A robust adaptive beamformer for microphone arrays with a blockingmatrix using constrained adaptive filters

This paper proposes a new robust adaptive beamformer applicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a new adaptive blocking matrix using coefficient-constrained adaptive filters (CCAFs) and a multiple-input canceller with norm-constrained adaptive filters (NCAFs). The CCAFs minimize leakage of the target-signal into the interference path of the GSC. Each coefficient of the CCAFs is constrained to avoid mistracking. The input signal to all the CCAFs is the output of a fixed beamformer. In the multiple-input canceller, the NCAFs prevent undesirable target-signal cancellation when the target-signal minimization at the blocking matrix is incomplete. The proposed beamformer is shown to be robust to target-direction errors as large as 200 with almost no degradation in interference-reduction performance, and it can be implemented with several microphones. The maximum allowable target-direction error can be specified by the user. Simulated anechoic experiments demonstrate that the proposed beamformer cancels interference by over 30 dB. Simulation with real acoustic data captured in a room with 0.3-s reverberation time shows that the noise is suppressed by 19 dB. In subjective evaluation, the proposed beamformer obtains 3.8 on a five-point mean opinion score scale, which is 1.0 point higher than the conventional robust beamformer     

Spectral analysis of subband adaptive digital filters

Subband adaptive digital filters at stationary points are analyzed in the frequency domain. Approximate expressions for the optimal subband filters are presented, and then, a spectral representation of the error variance is derived. These are expressed in the frequency domain and, hence, enable us to see the aliasing effects in subband adaptive filtering     

Lower error bound for oversampled subband adaptive filters

The authors evaluate error performance limitations in oversampled subband adaptive filter applications based on an analysis of aliasing in the subband signals. The power spectral density of the minimum error signal is given by the aliased signal components. The presented analysis closely agrees with simulation results     

Normalised subband adaptive filtering with extended adaptiveness on degree of subband filters

This paper proposes an adaptive normalised subband adaptive filtering (NSAF) to accomplish the betterment of NSAF performance. In the proposed NSAF, an extended adaptiveness is introduced from its variants in two ways. In the first way, the step-size is set adaptive, and in the second way, the selection of subbands is set adaptive. Hence, the proposed NSAF is termed here as variable step-size-based NSAF with selected subbands (VS-SNSAF). Experimental investigations are carried out to demonstrate the performance (in terms of convergence) of the VS-SNSAF against the conventional NSAF and its state-of-the-art adaptive variants. The results report the superior performance of VS-SNSAF over the traditional NSAF and its variants. It is also proved for its stability, robustness against noise and substantial computing complexity.     

Robust adaptive beamforming for large-scale arrays

For a large-scale adaptive array, heavy computational load and high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. Moreover, the large-scale array becomes extremely sensitive to array imperfections. First, based on a restructured recursive linearly constrained minimum variance algorithm and a gradient-based optimization method, a new robust recursive linearly constrained minimum variance (RRLCMV) algorithm is proposed in this paper. The computational load of the RRLCMV algorithm is on the order of o(N), which is less than that of the conventional gradient-based robust adaptive algorithm. Then, a new efficient parallel robust recursive linearly constrained minimum variance (PRRLCMV) adaptive algorithm is proposed by appropriately partitioning the RRLCMV algorithm into a number of operational modules. It can be easily executed in a distributed-parallel-processing fashion, sequentially and in parallel. As a result, the PRRLCMV algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. Finally, an implementation scheme of the PRRLCMV algorithm based on a distributed-parallel-processing system is also proposed. The simulation results demonstrate that the new PRRLCMV algorithm can significantly reduce the degradation due to various array errors.     

Robust adaptive beamforming for broadband arrays

It is very important in many applications to preserve a desired signal without distortion. This paper presents a robust adaptive beamforming method to extract a desired signal from the signals received by broadband arrays. The proposed method relaxes the requirement of approximate knowledge of the desired direction and the sensor gains and delays (phases). Also the method enhances the desired signal based on a focusing transform for that signal, requires less computation than the taped-delay-line beamforming method, and provides good results even in a multipath environment. Computer simulations are given to support the proposed method.On leave from the Department of Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, People's Republic of China.Nanjing 210016, People's Republic of China.     

基于麦克风阵列的宽带健壮自适应波束形成算法

研究了用于麦克风阵列语音增强的宽带健壮自适应波束形成算法。该算法结合频率聚焦技术和对角加载技术。在此基础上,通过优化最坏情况下的波束性能确定对角加载因子,求得了最优加载因子的近似解析表达式。和相关算法相比,使用最坏情况性能优化的算法具有更好的语音增强性能,由于求得了最优加载因子的解析解,还具有运算量低、容易实现等优点。同时,该解析解揭示了哪些因素可以影响最优加载因子,以及如何影响。计算机仿真验证了该结果的正确性和有效性。     

Robust perturbation algorithms for adaptive antenna arrays

The generation of a perturbation sequence for an adaptive beamformer is described. This perturbation sequence permits simultaneous adaption and reception by use of weight perturbations that do not obstruct the look direction constraint. It is shown that this sequence is generally shorter in length than previously described sequences and offers scope for computational savings through reduction of the number of projection operations required. Convergence in the mean of the resulting adaptive algorithm is demonstrated. Experiments conducted using a four-element linear array operating in the MW RF range have confirmed that the predicted results are achievable under the nonideal conditions of quantized array weights and finite word length arithmetic     

Delayless subband adaptive filtering using the Hadamard transform

In this correspondence, an analysis of a delayless critically decimated subband adaptive filter structure is presented. In this structure, adaptive weights in each subband are computed by the LMS algorithm and then transformed into those in fullband by the Hadamard transform. It is shown that a stationary point of the proposed algorithm corresponds to the fullband Wiener filter. Some numerical results are also presented to show the performance of this scheme     

Self-localizing dynamic microphone arrays

This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the proposed spatial observability function based microphone array integration technique, a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to localize and track a microphone array with a known and fixed geometrical structure, which can be viewed as the inverse sound localization problem. Simulations using a two-element dynamic microphone array illustrate the ability of the proposed technique to correctly localize and estimate the orientation of the array even in a very reverberant environment. Using 1 s male speech segments from three speakers in a 7 m by 6 m by 2.5 m simulated environment, a 30 cm inter-microphone distance, and PHAT histogram SLF generation, the average localization error was approximately 3 cm with an average orientation error of 19/spl deg/. The same simulation configuration but with 4 s speech segments results in an average localization error less than 1cm, with an average orientation error of approximately 2/spl deg/. Experimental examples illustrate localizations for both stationary and dynamic microphone pairs.     

Convergence analysis of alias-free subband adaptive filters based on a frequency domain technique

Convergence analysis of alias-free subband adaptive filters (SADFs) is presented based on a frequency-domain technique where instead of analyzing the adaptive algorithms in the time-domain, the averaging method and the ordinary differential equation (ODE) method are applied to the frequency-domain expressions of the adaptive algorithms converted by the discrete Fourier transform. As an alias-free SADF algorithm, the SADF proposed by Pradhan and Reddy is known. In this paper, this technique is first applied to the Pradhan's SADF. The stability of the Pradhan's SADF is verified in the frequency domain, and a simple formula to evaluate the mean square error (MSE) of the algorithm is theoretically derived. By using a slight modification, the technique can be applied to the two-band delayless subband adaptive filter (DLSADF) with the Hadamard transform. The stability condition and the MSE of the DLSADF with the Hadamard transform are also obtained. Simulation results of both algorithms show the validity of the theoretical results.     

Space-time adaptive processing using circular arrays

A direct data-domain (D³) least-squares space-time adaptive-processing (STAP) approach is presented for adaptively enhancing radar signals in a non-homogeneous environment of jammers, clutter, and thermal noise, utilizing a circular antenna array. The non-homogeneous environment may consist of non-stationary clutter. The D ³ approach is applied directly to the data collected by a circular antenna array (utilizing space), and in time (Doppler) diversity. Conventional STAP generally utilizes statistical methodologies, based on estimating a covariance matrix of the interference, using the data from various range cells of the circular array and assuming that it is a uniform linear array. However, for highly transient and inhomogeneous environments, the conventional statistical methodology may be difficult to apply. Moreover, the error in forming the covariance matrix by assuming that the data collected by the circular array is assumed to be a uniform linear array is highly problem dependent. Hence the D³ method is presented, as it analyzes the data in space and time over each range cell separately. However, it treats the antenna array as circular, i.e., it deals with the antenna structure in its proper form. Limited examples are presented to illustrate the application of this approach     

Region adaptive subband image coding

We present a region adaptive subband image coding scheme using the statistical properties of image subbands for various subband decompositions. Motivated by analytical results obtained when the input signal to the subband decomposition is a unit step function, we analyze the energy packing properties toward the lower frequency subbands, edges, and the dependency of energy distribution on the orientation of the edges, in subband decomposed images. Based on these investigations and ideal analysis/synthesis filtering done in the frequency domain, the region adaptive subband image coding scheme extracts suitably shaped regions in each subband and then uses adaptive entropy-constrained quantizers for different regions under the assumption of a generalized Gaussian distribution for the image subbands. We also address the problem of determining an optimal subband decomposition among all possible decompositions. Experimental results show that visual degradations in the reconstructed image are negligible at a bit rate of 1.0 b/pel and reasonable quality images are obtainable at rates as low as 0.25 b/pel.     

Subband processing for broadband microphone arrays

This paper considers array processing for wideband signals. The optimization techniques and associated performance results correspond to steerable but fixed beam microphone arrays, to be used in hearing aid applications, both in free-space and reverberant conditions. We first review the results on maximum energy (ME) broadband arrays. We subsequently formulate optimization criteria for array subband processing. The uniformly spaced subband and the non-uniformly spaced subband using quadrature mirror filter approaches are treated. Finally, various simulation results for free-space and reverberant conditions are presented to demonstrate the usefulness of this class of microphone arrays, as well as the feasibility of quadrature mirror filter-based subband processing.This work was partially supported by the House Ear Institute and the Retirement Research Foundation.     

Synthesis of optical filters using ring resonator arrays

Multiple micro-optical four-port resonators, such as ring resonators, can be combined to obtain response functions not attainable with a single element. A matrix propagator method for analysis of multi-element filters is presented which takes into account bidirectional coupling among elements of a linear resonator array. Examples of filters attaining flat-top passbands, desirable for all-optical wavelength-division-multiplexed networks, are given     

Color image processing using adaptive multichannel filters

New adaptive filters for color image processing are introduced and analyzed. The proposed adaptive methodology constitutes a unifying and powerful framework for multichannel signal processing. Using the proposed methodology, color image filtering problems are treated from a global viewpoint that readily yields and unifies previous, seemingly unrelated, results. The new filters utilize Bayesian techniques and nonparametric methodologies to adapt to local data in the color image. The principles behind the new filters are explained in detail. Simulation studies indicate that the new filters are computationally attractive and have excellent performance.     

A delayless subband adaptive filter architecture

Some adaptive signal processing applications, such as wideband active noise control and acoustic echo cancellation, involve adaptive filters with hundreds of taps. The computational burden associated with these long adaptive filters precludes their use for many low-cost applications. In addition, adaptive filters with many taps may also suffer from slow convergence, especially if the reference signal spectrum has a large dynamic range. Subband techniques have been previously developed for adaptive filters to solve these problems. However, the conventional approach is ruled out for many applications because delay is introduced into the signal path. The paper presents a new type of subband adaptive filter architecture in which the adaptive weights are computed in subbands, but collectively transformed into an equivalent set of wideband filter coefficients. In this manner, signal path delay is avoided while retaining the computational and convergence speed advantages of subband processing. An additional benefit accrues through a significant reduction of aliasing effects. An example of the general technique is presented for a 32-subband design using a polyphase FFT implementation. For this example, the number of multiplies required are only about one-third that of a conventional full band design with zero delay, and only slightly greater than that of a conventional subband design with 16 ms delay     

Multiplierless PR quadrature mirror filters for subband imagecoding

This correspondence deals with suboptimal multiplierless perfect reconstruction quadrature mirror filter (PR-QMF) solutions. It is shown that multiplierless PR-QMFs perform comparable to or better than the known filter banks and discrete-cosine-transform-based (DCT-based) image coding techniques objectively and subjectively. They are very efficient to implement on very large scale integrated (VLSI) systems. These PR-QMFs might find uses in real-time image and video coding and other applications