205 results about "Virtual array" patented technology

The invention discloses a target positioning method and system based on a single reference station, and relates to the field of wireless positioning, and the method comprises the steps: generating vortex electromagnetic waves carrying orbital angular momentum based on a transmitting end of a reference station, and generating a time-varying phase modulation transmitting signal and a metasurface time-varying coding sequence through a programmable metasurface; a time-varying phase modulation emission signal forms a multipath superposition effect in a propagation environment, a receiving end obtains a mixed signal of a direct wave and a reflected wave, and the receiving end carries out OAM mode separation on the mixed signal of the direct wave and the reflected wave through a spiral phase plate and an annular array to obtain signal components in different modes; and based on the signal component and the metasurface time-varying coding sequence, reconstructing an equivalent virtual array response by adopting a compressed sensing algorithm. According to the invention, the orbital angular momentum modal separation technology and the metasurface dynamic coding technology are creatively fused, and high-precision real-time direction finding in a complex multi-path environment is realized under a single base station architecture.

The invention belongs to the technical field of array signal processing, and particularly relates to a co-prime array design method based on virtual array hole filling, which comprises the following steps of: S1, forwards moving two sub-arrays of an extended co-prime array by a distance of Nd / 2; s2, turning over one sub-array of the shifted co-prime array to obtain an improved co-prime array; s3, generating a differential virtual array according to the improved co-prime array; s4, introducing and combining the array to carry out hole filling on the differential virtual array; s5, calculating a received signal model and a covariance matrix of the filled virtual array; and S6, DOA estimation is carried out by using an ROOT-MUSIC algorithm. The method has the advantages that better signal source resolution and lower array element mutual coupling are achieved, meanwhile, the continuous freedom degree is improved, more signal sources can be estimated at the same time, and high practical value is achieved.

The invention provides a sparse array direction-of-arrival estimation method based on a local and global self-supervised network, and the method comprises the steps: 1, carrying out the signal processing: constructing any sparse array receiving signal, and carrying out the difference set virtual array extension, and obtaining the difference set virtual array measurement data; constructing a neural network training data set according to the measurement data; 2, establishing a local and global feature extraction network; step 3, establishing an ANM (Atomic norm Minimization) self-supervised network; and step 4, performing meshless signal recovery and DOA (direction of arrival) estimation, realizing label-free self-supervision data recovery, and finally performing DOA estimation by using the recovered meshless data. The new scheme provided by the invention has meshless recovery performance, solves the problem of base mismatching of a traditional neural network method, and has more accurate recovery and estimation performance.

The invention discloses a non-circular EBNC-PFLOM joint optimization DOA estimation method under impulse noise, and belongs to the technical field of array signal processing, and the method comprises the steps: firstly, through an array antenna of a dual-interproton array structure, receiving a received signal; secondly, respectively calculating an EBNC matrix and a PFLOM matrix by different order moment parameters based on a received signal; and finally, on the basis of the EBNC matrix and the PFLOM matrix, virtual array receiving signals are obtained through calculation, a covariance matrix is constructed, and a DOA estimation value is obtained through dimension reduction MUSIC. According to the method, efficient DOA estimation without spatial smoothing is realized, and the problem of performance degradation of a traditional method under non-Gaussian noise is solved.

This disclosure describes techniques for detecting multipath radar returns and modifying radar data. A vehicle may use radar devices to receive radar data while traversing within an environment. The vehicle may process the radar data using a virtual array based on an arraignment of the antennae within an aperture of the radar device. Using the virtual array, the vehicle may determine an elevated noise level that may be indicative of a multipath radar return. Based on the elevated noise level, the vehicle may determine a second virtual array associated with multipath radar returns, and may process the radar data using the second virtual array. Based on determining that the noise level associated with the second virtual array is lower than the initial noise level, the vehicle may determine that the radar data includes a multipath radar return, and may modify the radar data to correct or mitigate the error caused by the multipath return.

The invention belongs to the crossing field of information and ocean science and technology, and discloses a DOA estimation method for a UUV broadside parallel co-prime array. According to the method, firstly, a virtual extension array is generated by utilizing an array auto-covariance and cross-covariance matrix, then, Toeplitz completion is carried out on'holes' in the virtual array through trace norm regularization and nuclear norm regularization constraints, a complete covariance structure is recovered, and finally, an extension matrix is constructed, and rotation invariance of a signal subspace of the extension matrix is utilized, so that the covariance structure of the virtual array is obtained. The pitch angle and the azimuth angle of the target are jointly solved, automatic angle pairing is achieved, and the effectiveness and the reliability of the method are verified through simulation results. According to the method, aiming at the application challenges that the UUV broadside array space is limited and the underwater environment is complex, all virtual array elements of the broadside parallel co-prime array are fully utilized, the array freedom degree and estimation precision are remarkably improved, the target detection capacity of the UUV is effectively enhanced, and the method has high practical engineering application value.

The invention discloses a real-time positioning method, system and device supporting multi-frequency Beidou signals and a medium. The method comprises the steps that multi-frequency observation is collected in parallel, and quality features are generated; performing distribution alignment of risk perception based on the quality features to obtain equivalent observation; generating a causal weight by adopting anti-fact evaluation based on influence approximation; in the cross-frequency fusion model, taking multiple paths as potential disturbance quantities, only implementing group stripping on suspicious stars, frequencies or time periods, and solving and outputting a positioning result in combination with robust constraint and increment; a confidence radius is generated on line, the confidence radius is used as a main control signal to execute risk-driven self-adaptive control, and the risk-driven self-adaptive control comprises weight adjustment, measurement subset selection and front-end loop and frequency chain working state adjustment; and implementing topological consistency goalkeeping on a multi-frequency phase level, and triggering time domain virtual array suppression and feeding back to the fusion model when abnormity occurs. The system can significantly improve the precision, robustness and integrity of Beidou multi-frequency real-time positioning.

The invention relates to the field of underwater acoustic detection, and discloses a high-resolution target orientation estimation method and device based on adjacent grid re-optimization, and the method comprises the steps: carrying out the expansion of an array manifold into a virtual array manifold, taking the virtual array manifold as a covariance matrix of an over-complete dictionary construction receiving signal, and carrying out the iterative updating of a noise signal component and a signal component; re-optimizing the adjacent grids to update the dictionary, and performing orientation estimation again in the re-divided intervals; and obtaining a direction-of-arrival estimation result through spectrum peak search. By applying the method, the orientation estimation performance of the underwater vehicle can be improved, and the DOA estimation performance with higher robustness and higher estimation precision can be obtained on a small array.

The invention relates to a high-signal-to-noise-ratio ultrasonic imaging method and device for internal defects of a curved surface component, a medium and a product, and belongs to the technical field of ultrasonic imaging. According to the method, a linear array ultrasonic probe is adopted to carry out single-time ultrasonic excitation on a curved surface component, a full-matrix echo signal is obtained, first arrival time extraction is carried out on the collected signal, an ultrasonic incident angle is estimated, and discrete coordinates of the surface of the component are obtained; the method comprises the following steps of: fitting a curved surface model, constructing an equivalent virtual array model, calculating transmitting and receiving delay time of each pixel point, realizing initial full-focusing beam forming of signals, estimating an expected signal variance and a noise variance based on maximum likelihood estimation, constructing an initial coherent beam forming machine and performing iterative updating, and finally forming a beam. And taking the coherent beam synthesizer obtained by iteration as a weighting factor, acting on an initial beam synthesis signal for weighting, and completing image reconstruction. The method has the advantages of being high in calculation efficiency, low in system overhead, high in imaging signal-to-noise ratio and the like, and accurate imaging can be achieved in a curved surface structure scene.

The invention discloses a sparse polarization MIMO radar multi-parameter estimation method based on tensor decomposition, and the method comprises the steps: firstly constructing a dual-station MIMO radar system based on a polarized antenna, and calculating a covariance matrix of a receiving signal of a matched filter of a receiving end; then converting the covariance matrix into a tensor form, performing dimension transformation on the tensor, and obtaining a virtual covariance tensor of continuous virtual array elements in the difference joint array by using two transformation matrixes; dividing the virtual covariance tensor into a plurality of sub-tensors and connecting the sub-tensors along a fifth dimension and a sixth dimension; and finally, tensor decomposition is performed on the tensor obtained after connection, and multi-dimensional parameter estimation of the far-field target can be realized by using a matrix obtained through decomposition. The method has the advantages that joint estimation of the direction of arrival, the direction of departure and the polarization parameters is achieved under the underdetermined condition, and the estimation precision is high.

The embodiment of the invention provides an antenna array, a radar, electronic equipment and a vehicle, and belongs to the technical field of antennas. Wherein the antenna array comprises a transmitting antenna array and a receiving antenna array. The transmitting antenna array and the receiving antenna array are used for forming a virtual array. The transmitting antenna array comprises at least two transmitting sub-arrays which are arranged at intervals in the first direction, and the distance between every two adjacent transmitting sub-arrays in the first direction is smaller than or equal to the aperture length of the receiving antenna array in the second direction. The receiving antenna array comprises at least two receiving sub-arrays arranged along the second direction, and each receiving sub-array comprises at least two receiving antennas arranged at intervals along the second direction. And the receiving antenna array satisfies the relational expression: 0 < dn-dn-1 < = 0.5 lambda. The antenna array provided by the embodiment of the invention has the characteristics of large array aperture, high resolution, no grating lobe and low side lobe.

The embodiment of the invention provides a millimeter wave radar transmit-receive array error calibration method and related equipment. The method comprises the following steps: acquiring a target virtual channel complex value matrix; determining a target calibration phase matrix according to the target virtual channel complex value matrix; determining a target amplitude-phase calibration factor matrix according to the target virtual channel complex value matrix and the target calibration phase matrix; executing a target phase calibration operation according to the target calibration phase matrix; and executing a target amplitude and phase calibration operation according to the target virtual channel complex value matrix and the target amplitude and phase calibration factor matrix. In this way, the phase error between the transmitting antennas caused by the machining process and the like can be compensated, so that the transmitting gain after synthesis is improved, the probability of distortion of spatial synthesis of a transmitting directional diagram is reduced, the amplitude-phase error between the MIMO virtual arrays is compensated, the accuracy of an angle measurement result is improved, and therefore the spatial synthesis precision is improved; and the radar detection quality and detection precision are improved.

This invention discloses a deep learning-based channel estimation method for asymmetric all-digital communication systems, comprising: designing an uplink receiving array based on a nested sparse array topology to recover the received signal of the sparse array into a virtual array signal of full dimension; decomposing the obtained virtual signal into a grid part and an off-grid part based on Taylor formula, and designing a two-step-angle estimation net (Ts-AEnet) to estimate the signal angle of arrival; solving a least-squares problem to estimate the signal path gain and reconstructing the downlink channel. This invention proposes an uplink receiving array based on a nested sparse array topology in asymmetric all-digital communication systems, minimizing information loss caused by missing antennas, and proposes a deep learning-based Ts-AEnet angle estimation network, which reduces the complexity of channel estimation while ensuring the system's estimation accuracy.

The invention belongs to the technical field of radar signal processing and imaging, and particularly relates to a distributed MIMO radar imaging method based on multi-technology fusion, which comprises the following steps: S1, constructing a distributed MIMO radar array: constructing a distributed array consisting of L identical MIMO radar units, each unit comprising M transmitting antennas and N receiving antennas; the multi-radar synchronous imaging method is characterized in that each radar unit adopts an offset frequency orthogonalization design, signals of each radar unit and different transmitting antennas in the same unit are mutually orthogonal in a time domain and a frequency domain by elaborately setting the offset frequency of each transmitting antenna, a virtual array is equivalent to a uniform linear array, and multi-radar synchronous imaging is realized by utilizing a high-precision synchronous control mechanism. According to the method, the equivalent aperture is greatly expanded through cooperative work of the distributed MIMO radar arrays, so that the angular resolution is remarkably improved, the accuracy and reliability of echo signals are guaranteed by adopting a unique orthogonal signal design, and the imaging stability is improved.

Existing approaches for channel estimation in Reconfigurable Intelligent Surface (RIS) assisted communication systems have the disadvantage that they require separate estimation of Angle of Arrival (AoA) and Angle of Departure (AoD), requiring additional step of computationally demanding data association. Embodiments disclosed herein provide a method and system for channel estimation in RIS assisted communication systems. In this approach, the system jointly visualizes the plurality of RIS elements and the plurality of multi-antenna receiver array elements as a RIS-SIMO virtual array, thereby eliminating need to separately estimate the AoA and AoD.

The invention discloses an MIMO signal channel separation and reconstruction method and system for a millimeter wave radar. The method comprises the steps of obtaining echo signals of the millimeter wave radar and converting the echo signals into a plurality of 4D matrixes; performing fast Fourier transform based on the 4D matrix to obtain a transformed 4D matrix and distance-Doppler spectrum data; distance-Doppler unit index value pairs corresponding to all peak values are obtained based on the distance-Doppler spectrum data; all the distance-Doppler unit index value pairs are substituted into the transformation 4D matrix, and a plurality of MIMO signal channel data two-dimensional matrixes are correspondingly obtained; constructing a channel reconstruction matrix based on the virtual array surface features; and filling the MIMO signal channel data two-dimensional matrix into the channel reconstruction matrix according to a specific sequence to obtain a non-sparse channel reconstruction matrix. The MIMO signal channel separation efficiency and accuracy are improved, and the processing efficiency and robustness of diversified and complex radar data are further improved.

The invention discloses a millimeter wave radar MIMO multichannel signal sparse separation reconstruction method and system, belongs to the technical field of MIMO radar target detection, and solves the problem of how to improve the MIMO multichannel signal separation efficiency and accuracy, and the method comprises the steps: obtaining a millimeter wave radar echo signal, and converting the millimeter wave radar echo signal into a 4D matrix; performing fast Fourier transform on the 4D matrix to obtain a frequency domain 4D complex matrix and distance-Doppler spectrum data; further obtaining distance-Doppler unit index value pairs corresponding to all peak values; inputting the distance-Doppler unit index value pair into the frequency domain 4D complex matrix to obtain an MIMO multichannel signal two-dimensional matrix; based on the sparse number matrix corresponding to the virtual array, combining with the MIMO multichannel signal two-dimensional matrix, obtaining a two-dimensional sparse reconstruction matrix through numerical relation mapping, and performing vacancy position zero padding operation on the two-dimensional sparse reconstruction matrix to obtain a two-dimensional reconstruction matrix; according to the invention, the efficiency and accuracy of MIMO multi-channel signal separation are improved.

The invention provides a multi-frequency distributed nested array DOA estimation method based on low-rank constraint, and the method comprises the steps: S1, building a receiving signal model of a distributed nested array, and obtaining a receiving signal based on the receiving signal model; s2, calculating a covariance matrix of the received signal, and performing vectorization processing on the covariance matrix to obtain a first virtual array corresponding to the distributed nested array; s3, extrapolating sub-arrays in the first virtual array to fill part of holes existing under the long baseline condition to obtain a second virtual array; s4, zero elements are inserted into the remaining hole positions to obtain a third virtual array, and the rank of the covariance matrix corresponding to the third virtual array is recovered; s5, establishing a matrix reconstruction model combining the low-rank constraint and the sparsity constraint, and solving to obtain a complemented covariance matrix; and S6, carrying out characteristic decomposition on the complemented covariance matrix to obtain a final DOA estimation value.

The invention discloses a millimeter wave scattering aperture sparse three-dimensional imaging method and a millimeter wave scattering aperture sparse three-dimensional imaging system, and aims to realize high-resolution three-dimensional reconstruction through a sparse reconstruction algorithm aiming at a non-vision field target imaging problem under a rough scattering surface condition. The method comprises the following steps: firstly, improving the spectral resolution of an echo signal by using a time domain zero padding technology, accurately positioning a scattering aperture position based on spectrum peak estimation and completing distance compensation, converting a non-vision field echo into an equivalent vision field echo, and retaining complete information of a target; secondly, in combination with target space scattering point sparsity and scattering aperture sparse sampling characteristics, a virtual array and a measurement matrix are constructed, an imaging problem is converted into a sparse reconstruction task, and a target scattering coefficient is efficiently solved by adopting a generalized orthogonal matching pursuit algorithm; the dependence on a mirror reflection condition is broken through, and a non-vision target can be accurately reconstructed in a diffuse reflection scene; compared with an existing scattering aperture algorithm, the method has the advantage that the imaging resolution and the anti-noise capability are remarkably improved through double sparsity constraints. The method has important application value.

A method, a sensor system, and a non-transitory computer readable medium are provided to determine the angle of arrival of signal 300 reflected of a target object 302. The method involving receiving a plurality of incident signals reflected from a target at a plurality of receiver antennas 304, identifying with a processor a subset of receiver antennas (404. Fig 4) from the plurality of receiver antennas when the target is in a near filed of the plurality of receiver antennas. The processor performs angle of arrival (AOA) processing on respective incident signals of the subset of receiver antennas to determine the angle of arrival of the signal. The method preferably determining an elevation and azimuth angle of the target based on the angle of arrival. The plural antenna are preferable part of a switched antenna array. The receiver antennas preferably being part of a multiple input multiple output (MIMO) radar and the subset corresponds to a virtual array formed by the MIMO radar. Preferably using all the plurality f antennas to perform AoA determination when the target is determined to be in the far field of the radar.

A reconfigurable array mode sharing method for an MIMO frequency modulation millimeter wave radar array comprises the steps that distance dimension fast Fourier transform and speed dimension fast Fourier transform are carried out on echo signal data matrixes obtained after analog-to-digital conversion is carried out on the basis of different modes, and distance Doppler spectrums of different receiving and transmitting antenna combinations are obtained; different modes with the same gain of the MIMO radar system are combined, the mode corresponding to the maximum virtual array aperture in the horizontal direction and the maximum virtual array aperture in the pitching direction under the gain is selected from the combination with the same gain, the two modes are subjected to angle solution and matching, angle solution of the maximum virtual array aperture is achieved in a combined mode, and the maximum virtual array aperture is obtained. A digital beam forming method is used for matching angle information of the two dimensions obtained by solving under a horizontal dimension virtual array and a pitching dimension virtual array with the maximum aperture. According to the invention, when a virtual array reconfigurable technology or an MIMO technology is used, the maximum array aperture in the original same gain mode can be effectively increased by using the complementary effect between different reconfigurable array modes.

The invention discloses a novel non-uniform array-based signal source positioning method, which comprises the following steps of: determining an actual array element position through flexible array distribution according to environmental characteristics when a target signal reaches the ground; calculating a virtual domain differential common array, determining the position of a virtual array element, constructing a signal model, and calculating a covariance matrix; vectorizing the covariance matrix, and removing redundancy to obtain an equivalent receiving signal of the virtual domain; performing spatial smoothing processing on the equivalent covariance matrix of the virtual domain to obtain a smoothed data correlation matrix; after characteristic decomposition, constructing a signal subspace; and finally, dividing signal subspaces based on an ESPRIT algorithm idea, and calculating a rotation matrix to obtain an estimated angle. The designed non-uniform array can flexibly adjust the array element layout according to complex environment characteristics, the flexible array layout strategy improves the freedom degree of the array, the spatial sampling and signal analysis efficiency is optimized, meanwhile, the calculation path is simplified, and the algorithm complexity is reduced.

The invention relates to a sparse array antenna, a construction method and device and electronic equipment. Wherein the sparse array antenna comprises a sparse sub-array and a uniform sub-array, and the sparse sub-array and the uniform sub-array are located at a group of diagonal positions of the same rectangle; the sparse sub-array comprises a first antenna array, a second antenna array, a third antenna array and a fourth antenna array, and a first straight line where the first antenna array and the second antenna array are located is perpendicular to a second straight line where the third antenna array and the fourth antenna array are located; the uniform sub-array comprises a fifth antenna array and a sixth antenna array, and a third straight line where the fifth antenna array is located is perpendicular to a fourth straight line where the sixth antenna array is located. The array structure of the sparse array antenna provided by the embodiment of the invention has a closed-form solution, so that unique deterministic structures of various scales can be realized; moreover, the structure enables the number of FODC virtual array holes of the sparse array antenna to be reduced, and effectively improves the degree of freedom.

The invention relates to an array aperture expansion method based on motion platform distance Doppler domain extrapolation, and belongs to the technical field of radar array signal processing. Comprising the following steps: receiving echo data of a target by using a motion array, and performing down-conversion and time domain segmentation processing on each array element data; performing distance Doppler transformation and target detection on the baseband data of each array element and each time period to obtain distance Doppler unit data of a target; target distance and speed are obtained and are suitable for moving target detection; and extrapolation processing is carried out based on target distance Doppler unit data of different array elements and different time periods, an estimated value of virtual array element data is obtained, and array aperture expansion is realized. The method is suitable for a shipborne high-frequency ground wave system radar, and through the distance Doppler domain processing and time domain segmentation technology, the problems that the radar array aperture is small and the radar angle measurement performance is reduced due to the limited space of a shipborne platform are solved.

The invention provides a downlink channel recovery method for an asymmetric large-scale MIMO system under UPA. The method comprises the following steps: S1, according to the distribution of an asymmetric array, carrying out zero padding on a received signal, defining a mixed angle and constructing a virtual array; s2, designing an antenna selection algorithm on the premise of ensuring the UPA first row array aperture, and constructing a maximum aperture virtual array with as few antennas as possible; s3, respectively executing improved Newton orthogonal matching pursuit on receiving signals of the virtual array and the first row of arrays, and obtaining all possible path gains, azimuth angles and elevation angles until the gains, azimuth angles and elevation angles respectively meet threshold values; s4, combining and pairing the estimated path gain, elevation angle and azimuth angle according to related criteria; and S5, recovering a downlink channel by using the obtained path gain and angle parameter pair and the downlink steering vector. According to the method, part of channel information contained in the virtual array is fully utilized, and the downlink channel recovery performance is effectively improved while the number of received uplink radio frequency chains and the calculation complexity are remarkably reduced.

The invention relates to a two-dimensional staggered array MIMO (Multiple Input Multiple Output) radar system for monitoring dynamic deformation of a bridge, which realizes decoupling of spatial resolution and time resolution by adopting a two-dimensional staggered array MIMO radar hardware architecture and replacing traditional mobile synthetic aperture with static virtual aperture synthesis through integrated design. According to the system, a continuous virtual area array is synthesized through transmitting and receiving arrays which are in non-uniform sparse arrangement, and high-resolution three-dimensional imaging of a bridge monitoring area is realized in combination with an FMCW signal processing and near-field three-dimensional imaging algorithm; and carrying out pixel-level processing on the serialized three-dimensional complex image by using a rapid time sequence interference and deformation extraction module to obtain a high-precision deformation sequence. The method does not need a mechanical scanning part, has the advantages of high environmental robustness, low hardware cost, flexible deployment and the like, and can provide panoramic and high-precision four-dimensional dynamic deformation field data for bridge structure state evaluation.

The invention discloses a TDM-MIMO radar Doppler phase offset compensation method based on iteration, and the method comprises the steps: carrying out the equivalent conversion of a TDM-MIMO radar model into a one-transmitting-multiple-receiving virtual array model, building a signal receiving model of a virtual array, and obtaining a beat signal; constructing a target echo space-time joint matrix; constructing an airspace signal vector based on the target initial Doppler frequency; and performing iterative estimation on target angle estimation and Doppler frequency, and estimating the angle by using a phase offset compensation result. According to the method, the Doppler frequency is scanned more meticulously by constructing the Doppler frequency scanning manifold matrix, the Doppler frequency dimension and the angle dimension are decoupled, the space-time combined two-dimensional estimation is converted into two one-dimensional estimation, and the accurate Doppler frequency and angle are obtained after few times of iteration.

A process and systems for constructing arbitrarily large virtual arrays using two or more collection platforms (e.g. AUX and MOV systems) having differing velocity vectors. Referred to as Motion Extended Array Synthesis (MXAS), the resultant imaging system is comprised of the collection of baselines that are created between the two collection systems as a function of time. Because of the unequal velocity vectors, the process yields a continuum of baselines over some range, which constitutes an offset imaging system (OIS) in that the baselines engendered are similar to those for a real aperture of the same size as that swept out by the relative motion, but which are offset by some (potentially very large) distance.

The embodiments of the present application relate to the field of vehicle-mounted radar technology, and disclose a MIMO vehicle-mounted radar multipath target identification method, device, medium and product. Perform spatial convolution on the transmitting antenna and receiving antenna of the MIMO vehicle-mounted radar, which is equivalent to receiving echo data of multiple virtual channels; calculate the average phase difference of the virtual array to obtain the virtual array angle measurement result; calculate the angle average of all row subarrays and the angle average of all column subarrays according to the two-dimensional array; construct a loss function, and calculate the judgment threshold of the multipath target according to the virtual array angle measurement result, the row subarray angle average and the column subarray angle average; compare the judgment threshold with the set threshold, and when the judgment threshold exceeds the set threshold, identify the current target as a multipath target, otherwise it is identified as a real target. It can at least be used to solve the technical problem of insufficient accuracy in radar multipath target identification.

The spatial resolution of the virtual array antenna and the accuracy of the virtual array antenna's target direction estimation are adjusted according to the purpose. [Solution] The antenna device according to the embodiment comprises a reference signal generation unit, a first module, a second module, and a phase value generation unit. The phase value generation unit generates a first phase value based on the phase difference of the received signals in at least two virtual antennas, which are formed based on the received signals received by at least a portion of the first receiving antenna and the second receiving antenna when the first transmitting antenna transmits a transmission signal based on the first reference signal. The first transmission processing circuit shifts the phase of the second reference signal, which is transmitted by the second transmitting antenna after the first transmitting antenna, by the first phase value.