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1.
In a previous paper, a new approach was proposed for the consistent estimation of the directions of arrival (DOA) of signals in an unknown spatially correlated noise environment using generalized correlation decomposition (GCD). Based on the various interesting properties of the eigenspace structure obtained by GCD, two effective methods (UN-MUSIC and UNCLE) of estimating the DOA in an unknown correlated noise were developed, In this paper, the performance of the two methods are analyzed. It is shown that the performance of these two methods can be optimized by assigning optimum weighting matrices in their respective criteria. Furthermore, and more importantly, it is also shown that of all the correlation decompositions, the canonical correlation decomposition (CCD) leads to the optimum performance of the methods. Computer simulations confirm these conclusions and show that the use of CCD is robust even under variable spatially correlated noise conditions  相似文献   

2.
We address the problem of maximum likelihood (ML) direction-of-arrival (DOA) estimation in unknown spatially correlated noise fields using sparse sensor arrays composed of multiple widely separated subarrays. In such arrays, intersubarray spacings are substantially larger than the signal wavelength, and therefore, sensor noises can be assumed to be uncorrelated between different subarrays. This leads to a block-diagonal structure of the noise covariance matrix which enables a substantial reduction of the number of nuisance noise parameters and ensures the identifiability of the underlying DOA estimation problem. A new deterministic ML DOA estimator is derived for this class of sparse sensor arrays. The proposed approach concentrates the ML estimation problem with respect to all nuisance parameters. In contrast to the analytic concentration used in conventional ML techniques, the implementation of the proposed estimator is based on an iterative procedure, which includes a stepwise concentration of the log-likelihood (LL) function. The proposed algorithm is shown to have a straightforward extension to the case of uncalibrated arrays with unknown sensor gains and phases. It is free of any further structural constraints or parametric model restrictions that are usually imposed on the noise covariance matrix and received signals in most existing ML-based approaches to DOA estimation in spatially correlated noise.  相似文献   

3.
蔡睿妍  杨力  钱杨 《电子与信息学报》2020,42(11):2600-2606
针对复杂电磁环境下被动无线监测定位问题,该文提出广义相关熵的概念,推导了广义相关熵的性质,用以抑制阵列输出信号中的脉冲噪声。为了实现脉冲噪声环境下相干分布源中心DOA和扩散角的联合估计,提出基于广义相关熵的DOA估计新方法,并证明了该方法的有界性。为进一步提升算法的鲁棒性,推导了一种仅依赖阵列输出信号的自适应核函数。仿真结果表明,该算法能够实现脉冲噪声环境下相干分布源参数的联合估计,相比已有算法,具有更高的估计精度和鲁棒性。  相似文献   

4.
Direction-of-arrival (DOA) estimation of multiple emitters with sensor arrays has been a hot topic in the area of signal processing during the past decades. Among the existing DOA estimation methods, the subspace-based ones have attracted a lot of research interest, mainly due to their satisfying performance in direction estimation precision and super-resolution of temporally overlapping signals. However, subspace-based DOA estimation methods usually contain procedures of covariance matrix decomposition and refined spatial searching, which are computationally much demanding and significantly deteriorate the computational efficiency of these methods. Such a drawback in heavy computational load of the subspace-based methods has further blocked the application of them in practical systems. In this paper, we follow the major process of the subspace-based methods to propose a new DOA estimation algorithm, and devote ourselves to reduce the computational load of the two procedures of covariance matrix decomposition and spatial searching, so as to improve the overall efficiency of the DOA estimation method. To achieve this goal, we first introduce the propagator method to realize fast estimation of the signal-subspace, and then establish a DOA-dependent characteristic polynomial equation (CPE) with its order equaling the number of incident signals (which is generally much smaller than that of array sensors) based on the signal-subspace estimate. The DOA estimates are finally obtained by solving the low-dimensional CPE. The computational loads of both the subspace estimation and DOA calculation procedures are thus largely reduced when compared with the corresponding procedures in traditional subspace-based DOA estimation methods, e.g., MUSIC. Theoretical analyses and numerical examples are carried out to demonstrate the predominance of the proposed method in both DOA estimation precision and computational efficiency over existing ones.  相似文献   

5.
针对基于分数低阶统计量波达方向估计方法的局限性,受相关熵概念的启发,本文提出广义类相关熵(GCAS)的概念和相应的波达方向估计新方法。计算机仿真结果表明,在Alpha稳定分布噪声环境下,本文提出的基于GCAS的MUSIC波达方向估计方法比基于分数低阶统计量的MUSIC方法在抗噪声特性和多源信号分辨特性等方面具有更好的性能。   相似文献   

6.
提出一种基于Toeplitz矩阵重构的相干信号源DOA估计算法。首先对各个阵元的接收数据与参考阵元(第一个阵元)的接收数据的相关函数进行排列,形成Hermitian Toeplitz矩阵,然后通过奇异值分解可以得到信号子空间和噪声子空间,从而实现相干信源的DOA估计。该算法在不减少阵列有效孔径的情况下,增加了可估计相干信号源数目,并在低信噪比条件下能够得到较好的估计性能,计算机仿真结果证实了算法的有效性。  相似文献   

7.
The problem of determining the number of signals in high-resolution array processing when the noise is spatially correlated (having an unknown covariance matrix) is examined. By considering a model in which two sensor arrays are well separated such that their noise outputs are uncorrelated, the authors develop a likelihood function whose maximum can be expressed in a very simple form involving the canonical correlation coefficients. This likelihood function and a choice of penalty functions constitute a number of new information theoretic criteria suitable for the determination of the number of signals in an unknown correlated noise environment. Furthermore, it is demonstrated that the new criteria are applicable in the case when only one sensor array is available  相似文献   

8.
色噪声背景下相干信源DOA估计的空间差分平滑算法   总被引:10,自引:1,他引:9       下载免费PDF全文
齐崇英  王永良  张永顺  陈辉 《电子学报》2005,33(7):1314-1318
文中提出了一种色噪声背景下相干信源波达方向(DOA)估计的新算法-空间差分平滑(SDS)算法.SDS算法利用均匀线阵协方差矩阵的Toeplitz分解特性,差分平滑运算,将非相干信源与相关(或相干)信源分开分辨,从而重复利用阵列接收数据,可分辨更多信源.SDS算法可对消空间色噪声,适用于更广泛的未知噪声背景及低信噪比环境.相比常规谱估计算法,SDS算法具有更强的信源过载能力及阵元节省能力,利用少数阵元进行迭代空间平滑运算,还可明显减小SDS算法的计算量.计算机仿真结果证明了SDS算法理论的正确性和有效性.  相似文献   

9.
陈明建  胡振彪  陈林  张超 《信号处理》2019,35(2):168-175
针对非均匀噪声背景下非相关信源与相干信源并存时波达方向(DOA)估计问题,提出了基于迭代最小二乘和空间差分平滑的混合信号DOA估计算法。首先,该算法利用迭代最小二乘方法得到噪声协方差矩阵估计,然后对数据协方差矩阵进行“去噪”处理,利用子空间旋转不变技术实现非相关信源DOA估计;其次,基于空间差分法消除非相关信号并构造新矩阵进行前后向空间平滑,利用求根MUSIC算法估计相干信源DOA。相比于传统算法,该算法能估计更多的信源数,在低信噪比情况下DOA估计性能更优越。仿真实验结果验证了该算法的有效性。   相似文献   

10.
The key of the subspace-based Direction Of Arrival (DOA) estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated, a novel approach for the estimation of DOA in unknown correlated noise fields is proposed in this paper. The approach is based on the biorthogonality between a matrix and its Moore-Penrose pseudo inverse, and made no assumption on the spatial covariance matrix of the noise. The approach exploits the structural information of a set of spatio-temporal correlation matrices, and it can give a robust and precise estimation of signal subspace, so a precise estimation of DOA is obtained. Its performances are confirmed by computer simulation results.  相似文献   

11.
The direction of arrival (DOA) estimation problem in the presence of signal and noise coupling in antenna arrays is addressed. In many applications, such as smart antenna, radar and navigation systems, the noise coupling between different antenna array elements is often neglected in the antenna modeling and thus, may significantly degrade the system performance. Utilizing the exact noise covariance matrix enables to achieve high-performance source localization by taking into account the colored properties of the array noise. The noise covariance matrix of the antenna array consists of both the external noise sources from sky, ground and interference, and the internal noise sources from amplifiers and loads. Computation of the internal noise covariance matrix is implemented using the theory of noisy linear networks combined with the method of moments (MoM). Based on this noise statistical analysis, a new four-port antenna element consisting of two orthogonal loops is proposed with enhanced source localization performance. The maximum likelihood (ML) estimator and the Cramer-Rao lower bound (CRLB) for DOA estimation in the presence of noise coupling is derived. Simulation results show that the noise coupling in antenna arrays may substantially alter the source localization performance. The performance of a mismatched ML estimator based on a model which ignores the noise coupling shows significant performance degradation due to noise coupling. These results demonstrate the importance of the noise coupling modeling in the DOA estimation algorithms.  相似文献   

12.
相干信号频率和到达角联合估计的算法   总被引:1,自引:0,他引:1  
基于均匀圆阵和四阶累积量,提出了一种相干信号频率和到达角联合估计的新算法。首先,利用计算量较小的PRO-ESPRIT算法和beamspace-ESPRIT算法分别估计广义阵列响应矢量和信号的频率。然后,对广义阵列响应矢量进行模式空间变换,并利用改进的前后向线性预测方法估计出相干信号的到达角。该算法能在色噪声环境下,精确地估计出空间相干信号的频率和到达角,并且无需平滑技术和谱峰搜索,具有计算量小,参数自动配对的特点。计算机仿真结果验证了算法的有效性。  相似文献   

13.
基于信号循环平稳特性的到达方向(DOA)估计算法在噪声成分过大或噪声本身具有循环平稳特性的情况下,性能会迅速下降,为提高算法的估计性能,提出了利用小波包去噪与广义谱相关子空间算法相结合的方法估计信号DOA,通过仿真分析证明该方法提高了估计精度,降低了估计误差,达到了与理论分析相一致的目的.  相似文献   

14.
Ye  Z. Zhang  Y. Xu  X. 《Signal Processing, IET》2009,3(5):416-429
In this paper, a novel two-dimensional direction of arrival (2-D DOA) estimation method is proposed based on a new array configuration when uncorrelated and coherent signals coexist. The DOAs of uncorrelated signals are estimated using the non-zero eigenvalues and corresponding eigenvectors of the DOA matrix (DOAM) combined with our proposed criterion. Meanwhile, we can form a new matrix without the information of uncorrelated signals. Then the coherent signals are resolved with the redefined DOAM that is constructed by the smoothed matrices of the new matrix. Simulation results demonstrate the effectiveness and efficiency of the proposed method. Other arrays that contain multiple identical central-symmetric subarrays (e.g. uniform rectangular arrays) can also be applied with our method.  相似文献   

15.
时频子空间拟合波达方向估计   总被引:10,自引:0,他引:10       下载免费PDF全文
金梁  殷勤业  李盈 《电子学报》2001,29(1):71-74
本文提出了一种基于信号空时特征结构的时频子空间拟合方法,利用双线性时频分布构造时频相关矩阵 C x代替传统的阵列相关矩阵 R x,通过 C x的特征分解实现了信号子空间与噪声子空间的分离.该方法在空域和二维时频域同时进行处理,能够区分具有不同时频特征的信号,既适用于平稳信号的场合又适用于时变、非平稳信号的情形,属于空时多维处理的范畴.可以证明,基于平稳信号假设的经典子空间方法是该方法的低维特例.由于包含了时变滤波的过程,因此该方法具有信号选择性以及抗干扰和抗噪声的能力.仿真结果证实了该方法的有效性.  相似文献   

16.
针对经典高分辨波达方位(DOA)估计方法在低信噪比下分辨性能较差的问题,该文提出一种适用于主动探测系统的基于互相关矩阵的改进多重信号分类(MUSIC)高分辨方位估计方法(I-MUSIC)。该方法首先利用主动声呐发射信号已知的特性,将发射信号与阵元接收信号进行互相关,利用互相关序列形成新的空域协方差矩阵,再进行特征分解。理论分析表明,互相关处理在抑制噪声的同时保留了阵元之间的相位信息,可以得到比MUSIC方法更准确的子空间划分,进而提高低信噪比方位估计性能。在此基础上,提出一种基于相关时间门限的改进MUSIC高分辨方位估计(T-MUSIC)方法,通过对互相关序列设置时间门限进一步提高方位估计信噪比。仿真结果表明,与MUSIC方法相比,I-MUSIC与T-MUSIC可以分别使低信噪比时的估计性能提高3 dB和6 dB,相应平均估计误差分别为原方法的77%和53%。在阵元间接收噪声存在相关性时,T-MUSIC与I-MUSIC方法相比可获得8 dB的估计增益,估计性能更优。I-MUSIC与T-MUSIC应用于多目标主动探测,可大幅提高探测系统在低信噪比下的方位估计性能。  相似文献   

17.
Direction of Arrival (DOA) estimation is one of the major tasks in array signal processing. In this paper, a new DOA estimation method is proposed using a rotational uniform linear array (RULA) consisting of omnidirectional sensors. The main contribution of the proposed method is that the number of distinguishable signals is larger than the methods in the literature with a uniform linear array consisting of the same number of omnidirectional sensors. Moreover, the new method can effectively reduce unknown spatial noises using a generalized complement projection matrix under the RULA framework. Simulations are presented to illustrate the effectiveness of the proposed method and comparison with some existing DOA estimation methods is also made.  相似文献   

18.
The direction of arrival (DOA) estimation analysis requires prior knowledge of frequency‐related information of the incident wideband signals, eg, center frequency and bandwidth, which are not available in many cases. This research is based on applications where DOA estimation of the wideband signal source is unknown, eg, in astronomy and unauthorized transmissions. Therefore, this paper has two major contributions. The first contribution is to identify the frequency spectrum of the wideband signals transmitted from an unknown source. The method use edge detection prestage to identify the frequency spectrum of the received signal. The second contribution is to estimate the DOA of the wideband signal at higher accuracy while keeping a minimum computational cost. The estimation of the DOAs was analyzed by measuring the orthogonal relationship between the signal and the noise subspaces of multiple frequency components of the sources. The introduced method utilizes subband as a reference frequency based on the extracted frequency‐related information rather than examining the complete incoming signal spectrum and exploits the spatial information of a few subbands. The introduced algorithm is implemented based on the well‐known method, test of orthogonality of projected subspaces (TOPS). Tests are conducted on a range of wideband signals with extreme values of signal‐to‐noise ratio (SNR). Considerable performance improvement is obtained.  相似文献   

19.
论文提出基于平行嵌套阵互协方差的2维(Two Dimensional, 2D)波达角(Direction Of Arrival, DOA)联合估计算法。算法基于两个互相平行的嵌套阵的互协方差生成较长虚拟阵列,同时将2维DOA估计问题降维为1维 DOA估计问题。在构造协方差矩阵时,利用方向矩阵范德蒙特性增加虚拟快拍数,保证了孔径的最小损失。最后算法基于酉旋转不变技术(Estimation of Signal Parameters via Rotational Invariance Technique, ESPRIT)和总体最小二乘(Total Least Squares, TLS)方法进一步降低噪声影响,并获得了自动配对的2维DOA估计。相比传统平行阵下的DOA估计算法,该算法拥有更好的DOA估计性能,能辨识更多的空间信源,对空间色噪声有更强的鲁棒性。仿真结果验证了算法的有效性。  相似文献   

20.
In this paper, we present a novel scheme to improve the two-dimensional (2-D) direction-of-arrival (DOA) estimation performance for narrowband signals impinging on two orthogonal uniform linear arrays (ULAs). The proposed scheme exploits the cross-correlation matrix information between subarray data to construct a stacking matrix and derive an expanded signal subspace representation through the singular value decomposition (SVD). This method enables the alleviation of the effects of additive noise. In particular, 2-D DOA estimation can be achieved by computing two rotation matrices with the same set of eigenvectors obtained by partitioning the expanded signal subspace. The pair matching procedure for elevation and azimuth angles is implemented by permutation test. Simulation results demonstrate that the proposed method performs better than the existing techniques in DOA estimation as well as the detection of successful pair matching.  相似文献   

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