31 results about "Virtual antenna array" patented technology

The invention provides a distributed coherent communication system synchronization method, and the distributed coherent communication system enables dispersed nodes in a space to cooperate with each other through the construction of a virtual antenna array, so as to form a directional wave beam, thereby achieving the control and enhancement of a signal direction. A distributed Kalman filtering framework is introduced, a frequency and phase joint state space model is constructed, local observation data of nodes and neighbor state information are optimally fused, and dynamic estimation and compensation of frequency offset and phase errors are achieved. An updating strategy is designed in combination with an event triggering mechanism, local Kalman filtering prediction is executed in conventional iteration to suppress random noise and control the communication burden and calculation complexity of a system, meanwhile, the standard deviation of a residual phase error is effectively reduced by one order of magnitude, and the synchronization performance is improved.

A communication method and a communication apparatus are provided. The method includes: sending motion information of a terminal device and sending time information of a first antenna in a first virtual antenna array to a network device; receiving first configuration information from the network device, where the first configuration information is used to configure a first reference signal corresponding to the motion information and the sending time information; sending the first reference signal to the network device based on the first configuration information; and receiving a first multipath angle from the network device, where the first multipath angle indicates a multipath angle at which the first reference signal reaches the network device. The first antenna is any antenna in the first virtual antenna array.

Embodiments of the present disclosure relate to devices, methods, apparatuses, and computer readable storage media for virtual antenna array capability reporting, particularly suitable for integrated sensing and communication (ISAC). The method includes receiving, at a first device, information from a second device, the information associated with an antenna array arrangement and a sensing resolution related capability of the second device; determining, based at least on the information, whether one or more sensing measurement requirements for the sensing service are satisfied by the second device; and sending an indication associated with the one or more sensed measurement requirements to a second device based on the determination.

The invention relates to the technical field of radio orientation, and discloses an unmanned aerial vehicle radio frequency countering monitoring system based on multi-source signal state perception, and the system comprises a radio frequency collection subsystem which employs a dual-channel common-source difference mechanism to synchronously collect target and reference signals; the state synchronous bus obtains a motion state vector of the unmanned aerial vehicle; and the virtual aperture synthesis processor calculates an instantaneous phase difference between channels to offset local frequency drift, generates a correction phase sequence, constructs a virtual antenna array model in combination with a motion trail, and solves a target space incident angle. And high-precision direction finding of long-wave signals is realized on a small platform.

The invention relates to a method for the radar-based localization of an object by means of a radar system (2), to a method for the supervised training of a learning algorithm for emulating a virtual antenna array, to a method for the at least partially automatic guidance of a vehicle (1), to a data processing system (3), to a radar system (2) for the localization of an object, to an electronic vehicle guidance system for the at least partially autonomous guidance of a vehicle, and to a computer program product. The method for localization comprises the following steps: - receiving first radar data (7) of a first antenna array of a first radar sensor (4) of the radar system (2); - receiving second radar data (8) of a second antenna array, different from the first antenna array, of a second radar sensor (5) of the radar system (2); - generating third radar data (10) by emulating a third antenna array, different from the first and second antenna arrays, depending on the first radar data (7) and the second radar data (8); and - localizing the object depending on the third radar data (10).

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 for designing a sparse MIMO virtual antenna array is disclosed. The method includes: determining the 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 as the maximum signal level of one or more side lobes of the ULA when the beam is directed towards a boresight; setting a second optimization target as the maximum signal level of one or more side lobes of the ULA when the beam is directed towards the edge of the field of view; determining a set of separation distances between antenna array elements of the sparse MIMO virtual antenna array, and simultaneously minimizing the first and second optimization targets simultaneously, or minimizing the sum of the first and second optimization targets; and constructing a sparse MIMO virtual antenna array based on the determined set of separation distances.

The invention relates to a computing device for evaluating radar data from at least one MIMO radar sensor (2) having a non-uniform antenna array (3), the computing device comprising: at least one interface (4) for receiving the radar data; and at least one computing module (5) which is designed to divide the radar data into first radar data of a uniform portion (6) of a virtual antenna array (7) and second radar data of a non-uniform portion (8) of the virtual antenna array (7), to further process the first and second radar data separately from one another in order 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) in order to obtain an overall beam pattern (11), and to evaluate the overall beam pattern (11) by means of a trained artificial neural network (12) in order to determine an unambiguous angular position of at least one radar target (13).

The disclosure relates to a method for determining at least one item of target information of a target object of a sensor system, which has multiple transmitting antennas and multiple receiving antennas, wherein in a transmission process, multiple electrical emitted signals, which are frequency shifted relative to one another, are emitted simultaneously by the multiple transmitting antennas into the surroundings, electrical receive signals, which are based on the emitted signals, are received by the multiple receiving antennas, a virtual antenna array which has multiple virtual receiving antennas is generated by antenna positions of the multiple transmitting antennas and by antenna positions of the multiple receiving antennas, on the basis of the received electrical receive signals, a surroundings reconstruction of the surroundings is performed on the basis of the virtual antenna array, and the at least one item of target information is determined on the basis of the surroundings reconstruction.

The invention relates to the technical field of communication, in particular to an unmanned aerial vehicle virtual antenna array and beamforming joint design method and device. The method comprises the following steps: constructing a signal near-field transmission model based on the position of each unmanned aerial vehicle and the distance between a communication user and a sensing target; based on the virtual antenna array, determining a flux-inductance integrated beam model; determining a communication user downlink signal transmission model and a sensing signal echo model based on the signal near-field transmission model; determining a Fisher information matrix and a Cramer-Rao bound of the sensing target; constructing a target function by taking Cramer-Rao bound minimization as a target; and solving the target function by adopting an inner loop algorithm and an outer loop algorithm, and determining the position of each unmanned aerial vehicle and a beam forming matrix. According to the method, cooperative position adjustment and cooperative beam forming of the multiple unmanned aerial vehicles are jointly considered, so that the communication quality of communication users and the sensing performance of sensing targets are improved, and the purpose of fully utilizing the flexible deployment characteristic of the unmanned aerial vehicles is achieved.

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.

The application discloses a high-speed dynamic communication multi-target optimization method based on unmanned aerial vehicle cooperative beam forming, which comprises the following steps: step one, establishing a calculation model of the sum of transmission rates of the virtual antenna array of the unmanned aerial vehicle in the whole communication time as a first target function, establishing a calculation model of the total energy consumption of the unmanned aerial vehicle as a second target function, and obtaining the position of the mobile user in the communication system in each time slot; step two, taking the maximum of the first target function and the minimum of the second target function as the optimization target, and determining the optimal position of the unmanned aerial vehicle and the optimal excitation current weight of the unmanned aerial vehicle; and step three, the unmanned aerial vehicle moves to the optimal position, and transmits communication data to the user according to the optimal excitation current weight. The high-speed dynamic communication multi-target optimization method based on unmanned aerial vehicle cooperative beam forming can output the optimal moving position of the unmanned aerial vehicle and the optimal excitation current weight according to the position of the mobile user in real time, and realizes high-speed dynamic communication of wireless network communication.

A computing device for evaluating radar data from at least one MIMO radar sensor (2) with a non-uniform antenna array (3) is proposed, 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 of a uniform portion (6) of a virtual antenna array (7) and second radar data of 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).

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.

In the described example, a frequency modulated continuous wave (FMCW) radar system includes a first FMCW device including a first processor and a second FMCW device including a second processor. The first and second processors receive first and second sets of FMCW signals corresponding to a field of view (FOV), respectively, and independently process the first and second sets of FMCW signals to generate first and second sets of virtual antenna array signals, respectively. The second FMCW device transmits the second set of virtual antenna array signals to the first FMCW device. The first processor determines angle-of-arrival information for one or more objects within the FOV in response to the first and second sets of virtual antenna array signals.

This invention proposes a robust adaptive beamforming method for coherent signals based on a virtual antenna array. The method includes: constructing a virtual antenna array symmetrical to the physical antenna array, and combining the physical and virtual antenna arrays to construct a virtual antenna array model; constructing observation vectors using the virtual antenna array and intermediate array elements, and then reconstructing a new covariance matrix using Toplitz; and using the ESPRIT-like algorithm to estimate the DOA of the signal using the newly reconstructed covariance matrix. This method not only maintains strong coherent signal processing capabilities without reducing the degrees of freedom, but also exhibits excellent output performance.

The application discloses a kind of based on nesting three-dimensional SAR antenna array design method and application.For the problem of low resolution of small unmanned aerial three-dimensional SAR imaging, a design method of small three-dimensional SAR sparse antenna array configuration based on nesting is proposed;At the same time, based on the design method of three-dimensional SAR sparse antenna array, using the characteristics of slow flight speed of small unmanned aerial SAR, low azimuth doppler frequency, it is proposed to use azimuth decimation to obtain azimuth multi-shot data.Compared with the traditional method, the aperture length of the virtual antenna array formed by difference is twice that of the real antenna array by designing the sparse antenna array configuration, so as to improve the resolution in height direction;At the same time, the problem of distance-azimuth resolution reduction caused by traditional spatial averaging method is solved, and the resolution of three-dimensional SAR imaging result is improved.

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.

The invention relates to a method for radar-based localization of an object using a radar system (2), a method for supervised training of a learning algorithm for emulating a virtual antenna array, a method for at least partially automated driving of a vehicle (1), a data processing system (3), a radar system (2) for localizing an object, an electronic vehicle guidance system for at least partially autonomous driving of a vehicle, and a computer program product. The localization method comprises the following steps: - Receiving first radar data (7) from a first antenna array of a first radar sensor (4) of the radar system (2); - Receiving second radar data (8) from a second antenna array different from the first antenna array of a second radar sensor (5) of the radar system (2); - Generating third radar data (10) by emulating a third antenna array different from the first and second antenna arrays depending on the first radar data (7) and the second radar data (8); and - Locating the object depending on the third radar data (10).

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.

The application belongs to the technical field of microwave imaging, and relates to a 3D microwave near-field imaging method, device, system and medium thereof, comprising the following steps: dividing the entire antenna array topology structure into a plurality of first sub-blocks, a plurality of second sub-blocks, a plurality of third sub-blocks and a plurality of fourth sub-blocks; according to the divided first sub-blocks, second sub-blocks, third sub-blocks and fourth sub-blocks, taking the midpoint of each group of transceiving antenna phase centers on each sub-block as the equivalent phase center of a virtual antenna, respectively determining the virtual antenna array element arrangement on the first sub-blocks, second sub-blocks, third sub-blocks and fourth sub-blocks; according to the virtual antenna array element arrangement, compensating the transceiving data phase of the antenna array topology structure pre-acquired for the target transceiving data of the virtual antenna; and according to the target transceiving data of the virtual antenna, adopting a wave number domain algorithm and a BP algorithm for imaging. The advantage lies in that under the condition of reducing the use of transceiving antennas, the resolution and definition of the generated image are ensured not to be reduced.

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.