Experimental evaluation of a nested microphone array with adaptive noise cancellers

This paper proposes a near-field broadband adaptive beamforming scheme for intelligent computer telephony and teleconferencing applications, namely the nested microphone array with adaptive noise canceller (NMA-ANC). The NMA-ANC scheme incorporates an harmonically nested array with a nonuniformly subbanded multirate filter bank. Each subband array employs several near-field delay-filter-and-sum beamformers and an adaptive noise canceller (ANC). The proposed NMA-ANC is evaluated via a noise rejection experiment and dereverberation experiment performed in an anechoic chamber and a real conference room, respectively. The experiment data are recorded by a multichannel digital recording system developed using commercial off-the-shelf (COTS) equipments. A perceptual analysis/measurement system (PAMS) test is also carried out using a COTS digital speech level analyzer. The results of the experimental evaluation and PAMS test show that the proposed NMA-ANC scheme is able to improve the sound quality by adaptively rejecting multiple interfering signals and attenuating the reverberant noises and avoiding the desired signal cancellation.     

阵元失效对克罗内克积波束形成性能的影响

对于一类规则阵型,可以引入克罗内克积提高最小方差无失真响应波束形成器的鲁棒性,同时降低其运算复杂度;然而,对于阵元数较多的规则阵列,阵元失效的可能性大幅增加,当某些阵元失效时,规则阵列不满足克罗内克分解。针对常见阵元失效问题,文章研究了阵元失效的三种情况对最小方差无失真响应波束形成器与克罗内克积自适应波束形成的性能影响。仿真与实验结果证明,信号完全缺失的通道对自适应波束形成器的影响最大,信号重复的通道对自适应波束形成器的影响最小。文章据此提出了一种低复杂度的信号恢复方法,通过使用相邻通道的信号代替信号缺失通道,提升阵元失效情况下的波束形成性能。     

MVDR自适应波束形成的一种智能算法

最小方差无失真响应（MVDR）自适应波束形成方法在声纳阵列信号处理中得到了广泛的应用。当存在强干扰时,传统的MVDR算法的稳定性较差,在有限次快拍数条件下,会带来一定的信噪比损失。将粒子群优化算法（PSO）引入MVDR的求解过程,提出了一种MVDR的数值实现方法。该方法在保持信号能量不变、干扰和噪声能量最小的约束条件下,利用粒子群优化算法通过数值搜索的方法获得MVDR的最优权向量。在小快拍数条件下,较一般的MVDR具有更好的抑制干扰能力。计算机仿真结果验证了该方法的有效性。     

一种具有多重稳健性的自适应波束形成算法

由于存在阵元幅相差、期望信号导向矢量误差和数据失配等问题,传统的自适应波束形成算法性能下降,针对这一问题,提出了一种新的对于上述多种误差同时具有稳健性的波束形成算法。该算法以最小二乘恒模算法为基础,结合最优对角加载和协方差矩阵锥消技术,使得算法适用于同时存在多种误差的情况。结果表明,与目前已有的同类算法相比,该算法克服了期望信号信噪比大时算法性能恶化的缺点,具有更好的输出信干噪比,并且通过计算机仿真验证了它的有效性和优越性。     

基于最小一乘的虚拟阵元波束形成仿真研究

水下多波束成像系统成像质量的关键主要在于波束形成的质量。在信号频率一定时,常规相移波束形成只有通过增加基阵的孔径来得到更窄的波束,但是在有限的应用条件下,这种方法又受到实际工程的限制。因此,提出一种基于最小一乘估计的虚拟阵元波束形成方法。在低信噪比的情况下,利用最小一乘估计的稳健性可以得到更加准确的估计信号,从而在不增加基阵尺寸的情况下获得更窄和抗干扰性更强的波束,提高阵增益和声呐图像的角度分辨率。通过Matlab仿真并与其他方法比较验证,证明了上述方法的优越性。     

自适应Notch滤波器在阵列信号处理中的应用

为了不增大阵列尺度采用信号处理方法得到高分辨率的波束指向性,首先利用Notch滤波器的＂离线重构＂实现窄带波束形成,进而结合其瞬时相位估计方法,研究了基于自适应Notch滤波器的恒定束宽波束形成技术,利用信号处理方法将矢量传感器阵列接收的低频窄带信号转化为具有指向性的较高频率波束,并采用虚拟阵元技术消除波束栅瓣的影响,给出了实际应用中具体的信号处理方法。仿真和湖试验证表明这种基于自适应Notch滤波器的恒定束宽波束形成方法是合理可行的。最后,针对适应实时信号处理的要求提出将这种方法与目标自动跟踪系统相结合的改进方向。     

Sigma-delta receive beamformer based on cascaded reconstruction for ultrasound imaging application

A pre-delay reconstruction sigma-delta beamformer (SDBF) was recently proposed to achieve a higher level of integration in ultrasound imaging systems. Nevertheless, the high-order reconstruction filter used in each channel of SDBF makes the beamformer highly complex. The beamformer can be simplified by reconstructing the signal after the delay-andsum process with only one filter. However, this post-delay reconstruction-based design degrades image quality when dynamic focusing is performed. This paper shows that employing a simple pre-delay filter is sufficient to achieve similar performance as conventional pre-delay reconstruction SDBF, as long as the pre-delay filter provides the required pre-delay signalto- quantization noise ratio (SQNR). Based on this finding, we proposed a cascaded reconstruction beamformer that uses a boxcar filter as the pre-delay filter in each channel. Simulations using real phantom data demonstrate that the proposed beamforming method can achieve a contrast resolution comparable to that of the pre-delay reconstruction beamforming method. In addition, the hardware can be greatly simplified compared with the pre-delay reconstruction beamformers.     

水下小孔径阵列远程目标检测方法研究

匹配滤波器频域自适应线谱增强方法是一种基于递归算法的非线性滤波技术,它大大提高了匹配滤波器的检测性能。针对当前该技术使用窄带信号作为发射信号存在可利用的带宽有限,不能充分发挥自适应线谱增强器性能的问题,文章提出将该技术与宽带信号相结合来检测远程目标。仿真显示,该方法在低信噪比条件下获得了较高的信噪比增益和检测概率。海试数据处理结果表明,该技术的处理增益较传统方法高6.24 dB。该方法的高处理增益适合应用在水下无人平台上,弥补了小孔径阵列空间增益不足的缺点,可以实现远程目标的检测。     

基于多普勒特征恢复的声矢量阵鲁棒自适应波束形成方法

在短快拍、信号导向矢量失配环境下,传统的自适应波束形成方法性能受到影响,对角加载技术是提高算法在复杂环境下性能鲁棒性的重要技术之一。针对水声环境和水声信号特点,提出一种基于声矢量阵的自适应波束形成方法。该方法利用水声信号的多普勒频率信息,在不同环境下自适应地选择最优对角加载因子,确定波束形成的权矢量,从而实现提取期望目标信号、抑制干扰和噪声的目的。无需任何用户参数,鲁棒性强、估计精度高。最后基于声矢量阵进行仿真实验,仿真结果证明了所提出的方法能够有效地获取目标信号,具有较好的抗干扰能力。     

Image quality evaluation with a new phase rotation beamformer

Over the last few decades, dynamic focusing based on digital receive beamforming (DRBF) has led to significant improvements in image quality. However, it is computationally very demanding due to its requirement for multiple lowpass filters (e.g., a complex filter for each receive channel in quadrature demodulation-based phase rotation beamformers (QD-PRBF)). We recently developed a novel phase rotation beamformer with reduced complexity, which can lower: 1) the number of lowpass filters using 2-stage demodulation (TSD) and 2) the number of beamforming points using adap tive field-of-view (AFOV) imaging. In TSD, dynamic focusing is performed on the mixed signals, while sampling frequency of the beamformed signal (i.e., beamforming frequency) is adjusted based on the displayed field-of-view (FOV) size in AFOV imaging. In this paper, the image quality of the developed beamformer (i.e., TSD-AFOV-PRBF) has been quantitatively evaluated using phantom and in vivo data. From the phantom study, it was found that TSD-AFOV-PRBF with only 1024 beamforming points provides comparable image quality to QD-PRBF. We obtained a median contrast resolution (CR) degradation of 7.6% for the FOV size of 160 mm. Image quality steadily improves with FOV size reduction (e.g., 2.3% CR degradation at 85 mm). Similar results were also obtained from an in vivo study. Thus, TSD-AFOV-PRBF could provide comparable image quality to conventional beamformers at considerably reduced computational cost.     

Eigenspace-based minimum variance beamforming applied to medical ultrasound imaging

Recently, adaptive beamforming methods have been successfully applied to medical ultrasound imaging, resulting in significant improvement in image quality compared with non-adaptive delay-and-sum (DAS) beamformers. Most of the adaptive beamformers presented in the ultrasound imaging literature are based on the minimum variance (MV) beamformer which can significantly improve the imaging resolution, although their success in enhancing the contrast has not yet been satisfactory. It is desirable for the beamformer to improve the resolution and contrast at the same time. To this end, in this paper, we have applied the eigenspace-based MV (EIBMV) beamformer to medical ultrasound imaging and have shown a simultaneous improvement in imaging resolution and contrast. EIBMV beamformer utilizes the eigenstructure of the covariance matrix to enhance the performance of the MV beamformer. The weight vector of the EIBMV is found by projecting the MV weight vector onto a vector subspace constructed from the eigenstructure of the covariance matrix. Using EIBMV weights instead of the MV ones leads to reduced sidelobes and improved contrast, without compromising the high resolution of the MV beamformer. In addition, the proposed EIBMV beamformer presents a satisfactory robustness against data misalignment resulting from steering vector errors, outperforming the regularized MV beamformer.     

Multiple-input multiple-output over-thehorizon radar: experimental results

Results from an experiment that applied one class of multiple-input multiple-output (MIMO) waveform techniques to over-the-horizon radar (OTHR) are reported. The experiment objective was to demonstrate that adaptive transmitter beamforming could be used in an appropriately design radar to reject spatially discrete Doppler-spread clutter. In the particular MIMO radar architecture that the authors call non-causal transmit beamforming, conventional or adaptive transmitter beamforming occurs following waveform transmission, propagation, scatter from targets and clutter sources, return propagation and finally signal reception. In the case reported herein spatially discrete clutter was successfully rejected to the noise floor of the radar return with rejection in excess of 35 dB achieved using common adaptive algorithms and straightforward training data selection. As part of the rejection algorithm the transmitted waveform direction-of-departure (DOD) from the transmitter array to the target was estimated and used as the preserved steer direction in the adaptive beamformer. The DOD estimates agree well with the geometrically determined true values. The demonstration of non-causal transmit beamforming suggests that it will be possible to create multiple simultaneous adaptive range-dependent transmitter beams with an appropriately designed OTHR. This has several applications including for the mitigation of Doppler-spread clutter.     

一种有效抑制阵列后方声源的心形指向性传声器阵列

基于心形指向性传声器的波束形成可以有效抑制阵列后方声源的干扰,提高前方声源的识别精度。以平面轮形传声器阵列为对象,借助MATLAB仿真计算,对阵列后方声源波束形成声源识别特性及其抑制方法进行研究。基于除自谱的互谱波束形成算法提出了含有传声器指向性的波束形成算法,对圆形和心形指向性传声器进行不同声源类型的波束形成仿真计算,并针对仿真结果显示出的不足,给出了既能保证阵列平面上最大声压贡献量的识别精度,又能降低旁瓣水平的幅值校正算法。试验结果证明了基于心形指向性传声器的波束形成可以有效抑制后方声源。     

A Fully Analog Adaptive-Disturbance Canceller

Analog adaptive filters are an important subset of adaptive-filter theory and practice. They are preferable at high speeds when low power consumption, small integrated area, and moderate linearity are required. In this paper, an analog adaptive-disturbance canceller is presented. The canceller uses the analog least mean square (LMS) algorithm, and its structure is similar to a linear combiner. The operation of the proposed canceller is based on the decomposition of the disturbances into the in-phase and quadrature components by means of a Hilbert transformer, which is used as an analog LMS for the cancellation of each component. Finally, some experimental results, which are obtained from a low-cost discrete-component realization of the proposed canceller, are presented. The proposed structure is also suitable for very large-scale integration designs.     

Experimental investigation of directional characteristics for ionospheric clutter in HF surface wave radar

The unwanted radar echoes from the ionosphere are collectively called ionospheric clutter. It has proved to be the greatest impediment to achieve consistently good performance in long-range detection of surface vessels and sea-state monitoring for high-frequency surface wave radar (HFSWR). Field experimental data recorded by the HFSWR OSMAR2003 (Ocean State Monitor and Analysis Radar, manufactured in 2003) has been used in detailed investigations of the directional characteristics for this ionosphere clutter, leading to the development of effective mitigation techniques based on antenna design and adaptive signal processing. Particular attention is given to the amplitude and phase relationship among multiple spatial channels for two types of ionospheric clutter. Preliminary experimental results show that the random gain and phase variation of the antenna pattern overhead null destroyed the amplitude and phase consistency among channels. As a result, no significant measured directivity is observed in this type of specular clutter. For the incidence clutter from a lower elevation angle, it is observed that the spread clutter possesses high directivity. A nonlinear receiving array composed of multiple V-shaped antennas without deep and broad null at near-vertical incidence is proposed for adaptive ionospheric clutter suppression     

旋转叶片高频涡脱落噪声源的双阵列声成像试验研究

旋转叶片的涡脱落噪声是一类典型的指向性声源,但由于叶片的旋转尚无法准确测量旋转叶片涡流噪声的指向性。利用两个平面阵列在叶片旋转面的平行和垂直两个方向对声源进行了声成像试验研究。试验中选择不同的叶片旋转方位角位置对涡脱落气动噪声进行波束形成声成像,通过比较声源在叶片不同方位角以及不同阵列方向的声成像结果验证了旋转叶片涡脱落噪声的指向性,并且分析了不同的叶片旋转方位角对涡脱落噪声的影响。试验结果验证了双阵列声成像测量方案的可行性和有效性,成像结果的对比表明使用的NACA0012桨叶在2.5 kHz下的旋转气动噪声源为指向性声源。     

单向水听器及其在波束形成中的应用

提出常规反向波束形成技术,构建了单向水听器,并探讨其应用于阵列波束形成的可能性。系统地构建单向水听器模型,导出常规反向波束形成技术,证明得到其空间响应单指向性的存在条件,其指向性指数在3~4.8 d B范围内。以单向水听器为基元构建标准线列阵进行常规波束形成,并与全向水听器比较,理论证明了使用单向水听器能够为线列阵提高3~4.8 d B的指向性指数。仿真实验结果验证了单向水听器自身具有心脏形空间响应、3~4.8 d B的指向性指数和空间响应的宽带一致性等三种特性,使用单向水听器能够在主瓣宽度不变的同时降低旁瓣级、提高指向性指数、保持良好的稳健性。因此,提出的常规反向波束形成技术是一种构建单向水听器的有效方法,在阵列波束形成中使用单向水听器是可行的、有利的。     

Minimum Variance Beamforming Combined with Adaptive Coherence Weighting Applied to Medical Ultrasound Imaging

Currently, the nonadaptive delay-and-sum (DAS) beamformer is used in medical ultrasound imaging. However, due to its data-independent nature, DAS leads to images with limited resolution and contrast. In this paper, an adaptive minimum variance (MV)-based beamformer that combines the MV and coherence factor (CF) weighting is introduced and adapted to medical ultrasound imaging. MV-adaptive beamformers can improve the image quality in terms of resolution and sidelobes by suppressing off-axis signals, while keeping onaxis ones. In addition, CF weighting can improve contrast and sidelobes by emphasizing the in-phase signals and reducing the out-of-phase ones. Combining MV and CF weighting results in simultaneous improvement of imaging resolution and contrast, outperforming both DAS and MV beamformers. In addition, because of the power of CF in reducing the focusing errors, the proposed method presents satisfactory robustness against sound velocity inhomogeneities, outperforming the regularized MV beamformer. The excellent performance of the proposed beamforming approach is demonstrated by several simulated examples.     

基于干扰抑制方法和引导声源的水平阵被动目标测距

基于引导声源的被动测距由于其对环境参数较少的要求受到了广泛关注。而处于浅海复杂环境下的被动声呐中,目标信号的声场干涉结构可能被邻近方位上的强干扰的旁瓣掩盖或改变,影响最终的测距精度。首先利用基于特征分解的自适应干扰抑制方法对强干扰环境中的接收信号进行干扰抑制,获得更高信噪比和信干比的目标信号;然后采用自适应的最小方差无失真波束形成器方法进行水平阵波束形成,得到更精确的目标声源声场干涉结构;其次基于干涉条纹的波导不变量特点,利用引导声源与目标声源干涉条纹的关系进行目标声源被动测距。实验结果验证了该方法的有效性和应用的可行性。     

水下单边带语音多通道增强技术

船舶噪声是影响水下语音通信质量的主要因素。为了提高单边带语音信号的信噪比和语音质量,采用多通道自适应增强算法对语音信号进行研究。该算法运用自适应信号增强技术,具有运算量小、易实时实现、消噪效果显著等优点,并且能够有效利用不同换能器接收到的信息。从理论上对该算法进行了分析,并结合海试数据进行验证。结果表明,低信噪比、非平稳噪声环境下,该算法有效抑制了接收信号中的尖锐噪声,并且当系统收敛时,使其趋于白化,明显提高了系统的输出信噪比,显著改善了语音质量,在性能上明显优于传统的信号相干叠加算法。