基于两维空变滤波的PFA波前弯曲误差补偿

极坐标格式算法(PFA)因受波前弯曲误差的影响,其有效成像场景范围受到一定的限制。采用图像域的空变滤波(SVPF)处理可以有效补偿波前弯曲误差,但为了简化分析,已有SVPF方法在补偿过程中都采取了一定的近似,在对大场景进行高分辨率成像时仍然不能满足聚焦精度要求。对PFA的极坐标格式转换给出了一种新的解析解释,利用该解释推导得到了精确的波前弯曲误差表达式;基于该波前弯曲误差模型,提出了一种基于两维SVPF处理的波前弯曲误差补偿方法。最后通过仿真数据处理验证了该算法的有效性。     

非理想均匀圆阵的波达方向和多普勒频率联合估计

针对均匀圆阵存在一般阵列误差 (如阵元的幅相误差和安装位置误差等 )的情况 ,提出了多个信号的波达方向和多普勒频率估计方法。直接利用均匀圆阵的阵列流形 ,采用波达矩阵法估计各个信号的多普勒频率。由一般阵列误差的统计特性构造加权矩阵 ,采用加权总体最小二乘法估计各个信号的波达方向。此方法具有鲁棒性强等特点。计算机仿真证明了此方法的有效性     

基于均匀圆阵的信号二维方向角高精度估计

基于均匀圆阵(UCA),提出一种信号二维方向角的高精度估计方法。首先,充分利用了信号的空、时域信息,构造时空旋转矩阵,从而达到多个信源分离的目的。其次,直接利用UCA的阵列流形,采用最小二乘法估计信号二维方向角。最后,给出解相位整周期性模糊的方法。计算机仿真表明了此方法具有估计精度高,对阵元的幅相误差鲁棒性强等特点。     

Acoustic node calibration using a moving source

Acoustic nodes, each containing an array of microphones, can track targets in x-y space from their received acoustic signals, if the node positions and orientations are known exactly. However, it is not always possible to deploy the nodes precisely, so a calibration phase is needed to estimate the position and the orientation of each node before doing any tracking or localization. An acoustic node can be calibrated from sources of opportunity such as beacons or a moving source. We derive and compare several calibration methods for the case where the node can hear a moving source whose position can be reported back to the node. Since calibration from a moving source is, in effect, the dual of a tracking problem; methods derived for acoustic target trackers are used to obtain robust and high resolution acoustic calibration processes. For example, two direction-of-arrival-based calibration methods can be formulated based on combining angle estimates, geometry, and the motion dynamics of the moving source. In addition, a maximum likelihood (ML) solution is presented using a narrowband acoustic observation model, along with a Newton-based search algorithm that speeds up the calculation the likelihood surface. The Cramer-Rao lower bound (CRLB) on the node position estimates is also derived to show that the effect of position errors for the moving source on the estimated node position is much less severe than the variance in angle estimates from the microphone array. The performance of the calibration algorithms is demonstrated on synthetic and field data.     

Tracking of conventional beamforming with hydrophone array ofvarying geometry

In conventional beamformers of a large towed hydrophone array of fixed linear array geometry the sensors may be displaced from their nominal positions due to various kinds of force on the array. The displacements are usually time varying and can severely degrade the performance of the beamformer. This problem is approached by restoring the sensor output signals before beamforming by adaptively tracking and compensating for the displacements. This approach does not require modifications of the conventional shipboard beamformer and hence can be used cost-effectively to upgrade existing conventional systems. Two adaptive algorithms are used for two different cases: known sensor moving trajectories and unknown trajectories with relatively small displacements compared with the intersensor spacing. Tracking performance of the algorithms is analyzed. Simulation results show that for known sensor trajectories the algorithm significantly improves the performance of the conventional shipboard beamformer whereas only limited improvement can be achieved when the trajectories are unknown     

基于外辐射源直达波的对消及仿真研究

利用外辐射源（如调频广播、电视、GPS等的发射信号）的无源雷达探测技术一直是国内外研究的热点。在目标检测上,直达波信号的干扰不但对通道的动态范围提出了极高的要求,同时对微弱目标回波的检测构成了限制。文中利用二元阵的方法对直达波的干扰进行抑制,并对其对消性能进行了仿真分析和研究。     

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。     

Joint calibration algorithm for gain-phase and mutual coupling errors in uniform linear array

The effect of gain-phase perturbations and mutual coupling significantly degrades the performance of digital array radar (DAR). This paper investigates array calibration problems in the scenario where the true locations of auxiliary sources deviate from nominal values but the angle intervals are known. A practical algorithm is proposed to jointly calibrate gain-phase errors and mutual coupling errors. Firstly, a simplified model of the distortion matrix is developed based on its special structure in uniform linear array (ULA). Then the model is employed to derive the precise locations of the auxiliary sources by one-dimension search. Finally, the least-squares estimation of the distortion matrix is obtained. The algorithm has the potential of achieving considerable improvement in calibration accuracy due to the reduction of unknown parameters. In addition, the algorithm is feasible for practical applications, since it requires only one auxiliary source with the help of rotation platforms. Simulation results demonstrate the validity, robustness and high per-formance of the proposed algorithm. Experiments were carried out using an S-band DAR test-bed. The results of measured data show that the proposed algorithm is practical and effective in appli-cation.     

Localization performance of arrays subject to phase errors

The passive localisation of radiating sources using an array subject to random perturbations in sensor phases is presented. All source signals as well as additive noises observed at the sensors are assumed to be independent identically distributed zero-mean Gaussian random processes. Cramer-Rao bounds are derived for source bearings and ranges for the phase errors at each sensor. It is shown that accurate phase calibration can be achieved when the number of sources exceeds a certain minimum. The locations of the calibrating sources need not be known a priori and need only satisfy mild regularity conditions. A calibration procedure is proposed which uses maximum-likelihood techniques     

基于空域稀疏性的宽带DOA估计

利用宽带阵列接收信号的空域稀疏性,将宽带信号的波达方向(DOA)估计转化为一个稀疏信号重构的问题,提出了一种新的宽带信号DOA估计算法。该算法将宽带信号分解为多个子带信号,联合利用多个子带信号的空域稀疏性进行重构。它是对用于稀疏重构的标准的稀疏贝叶斯学习算法的推广,可适用于多冗余字典的信号模型。另外,通过对多快拍的阵列接收信号进行奇异值分解(SVD),提取信号子空间作为算法的输入数据,可以在有效减少运算复杂度的同时,提高对噪声的稳健性。与传统的宽带阵列DOA估计方法相比,该算法能够用于低信噪比、快拍有限和信源相关性较高的场合,同时算法的性能对信源个数的估计值不太敏感。仿真实验表明,该算法相对现有的基于子空间类的方法,具有更好的DOA估计性能。     

非均匀温度场下声发射源定位方法

针对非均匀温度场下声发射信号传播速度不一致导致时差定位法定位精度下降的问题,研究基于波束形成法的声发射源定位效果.首先,基于板波理论研究声发射信号的传播特性,分析频散现象等对声发射信号速度测试的影响;然后通过数值仿真研究声发射波束形成法定位精度对不同重建速度的定位效果,进而发现在声发射波束形成法在阵列方向具有速度不敏感性.在加热前后的薄钢板上进行断铅定位实验,其结果表明声发射波束形成法可以在非均匀温度场中保持较高的定位精度,在机匣温度不均的航空发动机碰摩定位领域有良好的应用前景.      

General direction-of-arrival estimation: a signal subspace approach

A high-resolution algorithm is presented for resolving multiple incoherent and coherent plane waves that are incident on an array of sensors. The incident sources can be a mixture of narrowband and broadband sources, and, the geometry of the array is unrestricted. The algorithm makes use of a fundamental property possessed by those eigenvectors of the array spectral density matrix that are associated with eigenvalues that are larger than the sensor noise level. Specifically, it is shown that these eigenvectors can each be represented as linear combinations of the steering vectors identifying the incident plane waves. This property is then used to solve the important special cases of incoherent sources incident on a general array and coherent sources incident on an equispaced linear array. Simulation results are presented to illustrate the high-resolution performance achieved with this approach relative to that obtained with MUSIC and spatial smoothed MUSIC in which the coherent-signal-subspace focusing method is used     

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     

Moving target detection via airborne HRR phased array radar

We study moving target detection in the presence of temporally and spatially correlated ground clutter for airborne high range resolution (HRR) phased array radar. We divide the HRR range profiles into large range segments to avoid the range migration problems that occur in the HRR radar data. Since each range segment contains a sequence of HRR range bins, no information is lost due to the division and hence no loss of resolution occurs. We show how to use a vector autoregressive (VAR) filtering technique to suppress the ground clutter. Then a moving target detector based on a generalized likelihood ratio test (GLRT) detection strategy is derived. The detection threshold is determined according to the desired false alarm rate, which is made possible via an asymptotic statistical analysis. After the target Doppler frequency and spatial signature vectors are estimated from the VAR-filtered data as if a target were present, a simple detection variable is computed and compared with the detection threshold to render a decision on the presence of a target. Numerical results are provided to demonstrate the performance of the proposed moving target detection algorithm     

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.     

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。     

IBEX Backgrounds and Signal-to-Noise Ratio

The Interstellar Boundary Explorer (IBEX) mission will provide maps of energetic neutral atoms (ENAs) originating from the boundary region of our heliosphere. On IBEX there are two sensors, IBEX-Lo and IBEX-Hi, covering the energy ranges from 10 to 2000 eV and from 300 to 6000 eV, respectively. The expected ENA signals at 1 AU are low, therefore both sensors feature large geometric factors. In addition, special attention has to be paid to the various sources of background that may interfere with our measurement. Because IBEX orbits the Earth, ion, electron, and ENA populations of the Earth’s magnetosphere are prime background sources. Another potential background source is the magnetosheath and the solar wind plasma when the spacecraft is outside the magnetosphere. UV light from the night sky and the geocorona have to be considered as background sources as well. Finally background sources within each of the sensors must be examined.     

一种改进的声反卷积相关声源定位方法

基于传声器阵列的声源定位算法的性能优劣决定了气动噪声试验检测中气动噪声源定位成像的准确性。为了提高相关声源定位方法的稳健性和准确性，提出一种改进的声反卷积相关声源定位方法——D-MACS（Developed-Mapping of Acoustic Correlated Sources）方法。该方法的特点是：在传统MACS方法的基础上，将声反卷积模型进行改进，使模型体现出声场空间扫描点声压互谱矩阵与互谱波束形成输出矩阵之间的数学关系，其最终获得的声源定位结果，能够提高MACS方法声源定位辨识的稳健性和准确性。通过仿真信号研究和声学风洞环境中的声源定位试验研究，比较了DAS（Delay And Sum beamformming）、DAMAS-C（Deconvolution Approach for the Mapping of Acoustic Correlated Sources）、MACS和D-MACS这4种方法的声源定位性能，验证了D-MACS方法在声源定位性能上的优势。     

DOA and steering vector estimation using a partially calibratedarray

We consider the problem of estimating directions of arrival (DOAs) using an array of sensors, where some of the sensors are perfectly calibrated, while others are uncalibrated. We identify a cost function whose minimizer is a statistically consistent and efficient estimator of the unknown parameters-the DOAs and the gains and phases of the uncalibrated sensors. Next we present an iterative algorithm for finding the minimum of that cost function The proposed algorithm is guaranteed to converge. The performance of the estimation algorithm is compared with the Cramer Rao bound (CRB). The derivation of the bound is also included. It is shown that DOA accuracy can be improved by adding uncalibrated sensors to a precisely calibrated array. Moreover, the number of sources that can be resolved may be larger than the number that can be resolved by the calibrated portion of the array