This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the b...This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.展开更多
Traditional monopulse radar cannot resolve two targets present in one range and Doppler cell by means of the monopulse ratio. A novel algorithm is proposed to estimate the directions of two steady targets with two pul...Traditional monopulse radar cannot resolve two targets present in one range and Doppler cell by means of the monopulse ratio. A novel algorithm is proposed to estimate the directions of two steady targets with two pulses. The algorithm has a closedform expression and its variance is derived at high signal-to-noise ratios（SNRs）. Furthermore, the pulse pair selection criterion and the estimation method with multiple pulses are given. Finally, some numerical results are shown to validate the proposed algorithm and the effect of slight target fluctuations is tested.展开更多
In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exp...In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exponential kernel covariance matrix and obtain excellent performance via the maximumlikelihood(ML)algorithm.In order to obtain the global optimal solutions of this method,a quantum electromagnetic field optimization(QEFO)algorithm is designed.In view of the QEFO algorithm,the proposed method can resolve the difficulties of DOA estimation in the impulse noise.Comparing with some traditional DOA estimation methods,the proposed DOA estimation method shows high superiority and robustness for determining the DOA of independent and coherent sources,which has been verified via the Monte-Carlo experiments of different schemes,especially in the case of snapshot deficiency,low generalized signal to noise ratio(GSNR)and strong impulse noise.Beyond that,the Cramer-Rao bound(CRB)of angle estimation in the impulse noise and the proof of the convergence of the QEFO algorithm are provided in this paper.展开更多
Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capa...Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.展开更多
In recent years,the proliferation of beamforming signals has made the electromagnetic environment more complex.Traditional spectrum sensing techniques mainly focus on the detection of omnidirectional signals and can n...In recent years,the proliferation of beamforming signals has made the electromagnetic environment more complex.Traditional spectrum sensing techniques mainly focus on the detection of omnidirectional signals and can no longer meet the needs of beamforming signals.Moreover,the next-generation spectrum sensing technologies must not only reliably detect the presence of beamforming signals but also accurately estimate the spatial information of these signals.This paper investigates the issue of Direction of Arrival(DOA)of non-cooperative Unmanned Aerial Vehicle(UAV)beamforming signals,where most of the prior information about non-cooperative transmitters,such as the transmission power and the communication time slots,is unknown.In such conditions,we consider two types of data models for UAV beamforming signals with different Signalto-Noise Ratios(SNRs).Based on these data models,we develop a UAV Beamforming signals Detection-DOA Network(BD-DOANet),comprising convolutional modules,a channel attention module,and residual modules.Simulation results show that BD-DOANet effectively captures the angle information of non-cooperative UAV beamforming signals for both ideal and non-ideal data.At higher SNR levels,the average error is below 0.5 and its mean squared error is below 0.2.Even at lower SNR levels,BD-DOANet shows superior performance of DOA estimation.展开更多
Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as...Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as mutual coupling between array elements,array amplitude and phase errors,and array element position errors leads to defects in the array manifold,which makes the performance of the algorithm decline rapidly or even fail.In order to solve the problem of DOA estimation in the presence of amplitude and phase errors and array element position errors,this paper introduces the first-order Taylor expansion equivalent model of the received signal under the uniform linear array from the Bayesian point of view.In the solution,the amplitude and phase error parameters and the array element position error parameters are regarded as random variables obeying the Gaussian distribution.At the same time,the expectation-maximization algorithm is used to update the probability distribution parameters,and then the two error parameters are solved alternately to obtain more accurate DOA estimation results.Finally,the effectiveness of the proposed algorithm is verified by simulation and experiment.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
To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the ste...To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the steering vectors with amplitude and phase errors,assuming that mmWR works in the time-sharing mode.Then,approximate relationship between the near-field calibration steering vector and the far-field calibration steering vector is analyzed,which is used to accomplish the mapping between the two of them.Finally,simulation results verify that the proposed method can effectively improve the angle measurement accuracy of mmWR with existing amplitude and phase errors.展开更多
Feedforward active noise control(ANC)system are widely used to reduce the wide-band noise in different application.In feedforward ANC systems,when the noise source is unknown,the misplacement of the reference micropho...Feedforward active noise control(ANC)system are widely used to reduce the wide-band noise in different application.In feedforward ANC systems,when the noise source is unknown,the misplacement of the reference microphone may violate the causality constraint.We present a performance analysis of the feedforward ANC system under a noncausal condition.The ANC system performance degrades when the degree of noncausality increases.This research applies the microphone array technique to feedforward ANC systems to solve the unknown noise source problem.The generalized cross-correlation(GCC)and steering response power(SRP)methods based on microphone array are used to estimate the noise source location.Then,the ANC system selects the proper reference microphone for a noise control algorithm.The simulation and experiment results show that the SRP method can estimate the noise source direction with 84%accuracy.The proposed microphone array integrated ANC system can dramatically improve the system performance.展开更多
A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method ...A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.展开更多
Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element...Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element spacing of parallel uniform subarrays,we propose a generalized parallel coprime array(GPCA)geometry.The proposed geometry enjoys flexible array layouts by the coprime factors and enables to extend the array aperture to achieve great improvement of estimation performance.Meanwhile,we verify that GPCA always can obtain M2 degrees of freedom(DOFs)in co-array domain via 2M sensors after optimization,which outperforms sparse parallel array geometries,such as parallel coprime array(PCA)and parallel augmented coprime array(PACA),and is the same as parallel nested array(PNA)with extended aperture.The superiority of GPCA geometry has been proved by numerical simulations with sparse representation methods.展开更多
In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival （DOA） estimation of a ground sig...In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival （DOA） estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system （GPS） attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit （LEO） satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio （SNR） with DOA estimation.展开更多
Using super resolution direction of arrival（DOA） estimation algorithm to reduce the resolution angle is an effective method for passive radar seeker（PRS） to antagonize non-coherent radar decoy.Considering the powe...Using super resolution direction of arrival（DOA） estimation algorithm to reduce the resolution angle is an effective method for passive radar seeker（PRS） to antagonize non-coherent radar decoy.Considering the power and correlation property between radar and non-coherent decoy,an improved subspace DOA estimation method based on traditional subspace algorithm is proposed.Because this new method uses the invariance property of noise subspace,compared with traditional MUSIC algorithm,it shows not only better resolution in condition of closely spaced sources,but also superior performance in case of different power or partially correlated sources.Using this new method,PRS can distinguish radar and non-coherent decoy with good performance.Both the simulation result and the experimental data confirm the performance of the method.展开更多
The high resolution of DOA（direction of arrival） estimation could be obtained by using the min-norm algorithm. In this paper, the expression of the min-norm spatial spectrum based on acoustic vector-sensor（AVS） li...The high resolution of DOA（direction of arrival） estimation could be obtained by using the min-norm algorithm. In this paper, the expression of the min-norm spatial spectrum based on acoustic vector-sensor（AVS） linear arrays was presented and simulation study was carried out. Results of simulations indicated that left/right ambiguity could be removed and better performance for DOA estimation was obtainable when dealing with sources close to endfire than using pressure hydrophone linear arrays, and the interelement spacing was allowed to exceed the half-wavelength upper limit. A three-element vector hydrophone linear array with two meters interspace was designed. The AVS experiment was carried out at Songhua Lake in Jinlin Province. Experimental results show a high resolution tracking of targets can be obtained using the rain-norm algorithm.展开更多
A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.Acc...A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.According to the different characters of covariance matrix and general steering vector of the array received source,a second order blind identification method is used to separate the sources,the mixing matrix could be obtained.From the mixing matrix,the type of the source is identified by using an amplitude criterion.And the direction of arrival for the array received source is estimated by using the matching pursuit algorithm from the vectors of the mixing matrix.Computer simulations validate the efficiency of the method.展开更多
In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the...In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the circular convolution between a fixed coefficient vector and the received data vector.Thereafter, in order to refine coarse DOA estimates, we reconstruct the direction matrix based on the coarse DOA estimations and take the first order Taylor expansion with DOA estimation offsets into account.Finally, the refined estimations are obtained by compensating the offsets, which are obtained via least squares(LS) without any complex searches.In addition, the refinement can be iteratively implemented to enhance the estimation results.Compared to the offset search method, the proposed method achieves a better estimation performance while requiring lower complexity.Numerical simulations are presented to demonstrate the effectiveness of the proposed method.展开更多
The problem of two-dimensional direction of arrival(2D-DOA)estimation for uniform planar arrays(UPAs)is investigated by employing the reduced-dimensional(RD)polynomial root finding technique and 2D multiple signal cla...The problem of two-dimensional direction of arrival(2D-DOA)estimation for uniform planar arrays(UPAs)is investigated by employing the reduced-dimensional(RD)polynomial root finding technique and 2D multiple signal classification(2D-MUSIC)algorithm.Specifically,based on the relationship between the noise subspace and steering vectors,we first construct 2D root polynomial for 2D-DOA estimates and then prove that the 2D polynomial function has infinitely many solutions.In particular,we propose a computationally efficient algorithm,termed RD-ROOT-MUSIC algorithm,to obtain the true solutions corresponding to targets by RD technique,where the 2D root-finding problem is substituted by two one-dimensional(1D)root-finding operations.Finally,accurate 2DDOA estimates can be obtained by a sample pairing approach.In addition,numerical simulation results are given to corroborate the advantages of the proposed algorithm.展开更多
This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeit...This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.展开更多
This paper presents a multi-Bernoulli filter for tracking the direction of arrival(DOAs)of time-varying number of targets using sensor array.Our method operates directly on the measurements of sensor array and does no...This paper presents a multi-Bernoulli filter for tracking the direction of arrival(DOAs)of time-varying number of targets using sensor array.Our method operates directly on the measurements of sensor array and does not require any detection.Firstly,more information is reserved and compared with the after-detection measurements using a finite set of detected points.It can significantly improve the tracking performance,especially in low signal-to-noise ratio.Secondly,it inherits the advantages of the multi-Bernoulli approximation which models each of the targets individually.This allows more accurate multi-target state estimation,especially when targets cross.The proposed filter does not need clustering step and simulation results showcase the improved performance of the proposed filter.展开更多
This paper presents a low?complexity method for the direction?of?arrival(DOA)estimation of noncircular signals for coprime sensor arrays.The noncircular property is exploited to improve the performance of DOA estimati...This paper presents a low?complexity method for the direction?of?arrival(DOA)estimation of noncircular signals for coprime sensor arrays.The noncircular property is exploited to improve the performance of DOA estimation.To reduce the computational complexity,the rotational invariance propagator method(RIPM)is included in the algorithm.First,the extended array output is reconstructed by combining the array output and its conjugated counterpart.Then,the RIPM is utilized to obtain two sets of DOA estimates for two subarrays.Finally,the true DOAs are estimated by combining the consistent results of the two subarrays.This illustrates the potential gain that both noncircularity and coprime arrays provide when considered together.The proposed algorithm has a lower computational complexity and a better DOA estimation performance than the standard estimation of signal parameters by the rotational invariance technique and Capon algorithm.Numerical simulation results illustrate the effectiveness and superiority of the proposed algorithm.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61071163,61271327,and 61471191)the Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics,China(Grant No.BCXJ14-08)+2 种基金the Funding of Innovation Program for Graduate Education of Jiangsu Province,China(Grant No.KYLX 0277)the Fundamental Research Funds for the Central Universities,China(Grant No.3082015NP2015504)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA),China
文摘This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.
文摘Traditional monopulse radar cannot resolve two targets present in one range and Doppler cell by means of the monopulse ratio. A novel algorithm is proposed to estimate the directions of two steady targets with two pulses. The algorithm has a closedform expression and its variance is derived at high signal-to-noise ratios（SNRs）. Furthermore, the pulse pair selection criterion and the estimation method with multiple pulses are given. Finally, some numerical results are shown to validate the proposed algorithm and the effect of slight target fluctuations is tested.
基金supported by the National Natural Science Foundation of China(61571149)the Natural Science Foundation of Heilongjiang Province(LH2020F017)+1 种基金the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Heilongjiang Province Key Laboratory of High Accuracy Satellite Navigation and Marine Application Laboratory(HKL-2020-Y01).
文摘In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exponential kernel covariance matrix and obtain excellent performance via the maximumlikelihood(ML)algorithm.In order to obtain the global optimal solutions of this method,a quantum electromagnetic field optimization(QEFO)algorithm is designed.In view of the QEFO algorithm,the proposed method can resolve the difficulties of DOA estimation in the impulse noise.Comparing with some traditional DOA estimation methods,the proposed DOA estimation method shows high superiority and robustness for determining the DOA of independent and coherent sources,which has been verified via the Monte-Carlo experiments of different schemes,especially in the case of snapshot deficiency,low generalized signal to noise ratio(GSNR)and strong impulse noise.Beyond that,the Cramer-Rao bound(CRB)of angle estimation in the impulse noise and the proof of the convergence of the QEFO algorithm are provided in this paper.
基金the financial support from the National Key Research and Development Program of China(No.2023YFB3907001)the National Natural Science Foundation of China(Nos.U2233217,62371029)the UK Engineering and Physical Sciences Research Council(EPSRC),China(Nos.EP/M026981/1,EP/T021063/1 and EP/T024917/)。
文摘Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.
基金supported by the National Natural Science Foundation of China(Nos.U20B2038,62231027,62171462)。
文摘In recent years,the proliferation of beamforming signals has made the electromagnetic environment more complex.Traditional spectrum sensing techniques mainly focus on the detection of omnidirectional signals and can no longer meet the needs of beamforming signals.Moreover,the next-generation spectrum sensing technologies must not only reliably detect the presence of beamforming signals but also accurately estimate the spatial information of these signals.This paper investigates the issue of Direction of Arrival(DOA)of non-cooperative Unmanned Aerial Vehicle(UAV)beamforming signals,where most of the prior information about non-cooperative transmitters,such as the transmission power and the communication time slots,is unknown.In such conditions,we consider two types of data models for UAV beamforming signals with different Signalto-Noise Ratios(SNRs).Based on these data models,we develop a UAV Beamforming signals Detection-DOA Network(BD-DOANet),comprising convolutional modules,a channel attention module,and residual modules.Simulation results show that BD-DOANet effectively captures the angle information of non-cooperative UAV beamforming signals for both ideal and non-ideal data.At higher SNR levels,the average error is below 0.5 and its mean squared error is below 0.2.Even at lower SNR levels,BD-DOANet shows superior performance of DOA estimation.
基金supported by the National Natural Science Foundation of China (62071144)
文摘Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as mutual coupling between array elements,array amplitude and phase errors,and array element position errors leads to defects in the array manifold,which makes the performance of the algorithm decline rapidly or even fail.In order to solve the problem of DOA estimation in the presence of amplitude and phase errors and array element position errors,this paper introduces the first-order Taylor expansion equivalent model of the received signal under the uniform linear array from the Bayesian point of view.In the solution,the amplitude and phase error parameters and the array element position error parameters are regarded as random variables obeying the Gaussian distribution.At the same time,the expectation-maximization algorithm is used to update the probability distribution parameters,and then the two error parameters are solved alternately to obtain more accurate DOA estimation results.Finally,the effectiveness of the proposed algorithm is verified by simulation and experiment.
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.
文摘To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the steering vectors with amplitude and phase errors,assuming that mmWR works in the time-sharing mode.Then,approximate relationship between the near-field calibration steering vector and the far-field calibration steering vector is analyzed,which is used to accomplish the mapping between the two of them.Finally,simulation results verify that the proposed method can effectively improve the angle measurement accuracy of mmWR with existing amplitude and phase errors.
文摘Feedforward active noise control(ANC)system are widely used to reduce the wide-band noise in different application.In feedforward ANC systems,when the noise source is unknown,the misplacement of the reference microphone may violate the causality constraint.We present a performance analysis of the feedforward ANC system under a noncausal condition.The ANC system performance degrades when the degree of noncausality increases.This research applies the microphone array technique to feedforward ANC systems to solve the unknown noise source problem.The generalized cross-correlation(GCC)and steering response power(SRP)methods based on microphone array are used to estimate the noise source location.Then,the ANC system selects the proper reference microphone for a noise control algorithm.The simulation and experiment results show that the SRP method can estimate the noise source direction with 84%accuracy.The proposed microphone array integrated ANC system can dramatically improve the system performance.
基金supported by the National Natural Science Foundation of China(61301211)and the Aviation Science Foundation(20131852028)
文摘A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.
文摘Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element spacing of parallel uniform subarrays,we propose a generalized parallel coprime array(GPCA)geometry.The proposed geometry enjoys flexible array layouts by the coprime factors and enables to extend the array aperture to achieve great improvement of estimation performance.Meanwhile,we verify that GPCA always can obtain M2 degrees of freedom(DOFs)in co-array domain via 2M sensors after optimization,which outperforms sparse parallel array geometries,such as parallel coprime array(PCA)and parallel augmented coprime array(PACA),and is the same as parallel nested array(PNA)with extended aperture.The superiority of GPCA geometry has been proved by numerical simulations with sparse representation methods.
基金co-supported by the National Natural Science Foundation of China (No. 61073012)the Aeronautical Science Foundation of China (No. 20111951015)
文摘In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival （DOA） estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system （GPS） attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit （LEO） satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio （SNR） with DOA estimation.
文摘Using super resolution direction of arrival（DOA） estimation algorithm to reduce the resolution angle is an effective method for passive radar seeker（PRS） to antagonize non-coherent radar decoy.Considering the power and correlation property between radar and non-coherent decoy,an improved subspace DOA estimation method based on traditional subspace algorithm is proposed.Because this new method uses the invariance property of noise subspace,compared with traditional MUSIC algorithm,it shows not only better resolution in condition of closely spaced sources,but also superior performance in case of different power or partially correlated sources.Using this new method,PRS can distinguish radar and non-coherent decoy with good performance.Both the simulation result and the experimental data confirm the performance of the method.
文摘The high resolution of DOA（direction of arrival） estimation could be obtained by using the min-norm algorithm. In this paper, the expression of the min-norm spatial spectrum based on acoustic vector-sensor（AVS） linear arrays was presented and simulation study was carried out. Results of simulations indicated that left/right ambiguity could be removed and better performance for DOA estimation was obtainable when dealing with sources close to endfire than using pressure hydrophone linear arrays, and the interelement spacing was allowed to exceed the half-wavelength upper limit. A three-element vector hydrophone linear array with two meters interspace was designed. The AVS experiment was carried out at Songhua Lake in Jinlin Province. Experimental results show a high resolution tracking of targets can be obtained using the rain-norm algorithm.
文摘A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.According to the different characters of covariance matrix and general steering vector of the array received source,a second order blind identification method is used to separate the sources,the mixing matrix could be obtained.From the mixing matrix,the type of the source is identified by using an amplitude criterion.And the direction of arrival for the array received source is estimated by using the matching pursuit algorithm from the vectors of the mixing matrix.Computer simulations validate the efficiency of the method.
基金supported by the National Natural Science Foundation of China (61971217, 61601167)Jiangsu Planned Project for Postdoctoral Research Funds (2020Z013)+2 种基金China Postdoctoral Science Foundation (2020M681585)the fund of State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE 2021Z0101B)the fund of State Key Laboratory of Marine Resource Utilization in South China Sea (Hainan University)(MRUKF2021033)。
文摘In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the circular convolution between a fixed coefficient vector and the received data vector.Thereafter, in order to refine coarse DOA estimates, we reconstruct the direction matrix based on the coarse DOA estimations and take the first order Taylor expansion with DOA estimation offsets into account.Finally, the refined estimations are obtained by compensating the offsets, which are obtained via least squares(LS) without any complex searches.In addition, the refinement can be iteratively implemented to enhance the estimation results.Compared to the offset search method, the proposed method achieves a better estimation performance while requiring lower complexity.Numerical simulations are presented to demonstrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Nos.61631020,61971218,61601167,61371169)。
文摘The problem of two-dimensional direction of arrival(2D-DOA)estimation for uniform planar arrays(UPAs)is investigated by employing the reduced-dimensional(RD)polynomial root finding technique and 2D multiple signal classification(2D-MUSIC)algorithm.Specifically,based on the relationship between the noise subspace and steering vectors,we first construct 2D root polynomial for 2D-DOA estimates and then prove that the 2D polynomial function has infinitely many solutions.In particular,we propose a computationally efficient algorithm,termed RD-ROOT-MUSIC algorithm,to obtain the true solutions corresponding to targets by RD technique,where the 2D root-finding problem is substituted by two one-dimensional(1D)root-finding operations.Finally,accurate 2DDOA estimates can be obtained by a sample pairing approach.In addition,numerical simulation results are given to corroborate the advantages of the proposed algorithm.
文摘This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.
文摘This paper presents a multi-Bernoulli filter for tracking the direction of arrival(DOAs)of time-varying number of targets using sensor array.Our method operates directly on the measurements of sensor array and does not require any detection.Firstly,more information is reserved and compared with the after-detection measurements using a finite set of detected points.It can significantly improve the tracking performance,especially in low signal-to-noise ratio.Secondly,it inherits the advantages of the multi-Bernoulli approximation which models each of the targets individually.This allows more accurate multi-target state estimation,especially when targets cross.The proposed filter does not need clustering step and simulation results showcase the improved performance of the proposed filter.
基金supported by the National Natural Science Foundations of China (Nos.61371169,61601167, 61601504)the Natural Science Foundation of Jiangsu Province (No.BK20161489)+1 种基金the Open Research Fund of State Key Laboratory of Millimeter Waves, Southeast University (No. K201826)the Fundamental Research Funds for the Central Universities (No. NE2017103)
文摘This paper presents a low?complexity method for the direction?of?arrival(DOA)estimation of noncircular signals for coprime sensor arrays.The noncircular property is exploited to improve the performance of DOA estimation.To reduce the computational complexity,the rotational invariance propagator method(RIPM)is included in the algorithm.First,the extended array output is reconstructed by combining the array output and its conjugated counterpart.Then,the RIPM is utilized to obtain two sets of DOA estimates for two subarrays.Finally,the true DOAs are estimated by combining the consistent results of the two subarrays.This illustrates the potential gain that both noncircularity and coprime arrays provide when considered together.The proposed algorithm has a lower computational complexity and a better DOA estimation performance than the standard estimation of signal parameters by the rotational invariance technique and Capon algorithm.Numerical simulation results illustrate the effectiveness and superiority of the proposed algorithm.
