一种基于虚拟传感的无需误差传声器的自适应有源降噪方法*

该文基于虚拟传感技术引入了一种用于耳机的无需误差传声器的自适应有源降噪方法。该算法仅使用一个参考传声器实现了一种前馈和反馈自适应算法结合的有源降噪算法,提高了有源降噪稳定性,简化了耳机硬件结构。利用DSP平台实现了该文提出的方案,并通过实验验证了其良好的降噪性能和实用价值。     

一种有源头靠系统中虚拟传声器技术的改进方法

对人头移动导致有源头靠降噪效果下降的问题进行了理论分析,得到了残余噪声的预测表达式,提出了一种通过设计次级通道模型改进虚拟传声器技术性能的方法。分析表明,人耳位置处降噪量取决于虚拟传声器方法中采用的次级通道模型与人头移动到不同位置处的真实次级通道之间的匹配程度。通过设计合理的次级通道模型,可有效扩大人耳获得有效降噪量的人头允许移动范围。仿真分析和实验结果验证了该方法的有效性。     

复杂声学环境中人耳附近空间有源降噪研究综述

复杂声学环境中人耳附近空间降噪是有源噪声控制研究的重要课题,目前采用的主要方法为有源降噪头靠(AHR)和虚拟声屏障(VSB).本文简述AHR与VSB的发展历史和研究现状,介绍其物理原理和设计方法,评述其在实际应用中的优缺点,讨论了目前存在的问题与未来相关的研究方向.已有理论、数值仿真和实验研究验证了相关技术在人耳附近空间产生静区的可行性. AHR系统需要较少控制源,系统相对简单易实现,但静区范围较小,结合虚拟传声器技术和人头跟踪技术后可实现随人头移动的静区,降噪频率可达中高频; VSB产生的静区范围较大,但控制源个数较多,系统复杂和成本高,可通过代价函数和控制源优化,以及主被动混合控制技术来提高有效降噪频率范围和减少控制源个数.     

存在声反馈的前馈有源噪声控制系统性能分析

在一些应用场合,前馈有源噪声控制系统中次级源产生的声信号会反馈至参考传声器,影响参考信号质量和系统稳定,导致控制性能下降。引入了等效次级路径的概念,并通过等效次级路径与实际路径的相位偏差分析存在声反馈时的收敛性能。若某些频率的相位偏差大于90°,则这些频率附近将较难收敛,降噪性能下降,甚至导致系统不稳定。通过仿真和实验对单指向传声器声学方法、自适应滤波u型最小均方差(FuLMS)算法、反馈中和算法和在线建模算法共4种解决声反馈问题的方法的性能进行了比较。结果表明,4种方法都能提高存在声反馈时的前馈有源噪声控制系统的性能,有效解决声反馈引起的问题,但各有优缺点。单指向传声器方法最为方便,但低频指向性较差。FuLMS算法运算量较低,但不能保证收敛。反馈中和算法性能最好,但当系统时变时鲁棒性较差。在线建模算法不需要额外滤波器,但由于参数调节复杂,降噪性能稍差。      

基于脉冲声分离的刚性球散射声控制

提出了一种基于脉冲声的三维空间中刚性球散射声分离方法,并利用前馈、固定系数控制方式对分离出的散射声进行有源控制,抑制散射声强度,实现了刚性球散射体在观测点处“声学不可见”。该方法利用脉冲信号作为初级噪声,通过有无刚性球时传声器采集脉冲信号的差值确定散射声大小,实现散射声与声源直达声的分离。对分离出的散射声进行多通道有源控制以验证该文所提分离方法及控制系统的有效性。实验结果表明,700~1000 Hz范围内,有源控制开启后,双通道散射声的平均降噪量大于5 dB,多通道散射声的平均降噪量大于8 dB,且误差传声器处采集的残余声场与无刚性球时采集的初级声场信号波形基本一致,实现了刚性球散射体在误差传声器处“声学不可见”。此外,参考传声器布放位置的选取问题也在该文做了详细讨论。     

虚拟传声器在有源抗噪声护听器的应用

考察了虚拟传声器应用于有源抗噪声护听器的稳定性和降噪性能。理论上分析了虚拟传声器算法的稳定性,并通过引入反馈控制器和设计次级通道模型使得算法在不同护听器佩戴方式下都保持稳定,获得高噪声衰减和高稳定性。实验结果证实了虚拟传声器的应用可以在耳道口获得更高的窄带噪声衰减,而且所采取的措施可以保证护听器在不同佩戴状态下都能稳定。      

鲁棒性有源头枕系统的设计方法*

为了降低舱室内休息区域乘客双耳处的低频宽带噪声,采用最优维纳滤波器的设计准则,设计出一种基于局域空间有源降噪的多通道前馈有源头枕系统。实验对比了人工头在不同位置处和不同转动角度时两通道和四通道有源头枕系统在人耳处的降噪效果;进一步地,针对人头转动时控制效果变差的情况,提出了一种低复杂度的鲁棒性算法。仿真和实验表明,通道数量增加可使该系统在人耳附近获得更大的降噪量,使用鲁棒性算法的头枕系统在人头转动时有更好的控制性能。     

管道噪声的自适应抵消及其计算机模拟

本文提出一种采用自适应抵消的管道噪声有源降噪系统，自适应滤波器为有限冲激响应的横向结构，系统中采用了辅助滤波器和补偿滤波器，它们保证了最小均方算法的正确收敛，消除了声反馈效应，计算机模拟证实了该系统的可行性，通过对具有不同物理参数的管道的计算机模拟，得到了这些参数的变化对总降噪量的影响，这些参数包括温度、气流速度、管内的吸声情形、次级声源的Q值及次级声源到检测传声器的距离，模拟的结果有助于实际管道有源降噪的系统的设计。     

次级声源优化布放的局部空间有源降噪

针对区域有源降噪问题,为获得更优降噪效果,根据实际次级通路传递函数,提出次级声源优化布放的有源控制系统并详细比较了两种次级声源优化布放算法与次级声源均匀布放的实际降噪效果。应用的第一种次级声源优化算法是l2范数约束的约束匹配追踪算法,第二种次级声源优化算法是l1范数约束的稀疏正则化方法。在全消声室中利用扬声器线阵进行多通道有源降噪实验研究,实验结果表明,在200~1000 Hz,次级声源优化布放的控制系统的平均降噪量比次级声源均匀布放的控制系统的平均降噪量多5 dB左右;在1100~1900 Hz,次级声源优化布放的控制系统的平均降噪量比次级声源均匀布放的控制系统的平均降噪量多11~13 dB左右,次级声源优化布放的控制系统的降噪量分布更加均匀且次级声源输出能量更小。此外,两种优化算法中,稀疏正则化方法的降噪效果更佳。     

低复杂度的MIMO声呐协方差矩阵重构方法*

多输入多输出声纳在对目标进行测向时会产生复杂的运算量,从而降低算法的测向效率。针对这一问题,提出了一种基于降维变换方法的低复杂度协方差矩阵重构方法。该方法能够抑制噪声,提高目标侧向性能。首先利用降维变换方法对接收信号进行波束形成,获得低维度的协方差矩阵,再对矩阵进行Toeplitz处理,抑制矩阵的相干性。所得到的新的协方差矩阵,通过特征分解获得噪声子空间和信号子空间,利用MUSIC方法进行测向。为了进一步降低运算复杂度,利用阵型所满足的旋转不变性,可以采用ESPRIT算法对目标进行波达方向估计。理论分析和实验结果表明,该方法有效降低了运算复杂度,提高了算法的测向性能。在有限快拍数的情况下,与传统测向方法相比,具有运算速度快,目标分辨力强的特点。     

Implementation issues of the nearfield equivalent source imaging microphone array

This paper revisits a nearfield microphone array technique termed nearfield equivalent source imaging (NESI) proposed previously. In particular, various issues concerning the implementation of the NESI algorithm are examined. The NESI can be implemented in both the time domain and the frequency domain. Acoustical variables including sound pressure, particle velocity, active intensity and sound power are calculated by using multichannel inverse filters. Issues concerning sensor deployment are also investigated for the nearfield array. The uniform array outperformed a random array previously optimized for far-field imaging, which contradicts the conventional wisdom in far-field arrays. For applications in which only a patch array with scarce sensors is available, a virtual microphone approach is employed to ameliorate edge effects using extrapolation and to improve imaging resolution using interpolation. To enhance the processing efficiency of the time-domain NESI, an eigensystem realization algorithm (ERA) is developed. Several filtering methods are compared in terms of computational complexity. Significant saving on computations can be achieved using ERA and the frequency-domain NESI, as compared to the traditional method. The NESI technique was also experimentally validated using practical sources including a 125 cc scooter and a wooden box model with a loudspeaker fitted inside. The NESI technique proved effective in identifying broadband and non-stationary sources produced by the sources.     

A nonlinear active noise control algorithm for virtual microphones controlling chaotic noise

In active noise control (ANC) systems, virtual microphones provide a means of projecting the zone of quiet away from the physical microphone to a remote location. To date, linear ANC algorithms, such as the filtered-x least mean square (FXLMS) algorithm, have been used with virtual sensing techniques. In this paper, a nonlinear ANC algorithm is developed for a virtual microphone by integrating the remote microphone technique with the filtered-s least mean square (FSLMS) algorithm. The proposed algorithm is evaluated experimentally in the cancellation of chaotic noise in a one-dimensional duct. The secondary paths evaluated experimentally exhibit non-minimum phase response and hence poor performance is obtained with the conventional FXLMS algorithm compared to the proposed FSLMS based algorithm. This is because the latter is capable of predicting the chaotic signal found in many physical processes responsible for noise. In addition, the proposed algorithm is shown to outperform the FXLMS based remote microphone technique under the causality constraint (when the propagation delay of the secondary path is greater than the primary path). A number of experimental results are presented in this paper to compare the performance of the FSLMS algorithm based virtual ANC algorithm with the FXLMS based virtual ANC algorithm.     

Fast affine projections and the regularized modified filtered-error algorithm in multichannel active noise control

In this paper, real-time results are given for broadband multichannel active noise control using the regularized modified filtered-error algorithm. As compared to the standard filtered-error algorithm, the improved convergence rate and stability of the algorithm are obtained by using an inner-outer factorization of the transfer path between the actuators and the error sensors, combined with a delay compensation technique using double control filters and a regularization technique that preserves the factorization properties. The latter techniques allow the use of relatively simple and efficient adaptation schemes in which filtering of the reference signals is unnecessary. Results are given for a multichannel adaptive feedback implementation based on the internal model control principle. In feedforward systems based on this algorithm, colored reference signals may lead to reduced convergence rates. An adaptive extension based on the use of affine projections is presented, for which real-time results and simulations are given, showing the improved convergence rates of the regularized modified filtered-error algorithm for colored reference signals.     

Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance

Although cochlear implant (CI) users have enjoyed good speech recognition in quiet, they still have difficulties understanding speech in noise. We conducted three experiments to determine whether a directional microphone and an adaptive multichannel noise reduction algorithm could enhance CI performance in noise and whether Speech Transmission Index (STI) can be used to predict CI performance in various acoustic and signal processing conditions. In Experiment I, CI users listened to speech in noise processed by 4 hearing aid settings: omni-directional microphone, omni-directional microphone plus noise reduction, directional microphone, and directional microphone plus noise reduction. The directional microphone significantly improved speech recognition in noise. Both directional microphone and noise reduction algorithm improved overall preference. In Experiment II, normal hearing individuals listened to the recorded speech produced by 4- or 8-channel CI simulations. The 8-channel simulation yielded similar speech recognition results as in Experiment I, whereas the 4-channel simulation produced no significant difference among the 4 settings. In Experiment III, we examined the relationship between STIs and speech recognition. The results suggested that STI could predict actual and simulated CI speech intelligibility with acoustic degradation and the directional microphone, but not the noise reduction algorithm. Implications for intelligibility enhancement are discussed.     

基于稳态卡尔曼滤波的红外焦平面阵列非均匀校正算法

传统的卡尔曼滤波算法利用批处理实现非均匀校正,这样不仅会带来较大的计算量和存储量,而且更重要的是该方法不能实时处理.为此,提出了一种基于稳态卡尔曼滤波的红外焦平面阵列非均匀校正算法,它可以根据固定图案噪声的特点离线计算出滤波器的增益矩阵,并且非均匀校正过程也采用了逐帧迭代方式,因此大大降低了计算复杂度和存储占用量.详细阐述了该算法的基本原理,并用仿真数据和真实红外数据对算法性能进行验证,实验结果表明:本方法平均校正一帧图像所需CPU时间和内存占用量分别为1.7188 s和131.25 KB,完全可以满足实时处理的要求.     

Adaptive eigenvalue decomposition algorithm for passive acoustic source localization

To find the position of an acoustic source in a room, the relative delay between two (or more) microphone signals for the direct sound must be determined. The generalized cross-correlation method is the most popular technique to do so and is well explained in a landmark paper by Knapp and Carter. In this paper, a new approach is proposed that is based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the microphone signals contains the impulse responses between the source and the microphone signals (and therefore all the information we need for time delay estimation). In experiments, the proposed algorithm performs well and is very accurate.     

基于位的超光谱遥感图像无损压缩算法

图像压缩是超光谱遥感技术中急需解决的一个问题。分析了像素的高位与低位的相关性 ,提出了对字位进行运算的无损压缩算法。结果表明 ,本算法的压缩比与目前一些无损压缩比基本一致 (1 6～ 2 4) ,但这种算法运算简单 ,在去相关过程中 ,每位只进行一次运算 ,而且均为二进制运算 ,易于硬件电路的实现和进行实时压缩。所述思想为超光谱图像压缩提出了一条新思路     

球形阵列自适应网格分层定位算法

刚性球形传声器阵列可以在无空间模糊的条件下进行球谐域数据处理,基于球形阵列的可控波束形成器导向响应功率(SRP)算法定位精度高,但是计算量大,计算效率低。通过将球面致密的全局网格搜索替换为分层搜索策略可以有效减小SRP算法的计算量。提出MRE-SRP算法保持球形阵列SRP定位精度的同时降低计算量,首先通过球谐域MUSIC(SH-MUSIC)算法判断入射声源的数量减小搜索区域;其次将相对熵模型引入球谐域SRP(SH-SRP)定位算法中,提取网格分层前后的信息增益,设计自适应网格选择判据,实现分层多分辨率网格的精准再细分,从而降低计算量。实验验证了所提出算法的性能,结果显示在单双声源定位中,该算法可以实现较高的定位精度,精准选择分层网格,计算量减少75%以上。     

Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

The FXLMS algorithm, which is extensively used in active noise control, exhibits frequency dependent convergence behavior. This leads to degraded performance for time-varying and multiple frequency signals. A new algorithm called the eigenvalue equalization filtered-x least mean squares (EE-FXLMS) has been developed to overcome this limitation without increasing the computational burden of the controller. The algorithm is easily implemented for either single or multichannel control. The magnitude coefficients of the secondary path transfer function estimate are altered while preserving the phase. For a reference signal that has the same magnitude at all frequencies, the secondary path estimate is given a flat response over frequency. For a reference signal that contains tonal components of unequal magnitudes, the magnitude coefficients of the secondary path are adjusted to be the inverse magnitude of the reference tones. Both modifications reduce the variation in the eigenvalues of the filtered-x autocorrelation matrix and lead to increased performance. Experimental results show that the EE-FXLMS algorithm provides 3.5-4.4 dB additional attenuation at the error sensor compared to normal FXLMS control. The EE-FXLMS algorithm's convergence rate at individual frequencies is faster and more uniform than the normal FXLMS algorithm with several second improvement being seen in some cases.