Showing papers on "Adaptive beamformer published in 1997"

A signal subspace tracking algorithm for microphone array processing of speech

Abstract: This paper presents a method of adaptive microphone array beamforming using matched filters with signal subspace tracking. Our objective is to enhance near-field speech signals by reducing multipath and reverberation. In real applications such as speech acquisition in acoustic environments, sources do not propagate along known and direct paths. Particularly in hands-free telephony, we have to deal with undesired propagation phenomena such as reflections and reverberation. Prior methods developed adaptive microphone arrays for noise reduction after a time delay compensation of the direct path. This simple synchronization is insufficient to produce an acceptable speech quality, and makes adaptive beamforming unsuitable. We prove the identification of source-to-array impulse responses to be possible by subspace tracking. We consequently show the advantage of treating synchronization as a matched filtering step. Speech quality is indeed enhanced at the output by the suppression of reflections and reverberation (i.e., dereverberation), and efficient adaptive beamforming for noise reduction is applied without risk of signal cancellation. Evaluations confirm the performance achieved by the proposed algorithm under real conditions.

Design of an adaptive antenna array for tracking the source of maximum power and its application to CDMA mobile communications

Abstract: This paper presents an alternative method of adaptive beamforming. Under an assumption that the desired signal is large enough compared to each of interfering signals at the receiver, which is preconditionally achieved in code division multiple access (CDMA) mobile communications by the chip correlator, the proposed technique provides for a suboptimal beam pattern that increases the signal-to-noise/signal-to-interference ratio (SNR/SIR) and eventually increases the capacity of the communication channel. The main advantages of the new technique are: (1) the procedure requires neither reference signals nor a training period; (2) the signal intercoherency does not affect the performance or complexity of the entire procedure; and (3) the total amount of computation is tremendously reduced compared to that of most conventional beamforming techniques such that the suboptimal beam pattern is produced at every snapshot on a real-time basis. In fact, the total computational load for generating a new set of weights including the update of an N-by-N autocovariance matrix is O(3N/sup 2/+12N). It can further be reduced down to O(11N) by approximating the matrix with the instantaneous signal vector.

Strategies for combining acoustic echo cancellation and adaptive beamforming microphone arrays

Abstract: New concepts for efficient combination of acoustic echo cancellation (AEC) and adaptive beamforming microphone arrays (ABMA) are presented. By decomposing common beamforming methods into a time-invariant part, which the AEC can integrate, and a separate time-variant part, the number of echo cancellers is minimized without rendering the system identification problem more difficult. Methods for controlling the interaction of ABMA and AEC are outlined and implementations for typical microphone array applications are discussed.

System and method for adaptive interference cancelling

Abstract: An adaptive system and method for reducing interference in a signal received from an array of sensors. Adaptive filters are used to generate cancelling signals that closely approximate the interference present in the received signal. The adaptive filter weights are converted into the frequency domain where the frequency representation values in a selected frequency range are truncated to avoid signal leakage involving narrow band signals. Decolorizing filters are used to produce the cancelling signals having a flat frequency spectrum. Normalized power difference is used to limit the operation of the adaptive filters to the case where there is some directional interference to be eliminated.

Robust beamforming for interference rejection in mobile communications

Abstract: The problem of robust beamformer design for mobile communications applications in the presence of moving co-channel sources is addressed. A generalization of the optimum beamformer based on a statistical model accounting for source movement is proposed. The new method is easily implemented and is shown to offer dramatic improvements over conventional optimum beamforming for moving sources under a variety of operating conditions.

Adaptive beamforming algorithms with robustness against jammer motion

Abstract: The performance of adaptive array algorithms is known to degrade in rapidly moving jammer environments This degradation occurs due to the jammer motion that may bring the jammers out of the sharp notches of the adapted pattern We develop the robust modifications of the sample matrix inversion (SMI) algorithm, loaded SMI (LSMI) algorithm, and eigenvector projection (EP) algorithm by means of artificial broadening of the null width in the jammer directions For this purpose, data-dependent sidelobe derivative constraints that do not require any a priori information about the jammer directions are used

Robust DMR and multi-rate adaptive beamforming

Abstract: Dominant mode rejection (DMR) is an approach to adaptive beamforming in which only the large eigenvalues of the correlation matrix and their eigenvectors are used. It requires fewer snapshots due to the reduced degrees-of-freedom. Once the partial eigendecomposition has been performed, a variety of opportunities arise to adjust the algorithms on a beam-by-beam basis without significant additional computations. A modification is developed to improve the robustness to signal mismatch. An approach to controlling the quiescent beam pattern that works for ocean acoustic noise is also presented. The standard approaches fail because source array elements are usually spaced closer than one-half wavelength so that the noise is correlated. Finally a two stage adaptive approach is introduced. It involves a slowly adapting algorithm optimized for nearly stationary conditions followed by a thresholded DMR that rapidly adapts to dynamic interference, but only when the interference is strong.

Eigenspace-based adaptive array beamforming with robust capabilities

Abstract: This paper deals with adaptive array beamforming based on eigenspace-based (ESB) techniques with robust capabilities It has been shown that ESB adaptive beamformers demonstrate the advantages of fast convergence speed and less sensitivity to steering angle error over conventional beamformers In conjunction with a signal subspace construction method, we present an efficient technique to achieve the advantages of ESB adaptive beamforming with less computing cost and more robust capabilities over existing ESB techniques Several computer simulation examples are provided for illustrating the effectiveness of the proposed technique

Statistical analysis of the eigenvector projection method for adaptive spatial filtering of interference

Abstract: Adaptive beamforming based on eigenanalysis of the covariance matrix of the outputs of an array of sensors has been shown to be most effective for removing directional interference The author provides an analytical performance evaluation of the signal-to-noise-plus-interference ratio (SNIR) of the adaptive beamformer obtained by the eigenvector projection (EVP) method The approach presented to derive the statistical properties is based only on the statistics of the sensor outputs, rather than on the asymptotical distribution of the eigenvectors of the sample covariance matrix The expression for the probability density function can be used to predict the achievable rate of convergence and the resulting loss of performance for arbitrary sample sizes and interference environments, particularly when compared to the classical Wiener filter solutions or other suboptimum projection methods In the case of an infinite interference-to-noise ratio (INR), it is shown that the SNIR is exactly beta-distributed and independent of the number of sensor elements Furthermore, the case of finite INR is discussed and it is shown that the distribution is valid for nearly all practical cases Finally, some relevant numerical examples are presented to illustrate the agreement with the theoretical results

Large-aperture imaging using transducer array with adaptive element pitch control

Abstract: An adaptive transducer array in which the element pitch is controlled by the imaging system depending on the mode of operation. A multiplicity of transducer elements are connected to a multiplicity of beamformer channels by a multiplexing arrangement having multiple states. In one multiplexer state, successive transducer elements are respectively connected to successive beamformer channels to produce an aperture having a small element pitch equal to the distance separating the centerlines of two adjacent transducer elements. In another multiplexer state, selected transducer elements are respectively connected to successive beamformer channels to produce an aperture having an increased element pitch equal to the small pitch multiplied by a factor of two or more. The aperture is increased by connecting together pairs of adjacent elements to a respective beamformer channel or by connecting every other element to a respective beamformer channel to form a sparse array.

Near-field beamforming for microphone arrays

Abstract: This paper describes the application of array optimization techniques to improving the near-field response of an arbitrary microphone array The optimization exploits the differences in wavefront curvature between near-field and far-field sound sources and is suitable for reverberation reduction in small rooms The optimum near-field beamformer provides increased array gain over that obtained from a uniformly weighted delay-and-sum beamformer

Effects of motion on adaptive arrays

Abstract: Adaptive beamforming procedures based on linear least-squares estimation of a wanted signal, such as the sample matrix inverse (SMI) algorithm, have been shown to successfully excise unwanted interference from the beamformer output. It is usually assumed that the signal environment is stationary, however under nonstationary conditions, such as those experienced by an array mounted on a rapidly moving platform, performance may be significantly degraded. The paper examines the effects of array motion on the structure of the sample covariance matrix and derives expressions for the resulting eigenvalues. These results are used to show that even when the same data is used both to compute the adaptive weights and to form the beamformer output, performance can be sensitive to extremely small movements of the array. In particular, simple closed-form expressions are derived for the limiting angular displacements of linear arrays which can be tolerated without significant performance degradation during the time taken to acquire sufficient data to update the weights.

A robust generalized sidelobe canceller with a blocking matrix using leaky adaptive filters

Abstract: A new robust generalized sidelobe canceller structure suited to adaptive microphone arrays is proposed. In the proposed structure, the blocking matrix incorporates leaky adaptive filters whose input signals are the output of the fixed beamformer. The leaky adaptive filters alleviate the influence of phase error, which results in the robustness. Undesirable target-signal cancellation is avoided in the presence of array imperfections such as target-direction error and microphone-position error. The proposed structure can pick up a target signal with little distortion when the error in the sight direction from the target direction is large. It can be implemented with a small number of microphones. Simulations demonstrate that the proposed structure, designed to allow 20° directional error, reduces interference by more than 18 dB. © 1997 Scripta Technica, Inc. Electron Comm Jpn Pt 3, 80(8): 56–65, 1997

Adaptive beamforming based on the conjugate gradient algorithm

Abstract: Adaptive filtering using a version of the conjugate gradient (CG) method which does not involve matrix inversions and is hence computationally attractive has been presented in [1]. The method which uses a time average over a suitably chosen window in order to generate the required gradients, has been used in [2] for the design of an adaptive beamformer. The algorithm essentially uses time diversity to obtain improved performance. We consider a modification which essentially combines spatial and time diversity to obtain an algorithm for adaptive beamforming which has potential application in cellular communication systems. Simulation results are presented to demonstrate the performance of the algorithm.

Acoustic target detection, tracking, classification, and location in a multiple-target environment

Abstract: Commercially available Digital Signal Processors can be used to host state-of-the-art air acoustic adaptive beamforming algorithms in low power, low cost, real-time sensor systems. These systems are suitable for use as both unattended ground sensors and in platform-mounted applications. This paper describes a compact state-of-the-art, real-time adaptive beamforming approach and sensor hardware. Recent day/night field test results for detection range, multiple target tracking, and classification are presented for various vehicles. The data focuses on long range target detection as well as tracking and classification performance in multiple target environments composed of closely spaced or clustered targets. Target location (x-y position) performance using real-time netted sensors (sensor fusion) is also presented.

Evaluation of the dominant mode rejection beamformer using reduced integration times

Abstract: Increasing the number of hydrophones in an array should increase beamformer performance. However, when the number of hydrophones is large, integration times must be long enough to give accurate cross-spectral matrix (CSM) estimates, but short enough so that the dynamic behavior of the noise described by the CSM is captured. The dominant mode rejection (DMR) beamformer calculates adaptive weights based on a reduced rank CSM estimate, where the CSM estimate is formed with a subset of the largest eigenvalues and their eigenvectors. Since the largest eigenvalue/eigenvector pairs are estimated rapidly, the integration time required is reduced. The purpose of this study was to examine the DMR beamformer performance using a bottom-mounted horizontal line array in a shallow-water environment. The data were processed with a fully adaptive beamformer and the DMR beamformer. The DMR beamformer showed better performance than the fully adaptive beamformer when using arrays with larger numbers of hydrophones. Thus, in highly dynamic noise environments, the DMR beamformer may be a more appropriate implementation to use for passive sonar detection systems.

Constrained beamforming for cyclostationary signals

Abstract: The classical linearly constrained minimum variance (LCMV) beamformer corresponds, in the general case, to the linear, time invariant (TI) and spatio-temporal (ST) complex filter, the output power of which is minimized under some linear constraints. Optimal for stationary signals, this beamformer becomes sub-optimal for (quasi)-cyclostationary observations for which the optimal complex filters are (poly)-periodic (PP) and, under some conditions of widely linear non-circularity. Using these results and the fact that PP filtering is equivalent to FREquency SHifted (FRESH) filtering, the purpose of this paper is to present a first extension of the classical LCMV beamformer, taking into account the potential (quasi)-cyclostationarity and non-circularity properties of the observations. This new cyclic LCMV beamformer is shown to have an equivalent cyclic generalized sidelobe canceller (GSLC) structure. The performance computation of this new cyclic beamformer shows the interest of the latter in cyclostationary contexts and opens a reflection about the optimal constraint choice.

A new projection based algorithm for low sidelobe pattern synthesis in adaptive arrays

Abstract: The primary objective of adaptive beamforming is to suppress jamming signals while maintaining the response of the array in the desired signal direction. It is also desirable to obtain low sidelobes in the adaptive beam pattern and to minimise sidelobe jitter in order to aid the performance against clutter and pulsed deception jammers. Sample matrix inversion (SMI) is one of the simplest adaptive beamforming algorithms, involving minimisation of the average output power for a set of input data vectors (snapshots), subject to constraints on the beam pattern. However, the basic SMI algorithm tends to produce beam patterns with high sidelobes away from the jammer directions and considerable weight and sidelobe jitter. Penalty function methods as given in Hughes and McWhirter (see SPIE Proc.2563, p.170-81) and methods based on subspace projection e.g. Richardson (see Proc. of EUSIPCO-94, vol.3, p.1301-4, 1994), are two types of method which can be used to overcome the problem of high sidelobes and weight jitter while maintaining an acceptable signal to noise plus interference ratio (SNIR). This paper presents a new algorithm, which has been termed `constrained adaptive beam pattern synthesis' (CAPS). It is a projection based algorithm which incorporates the pattern fitting element of penalty function methods in order to obtain the best possible sidelobe levels. It therefore combines the benefits of subspace and penalty function approaches. Following an explanation of the algorithm, an investigation of its performance in the presence of mainlobe and sidelobe jamming is presented.

A novel method to improve the performance of Capon's minimum variance estimator

Abstract: An improved version of Capon's (1969) minimum variance estimator (MVE) direction finding algorithm, titled "loaded Capon", is proposed. In the new method, the diagonal elements of the covariance matrix are loaded with a fraction of the total power contained within the covariance matrix. A similar form of covariance loading has been proposed, by Carlson (1988), for adaptive beamforming when using sampled matrix inversion. Data from HF and VHF transmissions received with a multichannel direction finding system are used to verify the superior performance of the modified algorithm over the original MVE method. The performance of the loaded Capon is also compared with MUSIC, where it is found to have comparable performance, with the advantage of a greatly reduced computational burden.

Cooperative signal reception and down-link beam forming in cellular mobile communications

Abstract: The main focus of this presentation is adaptive down-link beam forming for PSK modulation based on subspace decomposition. A down-link beam forming algorithm with reasonable complexity is proposed which requires neither detection of other users' signals nor knowledge about the direction-of-arrival (DOA)s of the incident path components. The desired signal subspace is extracted from the composite space in cooperation with the optimal beam forming for uplink signal reception.

An adaptive algorithm for broadband frequency invariant beamforming

Abstract: Frequency invariant beamforming is array processing in which the spatial response remains constant (with respect to frequency) within a wide frequency band of interest. We present a new algorithm for adaptive broadband beamforming which solves a minimum variance beamforming problem, with a structural frequency invariant beampattern constraint. This constraint allows us to reduce the dimension of the adaptation problem. The proposed algorithm is a block adaptive LMS algorithm which uses only a fraction of the parameters of a conventional fully adaptive array. Hence, the computational complexity is reduced and the convergence speed is increased. A simulation example is presented to demonstrate the new algorithm.

Fast adaptive super-exponential multistage beamforming for cellular base-station transceivers with antenna arrays

Abstract: A new adaptive algorithm for blind adaptive beamforming is studied and applied to the problem of array processing in a cellular communication system using AMPS. The method is based on high-order statistics time-domain processing, and seems to be a good compromise in terms of computational complexity between some intensive high resolution subspace methods recently proposed and the simple, but not always satisfactory gradient-based CMA approach.

Control method of adaptive array and adaptive array device

Abstract: PROBLEM TO BE SOLVED: To reduce the noise caused by breathing and to speedingly follow up the movement of an interference signal source while maintaining the quality of the output signals high. SOLUTION: In a beam former 2, the sensitivity against an object signal source is made higher than the sensitivity against other signal sources. In a beam former 3, the sensitivity against the object signal source is made lower than the sensitivity against other signal sources. Then, the step size of an adaptive algorithm in adaptive filters 70 to 7M-1 is determined using the indexes related to the output signal amplitudes of the beam formers 2 and 3. Thus, the degradation of the signals in a final output and the noise caused by breathing are reduced even though the constant, which determines the step size, is set larger in order to increase the follow up speed against the movement of an interference signal source.

Robust adaptive beamforming for broadband arrays

Abstract: 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.

Adaptive beamforming with partitioned frequency-domain filters

Abstract: In this paper an adaptive broadband beamformer is presented which is based on a partitioned frequency-domain least-mean-square algorithm (PFDLMS) This block algorithm is known for its efficient computation and fast convergence even when the input signals are correlated In applications where long filters are required but only a small processing delay is allowed, a frequency domain adaptive beamformer without partitioning demands a large FFT length despite the small block size The FFT length can be shortened significantly by filter partitioning, without increasing the number of FFT operations The weaker requirement on the FFT size makes the algorithm attractive for acoustical applications

Adaptive beamforming for wideband jamming cancellation

Abstract: This paper presents two important results of our recent studies on adaptive wideband beamforming using subarrays and linear frequency modulation (LFM) for high resolution target image. By transmitting periodical sweeping waveforms, the received non-coherent signals, such as jammers, become nonstationary and therefore require special treatment to predict the system performance analytically. We approach the problem by constructing the system's covariance matrices from the elemental correlations. By incorporating the subarraying techniques and array steering methods in the associated elements, it is possible to compare the system performance adopting different signal processing schemes such as time-delay (TD) and phase-weight (PW) steering methods for the auxiliary array. Simulation results show that PW method perform better than TD method.

Effective interference cancellation scheme based on smart antennas

Abstract: An effective interference cancellation scheme based on a new multipath model is introduced. A CM (constant modulus) equalisation approach based on an adaptive array with a spatial prefilter is derived. It has been proven by numerical simulation that this method achieves a better performance, even under serious multipath conditions.

CMA beamforming for multipath correlated sources

Abstract: Blind adaptive beamforming is often used in communication systems to combat co-channel interference. Among a number of techniques, the constant modulus algorithm (CMA) has proven to be an effective tool for blind beamforming of uncorrelated signals. Unfortunately, CMA beamformers encounter problems for correlated signals and interferences. In this paper, we consider correlated co-channel input signals as a result of multipath. We present two adaptation methods based on CMA to capture distinct signal sources. One approach is to use an orthogonal projection constraint on the beamformer parameters. The other approach relies on the independence of source signals and exploit a Gram-Schmidt orthogonalization at beamformer outputs. The performance of our methods is shown through computer simulations.

Adaptive beamforming against reverberation for a three-sensor array

Abstract: Two algorithms for beamforming and bearing estimation of echoes from an active sonar transmission in a strongly reverberant bistatic environment are described. The receiving array consists of a single omnidirectional sensor and two collocated orthogonal dipole sensors, and is deployed in a bistatic configuration. Both beamforming algorithms are based on minimum-variance techniques. The first algorithm matches the pattern of the minimum-variance beamformed data with that expected from an impulse at a known bearing. The second algorithm reforms the sensor data from the minimum-variance beam response. Fixed-coefficient limacon beamforming is then applied to estimate the beam power map with reduced reverberation. The detection performance of both techniques is evaluated by injection of a synthetic target echo into experimental reverberation data. The results suggest an enhanced array gain against reverberation of the order of 3 dB for reasonable values of signal strength and probability of false alarm, compared to a direct application of fixed-coefficient limacon beamforming. The root-mean-squared bearing error for both techniques is reduced significantly, when compared to the limacon beamformer, by factors varying from 2 to 5.