing a global unified time-frequency phase reference benchmark; dynamically calculating complex weighting vectors of signals transmitted by each node according to relative positions of satellites, and constructing an enhanced coherent synthesis beam in a space domain; performing space-time-frequency multi-dimensional mapping coding on service data flows, and performing distributed parallel transmission through the enhanced coherent synthesis beam; using a motion trend prediction technology to pre-compensate phase drift and channel blockage at a future time, and maintaining the persistence of a cooperative link; constructing a virtual antenna array through multi-vehicle cooperation, breaking through the limitation of a single-vehicle physical aperture, and effectively overcoming the signal blockage and fading problem in a complex environment by using a physical layer synchronization and feedforward compensation technology.

This invention proposes a method for acquiring physical channel fingerprints and constructing physical channel maps for large-scale MIMO-OFDM systems based on virtual antenna arrays. This method targets each grid within a target communication area, controlling a measurement terminal to move along a preset trajectory within the grid to synthesize a virtual antenna array to collect channel samples in the spatial-frequency-time domain. Based on the mapping relationship between physical channel fingerprints and beam-domain statistical channel state information, the channel samples measured by the virtual antenna array are processed to construct and solve an optimization problem using beam-domain statistical channel state information as an auxiliary variable and physical channel fingerprints as the target variable, thus acquiring the physical channel fingerprints. The position coordinate indexes of each grid are associated and stored with their corresponding physical channel fingerprints to construct a physical channel map with position indexing functionality. This invention, through flexible measurement terminal deployment, achieves reliable physical channel fingerprint acquisition and can be used for applications such as auxiliary statistical channel information acquisition, instantaneous channel estimation, and precoding.

Embodiments of the present disclosure provide a method, device, equipment, medium and program product for measuring the position of an interference source. The method comprises: obtaining measurement data collected by at least one unmanned aerial vehicle; the measurement data at least comprising: unmanned aerial vehicle position information and an interference signal sequence; and determining the position information of the interference source based on the measurement data. The method uses multiple unmanned aerial vehicles to cooperatively measure, achieves the effect of a virtual antenna array, and realizes high-precision positioning measurement of the interference source. Based on the flexibility of the deployment and transformation of the unmanned aerial vehicles, the number of unmanned aerial vehicles and the number of tests can be freely adjusted, thereby improving the flexibility and measurement accuracy of the positioning of the interference source.

Computing device for evaluating radar data from at least one MIMO radar sensor (2) with a non-uniform antenna array (3), comprising at least one interface (4) for receiving the radar data, and at least one computing module (5) designed to split the radar data into first radar data from a uniform portion (6) of a virtual antenna array (7) and second radar data from a non-uniform portion (8) of the virtual antenna array (7), to process the first and second radar data separately to obtain a uniform beam pattern (9) and a non-uniform beam pattern (10), to combine the uniform and non-uniform beam patterns (9, 10) to obtain an overall beam pattern (11), and to evaluate the overall beam pattern (11) using a trained artificial neural network (12) to obtain a unique angular position of at least one radar target (13).wherein the artificial neural network (12) is designed as a two-dimensional convolutional neural network comprising a convolution arrangement which is block-wise trained for evaluation in at least two dimensions by means of a convolution kernel and in which another convolution kernel reduces a depth of an output of the convolution kernel.

For example, a processor can be configured to process range Doppler (RD) information corresponding to an RD bin to identify a first plurality of values ​​corresponding to a first plurality of virtual antennas of a virtual antenna array, and a second plurality of values ​​corresponding to a second plurality of virtual antennas of the virtual antenna array. For example, the RD information corresponding to the RD bin can be based on radar receive (Rx) signals received by a plurality of Rx antennas, based on radar transmit (Tx) signals from a Tx array that includes a first plurality of Tx antennas and a second plurality of Tx antennas.For example, the processor can be configured to determine one or more estimated RD azimuth (RDAz)-based Doppler convolutions corresponding to one or more RDAz bins, for example, based on the first plurality of values ​​and the second plurality of values.

The application relates to the technical field of radio orientation, and discloses a UAV radio frequency countermeasure monitoring system based on multi-source signal state sensing, which comprises the following steps: a radio frequency acquisition subsystem synchronously acquires target and reference signals by using a double-channel common-source differential mechanism; a state synchronization bus obtains a UAV motion state vector; a virtual aperture synthesis processor calculates an instantaneous phase difference between channels to offset a local oscillator frequency drift, generates a correction phase sequence, and constructs a virtual antenna array model in combination with a motion trajectory to solve a target space incident angle, the application solves a phase non-coherent problem in the construction of a virtual aperture by low-cost hardware by using a reference channel differential mechanism, and realizes high-precision direction finding of long-wave signals on a small platform.