估计相干源到达方位角的双向空间平滑技术

本文在Evans的空间平滑预处理技术基础上,提出了双向空间平滑预处理技术,并证明了后者在去相关、孔径的有效利用率以及孔径尺寸一定时,阵列最多可分辨的相干源数目方面均优于前者。计算机仿真结果验证了上述结论。     

相干信源波达方向估计的加权空间平滑算法

提出了一种用于空间相干源DOA估计的加权空间平滑算法(WSS，weighted spatial smoothing)。常规的空间平滑算法没有利用子阵输出的互相关信息，而且对相干信源的分辨力较差。WSS算法充分利用了子阵输出的自相关信息和互相关信息，将主阵协方差矩阵的所有子阵阵元数阶的子矩阵进行加权平均，以期提高常规空间平滑算法的分辨性能。文中以加权平滑后等效的信源协方差矩阵的对角化为约束条件，推导了加权矩阵的理论表达式。计算机仿真结果表明，WSS算法与常规空间平滑算法相比具有更高的分辨性能和更低的信噪比门限。特别是在于阵划分较多时其优越性更加明显。     

Simultaneous frequency and direction estimation of coherent signals

A new method is proposed in this paper for simultaneous frequency and directionestimation of coherent signals. The method is based on the rotational invariance techniques and uses an array triplet in motion to estimate the central frequencies and azimuths of coherent signals from narrowband sources. Without searching in the space of frequency-direction, the computational efficiency of the method is improved significantly. Simulation results in the typical examples demonstrate the performance of this new method.     

On spatial smoothing for two-dimensional direction-of-arrivalestimation of coherent signals

We present an analysis of a spatial smoothing scheme extended for the estimation of two-dimensional (2-D) directions of arrival (DOAs) of coherent signals using a uniform rectangular array. The uniform rectangular array is divided into overlapping rectangular subarrays by the extended scheme, which is referred to as the 2-D spatial smoothing scheme. The analysis shows that when the extended preprocessing scheme is used in conjunction with the eigenstructure technique, the size of the subarrays should be at least (K+1)×(K+1), and the number of the subarrays must be no less than K×K in order to guarantee the “decorrelation” of κ coherent signals for all possible scenarios. The minimum size of the total uniform rectangular array is thus shown to be 2K×2K. Instead of using a uniform rectangular array, a minimal subarray structure incorporated with a minimal subarray grouping is also devised for resolving the 2-D DOAs of K coherent signals. The number of sensor elements of the minimal total array is then (K²+4K-2) instead of 4K²     

SPATIAL SPECTRUM ESTIMATION OF COHERENT SOURCES IMPINGING ON NONUNIFORM ARRAYS

The problem of bearing estimation of coherent signal impingiog on an array ofarbitrary geometry is studied.Both approaches are developed,the first one synthesizes theobserved array data into the outputs of a linear uniform array and then processes them viaconventional techniques such as spatial smoothing etc.The second approach is based on theinvariant subspace rotation operation which is equivalent to the translational displacement ofthe artay,linearly independent signal vectors are obtained thereby to span perfectly the signalsubspace.As compared with the conventional processing techniques,the approach based oninvariant subspace rotation does not lead to an effective decrease in aperture size and thereforea decrease in resolution capability.The computer simulations are conducted to demonstrate theeffectiveness of the presented approaches.     

Two-dimensional DOA estimation of coherent signals using acoustic vector sensor array

In this paper, we present two new methods for estimating two-dimensional (2-D) direction-of-arrival (DOA) of narrowband coherent (or highly correlated) signals using an L-shaped array of acoustic vector sensors. We decorrelate the coherency of the signals and reconstruct the signal subspace using cross-correlation matrix, and then the ESPRIT and propagator methods are applied to estimate the azimuth and elevation angles. The ESPRIT technique is based on the shift invariance property of array geometry and the propagator method is based on partitioning of the cross-correlation matrix. The propagator method is computationally efficient and requires only linear operations. Moreover, it does not require any eigendecomposition or singular-value decomposition as for the ESPRIT method. These two techniques are direct methods which do not require any 2-D iterative search for estimating the azimuth and the elevation angles. Simulation results are presented to demonstrate the performance of the proposed methods.     

2-D direction finding of coherent signals VIA Temporo-Spatial processing

In most wireless communication systems, two-dimensional Directions-Of-Arrival (DOA) of multipath signals need to be found for spatial selective transmission. However, it is quite difficult to find their DOAs due to the coherent nature of multipath signals and considerable computations when performing 2-D searches. In this paper, a new algorithm to estimate 2-D DOA of multiple narrow-band signals is proposed. A DOA cyclic matrix is constructed whose eigenvalues and eigenvectors can be simultaneously used to extract 2-D DOA without 2-D searches. By exploiting the temporal property of cyclostationarity, the signal detection capability is significantly improved. Besides, based on the decorrelation model for mobile terminal signals, the algorithm can be effectively extended to the coherent case without spatial smoothing and the loss of array aperture. Simulation results are given to illustrate the performance of the new algorithm.     

基于特征空间的相干干扰抑制技术

该文把多线性约束和特征空间技术相结合,提出了基于特征空间的多约束最小方差波束形成器(EM-CMVB),该波束形成器可以有效抑制相干干扰。EMCMVB是利用估计得到的相干干扰方向和阵列信号相关矩阵特征分解来得到修改的信号子空间,再把多约束最小方差波束形成器(MCMVB)的权矢量向修改的信号子空间投影来得出新的权矢量。经分析表明,EMCMVB的性能优于MCMVB的性能。最后,给出了计算机仿真结果,证实了EMCMVB的优越性。     

Improved spatial smoothing techniques for DOA estimation ofcoherent signals

In the context of coherent signal classification, spatial smoothing is necessary for the application of the eigen-based direction of arrival (DOA) estimation methods. However, the currently known spatial smoothing algorithms not only reduce the effective aperture of the array, but also do not consider the cross correlations of the subarray outputs. An improved spatial smoothing algorithm which can fully utilize the correlations of the array outputs and produce a more stable estimate of the covariance matrix is presented. Simulation results are provided to verify the theoretical prediction. The superiority of this method over the conventional methods is obvious, especially when the SOSR (subarray to overall size ratio) is small     

一种改进的极化敏感阵列解相干算法

在相干信号源情形下,常用的极化敏感阵列信号处理方法(如参数估计、波束形成等)会出现性能下降甚至失效的现象。该文在极化平滑算法的基础上提出一种改进的解相干算法,通过对各子相关矩阵选择适当的加权系数,使平滑之后的相关矩阵具有Toeplitz的形式,进而消除信号之间的相干性。该文推导了最优加权系数的表达式及最大解相干信号个数,并利用加权平滑之后的相关矩阵完成了参数估计和波束形成。计算机仿真结果表明改进的方法具有比常规极化平滑算法更优越的性能,且适用于非均匀噪声和相干噪声的情况。     

相干信号源自适应波束形成

介绍了常规自适应波束形成的一般理论,并在此基础上分析了期望信号与干扰信号相干时常规自适应波束形成失效原理,引入了空间平滑技术,给出了空间平滑技术去相干的原理和在自适应波束形成上的应用,同时给出了计算机仿真结果。     

Direction-of-arrival estimation for coherent GPS signals based on oblique projection

A new direction-of-arrival (DOA) estimation method for coherent global positioning system (GPS) signals is proposed. It is applicable to the GPS propagation environment with rich multipath, strong interferences and noise. According to the properties of oblique projection, interferences and noise are first suppressed and only the coherent GPS signals are retained by projecting the received signal onto the signal subspace. Then, the coherent GPS signals are resolved by the Toeplitz decorrelation scheme. Using the proposed method, interferences and noise can be suppressed simultaneously, and more accurate DOA estimation for coherent GPS signals can be obtained in GPS propagation environment. Simulation results demonstrate the effectiveness of the proposed method.     

Direction finding of coherent signals via spatial smoothing foruniform circular arrays

We present a preprocessing technique that in conjunction with spatial smoothing circumvents the difficulty of direction-of-arrival estimation of coherent signals in the case of uniform circular arrays. Special consideration is given to problems arising in practice, such as mutual coupling and array geometry imperfections. Simulation results illustrating the performance of this scheme in conjunction with the MUSIC method are included     

相干宽带线性调频信号的波达方向估计新方法

提出了一种相干宽带线性调频(LFM)信号的波达方向(DOA)估计新方法。该方法利用LFM信号在分数阶Fourier域上的解线调特性,构造出新的解线调域阵列数据模型,然后结合传统的矩阵重构解相干以及MUSIC算法实现相干LFM信号的DOA估计。若同时存在多组相干LFM信号入射,则首先在不同的能量聚集域上将各信号组分离,然后逐一进行各组内相干信号的DOA估计。该方法充分地挖掘了观测信号所包含的时频信息,增加了可检测的DOA数目,提高了分辨性能和抗噪声性能。此外,该方法无冗余阵元与孔径损失,且适用于任意流型阵列。仿真结果显示,在DOA估计的均方根误差(RMSE)相同时,与传统方法相比,本方法可获得8dB左右的信噪比增益。     

MODE SPACE SMOOTHING ALGORITHM TO ESTIMATE DOA OF COHERENT SIGNALS IMPINGING ON UNIFORM CIRCULAR ARRAY

A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.     

基于均分阵元的空域平滑技术研究

空间谱估计是现代信号处理研究的重要课题,对于非相干信号的DOA估计,采用MUSIC就能取得好的分辨效果,对此算法进行了简要介绍.对于广泛存在的相干信号,直接采用MUSIC则存在很大的模糊性甚至失效,为了准确地进行DOA估计,必须经过预处理解相干.针对传统的空域平滑处理,提出了均分阵元的空间平滑技术,经仿真验证,新方法可行、有效,最后分析了该方法的优势和弊端.     

电磁矢量传感器阵列相干信号源波达方向和极化参数的同时估计:空间平滑方法

研究如何利用电磁矢量传感器阵列中隐含的冗余空域信息解决多个相干极化信号源的二维波达方向(DOA)和极化参数的同时估计问题。基于整个阵列中所隐含的多个空域旋转不变结构,将组成阵列的单个或多个电磁矢量传感器单元看作一个无模糊子阵,利用空间平滑方法对阵列数据进行预处理,以恢复信号协方差矩阵的秩特性。在此基础上,利用多信号分类方法(MUSIC)和旋转不变参数估计方法(ESPRIT)完成多个相干极化信号源的二维 DOA 和极化参数的同时估计。文中还讨论了成功进行信号解相干的必要条件,并通过计算机仿真验证和比较了所给方法的有效性及其辨识能力。     

存在相干信号时的最优波束形成

本文提出一种新的存在相干信号时的最优波束形成方法。该方法首先利用估计得到的期望信号和相干信号 的方向形成变换矩阵,去掉数据中的期望信号和相干信号成分，求得不相关干扰信号的子空间以及其正交子空间，然后得到期望信号和相干信号的合成导向矢量在该正交子空间中的投影矢量，并把该投影矢量作为自适应权矢量。经理论分析表明，这种方法基本上和理论上的最优方法相同。另外，该方法可以适用于任意的阵列结构，并且对期望信号和相干信号方向估计误差具有很强的稳健性。计算机仿真结果证实了本文方法的有效性。     

用于非合作信号噪底估计的改进自回归算法

非合作接收中由于信道或接收机模拟器件的影响可能导致接收信号功率谱存在噪声基底不平坦现象,为便于划定检测门限需要先估计噪声基底再对原始功率谱进行修正.传统的非线性自回归滑动滤波算法采用固定阈值,仅适用于窄带单信号的噪底估计.改进算法通过增加调节系数实现对阈值的动态调节,并根据功率谱特征计算初始阈值和调节系数,提高了原算法的适应范围和工程实用性.仿真结果表明,改进算法对不同种类的信号具有普适性,能解决原算法无法适应的宽带多信号噪底估计.     

基于REPT变换和空间EP谱的宽带LFM 信号参数估计

演化谱估计作为研究非平稳信号的重要手段,具有许多优良的性质。将演化谱应用于参数估计和宽带阵列信号处理中,提出了Radon-EP（Evolutionary Periodogram）谱变换（REPT）估计线性调频信号参数和空间分段短时EP谱估计宽带线性调频信号到达角。仿真实验显示了算法的有效性。