期刊文献+
共找到2,066篇文章
< 1 2 104 >
每页显示 20 50 100
Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform
1
作者 Xinwei Wang Xiaopeng Yan +2 位作者 Tai An Qile Chen Dingkun Huang 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第3期352-363,共12页
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf... Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method. 展开更多
关键词 Unmanned aerial vehicle(UAV) Uniform linear array(ULA) direction of arrival(doa) Difference co-array Nonuniform linear motion sampling method
下载PDF
A Novel CCA-NMF Whitening Method for Practical Machine Learning Based Underwater Direction of Arrival Estimation
2
作者 Yun Wu Xinting Li Zhimin Cao 《Journal of Beijing Institute of Technology》 EI CAS 2024年第2期163-174,共12页
Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based ... Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions. 展开更多
关键词 direction of arrival(doa) sonar array data underwater disturbance machine learn-ing canonical correlation analysis(CCA) non-negative matrix factorization(NMF)
下载PDF
Cyclic Beam Direction of Arrival Estimation Method for Ship Propeller Noise
3
作者 ZHANG Xiaowei NIE Weihang +1 位作者 XU Ji YAN Yonghong 《Journal of Ocean University of China》 SCIE CAS CSCD 2024年第4期883-896,共14页
In underwater acoustic applications,the conventional cyclic direction of arrival algorithm faces challenges,including a low signal-to-noise ratio and high bandwidth when compared with modulated frequencies.In response... In underwater acoustic applications,the conventional cyclic direction of arrival algorithm faces challenges,including a low signal-to-noise ratio and high bandwidth when compared with modulated frequencies.In response to these issues,this paper introduces a novel,robust,and broadband cyclic beamforming algorithm.The proposed method substitutes the conventional cyclic covariance matrix with the variance of the cyclic covariance matrix as its primary feature.Assuming that the same frequency band shares a common steering vector,the new algorithm achieves superior detection performance for targets with specific modulation frequencies while suppressing interference signals and background noise.Experimental results demonstrate a significant enhancement in the directibity index by 81%and 181%when compared with the traditional Capon beamforming algorithm and the traditional extended wideband spectral cyclic MUSIC(EWSCM)algorithm,respectively.Moreover,the proposed algorithm substantially reduces computational complexity to 1/40th of that of the EWSCM algorithm,employing frequency band statistical averaging and covariance matrix variance. 展开更多
关键词 CYCLOSTATIONARITY direction of arrival extended wideband spectral cyclic music cyclic covariance matrix
下载PDF
DOA estimation of high-dimensional signals based on Krylov subspace and weighted l_(1)-norm
4
作者 YANG Zeqi LIU Yiheng +4 位作者 ZHANG Hua MA Shuai CHANG Kai LIU Ning LYU Xiaode 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第3期532-540,F0002,共10页
With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direc... With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment. 展开更多
关键词 direction of arrival(doa) compressed sensing(CS) Krylov subspace l_(1)-norm dimensionality reduction
下载PDF
Combining Self-Organizing Map and Lipschitz Condition for Estimation in Direction of Arrival
5
作者 Xiuhui Tan Peng Wang +2 位作者 Hongping Hu Rong Cheng Yanping Bai 《Open Journal of Applied Sciences》 2023年第7期1012-1028,共17页
There are many DOA estimation methods based on different signal features, and these methods are often evaluated by experimental results, but lack the necessary theoretical basis. Therefore, a direction of arrival (DOA... There are many DOA estimation methods based on different signal features, and these methods are often evaluated by experimental results, but lack the necessary theoretical basis. Therefore, a direction of arrival (DOA) estimation system based on self-organizing map (SOM) and designed for arbitrarily distributed sensor array is proposed. The essential principle of this method is that the map from distance difference of arrival (DDOA) to DOA is Lipschitz continuity, it indicates the similar topology between them, and thus Kohonen SOM is a suitable network to classify DOA through DDOA. The simulation results show that the DOA estimation errors are less than 1° for most signals between 0° to 180°. Compared to MUSIC, Root-MUSIC, ESPRIT, and RBF, the errors of signals under signal-to-noise ratios (SNR) declines from 20 dB to 2 dB are robust, SOM is better than RBF and almost close to MUSIC. Further, the network can be trained in advance, which makes it possible to be implemented in real-time. 展开更多
关键词 doa Estimation Kohonen SOM Distance Difference of arrival Topological Order Lipschitz Condition
下载PDF
基于二阶统计特性的方向向量估计算法的DOA估计 被引量:1
6
作者 侯进 盛尧宝 张波 《电子与信息学报》 EI CAS CSCD 北大核心 2024年第2期697-704,共8页
为了减小天线阵流形误差对波达方向(DOA)估计结果的影响,以及克服基于传统盲源分离算法的DOA估计算法不能应用于少通道测向设备的不足,提出一种基于2阶统计特性的方向向量估计算法的DOA估计算法。首先,根据确定性最大似然(DML)估计算法... 为了减小天线阵流形误差对波达方向(DOA)估计结果的影响,以及克服基于传统盲源分离算法的DOA估计算法不能应用于少通道测向设备的不足,提出一种基于2阶统计特性的方向向量估计算法的DOA估计算法。首先,根据确定性最大似然(DML)估计算法谱函数的特征,构造关于协方差矩阵的酉约束下的优化问题;然后,通过优化该问题获得各个单信号的实际方向向量;最后,将各个单信号的实际方向向量输入到空间谱算法中实现DOA估计。由于将多信号的DOA估计转化为多个单信号的DOA估计,因此在天线阵列流形存在误差时,所提算法比传统的DOA方法具有更好的DOA估计性能。由于所提算法仅需使用协方差矩阵,因此所提算法可应用于少通道测向设备。由仿真实验结果可知,在阵列流形存在误差以及测向设备为少通道测向设备时,与传统DOA方法相比,所提算法的DOA估计的准确度、抗扰度以及分辨率更高。 展开更多
关键词 doa估计 天线阵列流形误差 盲源分离 酉约束
下载PDF
基于云平台的铁路无线电信号DOA跟踪算法
7
作者 代赛 孙宵芳 +4 位作者 左莹 吴欣蒙 丁建文 孙斌 钟章队 《北京交通大学学报》 CAS CSCD 北大核心 2024年第2期115-121,共7页
在高速铁路场景下,准确估计和跟踪无线电信号的波达方向(Direction of Arrival, DOA)能够有效提升无线通信服务质量.然而,高速移动的无线信道具有快速时变特性,对信号处理的速度和准确性提出了更高的挑战.针对传统的基于信号子空间的DO... 在高速铁路场景下,准确估计和跟踪无线电信号的波达方向(Direction of Arrival, DOA)能够有效提升无线通信服务质量.然而,高速移动的无线信道具有快速时变特性,对信号处理的速度和准确性提出了更高的挑战.针对传统的基于信号子空间的DOA估计算法,由于巨大的计算量而无法应用于高速铁路快速时变系统中进行DOA跟踪的问题,提出了基于卡尔曼滤波和正交压缩近似投影子空间跟踪(Kalman Filter-Orthonormal Projection Approximation and Subspace Tracking of deflation, K-OPASTd)的DOA算法.首先,搭建基于云平台的铁路信号动态测向系统;然后,建立列车接收信号模型,提出K-OPASTd算法对DOA进行动态跟踪;最后,将本文提出的算法与OPASTd算法所得到的估计角度的均方根误差进行仿真对比实验.研究结果表明:信噪比均为10dB时,本文所提算法的均方根误差比OPASTd算法低约60%;阵元均为20时,K-OPASTd算法的均方根误差比OPASTd算法低约80%. 展开更多
关键词 波达方向跟踪 正交压缩近似投影子空间跟踪 卡尔曼滤波 云平台
下载PDF
基于稀疏度自适应变步长的离格DOA估计方法
8
作者 李鹏 单钰强 +1 位作者 林事力 纵彪 《电子器件》 CAS 2024年第3期661-666,共6页
网格划分产生的量化误差是影响信源定位估计性能的一个重要缺陷。针对目前Lp类离格算法计算量大以及需要提前预知稀疏度的问题,提出了一种稀疏度自适应变步长的离格波达方向定位方法。首先根据一阶泰勒展开构建基于角度优化的离格参数模... 网格划分产生的量化误差是影响信源定位估计性能的一个重要缺陷。针对目前Lp类离格算法计算量大以及需要提前预知稀疏度的问题,提出了一种稀疏度自适应变步长的离格波达方向定位方法。首先根据一阶泰勒展开构建基于角度优化的离格参数模型,以残差能量的变化作为预估稀疏度K的条件。然后利用噪声子空间与信号子空间正交性作为原子误差入选判定依据,利用交替迭代优化方法实现离格模型下的准确求解。所提方法结合了贪婪算法支撑集选取策略与阵列协方差矩阵的有效信息。仿真实验表明,在满足稀疏性条件下,所提方法不仅大大缩短运算时间,而且可以实现空域角度范围内任意角度的精确估计。 展开更多
关键词 离格 波达方向 稀疏重构 贪婪算法
下载PDF
基于稀疏恢复的快速高精度DOA估计算法
9
作者 刘鲁涛 徐国珩 王振 《系统工程与电子技术》 EI CSCD 北大核心 2024年第11期3631-3638,共8页
传统的基于稀疏恢复的波达方向(direction of arrival,DOA)估计算法使用密集的采样网格,导致计算量显著增加,且对邻近入射信号的估计精度不高。针对这一问题,提出一种快速高精度DOA估计算法。该算法首先使用网格进化方法降低网格点总数... 传统的基于稀疏恢复的波达方向(direction of arrival,DOA)估计算法使用密集的采样网格,导致计算量显著增加,且对邻近入射信号的估计精度不高。针对这一问题,提出一种快速高精度DOA估计算法。该算法首先使用网格进化方法降低网格点总数。然后,对噪声方差和信号功率进行二次估计,进而使用离网求根稀疏贝叶斯学习(off-grid root sparse Bayesian learning,OGRSBL)技术来实现入射角的精确估计。仿真表明,相比传统稀疏贝叶斯学习类算法,所提算法计算效率高,同时对紧邻信号有着更好的估计能力。 展开更多
关键词 波达方向估计 离网 网格进化 稀疏贝叶斯学习
下载PDF
基于均匀圆阵的压制式相干干扰DOA估计算法
10
作者 王晓君 高祥博 刘昊昱 《大连工业大学学报》 CAS 2024年第4期307-312,共6页
针对导航抗干扰中一般干扰信号波达方向(direction-of-arrival, DOA)算法无法在均匀圆阵上有效地估计含有相干干扰的信号来向问题,提出了一种基于虚拟线阵的协方差矩阵重构的MUSIC算法。该算法通过对均匀圆阵进行模式空间变换,形成虚拟... 针对导航抗干扰中一般干扰信号波达方向(direction-of-arrival, DOA)算法无法在均匀圆阵上有效地估计含有相干干扰的信号来向问题,提出了一种基于虚拟线阵的协方差矩阵重构的MUSIC算法。该算法通过对均匀圆阵进行模式空间变换,形成虚拟线阵,将模式空间变换后的数据协方差矩阵的所有行进行Toeplitz重构,并将所有Toeplitz矩阵构造成一个新的等效的满秩数据协方差矩阵,以此来达到解相干的目的。结合在虚拟线阵上的MUSIC算法,并通过多谱峰搜索算法直接得到空间谱的谱峰位置,从而完成对干扰来向的DOA估计。经仿真验证,该算法在存在相干信号且信号角度相隔30°左右的条件下,依旧能够对信号的波达方向进行有效估计。 展开更多
关键词 导航抗干扰 波达方向估计 均匀圆阵 相干干扰 MUSIC算法
下载PDF
基于矩阵分布式重构的正交极化阵DOA估计
11
作者 张涛 孙昭乾 郭沐然 《信号处理》 CSCD 北大核心 2024年第10期1822-1833,共12页
对于子空间类算法而言,协方差矩阵估计的准确性将很大程度的影响到算法的性能,理想的协方差矩阵估计为无限长的信号运算得到,实际中大多使用有限快拍数的采样数据进行协方差矩阵估计。有学者研究表明,阵列协方差矩阵位于由接收信号的所... 对于子空间类算法而言,协方差矩阵估计的准确性将很大程度的影响到算法的性能,理想的协方差矩阵估计为无限长的信号运算得到,实际中大多使用有限快拍数的采样数据进行协方差矩阵估计。有学者研究表明,阵列协方差矩阵位于由接收信号的所有可能导向矢量构成的子空间中,可以利用子空间组成的完备重构矩阵对协方差矩阵进行重构,此类方法需要对阵列的所有可能接收信号进行积分,并获得由其主成分构成的重构矩阵。为了减小低快拍数和低信噪比下采样协方差矩阵误差,并降低其运算复杂度,提出了一种基于正交偶极子组成的均匀圆阵的采样协方差矩阵重构方法。将整体阵列划分为子阵1和子阵2,子阵内部仅存在空域相位差而没有极化敏感特性,子阵间空域相位差相同,极化敏感特性不同。并基于均匀圆阵的结构特点,给出了特殊的重构矩阵,特殊的重构矩阵不依赖信号特性,仅与圆阵结构相关,通过理论分析和仿真测试可以得到,特殊的重构矩阵在维度和复杂度方面均优于全角度域和极化域积分的重构矩阵。该方法将重构算法应用到了极化敏感阵列领域同时减少了运算的复杂度,通过后续对低信噪比和低快拍数的仿真测试表明,重构后的协方差矩阵可以有效提高信号子空间和理想噪声子空间的正交性,使用重构的协方差矩阵进行极化空间谱估计提高了在恶劣环境下的信源分辨力。 展开更多
关键词 极化敏感阵列 波达方向估计 矩阵重构 子空间算法
下载PDF
OFDM系统中一种低复杂度的TOA和DOA联合估计算法 被引量:1
12
作者 李铭 侯艳丽 苏佳 《电子测量技术》 北大核心 2023年第10期155-163,共9页
针对正交频分复用(OFDM)系统利用求根多重信号分类(Root-MUSIC)算法进行到达时间(TOA)和波达方向(DOA)联合估计时,由于多项式求根过程中所求根为共轭对称形式存在计算冗余的问题,提出一种基于谱分解的TOA和DOA联合估计算法——SF-Root-M... 针对正交频分复用(OFDM)系统利用求根多重信号分类(Root-MUSIC)算法进行到达时间(TOA)和波达方向(DOA)联合估计时,由于多项式求根过程中所求根为共轭对称形式存在计算冗余的问题,提出一种基于谱分解的TOA和DOA联合估计算法——SF-Root-MUSIC算法。该算法基于劳伦特多项式的结构特点,利用谱分解将求根多项式的阶次降低一半,降低了计算复杂度,完成独立的TOA和DOA估计,并通过构造代价函数进行参数配对,完成联合估计。仿真结果表明,SF-Root-MUSIC算法与Root-MUSIC算法具有相似的估计性能,且复杂度更低,在阵元数为12、子载波个数为512、快拍数为512时复杂度可降低69.94%,在保证精度的同时,以更低的复杂度实现TOA和DOA的联合估计,更适用于实时计算。 展开更多
关键词 正交频分复用 到达时间 波达方向 ROOT-MUSIC算法 谱分解
原文传递
基于改进SP算法的多目标DOA估计方法 被引量:1
13
作者 曹若石 赵永波 邱雨铖 《系统工程与电子技术》 EI CSCD 北大核心 2024年第7期2294-2300,共7页
稀疏重构类算法在雷达目标参数估计中的应用一直是近年来的热门,但由于稀疏重构类算法的局限性,在进行目标波达方向(direction of arrival,DOA)估计时受到原子间的互相影响,从而使多目标测角精度降低。针对此问题,提出一种基于信号分离... 稀疏重构类算法在雷达目标参数估计中的应用一直是近年来的热门,但由于稀疏重构类算法的局限性,在进行目标波达方向(direction of arrival,DOA)估计时受到原子间的互相影响,从而使多目标测角精度降低。针对此问题,提出一种基于信号分离迭代思想的松弛子空间追踪算法。首先求出回波信号与归一化后字典矩阵相关性最强的多个原子作为初步估计值,再利用初步估计的角度构建代价函数,反复估计直至代价函数收敛。仿真结果表明,所提算法减小了目标个数和相位差的影响,提高了多目标DOA估计的测角精度,同时相较于传统的松弛算法减少了运算量。 展开更多
关键词 波达方向估计 稀疏重构 子空间追踪 松弛算法
下载PDF
High-order extended coprime array design for direction of arrival estimation 被引量:5
14
作者 SHI Junpeng WEN Fangqing +2 位作者 LIU Yongxiang LIU Tianpeng LIU Zhen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第4期748-755,共8页
Nonuniform linear arrays,such as coprime array and nested array,have received great attentions because of the increased degrees of freedom(DOFs)and weakened mutual coupling.In this paper,inspired by the existing copri... Nonuniform linear arrays,such as coprime array and nested array,have received great attentions because of the increased degrees of freedom(DOFs)and weakened mutual coupling.In this paper,inspired by the existing coprime array,we propose a high-order extended coprime array(HoECA)for improved direction of arrival(DOA)estimation.We first derive the closed-form expressions for the range of consecutive lags.Then,by changing the inter-element spacing of a uniform linear array(ULA),three cases are proposed and discussed.It is indicated that the HoECA can obtain the largest number of consecutive lags when the spacing takes the maximum value.Finally,by comparing it with the other sparse arrays,the optimized HoECA enjoys a larger number of consecutive lags with mitigating mutual coupling.Simulation results are shown to evaluate the superiority of HoECA over the others in terms of DOF,mutual coupling leakage and estimation accuracy. 展开更多
关键词 high-order extended coprime array(HoECA) direction of arrival(doa) degree of freedom(Dof) mutual coupling
下载PDF
基于改进帝王蝶算法的最大似然DOA估计 被引量:2
15
作者 赵小梅 丁勇 王海涛 《广西师范大学学报(自然科学版)》 CAS 北大核心 2024年第3期131-140,共10页
针对传统最大似然波达方向(maximum likelihood direction of arrival,ML-DOA)估计存在计算量大、估计精度差等问题,本文提出一种采用改进帝王蝶优化算法(improved monarch butterfly optimization algorithm,IMBO)的ML-DOA估计方法。I... 针对传统最大似然波达方向(maximum likelihood direction of arrival,ML-DOA)估计存在计算量大、估计精度差等问题,本文提出一种采用改进帝王蝶优化算法(improved monarch butterfly optimization algorithm,IMBO)的ML-DOA估计方法。IMBO算法通过精英反向学习策略对初始帝王蝶种群进行优化,得到适应度值较优的初始帝王蝶个体,进而能够改善帝王蝶种群的多样性;引入差分进化算法启发的变异操作以及自适应策略对帝王蝶个体的寻优方式进行改进,扩大了算法的搜索空间;引入了高斯-柯西变异算子,自适应调整变异步长,避免算法陷入局部最优。将IMBO应用于ML-DOA,实验表明,与传统的DOA估计算法相比,在不同信源数目、信噪比以及种群数量下,本文提出的算法收敛性能更好,均方根误差更低,运算量更小。 展开更多
关键词 波达方向 最大似然估计 帝王蝶算法 精英反向学习 自适应策略 变异算子
下载PDF
稀疏阵列的鲁棒矩阵填充DOA估计算法
16
作者 张芸萌 董玫 陈伯孝 《系统工程与电子技术》 EI CSCD 北大核心 2024年第5期1477-1483,共7页
稀疏阵列布阵灵活,增大阵列孔径的同时还能减少阵元间耦合,但基于稀疏阵列的传统波达方向估计会导致角度模糊混叠,带来估计精度差和稳健性不足的问题。针对以上问题,提出一种适用于稀疏阵列波达方向估计的加权截断奇异值投影(weighted t... 稀疏阵列布阵灵活,增大阵列孔径的同时还能减少阵元间耦合,但基于稀疏阵列的传统波达方向估计会导致角度模糊混叠,带来估计精度差和稳健性不足的问题。针对以上问题,提出一种适用于稀疏阵列波达方向估计的加权截断奇异值投影(weighted truncated singular value projection,WT-SVP)的鲁棒矩阵填充算法。在填充迭代过程中根据奇异值的大小分配权重,突出大奇异值包含的阵列信息,减少小奇异值中不必要的噪声信息,从而优化传统奇异值投影算法。该算法可以实现稀疏阵列的孔洞信息恢复,对不连续阵元充分利用,同时WT-SVP填充算法实现了稀疏阵列波达方向估计的高精度、高分辨以及在低信噪比、低快拍时的高鲁棒性。 展开更多
关键词 稀疏阵列 矩阵填充 奇异值投影 波达方向估计
下载PDF
基于稀疏线阵协方差矩阵重构的DOA估计方法研究
17
作者 徐文成 李秀坤 于歌 《信号处理》 CSCD 北大核心 2024年第7期1266-1273,共8页
相比均匀线阵(Uniform Linear Array,ULA),相同阵元数目下稀疏线阵(Sparse Linear Array,SLA)的抗耦合效应更好,阵列孔径更大,到达方向(Direction of Arrival,DOA)估计的自由度(Degrees Of Freedom,DOF)更高,因而近年来得到了广泛的研... 相比均匀线阵(Uniform Linear Array,ULA),相同阵元数目下稀疏线阵(Sparse Linear Array,SLA)的抗耦合效应更好,阵列孔径更大,到达方向(Direction of Arrival,DOA)估计的自由度(Degrees Of Freedom,DOF)更高,因而近年来得到了广泛的研究。为了可以进行高DOF的DOA估计,学者们开始研究SLA的差分虚拟阵元,差分虚拟阵元对应的协方差矩阵相比原阵元对应的协方差矩阵维度更大,因而估计的DOF更高。当SLA的差分虚拟阵元连续取值时,可以利用已有阵元的接收信息,得到SLA的协方差矩阵,在该矩阵的基础之上构建差分虚拟阵元的协方差矩阵进而进行DOA估计。然而,当SLA的差分虚拟阵元存在孔洞时,即差分虚拟阵元不能连续取值时,不能直接利用重构的协方差矩阵进行DOA估计,需要恢复完全增广协方差矩阵的信息再进行DOA估计。对于该问题,本文基于矢量化后原协方差矩阵和虚拟差分阵协方差矩阵的误差分布情况,并结合完全增广协方差矩阵的低秩特性和半正定特性来构建优化问题。通过求解该问题来恢复维度更高的完全增广协方差矩阵。最后对该矩阵进行奇异值分解,利用多重信号分类(Multiple Signal Classification,MUSIC)算法就可以获得多源的空间谱。本文最后通过数值仿真试验验证了所提算法可以实现高DOF的DOA估计,并且相比于现有算法,本文所提算法对欠定DOA估计的效果更好,多源DOA估计的精度更高,产生的误差更小。 展开更多
关键词 doa估计 稀疏线阵 协方差矩阵 低秩矩阵重构
下载PDF
Determination of Direction of Arrival of Seismic Wave by a Single Tri-axial Fiber Optic Geophone 被引量:1
18
作者 CHANG Tianying CUI Hongliang 《Defence Technology(防务技术)》 SCIE EI CAS 2013年第1期1-10,共10页
A fiber Bragg grating (FBG) geophone and a surface seismic wave-based algorithm for detecting the direction of arrival (DOA) are described. The operational principle of FBG geophone is introduced and illustrated with ... A fiber Bragg grating (FBG) geophone and a surface seismic wave-based algorithm for detecting the direction of arrival (DOA) are described. The operational principle of FBG geophone is introduced and illustrated with systematic experimental data, demonstrating an improved FBG geophone with many advantages over the conventional geophones. An innovative, robust, and simple algorithm is developed for obtaining the bearing information on the seismic events, such as people walking, or vehicles moving. Such DOA estimate is based on the interactions and projections of surface-propagating seismic waves generated by the moving personnel or vehicles with a single tri-axial seismic sensor based on FBGs. Of particular interest is the case when the distance between the source of the seismic wave and the detector is less than or comparable to one wavelength (less than 100 m), corresponding to near-field detection, where an effective method of DOA finding lacks. 展开更多
关键词 information processing fiber optic geophone direction of arrival (doa) tri-axial seismic wave sensing surface seismic wave
下载PDF
改进的变分稀疏贝叶斯学习离格DOA估计方法
19
作者 王绪虎 金序 +3 位作者 侯玉君 徐振华 田雨 张群飞 《振动与冲击》 EI CSCD 北大核心 2024年第13期134-143,共10页
为提高阵列信号处理运算速率,改善其方位估计性能,提出了一种改进变分稀疏贝叶斯学习离格波达方向(direction-of-arrival, DOA)估计方法。该方法利用实值变换,将向量化后的接收信号协方差矩阵转化到实数域,结合变分稀疏贝叶斯学习和网... 为提高阵列信号处理运算速率,改善其方位估计性能,提出了一种改进变分稀疏贝叶斯学习离格波达方向(direction-of-arrival, DOA)估计方法。该方法利用实值变换,将向量化后的接收信号协方差矩阵转化到实数域,结合变分稀疏贝叶斯学习和网格演化的思想,在迭代过程中使网格从初始的均匀网格自适应地演化为非均匀网格,通过网格更新和网格裂变交替迭代使演化后的网格点逐渐逼近真实信源方位。仿真结果表明,改进方法与传统压缩感知类方法相比,减小了运算量,提高了运算速率,且具有更高的方位估计精度和方位分辨能力,在少快拍和低信噪比情况下,改进方法性能提升的优势更明显。湖上试验数据处理结果进一步验证了该方法的有效性和工程实用性。 展开更多
关键词 波达方向(doa)估计 离网格模型 实值变换 网格演化 变分稀疏贝叶斯学习
下载PDF
Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning 被引量:4
20
作者 文方青 张弓 贲德 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第11期70-76,共7页
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
关键词 multiple-input multiple-output radar random arrays direction of arrival estimation sparseBayesian learning
原文传递
上一页 1 2 104 下一页 到第
使用帮助 返回顶部