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
Based on principle of power synthesis of sparse array, mathematical model of spatial power combining is established. Relation between cross angle of beams and synthesis efficiency on aimed point from two antenna nodes...Based on principle of power synthesis of sparse array, mathematical model of spatial power combining is established. Relation between cross angle of beams and synthesis efficiency on aimed point from two antenna nodes is derived. Furthermore, the setting principle of sampling interval is analyzed for simulation experiment. Energy distributions of the useful points under different cross angles were simulated. Simulation shows that if distance between the antenna nodes and aimed point are equal, and frequency, polarization and an- tenna type are the same, synthesis efficiency relies on the cross angles of beams, shape and density on the useful points accumulation area also rely on the cross angles of beams.展开更多
With a goal to optimize the element positions to reduce the peak sidelobe level (PSLL) of the array pattern, a modified real Genetic Algorithms (MGA) for the synthesis of sparse linear arrays is described. The multipl...With a goal to optimize the element positions to reduce the peak sidelobe level (PSLL) of the array pattern, a modified real Genetic Algorithms (MGA) for the synthesis of sparse linear arrays is described. The multiple optimization constrains include the number of elements, the aperture and the minimum element spacing. The advanced new approach reduces the size of the searching area of GA by means of indirect description of chromosome and avoids infeasible solution during the optimization process by designing the new genetic operators. The elementary steps of MGA are presented. The simulated results confirm the great efficiency and the robustness of this algorithm.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
The automatic identification of underwater noncooperative targets without label records remains an arduous task considering the marine noise interference and the shortage of labeled samples.In particular,the data-driv...The automatic identification of underwater noncooperative targets without label records remains an arduous task considering the marine noise interference and the shortage of labeled samples.In particular,the data-driven mechanism of deep learning cannot identify false samples,aggravating the difficulty in noncooperative underwater target recognition.A semi-supervised ensemble framework based on vertical line array fusion and the sparse adversarial co-training algorithm is proposed to identify noncooperative targets effectively.The sound field cross-correlation compression(SCC)feature is developed to reduce noise and computational redundancy.Starting from an incomplete dataset,a joint adversarial autoencoder is constructed to extract the sparse features with source depth sensitivity,aiming to discover the unknown underwater targets.The adversarial prediction label is converted to initialize the joint co-forest,whose evaluation function is optimized by introducing adaptive confidence.The experiments prove the strong denoising performance,low mean square error,and high separability of SCC features.Compared with several state-of-the-art approaches,the numerical results illustrate the superiorities of the proposed method due to feature compression,secondary recognition,and decision fusion.展开更多
In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used...In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.展开更多
Spatial covariance matrix(SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output(MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital struc...Spatial covariance matrix(SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output(MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital structure has been widely adopted to reduce the cost of radio frequency chains.In this situation, signals received at the antennas are unavailable to the digital receiver, and as a consequence, traditional sample average approach cannot be used for SCM reconstruction in hybrid multi-antenna systems. To address this issue, beam sweeping algorithm(BSA) which can reconstruct the SCM effectively for a hybrid uniform linear array, has been proposed in our previous works. However, direct extension of BSA to a hybrid uniform circular array(UCA)will result in a huge computational burden. To this end, a low-complexity approach is proposed in this paper. By exploiting the symmetry features of SCM for the UCA, the number of unknowns can be reduced significantly and thus the complexity of reconstruction can be saved accordingly. Furthermore, an insightful analysis is also presented in this paper, showing that the reduction of the number of unknowns can also improve the accuracy of the reconstructed SCM. Simulation results are also shown to demonstrate the proposed approach.展开更多
We study the chiral bound states in a coupled-resonator array with staggered hopping strengths,which interacts with a two-level small atom through a single coupling point or two adjacent ones.In addition to the two ty...We study the chiral bound states in a coupled-resonator array with staggered hopping strengths,which interacts with a two-level small atom through a single coupling point or two adjacent ones.In addition to the two typical bound states found above and below the energy bands,this system presents an extraordinary chiral bound state located within the energy gap.We use the chirality to quantify the breaking of the mirror symmetry.We find that the chirality value undergoes continuous changes by tuning the coupling strengths.The preferred direction of the chirality is controlled not only by the competition between the intracell and the intercell hoppings in the coupled-resonator array,but also by the coherence between the two coupling points.In the case with one coupling point,the chirality values varies monotonously with difference between the intracell hopping and the intercell hoppings.While in the case with two coupling points,due to the coherence between the two coupling points the perfect chiral states can be obtained.展开更多
Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negli...Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negligible accuracy loss.Cambricon-Q is the ASIC design proposed to efficiently support quantized training,and achieves significant performance improvement.However,there are still two caveats in the design.First,Cambricon-Q with different hardware specifications may lead to different numerical errors,resulting in non-reproducible behaviors which may become a major concern in critical applications.Second,Cambricon-Q cannot leverage data sparsity,where considerable cycles could still be squeezed out.To address the caveats,the acceleration core of Cambricon-Q is redesigned to support fine-grained irregular data processing.The new design not only enables acceleration on sparse data,but also enables performing local dynamic quantization by contiguous value ranges(which is hardware independent),instead of contiguous addresses(which is dependent on hardware factors).Experimental results show that the accuracy loss of the method still keeps negligible,and the accelerator achieves 1.61×performance improvement over Cambricon-Q,with about 10%energy increase.展开更多
Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, t...Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods.展开更多
Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.I...Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.展开更多
Flexible pressure sensors have many potential applications in the monitoring of physiological signals because of their good biocompatibil-ity and wearability.However,their relatively low sensitivity,linearity,and stab...Flexible pressure sensors have many potential applications in the monitoring of physiological signals because of their good biocompatibil-ity and wearability.However,their relatively low sensitivity,linearity,and stability have hindered their large-scale commercial application.Herein,aflexible capacitive pressure sensor based on an interdigital electrode structure with two porous microneedle arrays(MNAs)is pro-posed.The porous substrate that constitutes the MNA is a mixed product of polydimethylsiloxane and NaHCO3.Due to its porous and interdigital structure,the maximum sensitivity(0.07 kPa-1)of a porous MNA-based pressure sensor was found to be seven times higher than that of an imporous MNA pressure sensor,and it was much greater than that of aflat pressure sensor without a porous MNA structure.Finite-element analysis showed that the interdigital MNA structure can greatly increase the strain and improve the sensitivity of the sen-sor.In addition,the porous MNA-based pressure sensor was found to have good stability over 1500 loading cycles as a result of its bilayer parylene-enhanced conductive electrode structure.Most importantly,it was found that the sensor could accurately monitor the motion of afinger,wrist joint,arm,face,abdomen,eye,and Adam’s apple.Furthermore,preliminary semantic recognition was achieved by monitoring the movement of the Adam’s apple.Finally,multiple pressure sensors were integrated into a 33 array to detect a spatial pressure distribu-×tion.Compared to the sensors reported in previous works,the interdigital electrode structure presented in this work improves sensitivity and stability by modifying the electrode layer rather than the dielectric layer.展开更多
The Five-hundred-meter Aperture Spherical Radio Telescope(FAST)Core Array is a proposed extension of FAST,integrating 24 secondary 40-m antennas implanted within 5 km of the FAST site.This original array design will c...The Five-hundred-meter Aperture Spherical Radio Telescope(FAST)Core Array is a proposed extension of FAST,integrating 24 secondary 40-m antennas implanted within 5 km of the FAST site.This original array design will combine the unprecedented sensitivity of FAST with a high angular resolution(4.3"at a frequency of 1.4 GHz),thereby exceeding the capabilities at similar frequencies of next-generation arrays such as the Square Kilometre Array Phase 1 or the next-generation Very Large Array.This article presents the technical specifications of the FAST Core Array,evaluates its potential relatively to existing radio telescope arrays,and describes its expected scientific prospects.The proposed array will be equipped with technologically advanced backend devices,such as real-time signal processing systems.A phased array feed receiver will be mounted on FAST to improve the survey efficiency of the FAST Core Array,whose broad frequency coverage and large field of view(FOV)will be essential to study transient cosmic phenomena such as fast radio bursts and gravitational wave events,to conduct surveys and resolve structures in neutral hydrogen galaxies,to monitor or detect pulsars,and to investigate exoplanetary systems.Finally,the FAST Core Array can strengthen China's major role in the global radio astronomy community,owing to a wide range of potential scientific applications from cosmology to exoplanet science.展开更多
In this paper,the covert age of information(CAoI),which characterizes the timeliness and covertness performance of communication,is first investigated in the short-packet covert communication with time modulated retro...In this paper,the covert age of information(CAoI),which characterizes the timeliness and covertness performance of communication,is first investigated in the short-packet covert communication with time modulated retrodirective array(TMRDA).Specifically,the TMRDA is designed to maximize the antenna gain in the target direction while the side lobe is sufficiently suppressed.On this basis,the covertness constraint and CAoI are derived in closed form.To facilitate the covert transmission design,the transmit power and block-length are jointly optimized to minimize the CAoI,which demonstrates the trade-off between covertness and timelessness.Our results illustrate that there exists an optimal block-length that yields the minimum CAoI,and the presented optimization results can achieve enhanced performance compared with the fixed block-length case.Additionally,we observe that smaller beam pointing error at Bob leads to improvements in CAoI.展开更多
Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up t...Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.展开更多
This study introduces a pre-orthogonal adaptive Fourier decomposition(POAFD)to obtain approximations and numerical solutions to the fractional Laplacian initial value problem and the extension problem of Caffarelli an...This study introduces a pre-orthogonal adaptive Fourier decomposition(POAFD)to obtain approximations and numerical solutions to the fractional Laplacian initial value problem and the extension problem of Caffarelli and Silvestre(generalized Poisson equation).As a first step,the method expands the initial data function into a sparse series of the fundamental solutions with fast convergence,and,as a second step,makes use of the semigroup or the reproducing kernel property of each of the expanding entries.Experiments show the effectiveness and efficiency of the proposed series solutions.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.
文摘Based on principle of power synthesis of sparse array, mathematical model of spatial power combining is established. Relation between cross angle of beams and synthesis efficiency on aimed point from two antenna nodes is derived. Furthermore, the setting principle of sampling interval is analyzed for simulation experiment. Energy distributions of the useful points under different cross angles were simulated. Simulation shows that if distance between the antenna nodes and aimed point are equal, and frequency, polarization and an- tenna type are the same, synthesis efficiency relies on the cross angles of beams, shape and density on the useful points accumulation area also rely on the cross angles of beams.
基金Supported by National Defense Science and Technology Key Laboratory Foundation Project of China
文摘With a goal to optimize the element positions to reduce the peak sidelobe level (PSLL) of the array pattern, a modified real Genetic Algorithms (MGA) for the synthesis of sparse linear arrays is described. The multiple optimization constrains include the number of elements, the aperture and the minimum element spacing. The advanced new approach reduces the size of the searching area of GA by means of indirect description of chromosome and avoids infeasible solution during the optimization process by designing the new genetic operators. The elementary steps of MGA are presented. The simulated results confirm the great efficiency and the robustness of this algorithm.
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the National Natural Science Foundation of China(No.6210011631)in part by the China Postdoctoral Science Foundation(No.2021M692628)。
文摘The automatic identification of underwater noncooperative targets without label records remains an arduous task considering the marine noise interference and the shortage of labeled samples.In particular,the data-driven mechanism of deep learning cannot identify false samples,aggravating the difficulty in noncooperative underwater target recognition.A semi-supervised ensemble framework based on vertical line array fusion and the sparse adversarial co-training algorithm is proposed to identify noncooperative targets effectively.The sound field cross-correlation compression(SCC)feature is developed to reduce noise and computational redundancy.Starting from an incomplete dataset,a joint adversarial autoencoder is constructed to extract the sparse features with source depth sensitivity,aiming to discover the unknown underwater targets.The adversarial prediction label is converted to initialize the joint co-forest,whose evaluation function is optimized by introducing adaptive confidence.The experiments prove the strong denoising performance,low mean square error,and high separability of SCC features.Compared with several state-of-the-art approaches,the numerical results illustrate the superiorities of the proposed method due to feature compression,secondary recognition,and decision fusion.
文摘In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.
基金supported by National Key Research and Development Program of China under Grant 2020YFB1804901State Key Laboratory of Rail Traffic Control and Safety(Contract:No.RCS2022ZT 015)Special Key Project of Technological Innovation and Application Development of Chongqing Science and Technology Bureau(cstc2019jscx-fxydX0053).
文摘Spatial covariance matrix(SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output(MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital structure has been widely adopted to reduce the cost of radio frequency chains.In this situation, signals received at the antennas are unavailable to the digital receiver, and as a consequence, traditional sample average approach cannot be used for SCM reconstruction in hybrid multi-antenna systems. To address this issue, beam sweeping algorithm(BSA) which can reconstruct the SCM effectively for a hybrid uniform linear array, has been proposed in our previous works. However, direct extension of BSA to a hybrid uniform circular array(UCA)will result in a huge computational burden. To this end, a low-complexity approach is proposed in this paper. By exploiting the symmetry features of SCM for the UCA, the number of unknowns can be reduced significantly and thus the complexity of reconstruction can be saved accordingly. Furthermore, an insightful analysis is also presented in this paper, showing that the reduction of the number of unknowns can also improve the accuracy of the reconstructed SCM. Simulation results are also shown to demonstrate the proposed approach.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11975095,12075082,11935006,and 12247105)the Major Sci-Tech Program of Hunan Province,China(Grant No.2023ZJ1010)the Natural Science Foundation of Guangdong Province,China(Grant Nos.2019A1515011400 and 2023A151501223).
文摘We study the chiral bound states in a coupled-resonator array with staggered hopping strengths,which interacts with a two-level small atom through a single coupling point or two adjacent ones.In addition to the two typical bound states found above and below the energy bands,this system presents an extraordinary chiral bound state located within the energy gap.We use the chirality to quantify the breaking of the mirror symmetry.We find that the chirality value undergoes continuous changes by tuning the coupling strengths.The preferred direction of the chirality is controlled not only by the competition between the intracell and the intercell hoppings in the coupled-resonator array,but also by the coherence between the two coupling points.In the case with one coupling point,the chirality values varies monotonously with difference between the intracell hopping and the intercell hoppings.While in the case with two coupling points,due to the coherence between the two coupling points the perfect chiral states can be obtained.
基金the National Key Research and Devecopment Program of China(No.2022YFB4501601)the National Natural Science Foundation of China(No.62102398,U20A20227,62222214,62002338,U22A2028,U19B2019)+1 种基金the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR-029)Youth Innovation Promotion Association Chinese Academy of Sciences。
文摘Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negligible accuracy loss.Cambricon-Q is the ASIC design proposed to efficiently support quantized training,and achieves significant performance improvement.However,there are still two caveats in the design.First,Cambricon-Q with different hardware specifications may lead to different numerical errors,resulting in non-reproducible behaviors which may become a major concern in critical applications.Second,Cambricon-Q cannot leverage data sparsity,where considerable cycles could still be squeezed out.To address the caveats,the acceleration core of Cambricon-Q is redesigned to support fine-grained irregular data processing.The new design not only enables acceleration on sparse data,but also enables performing local dynamic quantization by contiguous value ranges(which is hardware independent),instead of contiguous addresses(which is dependent on hardware factors).Experimental results show that the accuracy loss of the method still keeps negligible,and the accelerator achieves 1.61×performance improvement over Cambricon-Q,with about 10%energy increase.
基金supported in part by NUS startup grantthe National Natural Science Foundation of China (52076037)。
文摘Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods.
文摘Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.
基金supported in part by the National Natural Science Foundation of China(Grant No.62104056)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LQ21F010010)+4 种基金the National Natural Science Foundation of China(Grant Nos.62141409 and 62204204)the National Key R&D Program of China(Grant No.2022ZD0208602)the Zhejiang Provincial Key Research&Development Fund(Grant Nos.2019C04003 and 2021C01041)the Shanghai Sailing Program(Grant No.21YF1451000)the Key Research and Development Program of Shaanxi(Grant No.2022GY-001).
文摘Flexible pressure sensors have many potential applications in the monitoring of physiological signals because of their good biocompatibil-ity and wearability.However,their relatively low sensitivity,linearity,and stability have hindered their large-scale commercial application.Herein,aflexible capacitive pressure sensor based on an interdigital electrode structure with two porous microneedle arrays(MNAs)is pro-posed.The porous substrate that constitutes the MNA is a mixed product of polydimethylsiloxane and NaHCO3.Due to its porous and interdigital structure,the maximum sensitivity(0.07 kPa-1)of a porous MNA-based pressure sensor was found to be seven times higher than that of an imporous MNA pressure sensor,and it was much greater than that of aflat pressure sensor without a porous MNA structure.Finite-element analysis showed that the interdigital MNA structure can greatly increase the strain and improve the sensitivity of the sen-sor.In addition,the porous MNA-based pressure sensor was found to have good stability over 1500 loading cycles as a result of its bilayer parylene-enhanced conductive electrode structure.Most importantly,it was found that the sensor could accurately monitor the motion of afinger,wrist joint,arm,face,abdomen,eye,and Adam’s apple.Furthermore,preliminary semantic recognition was achieved by monitoring the movement of the Adam’s apple.Finally,multiple pressure sensors were integrated into a 33 array to detect a spatial pressure distribu-×tion.Compared to the sensors reported in previous works,the interdigital electrode structure presented in this work improves sensitivity and stability by modifying the electrode layer rather than the dielectric layer.
基金supported by the National Key R&D Program of China(2022YFA1602904)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR-063)the National Natural Science Foundation of China(12225303 and 12041301).
文摘The Five-hundred-meter Aperture Spherical Radio Telescope(FAST)Core Array is a proposed extension of FAST,integrating 24 secondary 40-m antennas implanted within 5 km of the FAST site.This original array design will combine the unprecedented sensitivity of FAST with a high angular resolution(4.3"at a frequency of 1.4 GHz),thereby exceeding the capabilities at similar frequencies of next-generation arrays such as the Square Kilometre Array Phase 1 or the next-generation Very Large Array.This article presents the technical specifications of the FAST Core Array,evaluates its potential relatively to existing radio telescope arrays,and describes its expected scientific prospects.The proposed array will be equipped with technologically advanced backend devices,such as real-time signal processing systems.A phased array feed receiver will be mounted on FAST to improve the survey efficiency of the FAST Core Array,whose broad frequency coverage and large field of view(FOV)will be essential to study transient cosmic phenomena such as fast radio bursts and gravitational wave events,to conduct surveys and resolve structures in neutral hydrogen galaxies,to monitor or detect pulsars,and to investigate exoplanetary systems.Finally,the FAST Core Array can strengthen China's major role in the global radio astronomy community,owing to a wide range of potential scientific applications from cosmology to exoplanet science.
文摘In this paper,the covert age of information(CAoI),which characterizes the timeliness and covertness performance of communication,is first investigated in the short-packet covert communication with time modulated retrodirective array(TMRDA).Specifically,the TMRDA is designed to maximize the antenna gain in the target direction while the side lobe is sufficiently suppressed.On this basis,the covertness constraint and CAoI are derived in closed form.To facilitate the covert transmission design,the transmit power and block-length are jointly optimized to minimize the CAoI,which demonstrates the trade-off between covertness and timelessness.Our results illustrate that there exists an optimal block-length that yields the minimum CAoI,and the presented optimization results can achieve enhanced performance compared with the fixed block-length case.Additionally,we observe that smaller beam pointing error at Bob leads to improvements in CAoI.
基金Research Supporting Project Number(RSPD2023R 585),King Saud University,Riyadh,Saudi Arabia.
文摘Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.
基金supported by the Science and Technology Development Fund of Macao SAR(FDCT0128/2022/A,0020/2023/RIB1,0111/2023/AFJ,005/2022/ALC)the Shandong Natural Science Foundation of China(ZR2020MA004)+2 种基金the National Natural Science Foundation of China(12071272)the MYRG 2018-00168-FSTZhejiang Provincial Natural Science Foundation of China(LQ23A010014).
文摘This study introduces a pre-orthogonal adaptive Fourier decomposition(POAFD)to obtain approximations and numerical solutions to the fractional Laplacian initial value problem and the extension problem of Caffarelli and Silvestre(generalized Poisson equation).As a first step,the method expands the initial data function into a sparse series of the fundamental solutions with fast convergence,and,as a second step,makes use of the semigroup or the reproducing kernel property of each of the expanding entries.Experiments show the effectiveness and efficiency of the proposed series solutions.
