机动车辆舱室内主动噪声控制系统的设计

针对主动噪声控制技术在改善机动车辆舱室内噪声状况的应用中存在的技术难点，如消除声反馈过程、准确获得参考信号和声学路径的估计等，进行了分析、研究，并在此基础上给出了一种机动车辆舱室内的主动噪声控制系统设计方案。     

一种新的自适应语音增强系统

针对自适应噪声对消(ANC)语音增强系统的性能高度依赖于参考信号的质量，任何原始语音信号泄漏到参考信号中，都会导致原始语音信号失真和噪声抵消性能恶化这一问题，本文提出一种对泄漏不敏感的附加随机噪声(ARN)自适应噪声对消语音增强系统。它通过在参考信号中加入一个低功率的宽带随机训练信号，然后用该训练信号作参考信号对噪声传输函数(NTF)进行自适应建模，并在使用自适应预测滤波器(APF)消除NTF自适应建模的语音信号干扰的同时，用补偿滤波器(CPF)来修正由APF引起的参考信号失真。计算机仿真表明，这种ARNANC语音增强系统在泄漏情况下能将原始语音信号从带噪语音信号中有效分离出来。     

基于同步方程方法的有源噪声控制

基于同步方程方法基本原理,对有源噪声控制系统中的参考输入信号和测量误差信号进行处理,得到最优的噪声控制滤波器,其无须对次路径进行辨识建模,且具有较好的鲁棒性;就前馈控制结构加以研究,仿真结果表明,该方法不仅在次路径固定不变时,使噪声信号得到明显衰减,并且在次路径发生改变时,依然能很好地控制噪声。     

基于IIR陷波器应对频率失调的窄带ANC系统新结构

窄带主动噪声控制（ANC ）系统中往往存在频率失调（FM ）问题，传统的频率失调补偿（FMC ）系统能应对一定程度的FM，但当噪声信号非平稳或失调量较大时，系统将无法工作。针对此问题，本文提出一种带有频率估计的窄带ANC系统新结构，其采用声学和非声学两路传感器获取参考信号，引入可变极半径及平滑下降（PG ）算法构建IIR陷波器，完成参考信号的频率估计，通过一阶FIR滤波器实现幅值和相位的调节。仿真表明，在保证合理的稳态误差情况下，与传统的FMC系统相比，新系统能够应对较大的FM ，且具有良好的收敛和追踪性能。     

锁相倍频器宽带捕捉窄带跟踪的工程设计

窄带锁相倍频器已广泛用作跟踪淹没于噪声之中的信号，最终输出是一个频谱干净的信号，并对相位抖动具有较强的抑制能力。本文提出一种采用鉴频鉴相器原理和高增益二阶环的自适应滤波器来实现窄带锁相倍频器变带宽快速捕捉。     

用于窄带声源定位的时延估计算法研究

提出了声源为窄带信号时,用一维麦克风阵列所得数据进行时延估计的算法。将由麦克风阵列采集,并通过窄带滤波器的声源信号建模为窄带信号;通过分析其频谱特征,定义了关于信号传至相邻麦克风时间差的搜索函数,以得出所求时延。对于含有背景噪声的情况,在白噪声环境下,用所得数据向量构造Hankel矩阵,通过奇异值分解法去噪;当存在窄带噪声时,用Chebyshev I低通滤波器构造出带通滤波器,达到去噪目的。最后,给出了实验仿真结果,验证方案的可行性。     

基于泄漏残余误差分离器的窄带主动噪声控制系统

传统窄带主动噪声控制系统中,各窄带噪声分量由各控制器并行处理,而相应的控制系数却仍由系统的整体残余误差进行更新。这导致各控制器之间相互影响,从而降低了系统的收敛速度。为保证各控制器单独利用自身的残余误差来更新控制系数,实现残余误差信号的频率分量分离,该文提出一种基于泄漏残余误差分离器的窄带主动噪声控制系统,并对新系统进行初步统计分析。理论分析、仿真及实验表明,这种引入泄漏因子的残余误差分离器,在不牺牲稳态性能情况下,提升了系统的鲁棒性和收敛性。     

基于信号包络和互相关的双端通话检测算法研究

声学回声消除(AEC)系统依赖于自适应滤波器的回声路径估计,当麦克风接收的信号存在回声和近端信号时,可能出现模拟回声路径的自适应滤波器发散,导致回声消除性能下降,严重时影响双端通话质量。一个成熟的声学回声消除器应该包含有双端通话检测算法,针对该问题,提出一种准确度高、性能稳定的基于信号包络检测(Env)和归一化互相关(NCC)估计相结合的双端通话检测(DTD)算法。该算法先使用远端信号与麦克风信号的能量包络来判断双端通话是否发生,当包络检测不能准确地判断双端通话时,再使用远端信号与麦克风信号的互相关估计对双端通话进行最终判断,保证双端通话检测的准确性。仿真实验表明,提出的算法可以准确判断双端通话的开始与结束,并且受回声路径变化的影响较小,提升了AEC系统的性能。     

一种应对窄带非线性主动噪声控制的混合结构

分析参考信号为窄带信号、初级路径为非线性路径、次级路径为非最小相位系统的主动噪声控制（ANC）的初级噪声特性,探究有限脉冲响应（FIR）反馈预测结构和前馈函数链接人工神经网络（FLANN）结构的消噪原理,并探讨其各自的优势及局限性.通过分析总结,本文提出FLANN-FIR混合结构ANC系统,该系统对FIR反馈预测结构和前馈FLANN结构进行优势互补,不仅可以消除可预测部分噪声,对不可预测部分噪声一样具有抑制作用.仿真表明,在不同信噪比参考信号和不同非线性初级路径下,提出的混合结构都具有良好的稳态误差和收敛速度.     

用System View滤除伴音中的窄带噪声

有效滤除伴音中的噪声对提高节目播出质量是有帮助的。System View是一个功能强大的数字信号处理和通信系统设计的仿真软件，它提供了信号从时域到频域的转换和滤波器的设计工具，方便捕捉声音信号中的噪声频谱并通过设计合理的滤波器滤除噪声。本例说明使用System View软件滤除伴音信号中的窄带噪声的方法。     

一种直扩通信系统窄带干扰变换域抑制方法

本文提出一种基于AR模型谱估计和变换域处理相结合的直接序列扩频（DS-SS）通信系统窄带干扰抑制方法。该方法采用AR模型估计信号的频谱,并由此构造频域窄带干扰抑制滤波器。由于谱估计的同时也估计了最小误差功率,这为频域抑制滤波器的门限提供了参考,从而实现了自动门限设置。与时域AR预测型窄带干扰抑制方法相比,频域处理利用FFT实现了并行处理,提高了处理速度。     

Blind Adaptive Suppression of Narrowband Digital Interferers from Spread Spectrum Signals

The application of the minimum-mean-square-error (MMSE) multiuser detection technique to the problem of suppressing the digital narrowband interference (NBI) from spread-spectrum signals is considered. The MMSE multiuser detector can be implemented using a blind adaptive method, which is ideally suited for use in the NBI suppression framework. The optimal linear filter for the recovery of the spread-spectrum signal is derived, and its performance is analyzed in terms of probability of error and signal-to-interference ratio (SIR). It is shown that the performance of this optimal filter is very close to the situation when there is no narrowband interference present, even at the presense of very strong interference. This application requires the treatment of a single narrowband digital signal as a group of related, virtual spread-spectrum signals with very simple spreading codes. This model gives a special structure to the matrices appearing in the optimization problem implied by the MMSE criterion, and this structure is exploited herein to develop and analyze a practical adaptive algorithm. The major contribution of this paper beyond the previous work in the field of NBI suppression is the development of this adaptive algorithm that can exploit the advantages of multiuser detection in suppressing narrowband digital interference from spread-spectrum networks.     

基于时间序列自适应建模的粒子滤波动态目标跟踪

在目标跟踪中为达到目标的运行模型与实际轨迹相符,本文提出基于时间序列自适应建模的粒子滤波算法（TS_PF）。采用时间序列方法动态构建预测模型,并将粒子滤波算法中一系列加权粒子以该模型进行状态转移,运用粒子滤波重采样技术,使预测误差进一步减小,预测精度逼近最优估计。仿真实验表明在粒子滤波算法中采用时间序列自适应建模,能够...     

Comparative tracking performance of the LMS and RLS algorithms forchirped narrowband signal recovery

This paper studies the comparative tracking performance of the recursive least squares (RLS) and least mean square (LMS) algorithms for time-varying inputs, specifically for linearly chirped narrowband input signals in additive white Gaussian noise. It is shown that the structural differences in the implementation of the LMS and RLS weight updates produce regions where the LMS performance exceeds that of the RLS and other regions where the converse occurs. These regions are shown to be a function of the signal bandwidth and signal-to-noise ratio (SNR). LMS is shown to place a notch in the signal band of the mean lag filter, thus reducing the lag error and improving the tracking performance. For the chirped signal, it is shown that this produces smaller tracking error for small SNR. For high SNR, there is a region of signal bandwidth for which RLS will provide lower error than LMS, but even for these high SNR inputs, LMS always provides superior performance for very narrowband signals     

最小均方误差检测器对扩频系统中窄带干扰的抑制性能分析

本文首先说明当码元间隔内的码片数目与扩频序列周期相等时,直接序列扩频(DSSS)系统中最小均方误差(MMSE)意义下的最优滤波器也是最小误码率意义下的最优滤波器,因而能很好地抑制大多数干扰样式。本文具体分析了最小均方误差检测器对音频干扰以及自回归干扰的抑制性能,给出了详细的推导过程以及结论。     

调制混合滤波器组的宽带模拟信号采样研究

对于超宽带模拟信号,很难用单个模拟数字转换器（ADC）直接进行采样。该文提出了一种新的并行调制混合滤波器组结构用于实现超宽带模拟信号的采样,首先,将每一路宽带模拟输入信号进行余弦调制,并用相同的低通模拟滤波器均匀分割输入信号的带宽;然后,采用相同的ADC将子带信号数字化;各路子带信号通过上采样器后用数字综合滤波器综合得到原宽带模拟输入信号的数字重构。综合滤波器采用总体最小二乘准则下的特征值滤波器设计方法得到。本文所提出的系统结构不需要使用高速的采样保持电路,降低了系统实现的难度,并且设计的系统具有与其它混合滤波器组相近的重构性能。仿真结果表明了本方法的有效性。      

Frequency shift keyed narrowband interference rejection: optimal exponential weighting factor for the RLS algorithm

Cochannel narrowband interference can limit the performance of direct sequence spread spectrum (DSSS) and high frequency (HF) systems. Narrowband interference (NBI) can be single tone, chirped or frequency shift keyed (FSK) in nature and numerous techniques for its removal have been proposed. Linear adaptive prediction filters based on autoregressive modelling have been suggested owing to their ability to perform in a non-stationary environment. In the FSK narrowband interference case, adaptive filters are susceptible to excess residual errors owing to instantaneous frequency step changes and the finite convergence time required for the filter to adapt to a new interference frequency. The signal degradation owing to this type of interference becomes greater in high SNR regimes and has been found to be a function of the frequency parameters of the FSK interference signal. The paper discusses the convergence and frequency tracking properties of the recursive least squares (RLS) adaptive lattice filter using a posteriori estimation errors in the presence of FSK narrowband interference. An optimal exponential weighting factor that balances convergence time and steady state error is derived for this case of NBI. Results are compared to those of a previously proposed fast converging minimum frequency error (FCMFE) RLS lattice filter.     

New unbiased adaptive IIR filter: it’s robust and variable step-size versions and application to active noise control

This paper proposes a robust variable step-size adaptive IIR filter realized by a new bias-free structure (BFS). Unlike equation error (EQE) method that uses a desired signal contaminated with observation noise, the BFS employs a filter driven by the output of the plant estimate and this achieves a bias-free estimate of the denominator of the system function. In addition, the adaptation is made robust to the observation noise by the Griffiths’ LMS adaptation, which uses the cross-correlation estimate between the input and the desired signal for its adaptation gradient computation. A robust variable step-size adaptation is also realized by the Griffiths’ gradient. The proposed structure is referred to as BFSGV and has good modeling capability with improved convergence rate and reduced misadjustment. For system identification, the proposed BFSGV algorithm gives a 3 dB improvement in the performance index over EQE method. The proposed BFSGV has been applied to active noise control (ANC). The BSFGV structure is used for secondary path (SP) estimation, and for the main path (MP), BFS structure with step-size varied according to Okello’s method (BSFV) is used. The new ANC system for narrowband noise field is found to be having 4 times faster convergence rate and an additional noise reduction of 15dB over that FIR for MP and the EQE for SP. Further, the use of the proposed ANC IIR algorithm achieves computational savings compared to that of FIR. For the broadband noise field, the proposed method that uses BSFV for MP and BSFGV for SP provides 18 times faster convergence rate and 2.5 dB reduction in ANC error compare to that of the ANC using FIR for MP and the EQE for SP estimation.     

High robustness of an SR motor angle estimation algorithm usingfuzzy predictive filters and heuristic knowledge-based rules

In this paper, the operation of a fuzzy predictive filter used to provide high robustness against feedback signal noise in a fuzzy logic (FL)-based angle estimation algorithm for the switched reluctance motor is described. The fuzzy predictive filtering method combines both FL-based time-series prediction, as well as a heuristic knowledge-based algorithm to detect and discard feedback signal error. As it is predictive in nature, the scheme does not introduce any delay or phase shift in the feedback signals, In addition, the fuzzy predictive filter does not require any mathematical modeling of the noise and, therefore, can be used effectively to control nonGaussian impulsive-type noise. An analysis of the noise and error commonly found in practical motor drives is given, and how this can effect position estimation. It is shown using experimental results that the FL-based scheme can cope well with erroneous and noisy feedback signals     

Adaptive narrow-band interference rejection in a DS spread-spectrumintercept receiver using transform domain signal processing techniques

An intercept receiver which uses a transform-domain-processing filter is described. This receiver detects direct-sequence binary-phase-shift-keyed (DS-BPSK) spread-spectrum signals in the presence of narrowband interference by employing adaptive narrowband interference rejection techniques. The improvement in the system performance over that of conventional detection techniques is shown by presenting the results of experimental measurements of probability of detection versus false alarm for an enhanced total power detector. Also presented are certain results corresponding to detection of the spectral lines generated at twice the carrier frequency, wherein the goal is often not just signal detection, but also carrier frequency estimation. The receiver uses one of two transform-domain-processing techniques for adaptive narrowband interference rejection. In the first technique, the narrowband interference is detected and excised in the transform domain by using an adaptive notch filter. In the second technique, the interference is suppressed using soft-limiting in the transform domain