公开(公告)号：US20230048116A1

公开(公告)日：2023-02-16

申请号：US17439813

申请日：2020-12-16

申请人： Zhejiang University

发明人： Jiming CHEN ,  Zhiguo SHI ,  Hang ZHENG ,  Chengwei ZHOU

IPC分类号： G01S3/14 ,  H01Q3/26

摘要： The present invention belongs to the field of array signal processing and relates to a composite tensor beamforming method for an electromagnetic vector coprime planar array. The method includes: building an electromagnetic vector coprime planar array; performing tensor modeling of an electromagnetic vector coprime planar array receiving signal; designing a three-dimensional weight tensor corresponding to a coprime sparse uniform sub-planar array; forming a tensor beam power pattern of the coprime sparse uniform sub-planar array; and performing electromagnetic vector coprime planar array tensor beamforming based on coprime composite processing of the sparse uniform sub-planar array. Starting from the principles of receiving signal tensor spatial filtering of two sparse uniform sub-planar arrays that compose the electromagnetic vector coprime planar array, the present invention forms a coprime composite processing method based on a sparse uniform sub-planar array output signal.

公开(公告)号：US20230280433A1

公开(公告)日：2023-09-07

申请号：US17922973

申请日：2021-10-29

申请人： Zhejiang University

发明人： Jiming CHEN ,  Hang ZHENG ,  Chengwei ZHOU ,  Zhiguo SHI

IPC分类号： G01S3/14

CPC分类号： G01S3/143

摘要： Disclosed in the present invention is a method for estimating a direction of arrival of a sub-array partition type L-shaped coprime array based on fourth-order sampling covariance tensor denoising, which mainly solves problems of a damage to a signal structure and noise term interference to high-order virtual domain statistics in an existing method. The implementation steps are as follows: constructing an L-shaped coprime array partitioned with linear sub-arrays; modeling a receiving signal of the L-shaped coprime array and deriving a second-order cross-correlation matrix thereof, deriving a fourth-order covariance tensor based on the cross-correlation matrix; realizing fourth-order sampling covariance tensor denoising based on kernel tensor thresholding; deriving a fourth-order virtual domain signal based on denoised sampling covariance tensor; constructing a denoised structured virtual domain tensor; obtaining a direction of arrival estimation result by decomposing the structured virtual domain tensor.

公开(公告)号：US20210364591A1

公开(公告)日：2021-11-25

申请号：US17395478

申请日：2021-08-06

申请人： ZHEJIANG UNIVERSITY

发明人： Chengwei ZHOU ,  Hang ZHENG ,  Jiming CHEN ,  Zhiguo SHI

IPC分类号： G01S3/14 ,  G01S3/02 ,  G01S3/04 ,  G01S3/74

摘要： Disclosed is a high-resolution accurate two-dimensional direction-of-arrival estimation method based on coarray tensor spatial spectrum searching with coprime planar array, which solves the problem of multi-dimensional signal loss and limited spatial spectrum resolution and accuracy in existing methods. The implementation steps are: constructing a coprime planar array; tensor signal modeling for the coprime planar array; deriving coarray statistics based on coprime planar array cross-correlation tensor; constructing the equivalent signals of a virtual uniform array; deriving a spatially smoothed fourth-order auto-correlation coarray tensor; realizing signal and noise subspace classification through coarray tensor feature extraction; performing high-resolution accurate two-dimensional direction-of-arrival estimation based on coarray tensor spatial spectrum searching. In the present method, multi-dimensional feature extraction based on coarray tensor statistics for coprime planar array is used to implement high-resolution, accurate two-dimensional direction-of-arrival estimation based on tensor spatial spectrum searching, and the method can be used for passive detection and target positioning.

公开(公告)号：US20240295595A1

公开(公告)日：2024-09-05

申请号：US18022990

申请日：2022-02-16

申请人： Zhejiang University

发明人： Zhiguo SHI ,  Hang ZHENG ,  Jiming CHEN ,  Chengwei ZHOU ,  Yong WANG

IPC分类号： G01R29/08

CPC分类号： G01R29/0892

摘要： Disclosed in the present invention is a space spectrum estimation method of a super-resolution coprime planar array based on tensor filling of an optimal structured virtual domain, which mainly solves problems that pieces of missing elements in the virtual domain tensor of the existing method are difficult to be filled effectively. The method includes: modeling a tensor signal of a coprime planar array; deriving an augmented virtual planar array based on a cross-correlation tensor dimension combination; constructing the virtual domain tensor based on a mirror extension of the discontinuous virtual planar array; reconstructing a virtual domain tensor by superposition transformation of virtual domain sub-tensors; obtaining the optimal structured virtual domain tensor based on the dimension optimization of the virtual domain sub-tensors; filling the structured virtual domain tensor based on an alternating direction method of multipliers; and decomposing the filled structured virtual domain tensor to achieve a super-resolution spatial spectrum estimation.

公开(公告)号：US20240210510A1

公开(公告)日：2024-06-27

申请号：US17920401

申请日：2022-02-16

申请人： Zhejiang University

发明人： Hang ZHENG ,  Chengwei ZHOU ,  Zhiguo SHI ,  Yong WANG ,  Jiming CHEN

IPC分类号： G01S3/14

CPC分类号： G01S3/143

摘要： Disclosed in the present invention is a two-dimensional direction-of-arrival estimation method for a coprime surface array based on virtual domain tensor filling, which mainly solves the problems of the loss of multi-dimensional signal structural information and the inability to fully utilize virtual domain statistics in the existing method. The steps thereof are as follows: constructing a coprime surface array; modeling a tensor of a received signal of the coprime surface array; constructing an augmented non-continuous virtual surface array based on cross-correlation tensor transformation of the coprime surface array; deriving a virtual domain tensor based on mirror extension of the non-continuous virtual surface array; dispersing contiguous missing elements by reconstructing the virtual domain tensor; filling the virtual domain tensor based on the minimization of a tensor kernel norm; and decomposing a filled virtual domain tensor to obtain a direction-of-arrival estimation result.

公开(公告)号：US20230055481A1

公开(公告)日：2023-02-23

申请号：US17623607

申请日：2021-01-20

申请人： Zhejiang University

发明人： Zhiguo SHI ,  Hang ZHENG ,  Chengwei ZHOU ,  Jiming CHEN ,  Yong WANG

IPC分类号： G01S3/14

摘要： 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.

公开(公告)号：US20230213606A1

公开(公告)日：2023-07-06

申请号：US17799930

申请日：2021-07-12

申请人： Zhejiang University

发明人： Hang ZHENG ,  Chengwei ZHOU ,  Zhiguo SHI ,  Jiming CHEN

IPC分类号： G01S3/14

CPC分类号： G01S3/143

摘要： The disclosure provides a method for estimating a direction of arrival of an L-type coprime array based on coupled tensor decomposition. The method includes: constructing an L-type coprime array with separated sub-arrays and modeling a received signal; deriving a fourth-order covariance tensor of the received signal of the L-type coprime array; deriving a fourth-order virtual domain signal corresponding to an augmented virtual uniform cross array; dividing the virtual uniform cross array by translation; constructing a coupled virtual domain tensor by stacking a translation virtual domain signal; and obtaining a direction of arrival estimation result by coupled virtual domain tensor decomposition. The present invention makes full use of the spatial correlation property of the virtual domain tensor statistics of the constructed L-type coprime array with the separated sub-arrays, and realizes high-precision two-dimensional direction of arrival estimation by coupling the virtual domain tensor processing, which can be used for target positioning.

公开(公告)号：US20220179031A1

公开(公告)日：2022-06-09

申请号：US17291993

申请日：2020-11-03

申请人： ZHEJIANG UNIVERSITY

发明人： Chengwei ZHOU ,  Zhiguo SHI ,  Jiming CHEN

IPC分类号： G01S3/14

摘要： The invention discloses a method for estimating the direction-of-arrival of a coprime array based on virtual domain statistics reconstruction of single-bit quantized signal, which mainly solves the problems of difficult realization of software and hardware, limited degree of freedom and the like in the prior art. The realization steps are as follows: arranging a coprime array and a single-bit analog-to-digital converter at a receiving end; calculating equivalent virtual signal corresponding to a single-bit receipt signal of the coprime array; constructing a virtual domain augmented covariance matrix of an initialized single-bit quantized signal; designing, based on statistical correlation analysis between statistics of the single-bit quantized signal and the original unquantized signal, an optimization problem based on virtual domain statistics reconstruction of quantized signal; and performing direction-of-arrival estimation by utilizing the virtual domain augmented covariance matrix corresponding to the optimized single-bit quantized signal.

公开(公告)号：US20210373113A1

公开(公告)日：2021-12-02

申请号：US17401345

申请日：2021-08-13

申请人： ZHEJIANG UNIVERSITY

发明人： Zhiguo SHI ,  Hang ZHENG ,  Chengwei ZHOU ,  Jiming CHEN

IPC分类号： G01S3/14 ,  G01S3/04

摘要： A two-dimensional direction-of-arrival estimation method for a coprime planar array based on structured coarray tensor processing, the method includes: deploying a coprime planar array; modeling a tensor of the received signals; deriving the second-order equivalent signals of an augmented virtual array based on cross-correlation tensor transformation; deploying a three-dimensional coarray tensor of the virtual array; deploying a five-dimensional coarray tensor based on a coarray tensor dimension extension strategy; forming a structured coarray tensor including three-dimensional spatial information; and achieving two-dimensional direction-of-arrival estimation through CANDECOMP/PARACFAC decomposition. The present disclosure constructs a processing framework of a structured coarray tensor based on statistical analysis of coprime planar array tensor signals, to achieve multi-source two-dimensional direction-of-arrival estimation in the underdetermined case on the basis of ensuring the performance such as resolution and estimation accuracy, and can be used for multi-target positioning.

公开(公告)号：US20210364564A1

公开(公告)日：2021-11-25

申请号：US17395480

申请日：2021-08-06

申请人： ZHEJIANG UNIVERSITY

发明人： Jiming CHEN ,  Hang ZHENG ,  Zhiguo SHI ,  Chengwei ZHOU

IPC分类号： G01R29/10 ,  G06K9/62

摘要： Disclosed is a spatial spectrum estimation method with enhanced degree-of-freedom based on block sampling tensor construction for coprime planar array, which mainly solves the multi-dimensional information loss in signals and degree-of-freedom limitation in the existing methods and which is implemented by the following steps: constructing a coprime planar array; modeling block sampling tensors of the coprime planar array; deducing coarray statistics based on the block sampling cross-correlation tensor; obtaining block sampling coarray signals of a virtual uniform array; constructing a three-dimensional block sampling coarray tensor and its fourth-order auto-correlation statistics; constructing signal and noise subspaces based on fourth-order auto-correlation tensor decomposition; estimating a tensor spatial spectrum with enhanced degrees-of-freedom. In the present disclosure, the block sampling tensors of the coprime planar array is constructed, where a coarray tensor is deduced, to realize tensor spatial spectrum estimation with enhanced degrees-of-freedom by extracting signal-to-signal subspace features from the four-order self-correlation tensor.