基于高阶累积量的空间特征估计方法

本文以均匀直线阵为基础,提出了一种基于阵列输出四阶累积量的信号空间特征估计方法,并将其用于相干多径环境下的多用户信号空间特征的估计.该方法构造了空间特征矩阵,对其作特征分解可以得到各用户的空间特征.该方法不依赖于信号具体特征,适用于任意加性高斯噪声.理论分析和仿真结果说明了算法的有效性和稳健性.     

一种基于四阶累积量的空间特征盲估计方法

该文以均匀直线阵为基础,提出了一种基于阵列输出四阶累积量的信号空间特征盲估计方法,并将其用于相干多径环境下的多用户信号空间特征的估计。作者利用四阶累积量构造了一个空间特征估计矩阵,并证明了对该矩阵作特征分解可以得到各用户的空间特征。该盲算法不依赖于信号具体特征,适用于任意加性高斯(白或有色)噪声。理论分析和仿真结果说明了算法的有效性和稳健性。     

高分辨率宽带相干信号波达方向的高效估计

本文给出了一种用于多源宽带相干信号波达方向(DOA)估计的快速算法。它是基于信号子空间技术,通过截取中心窄带频段数据并进行空间平滑来获得对方向的高效估计。文中最后通过计算机仿真,与CSM方法进行了比较,验证了本算法的快速、高分辨率等优良性能。     

基于高阶累积量的近场通信波达方向估计算法

通过对近场通信波达方向准确估计,提高目标信源的定位能力.传统方法中对近场源通信信源的波达方向估计采用多普勒估计方法,由于近场通信的空间信源为窄带信号,多普勒估计会导致DOA估计频谱失真.提出一种基于高阶累积量的近场通信波达方向估计算法.采用均匀间隔线列阵构建近场通信的信号模型,进行近场源目标特征构建,提取近场源通信信号的斜度和峰度等特征,采用高阶累积量特征提取方法,分别求得对应近场通信信源的方位角、频率和距离三维参数,使得每个信源的参数自动配对,提高了近场通信DOA波达方向估计的效率和精度,实现近场源通信信号的波达方向估计算法改进.仿真实验结果表明,采用该方法进行近场方法波达方向估计的精度较高,对信源方位的定位准确,性能优越于传统方法,在近场通信中具有较好的应用价值.     

空间相干源信号频率和波达方向的同时估计方法

本文针对宽频段窄带相干信号源,充分利用多重信号分类和旋转不变两大技术,结合一定的时域信息,提出了一种高精度的信号频率和波达方向同时估计方法.该方法通过构造平滑波达方向矩阵进行参数估计,无需搜索过程和配对处理.计算机仿真验证了本文所提出方法的有效性.     

宽带非高斯信号的二维波达方向估计方法

该文提出了一种解决宽带非高斯信号二维波达方向估计的方法。该方法利用相干信号子空间方法把宽带的阵列频域数据四阶累积量聚焦到同一个参考频段下,然后利用基于信号空时特征结构的时空DOA 矩阵方法来进行二维DOA估计。理论上证明该方法在高斯噪声环境下对宽带非高斯信号都具有很好的估计性能,通过计算机仿真也验证了该方法的有效性。     

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。     

宽带相干源波达方向估计的新方法

相干信号子空间处理方法（ＣＳＭ）是一种通过构造聚焦（ｆｏｃｕｓｉｎｇ）矩阵来估计宽带相干源波达方向（ＤＯＡ）的有效方法。本文基于一致聚焦的概念，给出了一种可用于任意阵列的完全聚焦方法，从而极大地改善了ＤＯＡ的估计分辨率、估计精度等性能，大大降低了估计方法的信噪比阈值。文中在最后通过计算机仿真，与ＣＳＭ方法进行了比较，验证了本方法的优良性能。     

一种低复杂度的二维波达方向估计方法

提出了一种基于传播算子的低复杂度二维波达方向估计新算法,该方法避免了常规子空间方法中占主要运算量的估计信号协方差矩阵及其高维矩阵的特征分解,降低了运算复杂度,并且由于无阵列孔径损失,获得了良好的参数估计性能.最后计算机仿真验证了算法的有效性.     

宽带非高斯信号波达方向的估计方法

本文提出了一种解决宽带非高斯相干信号波达方向估计的新方法，这种方法是采用阵列频域数据四阶累积量的新颖思想，通过将各频段的四阶累积量聚焦到同一参考频段下来实现的，它不仅能获得高斯噪声环境下非高斯宽频相干信号的高分辨率方向估计，同时，对于非高斯噪声环境也具很好的估计性能，且不需要有关噪声的原始分布的先验知识，文中还通过计算机仿真实验该方法进行了性能分析，验证了方法的有效性。     

A vector space approach to direction finding in a coherent multipath environment

The superresolution methods of spatial spectrum estimation heretofore reported are known to break down when arriving signals from different directions are coherent. It is shown here that this deficiency can be overcome by replacing the direction-of-arrival (DOA) search vector ordinarily used with a linear combination of such vectors. Particular attention is here given to extending the multiple signal classification (MUSIC) method to cover such cases. A procedure for determining the proper linear combination is presented so that determination of the separate coherent signal arrival angles involves a multidimensional search in angle only. Such a search is demonstrated for coherent two-ray and three-ray multipath environments.     

Linear prediction approach to direction estimation ofcyclostationary signals in multipath environment

We investigate the estimation of the directions-of-arrival (DOA) of closely spaced narrowband cyclostationary signals in the presence of multipath propagation. By exploiting the spatial and temporal properties of most communication signals, we propose a new cyclic forward-backward linear prediction (FBLP) approach for coherent signals impinging on a uniform linear array (ULA). In the proposed algorithm, the evaluation of the cyclic array covariance matrix is avoided, and the difficulty of choosing the optimal time lag parameter is alleviated. As a result, the proposed approach has two advantages: (1) the computational load is relatively reduced, and (2) the robustness of estimation is significantly improved. The performance of the proposed approach is confirmed through numerical examples, and it is shown that this approach is superior in resolving the closely spaced coherent signals with a small length of array data and at relatively low signal-to-noise ratio (SNR)     

Feedback beamforming technique for receiving multipath coherent signals

A novel feedback beamformer is proposed for receiving multipath coherent signals. First, a subtraction-based minimum variance distortionless response beamformer is utilized to obtain an estimation of the desired signal. Then its output is fed back to the original full aperture array where a minimum mean square error (MMSE) beamformer is applied. Due to multipath-matched feature of the MMSE beamformer, the novel feedback beamformer can combine multipath signals without aperture loss. Two feedback schemes are proposed and their effectiveness is verified via simulation.     

相干多径环境下自适应阵列的性能改进

针对传统自适应波束形成算法无法抑制相干干扰的问题,引入了一种预处理技术--自适应加权空间平滑(Weighted Spatial Smoothing,WSS)算法,结合线性约束最小方差准则,可以有效地抑制相干干扰.同时,针对WSS引起的孔径损失,提出了一种对子阵进行相位补偿,利用全阵做波束形成的方法.理论分析和仿真结果表明,该方法对相干干扰的抑制能力明显优于常规均匀空间平滑(Uniform Spatial Smoothing,USS)算法,而且避免了孔径损失.     

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.     

密闭狭小环境中多径信号对码环的影响

基于提高北斗接收机在密闭狭小环境中定位效果的目的,通过建立密闭狭小环境中多径信号的数学模型,选取直视信号与6路反射信号组成的复合信号进行分析,使用归一化非相干超前减滞后幅值法对信号进行鉴相,得到密闭狭小环境中多径信号造成的码相位误差,分析误差产生的原因。提出了一种通过布置吸波材料来减小北斗多径信号造成的码相位误差的方法,使多径信号造成的码相位误差减少90%。     

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     

Estimation of directions of arrival of multipath signals in CDMAsystems

An algorithm is proposed for estimating the directions of arrival (DOAs) of multipath signals received from multiple users on the uplink of a code-division multiple-access system. The correlation matrices of the received signal before and after code-matched filtering are used to provide unique estimates even when the number of required DOAs exceeds the number of antenna array elements. This scenario is well known to cause conventional direction-finding algorithms (such as MUSIC) to fail. Both intersymbol interference (ISI) and multiple-access interference (MAI) are modeled exactly, and so the algorithm performs much better than those which model ISI and MAI as Gaussian noise     

ON TWO-DIRECTION SPATIAL SMOOTHING FOR ESTIMATION ANGLE-OF-DIRECTION OF COHERENT SIGNALS

Based on Evans'spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum number of distinguishable coherent signals(whenarray size is given)of the new method are better than those of the Evans'method.Simulationresults give a comparison between the eigenvector spectrums produced by the two methods.     

Time delay and spatial signature estimation using knownasynchronous signals

This paper considers the problem of estimating the parameters of known signals received asynchronously by an array of antennas. The parameters of primary interest are the time delays of the signals and their spatial signatures at the array. Estimates of the signal directions of arrival are also considered but are of secondary importance in this work. Maximum likelihood algorithms and more computationally efficient approximations are developed for both the case where all received signals are identical (the channel estimation/overlapping echo problem) and where they are all distinct. Conditions are also derived under which the standard matched filter approach yields consistent and statistically efficient parameter estimates. The issue of solution uniqueness is addressed, and in particular, an upper bound on the number of signals whose parameters may be uniquely identified is derived for a number of different cases. Typically, the bound is far greater than the number of sensors and is limited only by the number of data samples collected. Some representative simulation examples are also included to illustrate the algorithms' performance relative to the Cramer-Rao bound