舷侧阵CBF和OBF的阵增益比较

以舷侧阵作为研究对象,首先介绍了常规波束形成器(CBF)和最佳波束形成器(OBF)的波束输出信号模型,然后推导了信号+噪声场合下的阵增益表达式,比较了在不同信号频率和不同信号源方向角下,CBF和OBF的阵增益,最后在增加了有指向性的CW干扰后,分析了此场合下的阵增益,并比较了不同的信号频率下,干扰源方向角的变化对两类波束形成器阵增益的影响。     

基于高阶累积量的自适应波束形成

常规波束形成器仅限于利用信号的二阶统计特性。作者采用高阶累积量估计期望信号的导向矢量 (Steering Vector) ,实现了一种基于高阶累积量的自适应波束形成器 (HCAB)。该波束形成器利用信号的更高阶统计特性 ,减少了对阵列流型的依赖 ,具有较好的容差性 ,能自动跟踪信号。数值模拟实验表明该波束形成器工作良好。     

高分辨率波束形成器在多波束测深系统中的应用

对于海底地形测量,基于FT波束形成的幅度检测法空间分辨率较低,只能较准确给出有限测点的水深信息;平坦海底前提下,分裂子阵检测法或多子阵检测法可以得到连续测点的水深信息,复杂海底地形条件下,这两种方法均难以应用。能否利用高分辨率波束形成器来提高测深系统的空间分辨率是一个值得研究的问题。使用ESPRIT波束形成器处理了多波束测深系统的试验数据,并就其性能与FT波束形成器进行了比较与分析。     

圆阵低频超增益波束形成用于水下目标探测研究

针对小尺度基阵难以取得低频空间增益的问题，研究了圆阵超增益波束形成技术检测低频目标的方法。利用小尺度基阵低频噪声的空间相关性，求出基阵的相关系数矩阵，该矩阵对常规波束形成的权系数进行加权，产生超增益波束形成器的最优加权向量。计算机仿真与实测数据处表明：超增益波束形成技术能够在较低的工作频率上形成波束，获得更好的探测定位性能，有良好的应用前景。     

浅水多波束测深仪高分辨率波束形成方法研究

常规波束形成技术以其稳健性好、计算量低等特点得到广泛应用,但其空间分辨率受阵元个数限制,不能突破瑞利限。因此,常规波束形成技术应用于高精度浅水多波束测深仪时,存在空间分辨率不足和旁瓣干扰等问题。对比研究了最小方差无失真(MVDR)及多重信号分类(MUSIC)波束形成在浅水多波束测深仪中的应用,给出了浅水多波束测深仪的常规波束形成、MVDR和MUSIC处理方法,并结合能量法和相位法两种底检测测深算法,处理了iBeam8120浅水多波束测深仪外场数据,验证了本文方法的性能。     

基于FieldⅡ的多波束海底检测性能仿真

基于Field Ⅱ声场仿真工具建立了仿真模型,模拟了平坦以及海底有凸起目标时的海底地形,分别采用常规波束形成器和超波束形成器对模拟的海底回波数据进行处理,结果表明超波束形成器分辨目标的性能更优;应用Monte Carlo方法进行仿真实验,结果表明基于超波束形成器的WMT算法深度估计均值更接近真值、标准差更低,可以有效提升多波束海底检测性能。     

一种基于稳健自适应波束形成的声隔离技术

介绍了一种基于稳健自适应波束形成的声隔离技术。通过分析声诱饵工作时干扰与信号的主要入射方位,建立了边发边收声诱饵模型。针对 STMV 波束形成器在基阵模型失配情况下容易出现信号自消的现象,研究了一种解决波束形成稳健性的新方法,即 Robust Capon Beamforming(RCB)算法,实现有效的干扰抑制和信号提取。仿真和试验数据表明：该方法对端射方向干扰具有良好的抑制效果,且能无失真提取出目标信号,为稳健自适应波束形成在声诱饵边发边收中的应用提供了参考。     

基于二阶锥规划的空域维纳滤波

提出了基于二阶锥规划的空域维纳滤波。基于噪声与阵列流型不相关的特性,将阵列的方向向量作为期望通过二阶锥规划方法对阵列快拍进行维纳滤波。利用维纳滤波抑制噪声的能力,提高阵列的信号检测和方位估计性能。通过仿真研究,验证了单目标时,其低信噪比下的信号检测性能优于Bartlett波束形成,其方位估计的信噪比门限要低于Bartlett波束形成和MUSIC算法,因而是一种优良的波束形成器。该波束形成器用于多波束测深仪和侧扫声纳等海洋测绘设备的阵列,可以有效的提高设备的作用距离和测量精度。     

基于二阶锥规划的空域维纳滤波

提出了基于二阶锥规划的空域维纳滤波。基于噪声与阵列流型不相关的特性,将阵列的方向向量作为期望通过二阶锥规划方法对阵列快拍进行维纳滤波。利用维纳滤波抑制噪声的能力,提高阵列的信号检测和方位估计性能。通过仿真研究,验证了单目标时,其低信噪比下的信号检测性能优于Bartlett波束形成,其方位估计的信噪比门限要低于Bartlett波束形成和MUSIC算法,因而是一种优良的波束形成器。该波束形成器用于多波束测深仪和侧扫声纳等海洋测绘设备的阵列,可以有效的提高设备的作用距离和测量精度。     

利用衰减器实现的相控波束形成

文章讨论了相控阵多普勒计程仪波束形成原理和数控衰减器混频及移相原理 ,提出了利用衰减器实现相控波束形成的方法。实验证明了数控衰减器实现相控波束形成器的可行性。     

Theory and analytical performance evaluation of generalizedcorrelation beamformers

Traditionally, passive detection and localization of an acoustic source has been based on exploiting the relative differences in temporally averaged power outputs of contiguous beams of an element-weighted beamformer. An alternate approach, the generalized correlation beamformer (GCBF), is proposed where a weighted Toeplitz-averaged (spatially averaged) correlation function is used to estimate the beamformer output power. All element-weight sequences can be transformed into correlation-weight sequences through a convolution operation. Additional weight sequences which cannot be generated from a convolution of real element-weight sequences are available for use in the GCBF. A special case of the GCBF was proposed by Wilson et al. (1995) in which the correlation-weights are set to unity, a correlation-weight sequence which cannot be obtained from any classical element-weight sequence. Although such a “boxcar” correlation-weight sequence produces a sharper main peak power response (improved resolution), it has the undesirable effect of producing abnormally high (positive and negative power) sidelobes. General analytical performance bounds are developed that accurately reflect the GCBF detection and bearing localization performance for a noise model that includes spatially white noise and spatially discrete interferers (clutter). Analysis results indicate that the GCBF with Bartlett correlation-weights outperformed the GCBF with unity correlation-weights for both detection and bearing estimation except when the clutter bearing is close to the signal bearing     

Spatial processing of signals received by platform mounted sonar

Acoustic signals received by platform mounted sonar arrays can be spatially processed to enhance the detection of targets in the presence of both ambient and platform generated (self) noise. Ambient noise in the ocean, such as that due to distant shipping or biological choruses, are known to be spatially correlated. The platform generated noise will be of near-field origin and may not be received by all elements in the array. In this paper we investigate the performance of the minimum variance distortionless response (MVDR) beamformer and the recently introduced Fourier integral method (FIM) and compare their performances with the conventional beamformer. Real passive sonar data, obtained from a platform mounted sparse linear array of hydrophones, is used to study the performance of the beamformers in a typical sonar environment. It is shown that in the absence of self noise, when the array is accurately calibrated the MVDR beamformer will perform very well, but when sensor gain or phase errors are present the performance of the MVDR beamformer is degraded. Further, the MVDR beamformer is unable to reject the self noise which is not "seen" by the entire array. FIM however seems to perform well and a modified version of FIM, which we call weighted FIM (WFIM), is shown to perform better and is at worst comparable to a well calibrated MVDR beamformer     

Remedying the effects of array shape distortion on the spatialfiltering of acoustic data from a line array of hydrophones

The effects of both small perturbations and large deformations to the array's shape on both conventional and adaptive beamformers are shown for two frequencies: the spatial Nyquist frequency (or design frequency) of the array and a frequency about three times greater. Large shape deformations lead to a decrease in the conventional beamformer's output power for a beam steered in the direction of the signal source, together with an increase in the sidelobe levels (or secondary maxima), while small perturbations in the array shape have little effect. Signal suppression is observed to be far greater for the adaptive beamformer because it is very sensitive to system errors. The imposition of a weight norm constraint on the adaptive beamformer reduces the signal suppression only for small shape perturbations array shape estimation techniques are needed to reduce signal suppression for large shape deformations. The adverse effects of a nonlinear array shape on both conventional and adaptive beamforming are shown to be substantially reduced by applying techniques that estimate the coordinates of the hydrophones prior to beamforming     

Adaptive beamforming: spatial filter designed blocking matrix

Controlling the resolution in adaptive beamformers is often crucial. A simple method that works for both narrow-band and broad-band arrays is presented. This method is based on the normalized leaky LMS algorithm in conjunction with a generalized sidelobe canceller (GSC) structure, where the GSC is designed using a spatial filtering approach. In essence, the suppression of the spatial filters and the implicit noise of the leaky LMS algorithm together determine the adaptive beamformer. Analytical expressions are given for the Wiener filters and the output spectrum versus frequency and point source location. These expressions are employed in the design specification of the spatial filters and to obtain conditions for a controlled quiescent beamformer response. Simulation results are presented to illustrate the behavior of the array     

Adaptive port-starboard beamforming of triplet sonar arrays

For a low-frequency active sonar (LFAS) with a triplet receiver array, it is not clear in advance which signal processing techniques optimize its performance. Here, several advanced beamformers are analyzed theoretically, and the results are compared to experimental data obtained in sea trials. Triplet arrays are single line arrays with three hydrophones on a circular section of the array. The triplet structure provides the ability to solve the notorious port-starboard (PS) ambiguity problem of ordinary single-array receivers. More importantly, the PS rejection can be so strong that it allows to unmask targets in the presence of strong coastal reverberation or traffic noise. The theoretical and experimental performance of triplet array beamformers is determined in terms of two performance indicators: array gain and PS rejection. Results are obtained under several typical acoustic environments: sea noise, flow noise, coastal reverberation, and mixtures of these. A new algorithm for (beam space) adaptive triplet beamforming is implemented and tuned. Its results are compared to those of other triplet beamforming techniques (optimum and cardioid beamforming). These beamformers optimize for only one performance indicator, whereas in theory, the adaptive beamformer gives the best overall performance (in any given environment). The different beamformers are applied to data obtained with an LFAS at sea. Analysis shows that adaptive triplet beamforming outperforms conventional beamforming algorithms. Adaptive triplet beamforming provides strong PS rejection, allowing the unmasking of targets in the presence of strong directional reverberation (e.g., from a coast) and at the same time provides positive array gain in most environments.     

Analysis of Signal Cancellation Due To Multipath in Optimum Beamformers for Moving Arrays

In this paper, we study the effect of array motion on signal cancellation and interference rejection in optimum beamformers in the presence of multipath with partially or fully correlated sources. First, we show how array motion causes signal decorrelation with a rate that depends on the spacing and directions of the sources. Next, we briefly discuss the signal cancellation and interference rejection behavior of the optimum beamformer in the presence of a correlated interference to motivate the need to decorrelate the desired source from the interference. We then propose an optimally weighted covariance averaging technique to ensure perfect decorrelation of the sources for any given displacement. Computer plots and simulation results are included to support our analysis.     

ROC evaluation of adaptive beamforming in a simulated shallow waterenvironment

An optimal evaluation of adaptive beamforming techniques in a reverberation-limited shallow water environment is presented. A comprehensive simulation, using the sonar simulation toolset (SST) software in conjunction with the generic sonar model (GSRT) software, is used to create realistic beam data complete with target, noise, and reverberation. Adaptive beamforming techniques from the recursive least squares (RLS) family are applied to enhance detection performance via interference rejection. Two techniques are considered: linearly constrained beamforming using the minimum variance distortionless response (MVOR) beamformer and constrained adaptive noise cancelling (ANC) using the joint process least squares lattice (JPLSL) algorithm. Target detection trials, summarized in the form of receiver operator characteristics (ROC), are used to evaluate performance of the two adaptive beamformers. Results demonstrate mixed performance in reverberation-limited shallow water environments     

Passive-range estimation using dual focused beamformers

The passive-range estimation technique using a single focused beamformer has been studied under the sea. However, there are not many more methods in the case of closed multisource environments. In this paper, we propose the technique using dual focused beamformers to estimate the ranges of a closed multisource, and compare the proposed technique with the previous method. The proposed method is verified via computer simulation under the simplified multipath underwater channel model.