Showing papers on "Adaptive beamformer published in 1998"

Joint optimal power control and beamforming in wireless networks using antenna arrays

Abstract: The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to increase the capacity in wireless communication networks. The minimum variance distortionless response beamformer maximizes the signal-to-interference-and-noise ratio (SINR) when it is employed in the receiver of a wireless link. In a system with omnidirectional antennas, power control algorithms are used to maximize the SINR as well. We consider a system with beamforming capabilities in the receiver, and power control. An iterative algorithm is proposed to jointly update the transmission powers and the beamformer weights so that it converges to the jointly optimal beamforming and transmission power vector. The algorithm is distributed and uses only local interference measurements. In an uplink transmission scenario, it is shown how base assignment can be incorporated in addition to beamforming and power control, such that a globally optimum solution is obtained. The network capacity and the saving in mobile power are evaluated through numerical study.

The past, present, and the future of underwater acoustic signal processing

Abstract: This is a collection of articles written by members of the Underwater Acoustic Signal Processing (UASP) Technical Committee. The first article, by D. W. Tufts, deals with the history of UASP prior to 1980. In this period, initial mathematical models were developed and the first experimental investigations of underwater acoustic propagation were performed. It was also recognized during this time that there are many similarities between radar and sonar signal processing. The article by J.P. Ianniello deals with research in passive and active sonar from 1980 to the present. Work in this period included experimental verification of algorithms that had been developed in the 1960s and 1970s (e.g. for adaptive beamforming), as well as the development of new approaches, which include acoustic propagation modeling in the design of signal processing algorithms. Such processing is referred to as matched field processing. A common task in passive sonar systems is to estimate the difference in times at which different sensors receive the same signal. Time-delay estimation is a first stage that feeds into subsequent processing blocks. I. Lourtie provides a concise review of work in this field. The article by J.C. Preisig deals with underwater acoustic communications. The underwater channel has several features that make reliable communication a challenging problem. Nevertheless, progress is being made by combining results from ocean acoustic modeling, communication theory, and signal processing. The final article, by J.M.F. Moura, deals with the future of signal processing in the ocean. In addition to considering advances in detection and localization, he deals with new applications such as acoustic tomography, physical oceanography, and synthetic aperture sonar.

Neural network-based adaptive beamforming for one- and two-dimensional antenna arrays

Abstract: We present a neural network approach to the problem of finding the weights of one- (1-D) and two-dimensional (2-D) adaptive arrays. In modern cellular satellite mobile communications systems and in global positioning systems (GPSs), both desired and interfering signals change their directions continuously. Therefore, a fast tracking system is needed to constantly track the users and then adapt the radiation pattern of the antenna to direct multiple narrow beams to desired users and nulls interfering sources. In the approach suggested in this paper, the computation of the optimum weights is accomplished using three-layer radial basis function neural networks (RBFNN). The results obtained from this network are in excellent agreement with the Wiener solution.

Sidelobe suppression for phased array aeroacoustic measurements

Abstract: Phased array test techniques are becoming increasingly popular in aeroacoustics. This is due, in part, to the use of optimized array designs (e.g., spiral shapes) which can operate over usefully wide frequency ranges with acceptable resolution and sidelobe rejection characteristics with practical numbers of microphones. Sometimes constraints such as limited space for microphone installation prevent the use of optimum array designs, raising the prospect of high sidelobe levels. Several modifications to classical beamforming which may reduce sidelobe levels for imperfect arrays (and possibly improve the performance of optimized arrays) are available. The effectiveness of these techniques is explored by applying three of them to four array designs using simulated wind tunnel data. The three bearnforrning techniques are robust adaptive beamforming, cross spectral matrix element weighting, and the CLEAN algorithm. The array designs are a cross, an array of four crosses, a filled square, and a spiral array. NOMENCLATURE N = Number of microphones yn = Location of microphone n, n=l...N M = Number of point sources xm — location of source m, m = 1...M w(r) = Narrowband array data vector Sm (t) = Narrowband source strength C(x) = Array steering vector for point x P(t) - Scattering matrix associated with turbulence in boundary layer W(t] = Gaussian noise vector ( ) = Time average, also assumed to give expected value A = Cross spectral matrix K = Normalization factor for C(x) Pnn> = yn~y*

Hybrid adaptive beamformer

Abstract: The hybrid adaptive beamformer of the present invention includes a plurality of microphones for receiving sound energy from an external environment and for producing a plurality of microphone outputs from the sound energy. A processor produces a plurality of first order beams based on the microphone outputs. The processor determines an amount of reverberation in the external environment and adaptively produces a second order output beam taking into consideration the determined amount of reverberation. The processor may determine the amount of reverberation based on a comparison of the first order beams. The processor may produce the second order output beam by adaptively combining the plurality of first order beams, as further described below, or by adaptively combining the microphone outputs. The adaptation varies taking into consideration the determined amount of reverberation. Alternatively, the adaptation may vary by measuring the signal-to-noise ratio of the first order beams and adaptively combining the first order beams based on the determined signal-to-noise ratios.

Method and apparatus for adaptively reducing the level of noise in an acquired signal

Abstract: An adaptive filtering method and apparatus for reducing the level of an undesired noise component in an acquired physiological signal having a desired signal component. The acquired physiological signal is applied to one input of the adaptive filter, and a synthetic reference signal that is modeled so as to exhibit a correlation with the desired signal component is applied to another input of the adaptive filter. Thereafter, in a feedback manner, the adaptive filter iteratively adjusts the modeled synthetic reference signal so as to progressively generate a more accurate approximation of the desired signal component in the adaptive filter, which approximation becomes a reconstruction of the acquired physiological signal wherein the level of the undesired noise component is reduced.

Control method of adaptive array and adaptive array apparatus

Abstract: An adaptive array apparatus can follow high speed movement of an interference signal source with reducing breathing noise and maintaining high quality of an output signal. The adaptive array apparatus uses an indicative value relating to an amplitude of an output signal of a beam former having higher sensitivity with respect to the target signal source than a sensitivity with respect to other signal source, and an indicative value relating to an amplitude of an output signal of a beam former having lower sensitivity with respect to the target signal source than a sensitivity with respect to other signal source, and determines a step size of an adaptive algorithm in the adaptive filter. Thus, even when a constant determining a step size is set large for making following speed with respect to the movement of the interference signal source higher to reduce signal degradation and breathing noise.

2-D spatial smoothing for multipath coherent signal separation

Abstract: The use of two-dimensional spatial smoothing (SS) to increase channel capacity of wireless communications system is discussed, The necessary and sufficient conditions on array configuration for applying SS to multiple signal classification (MUSIC), and adaptive beamforming algorithms are defined and proved, This array must have an orientational invariance structure with an ambiguity free center array, and the number of subarrays must be larger than or equal to the size of the largest group of coherent signals. We also studied the cause of ambiguities in a multipath environment. We found the necessary and sufficient conditions for a three-sensor array manifold to be ambiguity free and identified several higher order ambiguity situations, If an array is also central symmetric, the forward/backward SS (FBSS) can be used to improve the resolution. Finally, we extended our results to the estimation of signal parameters via rotational invariance techniques (ESPRIT). All the predicted results are verified by simulations.

Capacity enhancement using adaptive arrays in an AMPS system

Abstract: Adaptive arrays for an advanced mobile phone service (AMPS) system can significantly increase cell capacity, improve signal quality, and reduce transmitter power requirements. In this paper, we investigate the capacity improvement that can potentially be achieved using adaptive arrays at the base station of an AMPS system. For the analysis, we use two types of spatial filters at the base station: an ideal and flat-top beamformer. An ideal beamformer has a flat main lobe and no side lobes, while a flat-top beamformer has flat main and side lobes. Analysis includes calculation of outage probability when a beamformer is used at the base station, and then we calculate the capacity increase that can be offered by practical antenna arrays. In this paper, we show that spatial-division multiple access (SDMA), i.e., all the users in a cell occupying the same frequency, is impossible to achieve in an AMPS system. A cell-reuse factor of four can be easily achieved with a five-element uniform linear array (ULA) with /spl lambda//2 spacings, but to achieve a reuse factor of three, a ULA with eight elements is required.

Adaptive cancellation of nonstationary interference in HF antenna arrays

Abstract: The paper statistically analyses and compares temporal variability in the spatial structure of two HF interference signals propagated from known locations via ionospheric channels with different spatial and temporal characteristics. The impact of the particular ionospheric paths propagating HF interference on the cancellation performance of various adaptive beamforming algorithms is investigated using data collected by the receiving antenna array of the Jindalee Facility Alice Springs OTH radar in Alice Springs, Australia. Measurements and analysis statistically confirm that the spatial properties of HF interference signals, and the actual performance improvements gained through the use of adaptive beamforming techniques, are highly dependent on the spatio-temporal characteristics of the prevailing ionospheric circuits linking the particular source location to the receiving array at the selected operating frequency.

Utilizing Waveform Features for Adaptive Beamforming and Direction Finding with Narrowband Signals

Abstract: ■ Extensive research has been done on the use of antenna arrays for direction finding and beamforming; this research focuses on the detailed behavior of specific techniques rather than on actual signal processing applications. In most applications, there is a fundamental signal feature that provides essential leverage for an effective processing approach. This article, which is structured around such features, presents a comprehensive framework for selecting an appropriate adaptive approach for processing cochannel narrowband signals. We address the roles of antenna calibration and prior waveform knowledge, and give examples of effective, practical direction-finding and beamforming procedures that cover a wide range of potential applications.

Coherent interference suppression with complementally transformed adaptive beamformer

Abstract: This paper proposes a beamforming scheme for suppressing coherent interference with an array of arbitrary geometry. The scheme first uses estimates of the source directions to construct a transformation, which removes the desired signal while retaining the coherent interference. Optimum beamforming is then performed on the transformed data containing only interference and noise to produce the maximum output signal-to-interference-plus-noise ratio (SINR). Analysis and numerical results demonstrate that the proposed complementally transformed beamformer significantly outperforms the conventional multiply constrained minimum variance (MCMV) beamformers.

Minimum variance monopulse technique for an adaptive phased array radar

Abstract: Monopulse techniques allow the direction of arrival of a target to be estimated to better than a beamwidth accuracy from a single time sample of data. If adaptive beamforming is employed the sum and difference beams are distorted and the usual monopulse formulas produce errors. These errors are greatest in main beam jamming scenarios. A number of papers have been written on monopulse correction schemes which account for the distortion produced through adaptive beamforming, to produce an improved estimate of the target direction. However in the previous work, estimation noise has not been considered in detail. A new minimum variance adaptive monopulse (MVAM) scheme is developed which gives the unbiased target direction estimate least prone to the effects of noise. The advantages of MVAM over existing monopulse approaches are demonstrated using simulation data for targets set in severe clutter and mainbeam jamming environments.

Response of sample covariance based MVDR beamformer to imperfect look and inhomogeneities

Abstract: The sample covariance based (SCB) minimum variance distortionless response (MVDR) beamformer has desirable properties under ideal homogeneous data conditions with perfect look. Such properties include maximum-likelihood optimality yielding an unbiased asymptotically efficient estimate of the signal parameter. When target array response mismatch exists and inhomogeneities are present, however, its performance can degrade considerably. Exact means and variances are given for the SCR MVDR beamformer output accounting simultaneously for finite sample support, imperfect look, and inhomogeneities demonstrating biased signal estimates and potentially extreme vulnerability to undernulled interference and surprise jammers.

A recursive least squares implementation for adaptive beamforming under quadratic constraint

Abstract: Quadratic constraints on the weight vector of an adaptive linearly constrained minimum power (LCMP) beamformer can improve robustness to pointing errors and to random perturbations in sensor parameters. In this paper, we propose a technique for implementing a quadratic inequality constraint with recursive least squares (RLS) updating. A variable diagonal loading term is added at each step, where the amount of loading is found from the solution to a quadratic equation. Simulations under different scenarios demonstrate that this algorithm outperforms both the RLS beamformer with no quadratic constraint, and the RLS beamformer using the scaled projection technique.

Adaptive beamforming for spatially spread sources

Abstract: We consider the problem of adaptive beamforming for enhancing spatially spread sources. Traditional adaptive beamforming techniques have been designed for point sources which travel along a single path to an antenna array. However, in practical applications such as wireless communications, multipath propagation due to local scattering of the sources causes spreading of the signal energy around the nominal direction-of-arrival (DOA). We propose a non-parametric technique for estimating the spatial distribution, which is then used to design beamformer weights. Simulation examples demonstrate that the proposed technique performs well for a variety of multi-user scenarios using different spreading models.

Matched-beam processing: Application to a horizontal line array in shallow water

Abstract: Matched-beam processing of a horizontal line array in a multipath shallow-water environment is presented. With conventional beamforming, the signal is split into several beams when the target is away from the broadside direction. This can result in signal gain degradation and severe bearing bias. Matched-beam processing is matched-field processing applied in the beam domain. It offers an efficient and robust approach for correcting bearing errors and signal gain degradation of horizontal line arrays in shallow water. It is based on conventional beams but extends conventional processing to incorporate full-field processing. It is applicable to existing systems where the conventional beam outputs are the only data readily available. Many of the signal processing algorithms for horizontal arrays, such as adaptive beamforming for nulling strong interferences, can be incorporated directly into matched-beam processing. Target bearing tracking and depth discrimination are illustrated using matched-beam processing for a horizontal line array.

Adaptive array antenna and interference canceler in a mobile communications system

Abstract: A receiver in a mobile communications system is provided. The receiver includes an adaptive array antenna having a plurality of antenna elements for forming a beam in the direction of a desired signal. Each of the plurality of elements has an adaptive linear filter associated therewith. A real time adaptive receive processor controls beam patterns and directions of the plurality of antenna elements at a reception angle of the desired user. An interference canceller operatively connected to said adaptive array antenna detects a multi-user interference signal from the desired signal and cancels the multi-user signal.

Space-time adaptive processing for manoeuvring airborne radar

Abstract: Space-time adaptive processing (STAP) techniques provide simultaneous rejection of jamming and clutter in airborne radar. The greatest benefits over conventional MTI (moving target indication) approaches are in terms of a capability to detect slow-moving targets which possess the same Doppler frequency as mainlobe clutter returns. This paper examines the effects of platform manoeuvre on STAP clutter and jamming rejection performance for a forward-facing array (i.e. where the array is orientated transversally to the direction of travel). It is shown that STAP slow-target detection performance is not sensitive to the radar platform orientation. It is also demonstrated that, under conditions of manoeuvre, STAP can provide better jammer rejection performance than architectures which cascade conventional clutter filtering and spatial adaptive beamforming.

Adaptive signal processing

Abstract: We describe a novel modular learning strategy for detection of a target signal of interest in a nonstationary environment, which is motivated by the information preservation rule. The strategy makes no assumptions on the environment. It incorporates three functional blocks: time-frequency analysis, feature extractions, and pattern classification, the delineations of which are guided by the information preservation rule. The time-frequency analysis implemented using Wigner-Ville distribution, transforms incoming received signal into a time-frequency image and accounts for the time-varying nature of the received signal's spectral context. This image provides a common input to a pair of channels, one of which is adaptively matched to interference acting alone, and the other is adaptively matched to target signal plus interference. Each channel of the receiver consists of a principal components analyser (for feature extraction) followed by a multilayer perceptron (for feature classification), which are implemented using self-organized and supervised forms of learning in feedforward neural networks, respectively.

Rapid design of a single chip adaptive beamformer

Abstract: This paper presents the design of a single chip adaptive beamformer which contains 5 million transistors and can perform 50 gigaflops. The core processor of the adaptive beamformer is a QR-array processor implemented on a fully efficient linear systolic architecture. The paper highlights a number of rapid design techniques that have been used to realise the design. These include an architecture synthesis tool for quickly developing the circuit architecture and the utilisation of a library of parameterisable silicon intellectual property (IP) cores, to rapidly develop the circuit layouts.

Adaptive beamforming and power allocation for OFDM over wireless networks

Abstract: The performance of a multiuser wireless network using OFDM, combined with power control and adaptive beamforming for uplink transmission is presented. An adaptive power control algorithm is exploited to achieve the desired signal to noise and interference ratio (SINR) at each subchannel and increase the power efficiency of the mobile transmitter. At the receiver side, the base station uses an antenna array to optimize the SNR-power efficiency, and attenuate the interference from other users dramatically. Therefore, we can achieve a better overall error probability with a fixed total power. A distributed iterative algorithm is used to jointly update the transmission power and the beamformer weights at each subchannel so that it can converge to the optimal solution for both power and beamforming vectors at each subchannel. The algorithm uses only the interference measured locally by the transmitter. Unlike most of the loading algorithms which optimize the bit distribution and subchannel power allocation for a single transmitter this approach tries to optimize the power allocation and decrease the interference for the whole network.

A digital adaptive beamforming QAM demodulator IC for high bit-rate wireless communications

Abstract: A very large scale integration (VLSI) implementation of an integrated adaptive beamforming processor and quadrature amplitude modulation (QAM) demodulator which will be incorporated into a frequency-hopped spread spectrum portable receiver for 2.4-GHz industrial, scientific, and medical (ISM) band applications is presented. The chip performs coherent QAM demodulation of variable constellation size and complete adaptive beamforming processing including four-channel adaptive beamforming combining, a fully programmable training processor, a readable/writable system control processor, an acquisition state machine, and a microcontroller interface. Interleaving area intensive blocks such as the 49-tap square-root Nyquist filters and 12/spl times/12 b multipliers is employed to reduce chip area. This chip can operate as a stand-alone adaptive beamforming QAM demodulator, or it can work together with an adaptive equalizer for high bit rate indoor wireless applications. The core area of the chip is 6.22 mm/spl times/4.58 mm in 0.8-/spl mu/m CMOS technology, and the power dissipation is 610 mW at 5 V and a 5 MBaud symbol rate. In a 2.2-dB signal-to-interference-and-noise ratio environment, the receiver chip achieves a link quality of 32.6 dB SNR by performing digital adaptive beamforming to null out interferers.

Adaptive beamforming with a multiple beam antenna

Abstract: Adaptive array processing is seen as one possible solution to the severe bandwidth and power restrictions in a communications system between a geostationary satellite and a mobile terminal. This paper considers the use of an offset parabolic reflector with an array feed, referred to as a multiple beam antenna (MBA), as a way of combining the high gain of the reflector with the spatial filtering ability of the antenna array. A signal model is developed in which the key quantity is the steering vector which represents the response of the antenna array to a plane wave arriving from a given angle. The steering vector for the MBA is found numerically by finding the secondary field of each of the antenna elements, and then using the principle of reciprocity to relate this field to the received amplitude. Statistically optimum beamforming on the MBA is demonstrated followed by a simulation of the direct matrix inversion (DMI) algorithm.

Robust multiple suppression using adaptive beamforming

Abstract: Minimum variance unbiased (MVU) beamforming is a type of multichannel filtering which extracts coherent signals without distortion, whilst minimizing residual noise power. Adaptive beamforming estimates signal and noise characteristics as part of the extraction process. The adaptive beamformer used here is designed from models of primary and multiple reflection signals having parametrically specified moveout and amplitude variation with offset (MVO and AVO). Phase variation with offset (PVO) can also be included but it is not usually justified in practice. The resulting analysis provides data for input into AVO and PVO schemes for obtaining lithological information. Synthetic data examples illustrate details of implementation of parametric adaptive MVU beamforming and the response characteristics of the resultant design. Real data examples show that data-adaptive beamforming is more flexible and more effective in attenuating multiples in prestack common-midpoint seismic data than Radon transform methods. In common with other prestack multichannel processes, the advantages of beamforming are shown to best effect in data with a good signal-to-noise ratio.

Robust multiple suppression using adaptive beamforming

Abstract: Minimum variance unbiased (MVU) beamforming is a type of multichannel filtering which extracts coherent signals without distortion, whilst minimizing residual noise power. Adaptive beamforming estimates signal and noise characteristics as part of the extraction process. The adaptive beamformer used here is designed from models of primary and multiple reflection signals having parametrically specified moveout and amplitude variation with offset (MVO and AVO). Phase variation with offset (PVO) can also be included but it is not usually justified in practice. The resulting analysis provides data for input into AVO and PVO schemes for obtaining lithological information. Synthetic data examples illustrate details of implementation of parametric adaptive MVU beamforming and the response characteristics of the resultant design. Real data examples show that data-adaptive beamforming is more flexible and more effective in attenuating multiples in prestack common-midpoint seismic data than Radon transform methods. In common with other prestack multichannel processes, the advantages of beamforming are shown to best effect in data with a good signal-to-noise ratio.

Misadjustment and tracking analysis of the constant modulus array

Abstract: The constant modulus (CM) array is a blind adaptive beamformer that can separate cochannel signals. A follow-on adaptive signal canceler may be used to perform direction finding of the source captured by the array. In this paper, we analyze the convergence and tracking properties of the CM array using a least-mean-square approximation. Expressions are derived for the misadjustment of the adaptive algorithms, and a tracking model is developed that accurately predicts the behavior of the system during fades. It is demonstrated that the adaptive canceler contributes more to the overall misadjustment than does the adaptive CM beamformer. Computer simulations are presented to illustrate the transient properties of the system and to verify the analytical results.

Forward-backward averaging in the presence of array manifold errors

Abstract: We investigate the use of forward-backward (f/b) averaging for estimating the covariance matrix used for adaptive beamforming and space-time adaptive processing (STAP). We demonstrate that the estimation loss is reduced by the use of f/b averaging and, for some STAP cases, f/b averaging can even quadruple the available sample support. We also show that unknown array manifold errors have little effect on the effectiveness of f/b averaging. The gain from f/b averaging is demonstrated on data from the mountaintop database.

Blind CMA beamforming for narrowband signals with multipath arrivals

Abstract: The constant modulus algorithm (CMA) is a popular and effective method for blind adaptive beamforming in various wireless communication systems. Traditionally, signals of arrival are considered to be independent. However, multipath propagations in wireless systems often results in several correlated signal arrivals. Because of multipath arrivals, CMA beamformers cannot be expected to place nulls in the direction of all interferers as assumed in some existing beamforming. In this paper, we present a simple convergence analysis of CMA under multipath correlated arrival signals. We propose two adaptation techniques based on CMA to capture different source signals. 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. Both methods are tested through computer simulations. © 1998 John Wiley & Sons, Ltd.

Array pattern distortion and remedies in space-time adaptive processing for airborne radar

Abstract: Space-time adaptive processing (STAP) for airborne early warning radar has been a very active area of research since the late 1980's. An airborne rectangular planar array antenna is usually configured into subarrays and then partial adaptive processing is applied to the outputs of these subarrays. In practice, three kinds of errors are often encountered: the array gain and phase errors existing in each element, the channel gain and phase errors, and the clutter covariance matrix estimation errors due to insufficient secondary data samples. These errors not only degrade the clutter suppression performance, but also cause the adapted array patterns to suffer much distortion (high sidelobes and distorted mainbeams), which may result in the rise of false-alarm probability and make the adaptive monopulse tracking and sidelobe blanketing more difficult. In this paper, the causes of the above three kinds of errors to array pattern distortion are discussed and a novel quadratic soft constraint factored approach is proposed to precisely control the peak sidelobe level of adapted patterns. The soft constraint factor can be determined explicitly according to the peak sidelobe level desired and the known or desired tolerant error standard deviations. Numerical results obtained by using high-fidelity simulated airborne radar clutter data are provided to illustrate the performance of the proposed approach. Although the method is presented for STAP, it can be directly applied to the conventional adaptive beamforming for rectangular planar arrays used to suppress jammers.