数字助听器发展现状及其算法综述

首先简要介绍了数字助听器的发展现状,然后分析和比较了数字助听器信号处理算法中的三类比较重要的算法,多通道频响补偿、噪声抑制和反馈消除,最后展望了数字助听器发展趋势。     

Feedback cancellation in hearing aids: results from a computersimulation

Feedback cancellation in hearing aids involves estimating the feedback signal and subtracting it from the microphone input signal. The feedback-cancellation system described updates the estimated feedback path whenever changes are detected in the feedback behavior. When a change is detected, the normal hearing-aid processing is interrupted, a pseudorandom probe signal is injected into the system, and a set of filter coefficients is adjusted to give an estimate of the feedback path. The hearing aid is then returned to normal operation with the feedback-cancellation filter as part of the system. Two approaches are investigated for computing the filter coefficients: a least-mean square (LMS) adaptive filter and a Wiener filter. Test results are presented for a computer simulation of an in-the-ear (ITE) hearing aid. The simulation results indicate that more than 10 dB of cancellation can be obtained and that the Wiener filter is more effective in the presence of strong interference     

基于投影对消处理技术的稳健自适应波束形成

针对传统自适应波束形成算法中目标波达方向(Direction of Arrival,DOA)估计不准确引起的波束形成性能下降问题,提出了一种采用投影对消矩阵的稳健自适应波束形成算法.首先,寻找与估计波达方向有最大相关性的特征矢量作为目标信号特征矢量,然后构建对消矩阵消除协方差矩阵中的信号分量,最后通过增加零点约束实现干扰抑制.与传统对角加载类稳健波束形成算法相比,所提算法不受对角加载因子的影响,且在信干噪比较大时仍然具有良好的抗干扰性能.仿真对比实验验证了所提算法的有效性.     

一种基于并行次梯度投影技术的加速声回波抵消算法

该文在并行次梯度投影技术(Parallel Subgradient Projection,PSP)的基础上,提出一种加速回波抵消算法。加速算法通过一种角度寻优策略,对由分属不同状态下的输入信号组成的空间进行寻优,从而找到一对最优投影空间。然后向这一对最优半空间的交集投影,实现对自适应算法的加速。实验仿真表明,加速算法相比传统方法收敛速率更快,无论是用均方误差还是自适应滤波器失准(Echo Path Misalignment)指标衡量加速算法在性能上都有一定程度的提升。     

Acoustic feedback cancellation for long acoustic paths using a nonstationary source model

While several proactive acoustic feedback (Larsen-effect) cancellation schemes have been presented for speech applications with short acoustic feedback paths as encountered in hearing aids, these schemes fail with the long impulse responses inherent to, for instance, public address systems. We derive a new prediction error method (PEM)-based scheme (referred to as PEM-AFROW) which identifies both the acoustic feedback path and the nonstationary speech source model. A cascade of a short- and a long-term predictor removes the coloring and periodicity in voiced speech segments, which account for the unwanted correlation between the loudspeaker signal and the speech source signal. The predictors calculate row operations which are applied to prewhiten the speech source signal, resulting in a least squares system that is solved recursively by means of normalized least mean square or recursive least squares algorithms. Simulations show that this approach is indeed superior to earlier approaches whenever long acoustic channels are dealt with.     

A new evolving-update-based feedback cancellation scheme for hearing aids

This paper proposes an efficient adaptive feedback canceller (AFC) for hearing aid, which provides satisfactory performance both in sparse and in dispersive conditions as well as can adapt according to the variations in the sparseness level of the feedback path for coloured signal as input. This is achieved by incorporating the measure of sparseness intensity and the variable step size to the memory-improved proportionate affine projection algorithm (MIPAPA), and hence, an improved MIPAPA (IMIPAPA) is proposed. Further, in order to reduce the computations incurred by the AFC, an evolving-update IMIPAPA (E-IMIPAPA) is introduced, employing an intermittent update of taps of the adaptive filter by simultaneously adjusting the update interval. The proposed E-IMIPAPA is applied to the two-microphone-based AFC. The results of simulation-based experiments show the effectiveness of the proposed algorithm as compared to the existing methods for feedback cancellation in hearing aid in terms of misalignment and added stable gain. The proposed AFC model is further extended to the multiple-microphone and single-speaker set-up.     

一种适用于混响环境的双传声器自适应指向性算法

在许多语音信号处理系统(如助听器)中,都采用了指向性算法处理在空间上相互分离的信号,但在客厅、会议室等室内环境中混响的存在严重影响了指向性系统的降噪性能,现有的去混响算法不能有效地抑制干扰噪声。该文提出一种适用于混响环境的自适应双传声器指向性算法,采用两个间距很小的全向性传声器,将自适应零限波束形成(ANF)结构和利用概率模型抑制混响的方法相结合,实现了在混响环境中的自适应指向性。与现有指向性和抑制混响算法相比,该算法采用一个简单的结构同步实现了指向性和抑制混响,具有较低的复杂度和较强的实时性。仿真验证了算法在混响环境中的指向性降噪性能。     

基于小波变换的声学回波消除系统

声学回波消除技术一直是语音通信领域的研究热点。在声学回波消除系统中,通过估计回波路径中的固定时延区域来提高自适应滤波算法的收敛速度。提出了一种基于小波变换的固定时延估计算法以及基于小波变换的声学回波消除系统,解决传统时延估计算法在声学回波消除系统中估计误差大、抗干扰能力弱的问题。测试结果表明,算法稳健性、有效性等指标明显优于传统时延估计算法,基于小波变换的声学回波消除系统具有良好的消回波性能。     

子带仿射投影及子带双端检测算法的回声消除系统

文中提出了一种新的多相位子带自适应回声消除系统。在子带内进行自适应滤波对建模长度比较长的脉冲响应特别有效,同时由于仿射投影算法具有预白化的作用,它同样也具有改善滤波器收敛性能的功能。该系统集中了多相子带自适应滤波和仿射投影算法的优点,结合了子带内的双端检测算法,使得系统在临界采样的情况下能进行稳定有效的工作。实验表明：该系统对于语音信号和强相关信号都表现出了良好的性能。     

Estimation-based synthesis of H∞-optimal adaptive FIR filtersfor filtered-LMS problems

This paper presents a systematic synthesis procedure for H∞-optimal adaptive FIR filters in the context of an active noise cancellation (ANC) problem. An estimation interpretation of the adaptive control problem is introduced first. Based on this interpretation, an H∞ estimation problem is formulated, and its finite horizon prediction (filtering) solution is discussed. The solution minimizes the maximum energy gain from the disturbances to the predicted (filtered) estimation error and serves as the adaptation criterion for the weight vector in the adaptive FIR filter. We refer to this adaptation scheme as estimation-based adaptive filtering (EBAF). We show that the steady-state gain vector in the EBAF algorithm approaches that of the classical (normalized) filtered-X LMS algorithm. The error terms, however, are shown to be different. Thus, these classical algorithms can be considered to be approximations of our algorithm. We examine the performance of the proposed EBAF algorithm (both experimentally and in simulation) in an active noise cancellation problem of a one-dimensional (1-D) acoustic duct for both narrowband and broadband cases. Comparisons to the results from a conventional filtered-LMS (FxLMS) algorithm show faster convergence without compromising steady-state performance and/or robustness of the algorithm to feedback contamination of the reference signal     

Reverberation canceling wireless aid for hearing impaired

The stringent requirements on size and power consumption constrain the conventional hearing aid devices. Besides providing an economic and user friendly aid, reverberation/echo cancellation is an important requirement. With the technological advancements, wireless hearing aids exploiting the usage of multi-microphones, mixed signals and RF signals processing circuits, digital signal processing units sound promising to overcome existing constraints. A new wireless hearing aid system is proposed in this paper. Unlike the previously reported wireless hearing aid concept, it needs only one way data transfer from body unit to the earpiece. It helps in minimizing power consumption in the earpiece RF-linked with a body unit with DSP based reverberation canceling scheme. For this purpose, a noise cancellation algorithm is developed based on beam-forming technique. The functioning of the whole system comprising an earpiece and a body unit has been ensured using the Advanced Design System^TM. The ADS compatible behavioral models were developed in order to enable the system level simulation. A comprehensive noise analysis is carried out and validated.     

Symmetric adaptive maximum likelihood estimation for noisecancellation and signal separation

The symmetric adaptive maximum likelihood estimation (SAMLE) algorithm is proposed. It is shown to be a generalisation of the symmetric adaptive decorrelation (SAD) algorithm for noise cancellation and signal separation. Both the SAD and SAMLE algorithms are applied to the separation of a mixture of natural speech recorded in a realistic acoustic environment. A comparative simulation confirms that the SAMLE algorithm provides superior separation capabilities     

Robust Reduced-Rank Adaptive Algorithm Based on Parallel Subgradient Projection and Krylov Subspace

In this paper, we propose a novel reduced-rank adaptive filtering algorithm exploiting the Krylov subspace associated with estimates of certain statistics of input and output signals. We point out that, when the estimated statistics are erroneous (e.g., due to sudden changes of environments), the existing Krylov-subspace-based reduced-rank methods compute the point that minimizes a “wrong” mean-square error (MSE) in the subspace. The proposed algorithm exploits the set-theoretic adaptive filtering framework for tracking efficiently the optimal point in the sense of minimizing the “true” MSE in the subspace. Therefore, compared with the existing methods, the proposed algorithm is more suited to adaptive filtering applications. A convergence analysis of the algorithm is performed by extending the adaptive projected subgradient method (APSM). Numerical examples demonstrate that the proposed algorithm enjoys better tracking performance than the existing methods for system identification problems.      

Filtering approaches to accelerated consensus in diffusion sensor networks

The main objective in distributed sensor networks is to reach agreement or consensus on values acquired by the sensors. A common methodology to approach this problem is using the iterative and weighted linear combination of those values to which each sensor has access. Different methods to compute appropriate weights have been extensively studied, but the resulting iterative algorithm still requires many iterations to provide a fairly good estimate of the consensus value. In this paper, different accelerating consensus approaches based on adaptive and non‐adaptive filtering techniques are studied and applied on the problem of acoustic source localization using the adaptive projected subgradient method. A comparative simulation study shows that the non‐adaptive polynomial filters based on Newton's interpolating polynomials and semi‐definite programming can provide more accelerated consensus and better estimation accuracy than adaptive filters evaluated using constrained affine projection algorithm or stochastic gradient algorithm provided that the network topology is known beforehand. Copyright © 2013 John Wiley & Sons, Ltd.     

一种基于数字电视地面广播照射源的外辐射源雷达快速杂波相消算法

为了减小外辐射源雷达系统中常规杂波相消算法的运算量,该文利用数字电视地面广播(DTTB)照射源中的PN序列,提出了一种快速杂波相消算法。该算法基于PN序列良好的自相关特性,并考虑到DTTB信号对载频频偏(CFO)很敏感,提出2-D信道和CFO估计来提高估计精度;然后,利用估计的信道和CFO进行直达波重构和杂波相消,剩余目标回波和噪声。相比于传统的杂波相消算法,该方法运算量比较小,并且所有处理都基于预警天线,不需要参考天线,简化了系统模型。最后仿真实验验证了算法的有效性。     

基于CLEAN算法的自适应旁瓣对消技术

自适应旁瓣对消技术能够很好地抑制旁瓣干扰,但在应用中发现, 自适应旁瓣对消对跟踪的高信噪比目标带来的信噪比损失较大,导致单脉冲和差测角精度下降。本文提出了一种基于CLEAN算法的自适应旁瓣对消方法,首先通过观测目标的先验信息构建目标回波模型,再利用该回波模型剔除对消通道中的目标信息,然后基于剔除目标信息后的对消通道数据,重新计算最优加权值进行主通道的干扰对消,最后仿真和实测结果验证了该方法不仅可以减少主通道中目标对消后的信噪比损失,同时也降低了对消后对目标测角精度的影响。     

Active noise control: a tutorial review

Active noise control (ANC) is achieved by introducing a cancelling “antinoise” wave through an appropriate array of secondary sources. These secondary sources are interconnected through an electronic system using a specific signal processing algorithm for the particular cancellation scheme. ANC has application to a wide variety of problems in manufacturing, industrial operations, and consumer products. The emphasis of this paper is on the practical aspects of ANC systems in terms of adaptive signal processing and digital signal processing (DSP) implementation for real-world applications. In this paper, the basic adaptive algorithm for ANC is developed and analyzed based on single-channel broad-band feedforward control. This algorithm is then modified for narrow-band feedforward and adaptive feedback control. In turn, these single-channel ANC algorithms are expanded to multiple-channel cases. Various online secondary-path modeling techniques and special adaptive algorithms, such as lattice, frequency-domain, subband, and recursive-least-squares, are also introduced. Applications of these techniques to actual problems are highlighted by several examples     

Micropower gradient flow acoustic localizer

A micropower mixed-signal system-on-chip for three-dimensional localization of a broad-band acoustic source is presented. Direction cosines of the source are obtained by relating spatial and temporal differentials in the acoustic traveling wave field acquired across four coplanar microphones at subwavelength spacing. Correlated double sampling and least-squares adaptive cancellation of common-mode leakthrough in the switched-capacitor analog differentials boost localization accuracy at very low aperture. A second stage of mixed-signal least-squares adaptation directly produces digital estimates of the direction cosines. The 3mm /spl times/ 3mm chip in 0.5-/spl mu/m CMOS technology quantizes signal delays with 250-ns resolution at 16-kHz sampling rate, and dissipates 54 /spl mu/W power from a 3-V supply. Field tests of the processor with acoustic enclosure demonstrated its utility and endurance in tracking ground and airborne vehicles. Applications include acoustic surveillance, interactive multimedia, and intelligent hearing aids.     

单频网中继站自适应回波消除器的设计

以数字电视地面广播国家标准为背景,提出一种在单频网通信系统中,通过专门电路对中继站回波干扰进行消除的方法.该方法通过对TDS-OFDM信号中的PN序列进行分析和计算,获取对回波干扰信道的估计,然后利用信道估计的结果生成一路反馈信号,用于逼近回波干扰信号,最后从接收信号中除去该反馈信号即实现回波消除.其中信道估计的过程是迭代的、自适应的.实验结果表明,该方法具有良好的回波消除性能.     

基于梯度向量投影的自适应滤波算法的改进及其在多路回波消除中的应用

该文首先对Lim(2000)的基于梯度向量正交投影的算法(OGA)进行了分析和改进,在此基础上获得了一种新的自适应滤波算法(MOGA)。新算法使用时变遗忘因子对误差进行指数加权平均来估计均方误差,并使用该因子改变自适应迭代过程中滤波器系数向量的更新方向.然后将改进后的新算法扩展成两路回波消除算法用于多路回波的消除中,获得了良好的效果。仿真结果表明, MOGA不仅对时变或时不变系统具有很好的跟踪能力,克服了Lim(2000)所提算法收敛性不佳甚至有时发散的缺陷,而且应用于多路回波消除时具有计算量小,收敛速度快和精度高等特点,其收敛速度和精度优于J.Benesty(1996)和G.Sankaran(1999)的相应结果。