白噪声背景下基于MUSIC算法的信号频率检测仿真

描述了在白噪声干扰下使用MUSIC算法对信号进行特征分解频率估计的原理方法,并且通过对一个正弦信号和多个正弦信号的MATLAB仿真试验结果,讨论了算法的特点并且对虚假峰的成因做出了解释。     

一种色噪声背景下信号到达角与载频联合估计的简单算法

研究在色噪声背景下实现以较小的运算量完成多个信源到达角(DOA)及载频的估计。文中结合ESPRIT(Estimating signal parametcrs via rotational invariance techniques)法和信号、噪声的特点，提出了一种仅需一次维数较低的特征值分解(EVD)便可实现两参数估计的新算法。数值模拟结果验证了算法的有效性。     

基于稀疏重构的色噪声背景下未知线谱信号估计

针对色噪声背景下的未知线谱信号估计问题,该文提出一种基于分子频带处理的稀疏重构类线谱估计方法。首先,利用多速率余弦调制滤波器组对观测信号进行子带分解,得到功率谱相对平坦的子带信号。之后,在每个子带信号上,利用基于迭代最小化的稀疏学习方法进行线谱估计,并将各子带上的线谱估计结果进行频域综合滤波以及门限判决等处理。最终得到色噪声背景下的线谱估计结果。理论推导及仿真实验表明所提方法在色噪声背景下具有较好的线谱估计性能。其能够有效地去除色噪声背景,同时保留稀疏重构类线谱估计方法所具有的高频率分辨力等优点。     

电磁矢量阵列的四元数Toeplitz矩阵重构算法

对于电磁矢量阵列的相干信源波达方向估计,针对空间平滑算法解相干时减少阵列有效孔径的问题,提出了一种四元数Toeplitz矩阵重构算法。首先,根据四元数的正交特性建立了信号接收模型,很好地保持了电磁矢量阵列的阵元输出信号两分量间的正交性,同时保证了波达方向角信息和极化信息都能包含在重构矩阵中;然后,在阵列各阵元接收数据与参考阵元接收数据的相关函数基础上,构成Hermitian Toeplitz矩阵,从而实现解相干。该算法与空间平滑算法相比增加了相干信源估计个数,且在低信噪比和入射角度接近时具有更好的估计性能,通过仿真实验得到了验证。     

信号DOA和极化信息联合估计的降维四元数MUSIC方法

基于简化电磁矢量传感器阵列,该文提出了一种新的降维四元数MUSIC估计方法。文中引用了四元数的概念,利用四元数的正交特性能够很好地描述矢量传感器阵元的正交结构这一优点,建立了电磁矢量传感器阵列的四元数模型,利用降维Q-MUSIC (Quaternion-MUSIC)方法先对极化信号DOA进行估计,通过已经估计出来的DOA信息,再借助传统的V-MUSIC (long-MUSIC)方法估计极化信息。从而依次获得极化信号的4个参数。仿真实验验证了算法的可行性。     

一种基于旋转矩阵单位四元数分解的运动估计算法

本文基于旋转矩阵单位四元数分解定理,提出一种由3D特征点空间位置估计运动参数的算法。单位四元数表示旋转矩阵时不存在奇异点,故基于单位四元数的运动估计方法具有更大的实用价值,而本文算法无需Horn(1987)和Su等人(1989)提出的单位四元数方法的迭代运算。本文给出了解的唯一性分析和模拟实验结果,可见其性能是令人满意的。     

基于降维噪声子空间的二维阵列DOA估计算法

为提高波达方向(Direction Of Arrival, DOA)的估计速度,该文基于子空间的正交性原理,利用噪声子空间及其共轭的交集进行奇异值分解(SVD)实现噪声子空间的降维,并基于降维噪声子空间与导向矢量及其共轭的双正交性提出一种2维阵列快速DOA估计算法。理论分析和仿真实验表明：该算法不受实际阵型的限制,能将传统MUSIC谱的角度范围压缩至原来的一半,从而将DOA估计的计算量降至传统方法的50%,并具有与MUSIC算法相当的角度分辨率。     

基于四元数的Root-MUSIC的双基地MIMO雷达中角度估计算法

该文将四元数理论应用到双基地集中式多输入多输出(MIMO)雷达的角度估计中。文中通过传统数据模型构造四元数矩阵,提出了基于四元数的求根-多重信号分类(Root MUltiple SIgnal Classification, Root-MUSIC)的MIMO雷达中角度估计算法,该算法通过奇异值分解和Root-MUSIC来估计出发射角(Direction Of Departure, DOD)和接收角(Direction Of Arrival, DOA)。该算法的角度估计性能远优于现有文献的方法,并且无需谱峰搜索,复杂度大大降低。仿真结果验证了算法的有效性。     

基于四元数的极化敏感阵列波束形成

四元数信号模型保持了阵元各分量之间固有的正交特性,因而针对极化敏感阵列信号处理基于四元数的方法具有比常规基于复数的长矢量方法更优的性能。将最大信号干扰噪声比准则应用于波束形成求得四元数最优权向量,进而完成了极化敏感阵列的滤波。与长矢量方法相比在具有相同的滤波性能情况下,四元数方法减少了一半的数据存储单元,降低了除法计算复杂度,从而提高了算法的处理速度。同时四元数的四维超复数正交结构提高了阵列对指向误差的稳健特性,计算机仿真结果验证了文中方法的有效性。     

色噪声下估计信源数的方法及性能分析

分析了雷达谱估计信号源数的方法.在高频地波雷达中,当各阵元噪声功率非平稳时,提出了一种基于盖氏圆半径和Kullback对称散度的信号源数目估计方法.通过实验证明,该方法能够有效解决在小快拍数、阵元噪声功率不相等情况下信号源数目估计的问题,实现色噪声环境下信源数的估计.     

基于矢量传感器阵列的信号多参数估计方法

本文提出了一种基于非均匀L形矢量传感器（Vector-Sensor,VS）阵列的横平面电磁波信号频率、二维波达方向（2-D DOA）和极化参数估计的方法.为降低系统实现复杂度,文中采用了对信号欠Nyquist采样.为了降低不同频率信号在传感器间的互耦,阵列中各VS稀疏排布,同时,空间参数的估计精度也得到相应的提高.最后通过数值仿真验证了本文算法的有效性.     

Maximum likelihood estimation for array processing in colored noise

Direction of arrival estimation of multiple sources, using a uniform linear array, in noise with unknown covariance is considered. The noise is modeled as a spatial autoregressive process with unknown parameters. Both stochastic and deterministic signal models are considered. For the random signal case, an approximate maximum likelihood estimator of the signal and noise parameters is derived. It requires numerical maximization of a compressed likelihood function over the unknown arrival angles. Analytical expressions for the MLEs of the signal covariance and the AR parameters are given. Similar results for the case of deterministic signals are also presented     

色噪声背景下的重采样信源数目估计方法

针对盖氏圆信源数目估计方法在低快拍数、低信噪比情况下性能变差的问题,设计了一套能在有色噪声中提高估计准确率的方法。首先,对接收信号样本集多次抽样,利用多个子样本集协方差矩阵的行列变换构建不同酉矩阵,然后对多个酉变换结果取平均,最后通过多次重采样循环迭代得到最优估计值。仿真结果表明,相比传统GDE的统计方法,文中提出的方法能得到更稳定、准确的估计结果,同时计算所需的接收信号快拍数目更少、信噪比更低。     

Two-dimensional DOA estimation for acoustic vector-sensor array using a successive MUSIC

This paper discusses the problem of two-dimensional (2D) direction of arrival (DOA) estimation for acoustic vector-sensor array, and derives a successive multiple signal classification (MUSIC) algorithm therein. The proposed algorithm obtains initial estimations of the azimuth and elevation angles obtained from the signal subspace, and uses successively one-dimensional local searches to achieve the joint estimation of 2D-DOA. The proposed algorithm, which requires the one-dimension local searches, can avoid the high computational cost within 2D-MUSIC algorithm. The proposed algorithm can obtain automatically-paired 2D-DOA estimation for acoustic vector-sensor array, and it has better DOA estimation performance than propagator method, estimation of signal parameters via rotational invariance technique algorithm and trilinear decomposition algorithm. Meanwhile, it has very close angle estimation to 2D-MUSIC algorithm. Furthermore, it is suitable for non-uniform linear arrays, works well for the sources with the same azimuth angle, and imposes less constraint on the sensor spacing, which does not have to be restricted within half-wavelength. We have also derived the mean-square error of DOA estimation of the proposed algorithm and the Cramer-Rao bound of DOA estimation. Simulation results verify the usefulness of the proposed algorithm.     

Bayesian detection and estimation of cisoids in colored noise

The problem of estimating the number of cisoids in colored noise is addressed. It is assumed that the noise can be modeled by an autoregression whose order has also to be estimated. A new criterion is proposed for estimating the number of cisoids and the autoregressive model order, as well as a new algorithm for estimating the cisoidal frequencies. In the derivation, a Bayesian methodology and subspace decomposition are employed. The proposed criterion significantly outperforms the popular MDL and AIC as applied in a paper by Nagesha and Kay. In addition, an algorithm that reduces the computational complexity of the solution is developed, computer simulations that demonstrate the performance of the criterion are included     

声矢量传感器阵中基于PASTd的二维DOA跟踪算法

通过研究声矢量传感器阵列中高效的运动目标到达角(DOA)跟踪算法,提出一种声矢量传感器阵列中基于紧缩投影近似子空间跟踪(PASTd)的DOA跟踪方法。该方法利用PASTd算法进行声矢量传感器任意阵的DOA跟踪,其快速收敛的特点可以降低运算复杂度。同时,其角度跟踪的均方根误差(RMSE)性能优于常用的PAST算法。仿真结果验证了该算法的有效性。     

高斯白噪声下L阵二维波达方向快速估计

针对L型阵列,提出一种在高斯白噪声环境下的二维波达方向( DOA)快速估计方法。首先利用阵列结构特点构建两个互协方差矩阵,同时实现了噪声分量的有效抑制,再依据协方差矩阵的性质构造了波达方向矩阵。对该矩阵进行一次特征分解即可分别得到包含方位角和俯仰角信息的方向矢量和方向元素,实现二维DOA估计。该算法避免了传统算法的谱峰搜索或大矩阵构造及其特征分解过程,计算量小,且参数自动配对。仿真结果表明,该算法在低性噪比和少快拍下的估计精度与2 D ESPRIT算法近似,但计算复杂度大幅降低,适用于实时性高的工程应用背景。     

Efficient 2-D DOA estimation for coherent sources with a sparse acoustic vector-sensor array

This paper proposes a computationally efficient two-dimensional (2-D) direction-of-arrival (DOA) estimation algorithm based extended-aperture for acoustic coherent signals impinging on a sparse acoustic vector-sensor array. The coherency of incident signals is decorrelated through matrix averaging and the signal/noise subspaces are reconstructed through a linear operation of a matrix formed from the cross-correlations between some sensor data, where the effect of additive noise is eliminated. Consequently, DOAs can be estimated without performing eigen-decomposition (into signal/noise subspaces), and there is no need to evaluate all correlations of the array data. The derived estimates are automatically matched by translating eigenvalues into real-valued ones, furthermore, the proposed method can achieve the unambiguous direction estimates with enhanced accuracy by setting the vector sensors to space much farther apart than a half-wavelength, and it is also suitable for the case of spatially nonuniform noise, which may be more realistic scenario for the sparsely placed sensors. The performance of the proposed method is demonstrated through numerical examples.     

全相位滤波白噪声产生有色噪声及其功率谱估计

本文提出用全相位数字滤波器这种新型滤波器滤波白噪声产生有色噪声的方法,这种方法比用传统FIR滤波器产生的有色噪声频谱泄漏少,阻带衰减功率大等优点.并且分别用Welch法和全相位法对在有色噪声中混入的双频小信号余弦波进行谱估计,实验证明全相位谱估计性能优于经典谱估计.