Array geometry impact on music in the presence of spatially distributed sources

The MUltiple SIgnal Classification (MUSIC) estimator has been widely studied for a long time for its high resolution capability in the domain of the direction of arrival (DOA) estimation, with the sources assumed to be point. However, when the actual sources are spatially distributed with angular dispersion, the performance of the conventional MUSIC is degraded. In this paper, the impact of the array geometry on the DOA estimation of spatially distributed sources impinging on a sensor array is considered. Taking into account a coherently distributed source model, we establish closed-form expressions of the MUSIC-based DOA estimation error as a function of the positions of the array sensors in the presence of model errors due to the angular dispersion of the signal sources. The impact of the array geometry is studied and particular array designs are proposed to make DOA estimation more robust to source dispersion. The analytical results are validated by numerical simulations.¹     

基于三维交叉阵的相干分布式信号源DOA估计

研究了相干分布式信号源的二维中心波达方向估计（Direction of arrival, DOA）。利用三维交叉阵的对称特性,用求根的方法和广义ESPRIT算法分别估计出相干分布式信号源的中心俯仰角和中心方位角。所提算法无需知道相干分布式信号源的角信号分布函数,并且只需要一维谱搜索。此外,非圆信号的引入使得算法获得了更高的估计精度。计算机仿真验证了算法的有效性。     

多分量调频信号的阵列处理时频交叉项的抑制方法

在应用时频-MUSIC方法对多分量调频信号进行到达角估计的问题中,针对时频分布中交叉项的存在对估计性能的影响,提出了一种基于阵列信号处理抑制时频分布交叉项的新方法。该方法利用多信源在各阵元上的延迟对时频分布交叉项振荡相位的影响,联合运用多通道信号处理和图像处理的方法,采用二维乘法滤波,减小高频振荡交叉项在时频图像中的占据区域,从而达到抑制交叉项的目的。仿真实验显示该方法具有良好的效果。     

基于环形阵列的近场多声源波达方向跟踪

针对基于可控功率响应的多声源跟踪算法定位复杂度高,且弱声源易受强声源影响而造成无法跟踪的问题,提出了一种利用环形阵列的近场多声源波达方向跟踪方法,首先利用语音信号在时-频域的稀疏性和声源间的屏蔽效应定义了信号的相关性,并利用相关性检测主声源较强的帧,其次利用环形阵列结合SRP方法获取单帧主声源的方位角,然后集合多帧的数据从方位角的统计直方图中分析出当前声源的数目和所在方位。仿真实验结果表明,本文方法对声源数目估计的准确率为92%,且具有较高的方位角跟踪精度,其误差小于1.5?,因此可有效应用于近场环境中声源数目和方位的跟踪中。     

极化分布源模型及角度估计

通过对“分布源是在一定空间分布的多个点源信号的叠加”的分析，提出了极化分布源模型和一阶近似的极化分布源模型。对极化分布源模型，为减少噪声子空间拟合算法(NSF)的搜索空问雏数，文中提出只搜索角度空间求解到达角，对极化参数通过求解线性方程组获得；对一阶近似的极化分布源模型，利用旋转予空间不变(ESPRIT)类算法求解到达角，极化参数同样通过求解线性方程组获得。仿真结果表明：极化的引入对NSF的性能有很大提高，以及一阶近似模型对角度分布的盲性。     

一种强干扰环境下的离格稀疏贝叶斯DOA估计方法

强干扰的环境下,基于传感器阵列的波达方向(Direction of arrival,DOA)估计是阵列信号处理中的重要问题。虽然对于网格点目标现有方法的DOA估计精度较高,但对于离格点目标现有方法的DOA估计性能会严重下降。本文提出一种离格情况下的DOA估计方法,首先设计一种鲁棒的正交零陷矩阵滤波法(Robust orthogonal matrix filter with nulling,ROMFN),它结合了正交零陷滤波法(Orthogonal matrix filter with nulling,OMFN)和最差性能下的鲁棒自适应波束形成,在对离格点目标达到滤波效果的同时只需设计较少的网格点。此外,新的矩阵滤波法保留了高斯白噪声的特性,避免了噪声白化的预处理过程。其次基于离格点稀疏贝叶斯推断(Off-grid sparse Bayesian inference,OGSBI)和ROMFN,形成一种强干扰下DOA估计的新方法。与现有方法相比,仿真结果表明该方法可以在不同的网格间距、不同的信噪比和干噪比下获得更高的估计精度。     

A coherent direction of arrival estimation method using a single pulse

This paper addresses the problem of coherent direction of arrival (DOA) estimation in monostatic multi-input multi-output (MIMO) radar using a single pulse, and links the trilinear model to derive a coherent DOA estimation method. We use the received data to construct a set of Toeplitz matrices through which a trilinear model is formed, and then the trilinear decomposition is used to attain the DOAs of sources. The proposed algorithm is effective for a single pulse. Compared to the forward backward spatial smoothing estimation method of signal parameters via rotational invariance techniques (ESPRIT), the ESPRIT-like of Han, and the ESPRIT-like of Li algorithms, our method has better angle estimation performance. Numerical simulations present the effectiveness and improvement of our approach.     

Joint diagonalization DOA matrix method

A novel joint diagonalization （DOA） matrix method is proposed to estimate the two-dimensional （2-D） DOAs of uncorrelated narrowband signals. The method constructs three subarrays by exploiting the special structure of the array, thereby obtaining the 2-D DOAs of the array based on joint diagonalization directly with neither peak search nor pair matching. The new method can handle sources with common 1-D angles. Simulation results show the effectiveness of the method.     

An effective localization method for mixed far-field and near-field strictly non-circular sources

In this paper, an effective direction-of-arrival (DOA) and range estimations method for mixed far-field and near-field non-circular sources is proposed based on a large centrosymmetric uniform linear array (ULA). By exploiting the non-circularity of the sources, an extended signal is generated by concatenating the received array data and its conjugate counterparts. Then the DOAs of far-field signals are estimated based on the extended covariance matrix with the traditional MUSIC algorithm. After eliminating the far-field components from the extended signal subspace, the extended covariance matrix of the near-field signals is obtained. Thus a near-field estimator is constructed based on symmetric property of the extended array manifold where the generalized ESPRIT method is adopted to estimate the DOAs of near-field sources. Finally, the range estimator is derived using the DOA estimations of near-field sources. Simulation results are provided to validate that the proposed method has achieved a better performance than existing ones and is quite suitable for massive MIMO (multiple-input multiple-out) system.     

基于最小冗余线阵的二维DOA估计方法

针对传感器阵列二维DOA估计中阵元数较多且阵元利用率较低的问题,提出了一种低阵元冗余的二维DOA估计方法.该方法通过在最小冗余线阵基础上添加两个导向阵元的方法,将最小冗余线阵的应用拓展到二维DOA估计.同时该方法利用多个时延的阵元输出共轭循环相关函数构造"伪数据阵",在时空域中等效出两个具有旋转不变性的平行子阵,进而运用DOA矩阵法估计信号二维DOA.该方法不仅避免了最优时延选择问题,继承了DOA矩阵法无需谱峰搜索且无需二维角度参数配对等优点.还用较少的阵元获得了较大的阵列有效孔径.仿真结果表明,该方法与CCDM算法相比具有更好的低信噪比适应能力和稳健性.     

多径相干信号到达角和衰落系数的最大似然估计

针对多径相干信号到达角(DOA)和衰落系数(FC)的估计问题,在已知信号波形条件下,提出了一种联合估计DOA和衰落系数的改进最大似然估计方法。通过改进最大似然估计求极值获得DOA和衰落系数的解,在联合估计参数时,使用交替极大值技术,降低了估计算法的复杂度,并且推导了最大似然估计的Cramér-Rao界。理论分析和实验表明,该方法与现有方法相比具有更好的估计性能,当来自不同辐射源的多径信号中存在相同DOA时,仍然可以得到很好的估计效果。     

Two-Dimensional DOA Estimation of Sound Sources Based on Weighted Wiener Gain Exploiting Two-Directional Microphones

We propose a new method for estimating directions of arrival (DOAs) of sound sources, both in azimuthal and elevation angle, using two directional microphones. This method adopts weighted Wiener gain (WWG) for DOA estimation. WWG is an estimate of the Wiener gain that we proposed for use in automatic gain control to enhance speech that is degraded by additive noise. Angular resolution of WWG arises from spectral subtraction (SS)-based noise reduction involved in the WWG calculation, which enhances the signal from the look direction while suppressing signals from other directions. Because WWG involves two-channel SS, which can deal with instantaneous noise, noise sources need not to be stationary, as they must be with ordinary single-channel SS. We further propose the exploitation of a pair of directional microphones whose front directions are arranged in rotational symmetry. The time difference and amplitude difference between the two-channel signal provided by the microphones are utilized to yield a two-dimensional resolution of DOA. We evaluated the proposed method through computer simulations and compared it to three DOA estimation methods that are based on a cross-correlation function and two popular high-resolution methods of multiple signal classification and minimum variance method. Evaluation results of the source detection rate and estimation accuracy demonstrate the remarkable superiority of our method compared to the other methods in conditions where multiple speech sources exist     

一种基于压缩感知的离格阵列测向方法

基于稀疏表示的阵列测向技术中的一系列高精度鲁棒性方法都基于网格假设,即假设入射信号来向无误差地落在网格上,这一假设与现实中信号来向落在连续角度域内相违背,所造成的网格偏差效应会带来模型失配,从而导致估计性能的恶化。针对这一问题,本文提出了一种基于泰勒展开的离格类信号模型,该模型允许信号来向偏离网格,从而消除了网格误差效应,减小了估计误差。同时采用一种交替迭代优化的方法对模型进行求解,并利用奇异值分解等方法降低计算量。该方法能够有效减小网格误差,提高估计精度。仿真结果验证了所提方法的有效性。     

一种混合源环境下的波达方向估计方法

提出了一种基于均匀线阵的混合源波达方向DOA估计的新方法。该方法首先利用传统MUSIC方法估计出非相干信号源的DOA,然后对整个阵列数据协方差矩阵进行差分消除不相关源信号和噪声的影响,再对此差分矩阵进行特殊的空间平滑去相干,利用重建的数据协方差矩阵估计相干源的DOA。此方法的特点是分别估计不相关信号和相干信号的DOA,优点是在可估计出多于阵元数信号的前提下具有较高的DOA估计精度和稳健性。理论分析和仿真结果表明此方法的估计性能优于空间差分平滑算法。     

Binaural Localization Based on Weighted Wiener Gain Improved by Incremental Source Attenuation

This paper addresses the problem of direction-of-arrival (DOA) estimation both in azimuthal and elevation angle from binaural sound that is processed with a head-related transfer function (HRTF). Previously, we proposed a weighted Wiener gain (WWG) method for two-dimensional DOA estimation with two-directional microphones. However, for signals processed with HRTFs, peaks in the spatial spectra of WWG indicating true sources can mingle with spurious peaks. To resolve this situation, we propose to apply incremental source attenuation (ISA) in combination with WWG. In fact, ISA reduces spectral components originating from specified sound sources and thereby improves the localization accuracy of the next targeted source in the proposed incremental estimation procedure. We conduct computer simulations using directional microphones and four HRTF sets corresponding to four individuals. The proposed method is compared to two DOA estimation methods that are equivalent to two generalized cross-correlation functions and two high-resolution methods of multiple signal classification (MUSIC) and minimum variance method. For comparison purposes, we introduce binary coherence detection (BCD) to high-resolution methods for emphasizing valid spectral components for localization in multiple source conditions. Evaluation results demonstrate that, although MUSIC with BCD yield comparable performance to that of WWG in conditions where single speech source exists, WWG with ISA surpasses the other methods in conditions including two or three speech sources.     

Efficient and Accurate Rendering of Complex Light Sources

We present a new method for estimating the radiance function of complex area light sources. The method is based on Jensen's photon mapping algorithm. In order to capture high angular frequencies in the radiance function, we incorporate the angular domain into the density estimation. However, density estimation in position-direction space makes it necessary to find a tradeoff between the spatial and angular accuracy of the estimation. We identify the parameters which are important for this tradeoff and investigate the typical estimation errors. We show how the large data size, which is inherent to the underlying problem, can be handled. The method is applied to different automotive tail lights. It can be applied to a wide range of other real-world light sources.     

声音与震动阵列的分析、实现与应用

In this paper, we consider the analysis, implementation, and application of wideband sources using both seismic and acoustic sensors. We use the approximate maximum likelihood (AML) algorithm to perform acoustic direction of arrival (DOA). For non-uniform noise spectra, whitening filtering was applied to the received acoustic signals before the AML operation. For short-range seismic DOA applications, one method was based on eigen-decomposition of the covariance matrix and a second method was based on surface wave analysis. Two well-known optimization schemes were used to estimate the source locations from the estimated DOAs at sensors of known locations. Experimental estimation of the DOAs and resulting localizations using the acoustic and seismic signals generated by striking a heavy metal plate by a hammer were reported.     

SNR estimation algorithm based on the preamble for wireless OFDM systems

Based on the analysis of the performance of Boumard＇s SNR method for wireless orthogonal frequency division multiplexing （OFDM） systems, a new estimation algorithm of the noise variance is proposed by only using the data samples of the two training symbols in the preamble, and the second order moment of these data samples is employed to estimate the signal power. The average SNR and the SNRs on the subchannels can all be estimated by the proposed algorithm, and its performance is independent of the channel＇s frequency selectivity. Simulation results show that the performance of the proposed method is highly improved and much better than that of Boumard＇s method.     

单电磁矢量传感器DOA和极化的同时估计

针对单个电磁矢量传感器，提出基于四阶累积量的极化域虚拟ESPRIT二维波达方向(DOA)和极化参数同时估计算法。该方法借助累积量操作提取信号在极化域的旋转不变结构，并利用虚拟ESPRIT方法同时估计信号的二维DOA和极化参数，它可以分辨多个极化域可分的非高斯信号。给出的仿真结果验证了算法的可行性和有效性。     

DOA Estimation Based on Sparse Representation of the Fractional Lower Order Statistics in Impulsive Noise

This paper is mainly to deal with the problem of direction of arrival (DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as fistable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithms, the fractional lower order statistics vectors of the array output signal are sparsely represented on an overcomplete basis and the DOAs can be effectively estimated by searching the sparsest coefficients. To enhance the robustness performance of the proposed algorithms, the improved algorithms are advanced by eliminating the fractional lower order statistics of the noise from the fractional lower order statistics vector of the array output through a linear transformation. Simulation results have shown the effectiveness of the proposed methods for a wide range of highly impulsive environments.