Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective...Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.展开更多
Recently,Reconfigurable Intelligent Surfaces(RISs)have drawn intensive attention in the realization of the smart radio environment.However,existing works mainly consider the RIS as a whole uniform plane,which may be u...Recently,Reconfigurable Intelligent Surfaces(RISs)have drawn intensive attention in the realization of the smart radio environment.However,existing works mainly consider the RIS as a whole uniform plane,which may be unrealistic to be installed on the facade of buildings when the RIS is extremely large.In contrast,this paper investigates a practical Sparse Array of Sub-surface(SAoS)deployment of the RIS for uplink multi-user millimeter Wave(mmWave)communication systems,in which the Mobile Stations(MSs)are distributed in the blind coverage area due to the blockage.In order to exploit the benefits of the sparse deployment,the correlation of the effective channel is firstly investigated.Then the approximation and lower bounds of the ergodic spectral efficiency are derived under frequency and spatial multiplexing scenarios,respectively.Based on the autocorrelation of the effective channel,we obtain an optimal reflect coefficient design as well as the deployment guidelines of RIS tiles.Moreover,the RIS tile scheduling algorithms are also proposed.Numerical results show that the ergodic spectral efficiency approximation matches well with the Monte Carlo result under frequency multiplexing scenarios,and the lower bound is tight under spatial multiplexing scenarios only when the effective channel is strongly correlated.On the basis of the RIS tile scheduling algorithm and the reflect coefficient design,the system performance can be significantly improved under frequency multiplexing scenarios.On the other hand,by deploying more sparse RIS tiles,we can increase the multiplexing gain under spatial multiplexing scenarios.展开更多
In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged withi...In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
In this paper,a method for designing supermassive sparse phased arrays(SMSPAs)known as the unitary modified matrix enhancement and matrix pencil(UMMEMP)method is proposed.In this method,an eigenvalue pairing method,wh...In this paper,a method for designing supermassive sparse phased arrays(SMSPAs)known as the unitary modified matrix enhancement and matrix pencil(UMMEMP)method is proposed.In this method,an eigenvalue pairing method,which is inspired by the modified MEMP,effectively pairs the repeated eigenvalues intractable in the unitary matrix pencil method,and it is more effective in determining the locations of elements in the sparse array.Three numerical examples and a full-wave validation are presented to demonstrate the effectiveness of the method,implemented via SMSPA,in achieving low sidelobe level wide-angle scanning radiation patterns,circular flattop radiation patterns,and ultra wide-angle scanning radiation patterns.展开更多
Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the...Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the hole-filling strategy.Specifically,we first introduce the improved nested array(INA)and prove its properties.Subsequently,we extend the sum-difference coarray(SDCA)by adding an additional sensor to fill the holes.Thus the larger uniform degrees of freedom(uDOFs)and virtual array aperture(VAA)can be abtained,and the ENAFS is designed.Finally,the simulation results are given to verify the superiority of the proposed ENAFS in terms of DOF,mutual coupling and estimation performance.展开更多
Designing a sparse array with reduced transmit/receive modules(TRMs)is vital for some applications where the antenna system’s size,weight,allowed operating space,and cost are limited.Sparse arrays exhibit distinct ar...Designing a sparse array with reduced transmit/receive modules(TRMs)is vital for some applications where the antenna system’s size,weight,allowed operating space,and cost are limited.Sparse arrays exhibit distinct architectures,roughly classified into three categories:Thinned arrays,nonuniformly spaced arrays,and clustered arrays.While numerous advanced synthesis methods have been presented for the three types of sparse arrays in recent years,a comprehensive review of the latest development in sparse array synthesis is lacking.This work aims to fill this gap by thoroughly summarizing these techniques.The study includes synthesis examples to facilitate a comparative analysis of different techniques in terms of both accuracy and efficiency.Thus,this review is intended to assist researchers and engineers in related fields,offering a clear understanding of the development and distinctions among sparse array synthesis techniques.展开更多
An improved adaptive genetic algorithm is presented in this paper. It primarily includes two modified methods： one is novel adaptive probabilities of crossover and mutation, the other is truncated selection approach....An improved adaptive genetic algorithm is presented in this paper. It primarily includes two modified methods： one is novel adaptive probabilities of crossover and mutation, the other is truncated selection approach. This algorithm has been validated to be superior to the simple genetic algorithm （SGA） by a complicated binary testing function. Then the proposed algorithm is applied to optimizing the planar retrodirective array to reduce the cost of the hardware. The fitness function is discussed in the optimization example. After optimization, the sparse planar retrodirective antenna array keeps excellent retrodirectivity, while the array architecture has been simplified by 34%. The optimized antenna array can replace uniform full array effectively. Results show that this work will gain more engineering benefits in practice.展开更多
In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spat...In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spatial smoothing(PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition(SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by PSS.The elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques(ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.展开更多
In this paper,a sparse nonuniform rectangular array based on spatially spread electromagnetic vector sensor(SNRASSEMVS)is introduced,and a method for estimating 2D-direction of arrival(DOA)and polarization is devised....In this paper,a sparse nonuniform rectangular array based on spatially spread electromagnetic vector sensor(SNRASSEMVS)is introduced,and a method for estimating 2D-direction of arrival(DOA)and polarization is devised.Firstly,according to the special structure of the sparse nonuniform rectangular array(SNRA),a set of accurate but ambiguous direction-cosine estimates can be obtained.Then the steering vector of spatially spread electromagnetic vector sensor(SSEMVS)can be extracted from the array manifold to obtain the coarse but unambiguous direction-cosine estimates.Finally,the disambiguation approach can be used to get the final accurate estimates of 2DDOA and polarization.Compared with some existing methods,the SNRA configuration extends the spatial aperture and refines the parameters estimation accuracy without adding any redundant antennas,as well as reduces the mutual coupling effect.Moreover,the proposed algorithm resolves multiple sources without the priori knowledge of signal information,suffers no ambiguity in the estimation of the Poynting vector,and pairs the x-axis direction cosine with the y-axis direction cosine automatically.Simulation results are given to verify the effectiveness and superiority of the proposed algorithm.展开更多
Downward Looking Sparse Linear Array Three Dimensional SAR(DLSLA 3D SAR) is an important form of 3D SAR imaging, which has a widespread application field. Since its practical equivalent phase centers are usually distr...Downward Looking Sparse Linear Array Three Dimensional SAR(DLSLA 3D SAR) is an important form of 3D SAR imaging, which has a widespread application field. Since its practical equivalent phase centers are usually distributed sparsely and nonuniformly, traditional 3D SAR algorithms suffer from low resolution and high sidelobes in cross-track dimension. To deal with this problem, this paper introduces a method based on back-projection and convex optimization to achieve 3D high accuracy imaging reconstruction. Compared with traditional SAR algorithms, the proposed method sufficiently utilizes the sparsity of the 3D SAR imaging scene and can achieve lower sidelobes and higher resolution in cross-track dimension. In the simulated experiments, the reconstructed results of both simple and complex imaging scene verify that the proposed method outperforms 3D back-projection algorithm and shows satisfying cross-track dimensional resolution and good robustness to noise.展开更多
Electromagnetic vector sensor(EMVS)embedded multiple-input multiple-output(MIMO)radar is an emerging technology that enables two-dimensional(2D)direction of arrival(DOA)estimation.In this paper,we proposed a low-compl...Electromagnetic vector sensor(EMVS)embedded multiple-input multiple-output(MIMO)radar is an emerging technology that enables two-dimensional(2D)direction of arrival(DOA)estimation.In this paper,we proposed a low-complexity estimation of signal parameters via rotational invariance techniques(ESPRIT)algorithm for uniform linear array(ULA)EMVSMIMO radar at a monostatic,enabling rapid estimation of 2D target angles.Initially,by employing a selection matrix,complexity reduction is applied to the array data,thereby eliminating redundancy in the array data.Subsequently,leveraging the rotation invariance propagator method(PM)algorithm,obtain the estimation of the elevation angle,but due to array sparsity,this estimation exhibits ambiguity.Then,the vector cross-product(VCP)technique is employed to achieve unambiguous 2D-DOA estimation.Finally,the aforementioned estimates are synthesized to obtain highresolution,unambiguous elevation angle estimation.The proposed algorithm is applicable to largescale and spare EMVS-MIMO radar systems and provides higher estimation accuracy compared to existing ESPRIT algorithms.The effectiveness of the algorithm is verified through matrix laboratory(MATLAB)simulations.展开更多
It has long been a challenging task to improve the light collection efficiency of conventional image sensors built with color filters that inevitably cause the energy loss of out-of-band photons. Here, we demonstrate ...It has long been a challenging task to improve the light collection efficiency of conventional image sensors built with color filters that inevitably cause the energy loss of out-of-band photons. Here, we demonstrate a pixelated spectral router based on a sparse meta-atom array, which can efficiently separate incident R(600±700 nm), G(500±600 nm), and B(400±500 nm)band light to the corresponding pixels of a Bayer image sensor, providing over 56% signal enhancement above the traditional color filter scheme. It is enabled by simple compound Si_(3)N_(4) nanostructures, which are very suitable for massive production. Imaging experiments are conducted to verify the router's potential for real applications. The complementary metal-oxide-semiconductor(CMOS)-compatible spectral router scheme is also found to be robust and can be freely adapted to image sensors of various pixel sizes, having great potential in building the new generation of high-performance image sensing components.展开更多
The problem of two-dimensional direction finding is approached by using a multi-layer Lshaped array. The proposed method is based on two sequential sparse representations,fulfilling respectively the estimation of elev...The problem of two-dimensional direction finding is approached by using a multi-layer Lshaped array. The proposed method is based on two sequential sparse representations,fulfilling respectively the estimation of elevation angles,and azimuth angles. For the estimation of elevation angles,the weighted sub-array smoothing technique for perfect data decorrelation is used to produce a covariance vector suitable for exact sparse representation,related only to the elevation angles. The estimates of elevation angles are then obtained by sparse restoration associated with this elevation angle dependent covariance vector. The estimates of elevation angles are further incorporated with weighted sub-array smoothing to yield a second covariance vector for precise sparse representation related to both elevation angles,and azimuth angles. The estimates of azimuth angles,automatically paired with the estimates of elevation angles,are finally obtained by sparse restoration associated with this latter elevation-azimuth angle related covariance vector. Simulation results are included to illustrate the performance of the proposed method.展开更多
Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteris...Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteristics play a significant role in improving the direction-of-arrival(DOA)estimation accuracy.However,most of the existing NULA geometries are primarily applicable to circular sources(CSs),while they limitedly improve the DOF and continuous virtual aperture for noncircular sources(NCSs).Toward this purpose,we present a triaddisplaced ULAs(Tdis-ULAs)configuration for NCS.The TdisULAs structure generally consists of three ULAs,which are appropriately placed.The proposed antenna array approach fully exploits the non-circular characteristics of the sources.Given the same number of elements,the Tdis-ULAs design achieves more DOF and larger hole-free co-array aperture than its sparse array competitors.Advantageously,the number of uniform DOF,optimal distribution of elements among the ULAs,and precise element positions are uniquely determined by the closed-form expressions.Moreover,the proposed array also produces a filled resulting co-array.Numerical simulations are conducted to show the performance advantages of the proposed Tdis-ULAs configuration over its counterpart designs.展开更多
The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-...The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-track direction, and three virtual phase centers will be obtained through one-input and three-output. These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution. Because the cross-track array is short, the cross-track resolution is low. When the system works in side-looking mode, the cross-track resolution and height resolution will be coupling, and the low cross-track resolution will partly be transformed into the height uncertainty. The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array. In order to suppress the high cross-track sidelobes, a weighting preprocessing method is proposed. The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method. And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.展开更多
Large-element-spacing(LES)antenna arrays present an attractive proposition with their cost-effectiveness and sim-plified structures.However,they often encounter the challenge of high-level grating lobes.This paper pro...Large-element-spacing(LES)antenna arrays present an attractive proposition with their cost-effectiveness and sim-plified structures.However,they often encounter the challenge of high-level grating lobes.This paper proposes a novel meta-lens methodology to effectively address the grating lobe issue in fixed-beam LES arrays.The proposed approach involves strategically positioning a meta-lens above the LES arrays at a suitable vertical distance.This setup enables precise manipulation and compen-sation of the near-field phase,resulting in the suppression or elimination of grating lobes without introducing additional design com-plexity.Comprehensive theoretical analyses,meticulous design calculations employing efficient numerical methods,rigorous field simulations,and practical experiments are conducted.The results demonstrate that our meta-lens solution achieves significant grating-lobe suppressions and substantial gain enhancements with only a marginal increase in system profile or volume.The proposed meta-lens approach is versatile and applicable to various LES antenna arrays,including sparse/thinned arrays,regardless of their size,element spacing,and configuration(uniform or non-uniform,periodic or aperiodic).展开更多
To obtain high cross-range resolution, the underwater 3-D acoustic imaging system usually requires a rectangular array with a great number of sensors and a large physical size. To reduce the sensor number and the arra...To obtain high cross-range resolution, the underwater 3-D acoustic imaging system usually requires a rectangular array with a great number of sensors and a large physical size. To reduce the sensor number and the array physical size simultaneously, this paper proposes a new underwater 3-D acoustic imaging approach based on a novel multiple-input multiple-output (MIMO) array. Specifically, the MIMO array is composed of four uniform linear arrays (ULAs) located on four sides of a rectangle. The transmitting array composed of two ULAs is located on a pair of opposite sides, and the receiving array composed of another two ULAs is located on the other two sides. Furthermore, narrowband waveforms coded with orthogonal polyphase sequences are employed as transmitting waveforms. When the subcode numbers in the polyphase coded sequences are sufficient, the MIMO array has the same 3-D imaging ability as a rectangular array, which has a two-time bigger size than that of the former. Consequently, the MIMO array can not only save a great number of sensors, but halve the array size, when compared to a rectangular array with the same cross-range resolution. Computer simulations are provided to demonstrate the effectiveness of the proposed imaging approach.展开更多
文摘Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.
基金This work was supported in part by the National Key Research and Development Program 2018YFA0701602the National Science Foundation of China(NSFC)for Distinguished Young Scholars with Grant 61625106,and the NSFC under Grant 61941104.
文摘Recently,Reconfigurable Intelligent Surfaces(RISs)have drawn intensive attention in the realization of the smart radio environment.However,existing works mainly consider the RIS as a whole uniform plane,which may be unrealistic to be installed on the facade of buildings when the RIS is extremely large.In contrast,this paper investigates a practical Sparse Array of Sub-surface(SAoS)deployment of the RIS for uplink multi-user millimeter Wave(mmWave)communication systems,in which the Mobile Stations(MSs)are distributed in the blind coverage area due to the blockage.In order to exploit the benefits of the sparse deployment,the correlation of the effective channel is firstly investigated.Then the approximation and lower bounds of the ergodic spectral efficiency are derived under frequency and spatial multiplexing scenarios,respectively.Based on the autocorrelation of the effective channel,we obtain an optimal reflect coefficient design as well as the deployment guidelines of RIS tiles.Moreover,the RIS tile scheduling algorithms are also proposed.Numerical results show that the ergodic spectral efficiency approximation matches well with the Monte Carlo result under frequency multiplexing scenarios,and the lower bound is tight under spatial multiplexing scenarios only when the effective channel is strongly correlated.On the basis of the RIS tile scheduling algorithm and the reflect coefficient design,the system performance can be significantly improved under frequency multiplexing scenarios.On the other hand,by deploying more sparse RIS tiles,we can increase the multiplexing gain under spatial multiplexing scenarios.
文摘In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
文摘In this paper,a method for designing supermassive sparse phased arrays(SMSPAs)known as the unitary modified matrix enhancement and matrix pencil(UMMEMP)method is proposed.In this method,an eigenvalue pairing method,which is inspired by the modified MEMP,effectively pairs the repeated eigenvalues intractable in the unitary matrix pencil method,and it is more effective in determining the locations of elements in the sparse array.Three numerical examples and a full-wave validation are presented to demonstrate the effectiveness of the method,implemented via SMSPA,in achieving low sidelobe level wide-angle scanning radiation patterns,circular flattop radiation patterns,and ultra wide-angle scanning radiation patterns.
基金supported by China National Science Foundations(Nos.62371225,62371227)。
文摘Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the hole-filling strategy.Specifically,we first introduce the improved nested array(INA)and prove its properties.Subsequently,we extend the sum-difference coarray(SDCA)by adding an additional sensor to fill the holes.Thus the larger uniform degrees of freedom(uDOFs)and virtual array aperture(VAA)can be abtained,and the ENAFS is designed.Finally,the simulation results are given to verify the superiority of the proposed ENAFS in terms of DOF,mutual coupling and estimation performance.
基金supported by the National Natural Science Foundation of China under Grant No.U2341208.
文摘Designing a sparse array with reduced transmit/receive modules(TRMs)is vital for some applications where the antenna system’s size,weight,allowed operating space,and cost are limited.Sparse arrays exhibit distinct architectures,roughly classified into three categories:Thinned arrays,nonuniformly spaced arrays,and clustered arrays.While numerous advanced synthesis methods have been presented for the three types of sparse arrays in recent years,a comprehensive review of the latest development in sparse array synthesis is lacking.This work aims to fill this gap by thoroughly summarizing these techniques.The study includes synthesis examples to facilitate a comparative analysis of different techniques in terms of both accuracy and efficiency.Thus,this review is intended to assist researchers and engineers in related fields,offering a clear understanding of the development and distinctions among sparse array synthesis techniques.
文摘An improved adaptive genetic algorithm is presented in this paper. It primarily includes two modified methods： one is novel adaptive probabilities of crossover and mutation, the other is truncated selection approach. This algorithm has been validated to be superior to the simple genetic algorithm （SGA） by a complicated binary testing function. Then the proposed algorithm is applied to optimizing the planar retrodirective array to reduce the cost of the hardware. The fitness function is discussed in the optimization example. After optimization, the sparse planar retrodirective antenna array keeps excellent retrodirectivity, while the array architecture has been simplified by 34%. The optimized antenna array can replace uniform full array effectively. Results show that this work will gain more engineering benefits in practice.
基金supported by the National Natural Science Foundation of China (62261047,62066040)the Foundation of Top-notch Talents by Education Department of Guizhou Province of China (KY[2018]075)+3 种基金the Science and Technology Foundation of Guizhou Province of China (ZK[2022]557,[2020]1Y004)the Science and Technology Research Program of the Chongqing Municipal Education Commission (KJQN202200637)PhD Research Start-up Foundation of Tongren University (trxyDH1710)Tongren Science and Technology Planning Project ((2018)22)。
文摘In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spatial smoothing(PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition(SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by PSS.The elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques(ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.
基金This work was supported by the innovation project of Science and Technology Commission of the Central Military Commission。
文摘In this paper,a sparse nonuniform rectangular array based on spatially spread electromagnetic vector sensor(SNRASSEMVS)is introduced,and a method for estimating 2D-direction of arrival(DOA)and polarization is devised.Firstly,according to the special structure of the sparse nonuniform rectangular array(SNRA),a set of accurate but ambiguous direction-cosine estimates can be obtained.Then the steering vector of spatially spread electromagnetic vector sensor(SSEMVS)can be extracted from the array manifold to obtain the coarse but unambiguous direction-cosine estimates.Finally,the disambiguation approach can be used to get the final accurate estimates of 2DDOA and polarization.Compared with some existing methods,the SNRA configuration extends the spatial aperture and refines the parameters estimation accuracy without adding any redundant antennas,as well as reduces the mutual coupling effect.Moreover,the proposed algorithm resolves multiple sources without the priori knowledge of signal information,suffers no ambiguity in the estimation of the Poynting vector,and pairs the x-axis direction cosine with the y-axis direction cosine automatically.Simulation results are given to verify the effectiveness and superiority of the proposed algorithm.
基金Supported by the National Natural Science Foundation of China General Programs(Nos.61072112,61372186)the National Natural Science Foundation of China Key Program(No.60890071)
文摘Downward Looking Sparse Linear Array Three Dimensional SAR(DLSLA 3D SAR) is an important form of 3D SAR imaging, which has a widespread application field. Since its practical equivalent phase centers are usually distributed sparsely and nonuniformly, traditional 3D SAR algorithms suffer from low resolution and high sidelobes in cross-track dimension. To deal with this problem, this paper introduces a method based on back-projection and convex optimization to achieve 3D high accuracy imaging reconstruction. Compared with traditional SAR algorithms, the proposed method sufficiently utilizes the sparsity of the 3D SAR imaging scene and can achieve lower sidelobes and higher resolution in cross-track dimension. In the simulated experiments, the reconstructed results of both simple and complex imaging scene verify that the proposed method outperforms 3D back-projection algorithm and shows satisfying cross-track dimensional resolution and good robustness to noise.
文摘Electromagnetic vector sensor(EMVS)embedded multiple-input multiple-output(MIMO)radar is an emerging technology that enables two-dimensional(2D)direction of arrival(DOA)estimation.In this paper,we proposed a low-complexity estimation of signal parameters via rotational invariance techniques(ESPRIT)algorithm for uniform linear array(ULA)EMVSMIMO radar at a monostatic,enabling rapid estimation of 2D target angles.Initially,by employing a selection matrix,complexity reduction is applied to the array data,thereby eliminating redundancy in the array data.Subsequently,leveraging the rotation invariance propagator method(PM)algorithm,obtain the estimation of the elevation angle,but due to array sparsity,this estimation exhibits ambiguity.Then,the vector cross-product(VCP)technique is employed to achieve unambiguous 2D-DOA estimation.Finally,the aforementioned estimates are synthesized to obtain highresolution,unambiguous elevation angle estimation.The proposed algorithm is applicable to largescale and spare EMVS-MIMO radar systems and provides higher estimation accuracy compared to existing ESPRIT algorithms.The effectiveness of the algorithm is verified through matrix laboratory(MATLAB)simulations.
基金supported by the Natural Science Foundation of China (Nos. 62075196 and 62105282)the Natural Science Foundation of Zhejiang Province (No. LDT23F05014F05)+1 种基金the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang (No. 2021R01001)the Fundamental Research Funds for the Central Universities。
文摘It has long been a challenging task to improve the light collection efficiency of conventional image sensors built with color filters that inevitably cause the energy loss of out-of-band photons. Here, we demonstrate a pixelated spectral router based on a sparse meta-atom array, which can efficiently separate incident R(600±700 nm), G(500±600 nm), and B(400±500 nm)band light to the corresponding pixels of a Bayer image sensor, providing over 56% signal enhancement above the traditional color filter scheme. It is enabled by simple compound Si_(3)N_(4) nanostructures, which are very suitable for massive production. Imaging experiments are conducted to verify the router's potential for real applications. The complementary metal-oxide-semiconductor(CMOS)-compatible spectral router scheme is also found to be robust and can be freely adapted to image sensors of various pixel sizes, having great potential in building the new generation of high-performance image sensing components.
基金Supported by the National Natural Science Foundation of China(61331019,61490691)
文摘The problem of two-dimensional direction finding is approached by using a multi-layer Lshaped array. The proposed method is based on two sequential sparse representations,fulfilling respectively the estimation of elevation angles,and azimuth angles. For the estimation of elevation angles,the weighted sub-array smoothing technique for perfect data decorrelation is used to produce a covariance vector suitable for exact sparse representation,related only to the elevation angles. The estimates of elevation angles are then obtained by sparse restoration associated with this elevation angle dependent covariance vector. The estimates of elevation angles are further incorporated with weighted sub-array smoothing to yield a second covariance vector for precise sparse representation related to both elevation angles,and azimuth angles. The estimates of azimuth angles,automatically paired with the estimates of elevation angles,are finally obtained by sparse restoration associated with this latter elevation-azimuth angle related covariance vector. Simulation results are included to illustrate the performance of the proposed method.
基金supported by the National Natural Science Foundation of China(62031017,61971221)the Fundamental Research Funds for the Central Universities of China(NP2020104)。
文摘Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteristics play a significant role in improving the direction-of-arrival(DOA)estimation accuracy.However,most of the existing NULA geometries are primarily applicable to circular sources(CSs),while they limitedly improve the DOF and continuous virtual aperture for noncircular sources(NCSs).Toward this purpose,we present a triaddisplaced ULAs(Tdis-ULAs)configuration for NCS.The TdisULAs structure generally consists of three ULAs,which are appropriately placed.The proposed antenna array approach fully exploits the non-circular characteristics of the sources.Given the same number of elements,the Tdis-ULAs design achieves more DOF and larger hole-free co-array aperture than its sparse array competitors.Advantageously,the number of uniform DOF,optimal distribution of elements among the ULAs,and precise element positions are uniquely determined by the closed-form expressions.Moreover,the proposed array also produces a filled resulting co-array.Numerical simulations are conducted to show the performance advantages of the proposed Tdis-ULAs configuration over its counterpart designs.
基金Supported by the National Basic Research Program (973) of China (No. 2009CB72400)
文摘The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-track direction, and three virtual phase centers will be obtained through one-input and three-output. These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution. Because the cross-track array is short, the cross-track resolution is low. When the system works in side-looking mode, the cross-track resolution and height resolution will be coupling, and the low cross-track resolution will partly be transformed into the height uncertainty. The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array. In order to suppress the high cross-track sidelobes, a weighting preprocessing method is proposed. The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method. And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.
基金National Natural Science Foundation of China(Grant Nos.62071187,62071125,and 62301162)Natural Science Foundation of Fujian Province,China(Grant No.2023J01058)+1 种基金Industry-Education Cooperation Project in Fujian Province,China(Grant No.2022H6018)Fujian Province Major Special Topic Project(Grant No.2022HZ026007).
文摘Large-element-spacing(LES)antenna arrays present an attractive proposition with their cost-effectiveness and sim-plified structures.However,they often encounter the challenge of high-level grating lobes.This paper proposes a novel meta-lens methodology to effectively address the grating lobe issue in fixed-beam LES arrays.The proposed approach involves strategically positioning a meta-lens above the LES arrays at a suitable vertical distance.This setup enables precise manipulation and compen-sation of the near-field phase,resulting in the suppression or elimination of grating lobes without introducing additional design com-plexity.Comprehensive theoretical analyses,meticulous design calculations employing efficient numerical methods,rigorous field simulations,and practical experiments are conducted.The results demonstrate that our meta-lens solution achieves significant grating-lobe suppressions and substantial gain enhancements with only a marginal increase in system profile or volume.The proposed meta-lens approach is versatile and applicable to various LES antenna arrays,including sparse/thinned arrays,regardless of their size,element spacing,and configuration(uniform or non-uniform,periodic or aperiodic).
基金supported in part by the Doctorate Foundation of Northwestern Polytechnical University(Grant No. CX201101)
文摘To obtain high cross-range resolution, the underwater 3-D acoustic imaging system usually requires a rectangular array with a great number of sensors and a large physical size. To reduce the sensor number and the array physical size simultaneously, this paper proposes a new underwater 3-D acoustic imaging approach based on a novel multiple-input multiple-output (MIMO) array. Specifically, the MIMO array is composed of four uniform linear arrays (ULAs) located on four sides of a rectangle. The transmitting array composed of two ULAs is located on a pair of opposite sides, and the receiving array composed of another two ULAs is located on the other two sides. Furthermore, narrowband waveforms coded with orthogonal polyphase sequences are employed as transmitting waveforms. When the subcode numbers in the polyphase coded sequences are sufficient, the MIMO array has the same 3-D imaging ability as a rectangular array, which has a two-time bigger size than that of the former. Consequently, the MIMO array can not only save a great number of sensors, but halve the array size, when compared to a rectangular array with the same cross-range resolution. Computer simulations are provided to demonstrate the effectiveness of the proposed imaging approach.
