A novel direction-of-arrival estimation method for wideband signals

A simple and novel direction-of-arrival (DOA) estimation method for wideband signals is proposed. The proposed method estimates DOAs according to a covariance matrix which is constructed by summing up the covariance matrices of various frequency bins. It provides a lower computation complexity and a better performance compared to the traditional wideband DOA methods. This new idea is inspired by the concept of focusing transformation, and its validity is theoretically proved. A technique to determine an optimal focusing frequency is also introduced. Finally, simulation results demonstrate the effectiveness of the method.     

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。     

宽带信号源个数估计频域bootstrap方法

针对宽带和非平稳信号,在未知信源类型及其它任何统计特性条件下,基于bootstrap方法,利用样本频域协方差矩阵的特征值特性,结合多假设检验过程,提出一种新的信源个数估计方法.理论分析和仿真实验表明该算法的有效性.     

JTIDS信号阵列高分辨测向仿真

提出了一种对JTIDS信号的高精度测向方法。首先详细分析了JTI DS信号的传输特点,利用Matlab生成的JTIDS信号,然后依据空间谱估计中MUSIC测向算法的 特点,将接收到的JTIDS信号按照脉冲分段,对单个脉冲所携带的数据进行处理,最后通过 仿真得到不同信噪比环境下多个JTIDS信号方位角和俯仰角的估计精度,验证了该方法的有 效性。     

一种新的宽带信号DOA估计算法

本文针对均匀线性阵列,在正交投影子空间(TOPS)算法的基础上,提出了一种新的宽带非相关和相干信号的DOA估计算法。首先,利用TOPS算法直接估计出宽带非相关信号的DOA;其次,在各个频率点,使用空间差分技术消除非相关信号和噪声的分量,并构造新矩阵;最后,对新矩阵进行空间平滑操作,再利用TOPS算法估计出宽带相干信号的DOA。由于分开估计宽带非相关信号和相干信号的DOA,算法适用于信号个数多于阵元个数的场合。计算机仿真结果证明了算法的有效性。     

宽带循环平稳信号的二维空间谱估计

本文提出了一种新的宽带二维波达方向估计方法。理论分析表明,该方法不需要进行二维搜索,既适用于宽带信号,也适用于窄带信号,且能够实现二维参数的自动配对。通过利用循环平稳特性,该方法能够抑制宽带干扰和加性噪声的影响,从而大大提高了算法的信号检测能力。     

波达方向估计中的宽带信号个数检测新方法

在进行波达方向估计时,往往要对信号个数进行判断,传统的宽带信号个数检测方法需要在每个频点上进行多次采样,否则无法正确完成测向.针对此问题,提出了一种基于Bootstrap准则实现的宽带信号个数检测新方法.将宽带信号划分为若干个互不重叠的子带部分,之后对每个子带信号进行特征分解,利用特征值对相应的特征向量进行加权,再通过Bootstrap准则构造新的信号重采样矩阵,用聚类的方法判断出该子带上的信号个数,最后将各个子带上的结果进行综合判断出宽带信号个数.所提方法回避了聚焦的过程,且在非高斯噪声背景下也有较高的估计成功概率,尤其是在小快拍数下有着较好的估计性能,仿真结果证明了该方法的性能.     

A novel compressed sensing ultra‐wideband channel estimation method based on non‐convex optimization

Due to the low power spectral density and complicated transfer propagation of ultra‐wideband (UWB) signal, it is important to estimate UWB channel accurately. But it is difficult to sample UWB signals directly due to their wider band width. However, compressed sensing (CS) theory provides a feasible way through lower sampling speed. Common CS‐UWB channel estimation methods adopt convex optimization, non‐sparse or non‐restricted form. In order to strengthen the restriction on sparsity of the reconstructed channel vector, a non‐convex optimization method is proposed in this paper to estimate UWB channel. Proposed method sets the objective function as a non‐convex optimization model using l_p–norm. This model is combined as a convex function to approximate the objective function and reconstruct the UWB channel vector iteratively. Because l_p–norm is closer to l₀–norm than l₁ and l₂–norm, its restriction on sparsity of objective vector is stricter. The simulation results show that this method can enhance reconstruction performance compared with existing CS‐UWB channel estimation methods. Copyright © 2013 John Wiley & Sons, Ltd.     

宽带信号DOA估计处理方法研究

从频域上建立宽带阵列接收信号的模型,引出了2种宽带阵列信号处理的研究方法:非相干信号的处理方法(ISM)和相干信号子空间算法(CSM)。并利用MATLAB仿真软件,模拟远场、等功率、平稳的第三代移动通信手机信号,对2种算法性能进行对比。仿真结果表明,CSM算法相对ISM算法虽然加大了运算复杂度,但是能够更有效分辨出宽带相干信号。     

基于MP分解的宽带LFM信号参数估计

将MP分解应用于宽带阵列信号处理中,提出一种针对线性调频信号(LFM)参数估计新算法.根据LFM信号形式建立过完备原子库Gf,其中原子参数由起始频率和调频斜率决定,将阵列参考阵元接收数据在Gf上作MP分解,获得各个信号的起始频率和调频斜率参数,从而得到宽带信号的具体形式;在上一步频率参数估计的基础上,根据阵列结构建立过完备原子库Gθ,其中原子参数由到达角决定,将阵列全部阵元接收数据在Gθ上作MP分解,实现信号DOA估计.新算法估计性能优于传统空间时频分布(STFD)方法,尤其在低信噪比、多信源情况下仍然有较高的估计精度.计算机仿真结果验证了算法的有效性.     

基于尺度变换的宽带线性调频信号时差/尺度差估计算法

提出了一种基于尺度变换的宽带线性调频信号时差和尺度差的快速算法.根据两路接收到的线性调频信号间调频率之比为尺度差的平方的特点,利用分数阶傅里叶变换分别估计出两路信号的调频率,即可获得尺度差的估计.将估计的尺度差对一路信号进行伸缩,并计算伸缩后信号与另一接收信号的时域相关,根据相关峰的位置估计出时差.相比于传统基于宽带互模糊函数的方法,该方法避免了二维搜索宽带互模糊函数的峰值,只需若干次快速傅里叶变换即可实现,能够显著降低运算量.仿真结果显示该方法在高信噪比下逐渐接近克拉美-罗下界.     

Compressive sensing for ultra‐wideband channel estimation: on the sparsity assumption of ultra‐wideband channels

Due to the sparse structure of ultra‐wideband (UWB) multipath channels, there has been a considerable amount of interest in applying the compressive sensing (CS) theory to UWB channel estimation. The main consideration of the related studies is to propose different implementations of the CS theory for the estimation of UWB channels, which are assumed to be sparse. In this study, we investigate the suitability of standardized UWB channel models to be used with the CS theory. In other words, we question the sparsity assumption of realistic UWB multipath channels. For that, we particularly investigate the effects of IEEE 802.15.4a UWB channel models and the selection of channel resolution both on channel estimation and system performances from a practical implementation point of view. In addition, we compare the channel estimation performance with the Cramer‐Rao lower bound for various channel models and number of measurements. The study shows that although UWB channel models for residential environments (e.g., channel models CM1 and CM2) exhibit a sparse structure yielding a reasonable channel estimation performance, channel models for industrial environments (e.g., CM8) may not be treated as having a sparse structure due to multipaths arriving densely. Furthermore, it is shown that the sparsity increased by channel resolution can improve the channel estimation performance significantly at the expense of increased receiver processing. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive beamspace focusing for direction of arrival estimation of wideband signals

In this paper, we present an adaptive beamspace focusing technique for the direction of arrival (DOA) estimation of wideband signals. The proposed focusing scheme can perform coherent signal subspace transformation in the beamspace domain without preliminary DOA estimation or iteration. It can maintain low focusing error over a predefined sector-of-interest in the field-of-view (FOV) of the array while adaptively suppressing out-of-sector sources. The beamspace gain outside the sector-of-interest is controlled via additional constraints that provide robustness against moving or suddenly appearing out-of-sector sources. We formulate the adaptive beamspace design problem as a second-order cone program (SOCP) that can be solved efficiently using interior point methods. Numerical simulations are presented showing the superior performance of our approach compared to classical non-adaptive beamspace focusing techniques.     

MUSIC算法的DoA估计时间分析

在基于波束赋形(Beamforming)的无线通信系统中,使用MUSIC算法的波达方向(Direction of Arrival,DOA)估计具有良好的性能。但是,对于MUSIC算法在低信噪比下Do A估计时间和精度之间的关系,却一直未有深入研究。因此,对均匀圆阵数学模型和MUSIC算法进行分析,研究样本数量与DOA估计精度的关系。仿真结果表明,在低信噪比下,DOA估计性能下降,通过增加估计协方差矩阵的样本数量,可以提高MUSIC算法的性能。根据仿真结果,拟合发现DOA估计角度分辨率达到1度,所需样本数量和信噪比的关系服从负指数分布。     

多径传播条件下宽带线性调频信号波达方向估计方法

针对信号出现多径传播情况时现有宽带信号波达方向（direction of arrival, DOA）估计方法性能下降的问题,提出了一种多径传播条件下宽带线性调频（chirp）信号波达方向估计方法,该方法将导向有效投影（steered effective projection, STEP）技术与宽带线性调频信号的时频特性相结合,对具有不同时频特性的信号分量进行分离,逐个处理,并以时频分布矩阵代替传统的协方差矩阵,从而构造有效噪声子空间,实现时域角度估计。本方法无需进行信号聚焦操作,因此理论上不受聚焦误差的影响。仿真结果验证了所提方法的有效性。      

Mixing matrix estimation method for dual‐channel time‐frequency overlapped signals based on interval probability

For dual‐channel time‐frequency (TF) overlapped signals with low sparsity in underdetermined blind source separation (UBSS), this paper proposes an effective method based on interval probability to estimate and expand the types of mixing matrices. First, the detection of TF single‐source points (TF‐SSP) is used to improve the TF sparsity of each source. For more distinguishability, as the ratios of the coefficients from different columns of the mixing matrix are close, a local peak‐detection mechanism based on interval probability (LPIP) is proposed. LPIP utilizes uniform subintervals to optimize and classify the TF coefficient ratios of the detected TF‐SSP effectively in the case of a high level of TF overlap among sources and reduces the TF interference points and redundant signal features greatly to enhance the estimation accuracy. The simulation results show that under both noiseless and noisy cases, the proposed method performs better than the selected mainstream traditional methods, has good robustness, and has low algorithm complexity.     

基于Lanczos算法的宽带相关信号DOA快速估计

本文提出了一种新的宽带信号DOA(Direction of Arrival)快速估计方法。该方法既不需要对阵列观测输出进行“聚焦”变换,也不需要对阵列输出的协方差矩阵进行特征值分解,从而使得该方法运算量比常用的宽带空间谱估计方法要小很多。计算机仿真试验证实了方法的有效性。     

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。     

基于Toeplitz矩阵重构算法的宽带相干信号方位估计

根据天线阵列接收到的数据,提出了一种基于Toeplitz矩阵重构的宽带相干源方位估计算法.该算法先由Toeplitz 阵列接收到的数据得到包含波达方向信息的协方差矩阵,再对该协方差矩阵进行聚焦处理,得到同一频率的阵列协方差矩阵,最后由高分辨子空间处理方法得到宽带相干信号的波达方向估计.仿真实验证明了该方法的有效性.     

基于一致聚焦的宽带信号波达方向估计

MTLS聚焦需要预估计波达方向,预估计偏差会影响聚焦效果,严重时会导致CSM算法失效。基于AMI思想构造了CMTLS一致聚焦变换,该聚焦变换无需预估计波达方向,提高了聚焦性能的同时,增强了算法的实时性。