Direction-of-arrival estimation using signal subspace modeling

A computationally viable algorithm for estimating the direction-of-arrival (DOA) of multiple wavefields that are incident on an array of sensors is developed. The geometry of the array is unrestricted and the incident wavefields may be generated by mixtures of incoherent and coherent emitting sources. In the approach taken, the sensor signals are modeled as a noise-contaminated linear combination of steering vectors which are functionally dependent on a set of DOA parameters. These parameters are to be chosen so that this sensor signal model is most compatible with empirically measured data (i.e., snapshot data). An iterative procedure is developed for selecting the most data compatible set of DOA parameters in both the snapshot domain and the array covariance matrix domain. Critical to the success of such iterative solution procedures is the generation of quality DOA parameters to initialize the algorithm. A sequential beamforming method for this initialization is presented. Numerical examples to illustrate the effectiveness of the proposed algorithmic approach are given     

Angle and polarization estimation in a coherent signal environment

It is shown how a uniform linear array of crossed dipoles may be used with the ESPRIT algorithm and spatial smoothing techniques to estimate the arrival directions and polarizations of incoming coherent plane waves. Some examples showing typical performance are presented. One method of smoothing can be used where it is necessary to estimate both the arrival angles and polarizations of signals. Two other methods can be used when only the arrival angles are of interest     

Analysis of Min-Norm and MUSIC with arbitrary array geometry

A nonasymptotic performance comparison is presented between the Min-Norm and MUSIC algorithms for estimating the directions of arrival of narrowband plane waves impinging on an array of sensors. The analysis is based on a finite amount of sensor data. The analysis makes the assumption of high signal-to-noise ratio (SNR), and it applies to arrays of arbitrary geometry. It is shown that Min-Norm can be expressed as a certain data-dependent weighted MUSIC algorithm, and that this relationship allows a unified performance comparison. It is also shown that the variances of the estimated directions-of-arrival from the MUSIC algorithm are always smaller than those of the Min-Norm algorithm at high SNR when both algorithms employ a numerical search procedure to obtain the estimates     

短波段内多重信号分类算法的窄带假设分析

经典空间谱估计算法的两个适用假设是远场平面波和窄带信号。文章利用7单元均匀线列阵仿真分析了短波波段内多重信号分类（MUSIC）算法的窄带假设上限带宽。可以发现：对于短波信号,50kHz的带宽所带来的测向误差不超过O．08°。这就意味着,对于短波通信信号的侦察测向完全可以采用经典空间谱估计算法,比如MUSIC算法,而不需要为窄带假设来付出代价,这便为设计高精度的短波通信实时测向系统提供了条件。     

线性极化敏感阵列的极化平滑算法及相干源参数估计

 研究了基于极化敏感阵列的相干信号参数估计问题。首先,提出一种利用均匀线性极化敏感阵列的新型极化平滑算法(ULAPSA),其能够处理更多相干信号的参数估计,且具有更小的计算量。然后,基于ULAPSA给出了波达方向（DOA）和极化参数估计的两种方法：第1种方法利用角度搜索得到信号的DOA估计,适应任何多分量的电磁矢量传感器阵列;第2种方法结合传播算子算法,无需奇异值分解和角度搜索,能够同时估计信号的DOA和极化参数。该方法适应完备的电磁矢量传感器、三偶极子或三磁环构成的矢量传感器。最后,通过仿真实验比较和分析了所提算法的性能。     

确定相干机器多噪声源位置的方法研究

提出利用均匀线阵接收的数据构造一种矩阵进行奇异值（SVD）分解,以实现对相干噪声源的方位估计。利用这种方法,通过改变阵列中心位置便可确定机器多噪声源位置。计算机模拟和声学实验证实了这种方法的可行性。     

嵌套阵列最大似然估计测向算法

针对在辐射源个数未知的条件下嵌套阵列难以估计多个辐射源角度的问题,提出了基于最大似然估计(MLE)的嵌套阵列角度估计算法。算法在嵌套阵列模型的基础上,首先通过推导阵列截获多辐射源信号的最大似然函数及其梯度,利用最速下降法估计出空域中所有潜在辐射源的角度;然后,通过多元假设检验,利用最大似然比与门限进行比较,确定出空域中所有潜在辐射源中某一时刻发射信号的活跃辐射源角度,排除其余噪声形成的虚假辐射源角度,解决了在辐射源个数未知条件下嵌套阵列对多个辐射源角度估计问题。仿真结果表明:与传统多重信号分类(MUSIC)算法相比,该算法在辐射源数目未知、存在相干信号、低信噪比(SNR)、低快拍数条件下,均具有较好的角度估计精度,并且算法形成的虚拟阵列自由度是空间平滑MUSIC算法的2倍;多元假设检验法比传统信源数目估计算法在低信噪比条件下和处理相干信号方面具有明显优势。     

运动单阵元被动合成阵列波达方向估计

 提出了一种运动单阵元被动合成阵列波达方向(DOA)估计算法。该算法基于被动合成阵列(PSA)的概念,结合空间谱估计的思想构建了运动单阵元被动合成阵列模型,通过多次不同速度合成阵列过程实现对信号DOA的无模糊估计。通过对单次匀速合成阵列过程进行分析得到,在假设信号频率已知条件下,合成阵列算法能够达到与同孔径实阵列多重信号分类（MUSIC）算法相当的DOA估计性能。仿真验证了被动合成阵列与同孔径实阵列的渐近等效性及算法的有效性。     

An Algebraic Approach to Superresolution Array Processing

In a recent paper we made an algebraic characterization of the problem of resolving closely spaced plane waves incident on a linear array. The characterization encompassing several superresolution processing methods and encompassed the Wiener, maximum likelihood, and Pisarenko methods as well as suggesting new procedures. In this paper we amplify the algebraic approach and extend the results to consider correlated noise. An adaptive algorithm is given for a particularly effective processing method.     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Further study of the Pencil-MUSIC algorithm

For finding 2-D angles and polarizations of waves arriving at a rectangular array of crossed dipoles, the Pencil-MUSIC method can achieve the near optimum performance with much less computational burden than the MUSIC (multiple signal classification). Following an angle-only ESPRIT (estimation of signal parameters via rotational invariance techniques) method, an angle-only Pencil-MUSIC can be easily formulated which is far more accurate than the former especially in the coherent case. The angle-only Pencil-MUSIC is analyzed and compared with the original Pencil-MUSIC. The new version sacrifices the polarization estimation to achieve about 8 times more efficient computation The accuracy of the new version seems no more than 4 times worse in terms of estimation deviation     

四阶累积量MUSIC算法及其在谐波提取中的应用

MUSIC方法具有很好的分辨性能,而四阶累积量具有良好的盲噪声特性,将四阶累积量与MUSIC方法相结合,将能够很好的应用于诸如动态目标回波谐波特征等微弱信号的提取.文中简要说明了四阶累积量MUSIC算法的构造方法,以及为了降低算法的估计方差而进行的Toeplitz化预处理方法,详细讨论了谐波个数与谐波振幅对算法分辨性能的影响,认为对于有限的采样数,在一定的信噪比下,谐波数目和谐波振幅对算法的性能存在着一定的影响.文中应用四阶累积量MUSIC算法对某运动目标的实测回波进行计算,得到了目标回波真实的谐波构造特征,计算结果与目标的运动特性一致.     

High-resolution multiple target angle tracking

An approach to high-resolution multiple-target-angle tracking that uses the output of an array of sensors is presented. The results of direction-of-arrival estimation by eigenstructure analysis are extended to derive a recursive procedure for tracking moving sources. This procedure involves recursive eigenvalue decomposition and a zero-tracking algorithm, using the coefficient derived from the minimum-norm criterion. The algorithm has superresolution capability in that a pair of closely spaced target angles can be resolved and tracked even though the angular separation between them is less than the reciprocal of the aperture size. Simulation results verify that the algorithm works well in tracking multiple-target sources     

一种联合估计的有源校正高精度测向算法

针对存在系统误差的阵列模型,提出了一种有源标校下的联合估计测向算法。该算法把误差矩阵估计转化为误差系数估计,并采用到达角精确已知的源信号进行标校,在此基础上使用最小二乘法联合估计幅相不一致误差系数和互耦误差系数,最后使用结合误差矩阵的MUSIC算法测量信号的到达角。仿真表明,该算法仅需要3个标校源,其精度相比于无阵列误差情况下降0.05°,具有较好的工程可实现性。     

An intelligent algorithm for coherent sound source localization based on a strong tracking filter

Background noise is inevitable when sensor arrays are used for aeroacoustic measurements in wind tunnels. The direct removal of background noise, however, would affect the measurement accuracy. In particular, the existing array signal processing algorithms are either invalid or inefficient for removing the noise that is coherent with the signal of interest. In this paper, an intelligent algorithm is developed to localize the coherent sound sources and background noise in real time by iteratively checking the collected data from the array. The proposed method can automatically adjust the suboptimal fading factor to extract useful information as much as possible in residual sequence. This algorithm is tested in simulations and then demonstrated in an experiment.Compared to the two existing methods, the results indicate that the new method has a good phase-shift tracking ability and rapid estimation-error convergence speed, and can achieve an acceptable performance even for low-cost acoustic sensors. Overall, the proposed method should assist array beamforming and hence benefit aeroacoustic measurement.     

Analysis of a Signal Processor for an Antenna Array

A signal processor that provides ratio-squared predetection combining, has been investigated for application in an adaptive antenna array. The analysis and experimental data presented here pertain to the signal processing gain when the antenna array is illuminated by a coherent signal source and a partially coherent noise source. For a noise source which is coherent, the processing gain depends on relative strength of the signal and noise, relative directions of arrival, and the usual "array factor." The array exhibits capturing effects much as in an FM receiver. The effective antenna pattern is a superposition of two beams of different magnitudes, one directed to the signal source and the other to the noise source. When the noise is partially coherent, the behavior of the signal processor is quite complex. Analytical prediction and experimental simulation measurement on a four-channel system indicate that the partially coherent noise may be regarded as the source of an incoherent noise component plus a coherent noise component with the magnitude of the latter determined by the coherence coefficient for the noise source.     

大型客机前起落架气动噪声源三维阵列识别技术研究

起落架噪声作为现代大型飞机机体噪声在起降阶段的主要贡献成分,其噪声机理较为复杂,涉及到钝体湍流涡脱落噪声、腔体部件空腔噪声以及起落架舱腔体与支柱柱体之间的非线性耦合噪声。由于起落架中存在复杂的三维流场以及声波的反射和绕射会产生噪声,而二维麦克风阵列在垂向的分辨率较差,无法获得声源完整且准确的三维空间分布信息,因此采用三维麦克风阵列技术对起落架噪声进行研究。使用3D Beamforming算法(波束成形算法)和3D CLEAN-SC算法(空间相干的洁净算法)结合同步测量和非同步测量的方式实现了对模拟信号和实际测量数据所得频谱中特定的离散声进行声源识别定位,并在北航D5低速风洞进行开口段气动噪声实验,以1/2缩比的LAGOON起落架为研究对象,在过顶和流向方向布置两组平面阵列,构成三维阵列进行同步和非同步的噪声测量,确定了起落架中主要噪声源的位置,对认知噪声机理提供了新的借鉴和思考。     

面向高轨目标的强度相干成像技术研究

强度相干成像技术是指利用地基强度相干阵列测量空间目标光强随机涨落的相干性,可获得目标的空间频谱模值,结合目标先验信息即可恢复目标光强分布图像.这种成像方法具有成像分辨力高、设备精度要求低、受大气湍流影响小等优点,目前已应用于恒星目标的成像观测领域,是一种有发展前景的地基光学成像手段.在综述强度相干技术原理与发展历程基础上,分析了利用强度相干阵列对高轨目标成像的可行性,认为在利用强度相干阵列对高轨目标成像过程中,主要存在空间频谱探测信噪比低和相位恢复复杂2大难题,提出利用激光主动照明对目标进行探测,同时采用符合计数方法和正则化优化方法可提高探测信噪比与相位恢复质量,对实现高轨目标成像有一定参考.     

存在阵列模型误差情况下的宽带DOA估计

 针对工程应用中存在阵列模型误差的任意形状天线阵列的宽带波达方向（DOA）估计问题,提出一种基于信号分离的相关域宽带松弛（RELAX）算法。此算法利用具有记忆与遗忘特征的矩阵算子的投影机理对入射信号进行有效的分离,因此对一定范围内的阵列模型误差较之基于子空间理论的传统宽带测向算法具有较好的鲁棒性与良好的工程应用前景。分析并证明了此算法的信号分离机理及此算法对阵列模型误差稳健的原理。理论分析与仿真结果均表明存在阵列模型误差时此算法宽带DOA估计的有效性和稳健性。     

北斗B1 QPSK调制信号的高灵敏度捕获算法

卫星信号在复杂环境中功率存在衰减,导致其低于接收机正常捕获范围,给信号捕获带来较大困难。在分析北斗B1频点信号体制及研究码并行捕获算法基础上,提出了针对北斗B1 QPSK调制信号的双通道并行搜索捕获算法,设计了优化的相干、非相干码并行捕获算法,解决了信噪比较低环境中北斗卫星信号捕获困难的问题。利用卫星信号模拟器产生的仿真信号对双通道并行捕获算法和相干、非相干累加捕获算法进行验证与分析,结果表明,前者性能明显优于单通道捕获,后者较普通捕获算法具有更理想的捕获灵敏度。