Showing papers on "Adaptive beamformer published in 1988"

Beamforming: a versatile approach to spatial filtering

Abstract: An overview of beamforming from a signal-processing perspective is provided, with an emphasis on recent research. Data-independent, statistically optimum, adaptive, and partially adaptive beamforming are discussed. Basic notation, terminology, and concepts are included. Several beamformer implementations are briefly described. >

Optimum beamforming for coherent signal and interferences

Abstract: An approach is described to optimum beamforming in the presence of correlated interferences completely overcoming the signal cancellation phenomenon. In contrast with classical adaptive beamforming where no assumptions are made on the statistical properties of the interference and noise, other than their being uncorrelated with the desired signal, the present approach is based on an explicit statistical model of the signal environment. The method is adaptive, however, in that the characterization of the signal environment is extracted from the measured array data. >

On the performance analysis of the MVDR beamformer in the presence of correlated interference

Abstract: Expressions are developed that describe the output of an adaptive array, based on the minimum variance distortionless response (MVDR) beamformer when multiple correlated interfering signals are present. Such signals may arise in certain multipath scenarios or in the case of smart jamming. Previous analyses considered only the case of single correlated interferer. Three scenarios of interest are examined: very high signal-to-noise ratio (SNR), moderately high SNR, and very low SNR. The analysis is based on simpler linear algebra concepts and generalizes a number of previously reported results proved for special cases. In addition, a modification of MVDR beamforming based on total least squares is introduced as a means of mitigating the sensitivity of the MVDR beamformer to uncertainties in element positions, pointing angle, etc. >

Multipath reduction system

Abstract: The effects of multipath and other interference signals in communication receivers are reduced by using adaptive signal processing. The feedback of the adaptive signal processor (104) is changed so that an external reference signal is not required. The invention addresses a signal environment in which the directions of arrival and the times of arrival of the signal of interest and the unwanted multipath or interference signals are unknown. The system uses the strongest received signal as the signal of interest.

Improved power minimization based partially adaptive beamformer design

Abstract: A technique for designing partially adaptive beamformers by minimization of output interference power was previously derived using a rather complicated approximation. The author presents an alternate derivation which clearly illustrates the nature of the approximation. A block diagram explicitly shows the modified partially adaptive system implied by the design procedure. This interpretation facilitates understanding of the limitations imposed by the approximation and suggests an improved design method. >

Systolic implementation of a general adaptive array processing algorithm

Abstract: The authors present a general adaptive array processing algorithm based on the MVDR (minimum variance distortionless response) beamformer for multiple steering vectors and multiple frequencies. They show how they use a sequence of Givens rotations to update the beamformer output, and how they implement the algorithm by means of two linear systolic arrays. The pipelined CORDIC processor is proposed as the processing element to achieve a high data throughput and a straightforward implementation. The problem of complex arithmetic for frequency-domain data is discussed. >

Dimensionality Reduction In High Resolution Direction Of Arrival Estimation

Abstract: Reducing data dimension prior to application of direction of arrival estimation algorithms is shown to lower computational requirements and improve certain aspects of performance. In this paper we utilize linear transformations for mapping full dimension data into a lower dimensional space. The transformation is designed to maximize the average signal to noise ratio over a set of likely signal scenarios. Reduced dimension versions of the MUSIC and minimum norm algorithms are presented and discussed. An example illustrates the effectiveness of the method.

Large-aperture sparse array detector system for multiple emitter location

Abstract: A detector beamformer array system having a sparse array and a reference ay. The reference array is adapted, according to known principles, to have an output response with one main lobe significantly larger than all other side lobes, and with a substantially flat response. Signals received by both arrays are cross-correlated with one another, and only signals sufficiently correlated are annunciated. The resulting adaptive array system has a resolution even better than that of the sparse array's aperture, and with directional sector selectivity corresponding to the angular width of the reference array's mainlobe, providing a system having high resolution and directional selectivity, but with far fewer sensors than with filled arrays used for this purpose.

A multimode adaptive beamformer for quadrature-amplitude-modulated signals

Abstract: The authors present the results of recent work on an adaptive beamformer designed to enhance the reception of N-state quadrature amplitude modulated (N-QAM) signal in the presence of multipath distortion and cochannel interference. Adaptation of the beamformer is based on a series of performance criteria derived from known properties of the transmitted signal. Neither calibrated look-direction constraints nor prearranged training signals are required. Instead, the beamformer uses blind adaptation to initially suppress multipath distortion and cochannel interference and then switches into decision-directed adaptation to achieve optimal combining. >

In high resolution microwave imaging

Abstract: 'Modern siectral estimation techniques offer higher angular resolution than Fourier-based methods in microwave imaging with large phased arrays. Two problems limit the applicability of these methods. Both are solved by data-adaptive feedback control of the weight vector of the array. The method is adaptive beamforming, developed for the radio camera. The problems are 1) intrinsic mechanical and electrical distortion in large systems of antennas and 2) the l ack of spatial stationarity in the radiation field from near-field targets. at X-band (3-cm wavelength) are presented.

Spatial acquisition of wideband frequency-hopping signals using adaptive array processing

Abstract: Algorithms for an adaptive antenna system are developed to estimate the direction of arrival for multiple signals to reduce spatial search. The system works in conjunction with a frequency hopping modem to minimize average acquisition time while improving the signal-to-interference-plus-noise ratio at the modem input. Simulation results indicate that an adaptive antenna can optimize acquisition time and estimate signal direction simultaneously in the presence of interference. >

A structured gradient algorithm for adaptive beamforming

Abstract: The constrained least-mean-squares (LMS) algorithm uses a noise estimate of the required gradient to adaptively estimate the weights of an optimal antenna array. The gradient is estimated by multiplying the array output with the array receiver outputs. An alternative scheme for estimating the required gradient is proposed. The proposed scheme uses a structured estimate of the array correlation matrix to estimate the gradient. This structure reflects the structure of the exact array correlation matrix and is obtained by a spatial averaging of the elements of the noisy array correlation matrix used in the standard algorithm. The authors compare the performance of the standard LMS algorithm with the proposed algorithm and shows that their algorithm has a better convergence performance. >

Direct computation of a minimum-variance distortionless-response beamformer

Abstract: A QR-decomposition constrained least-squares (QRD-CLS) algorithm is presented to solve directly for a minimum-variance distortionless-response adaptive beamformer without explicit computation of its weights. Generally, the QRD-CLS algorithm is capable of solving deterministic least-squares optimization problems subject to an equality constraint in an iterative adaptive manner by imposing a 'soft' constraint via the quadratic penalty function optimization method. The proposed algorithm is able to perform both linearly constrained and unconstrained least-squares minimizations; in addition, it is implemented with a unique triangular systolic array architecture where an orthogonal triangularization process is performed on the input data by means of new 'three-dimensional' Givens rotations. >

Detection: a new approach (signals)

Abstract: A method for the detection of the number of signals in array processing is proposed. This technique can provide the number of signals irrespective of the signal-to-noise ratio, whereas existing detection techniques fail to perform at low signal-to-noise ratios even asymptotically. The asymptotic error performance of the proposed technique is studied, and it is shown that the probability of error is nearly zero. An objective criterion is given to obtain the number of signals for the case in which the number of snapshots are finite. The concept of detectability is introduced, and a methodology is developed to obtain the detectability of an array system together with number of signals. >

On adaptive beamforming in correlated noise

Abstract: This paper deals with the problem of adaptive beamforming in the presence of fully coherent (correlated) noise sources. Two different techniques are developed for minimizing the effects of coherent interference. The first method employs spatial interpolation of the array aperture, followed by spatial smoothing in order to decorrelate the desired signal and the interference. The second technique is based on a simple algebraic transformation for restoring the rank of the array signal correlation matrix, which is normally rank deficient in such situations. This technique is shown to work for nonuniform adaptive arrays as well. Extensive computer simulation results are presented to illustrate the effectiveness of the proposed techniques.

On a modified Duvall beamformer

Abstract: The authors are concerned with the use of derivative null constraints in an adaptive beamformer in the spatial and frequency domains with respect to the Duvall beamformer to obtain a modified Duvall beamformer. Simulation results demonstrate that the modified beamformer's performance is improved under the following conditions:L jammer frequencies are the same as the desired signal; jammer directions are different from the desired signal; and jammer directions and frequencies are known. >

Signal Processing For Ocean Tomography With Moving Ships

Abstract: In ocean acoustic tomography, maximal length binary shift- register sequences, m-sequences, are used to modulate acoustic carriers to achieve high average power and good time and Doppler resolution. To date, the underwater transmitters and receivers have been in fixed positions, and signal processing has consisted of demodulation followed by factor inverse filtering. Ocean tomography now is being extended to include the use of moving, ship-towed, transmitters and receivers, where signal processing must account for Doppler time and frequency resealing. This paper describes the signal demodulation and processing methods developed for moving ship tomography and presents illustrative results.

Adaptive beamforming for correlated signal and interferences: A frequency-domain smoothing approach

Abstract: A novel approach is presented to wideband adaptive beamforming for correlated desired signal and interferences. Unlike spatial smoothing, it solves the signal cancellation problem by using the idea of frequency-domain smoothing. Advantages over the spatial smoothing are identified, and a particular method is developed for moderately wideband system applications. A preliminary performance study shows that proper spatial filtering can be achieved whether the desired signal and the interferences are correlated or not. >

An adaptive recursive array processing algorithm for resolving closely spaced signals with low SNR and widely disparate signal power

Abstract: The authors introduce a novel modified eigensystem decomposition method to decompose the covariance matrix of the array elements into the signal and noise components. The noise contribution can thus be suppressed and the signal covariance matrix reconstructed for detection. Furthermore, this algorithm can be easily extended to cope with coherent signals. It is shown that, from the enhanced covariance matrix, the signal-to-interference-plus-noise ratio at reception has improved significantly. >

A pole-zero complex adaptive joint process least-squares lattice

Abstract: A pole-zero adaptive noise cancelling structure is described and its relevance to the adaptive beamforming problem discussed. An embedding approach is taken where a scalar ARMA (autoregressive moving-average) process is embedded into a two-channel AR process. Drawing on previously developed recursions for the joint process, multichannel, least-squares lattice, the recursions for the pole-zero adaptive noise canceller are implemented. A performance comparison is made between the resulting pole-zero adaptive noise cancelling structure and the all-zero least-squares lattice adaptive noise cancelling structure. The ability to implement adaptive poles is shown to be particularly advantageous in the region where the reference channel has a null. >

Signal separation theory using adaptive arrays

Abstract: The signal separation technique using adaptive arrays is a new area in array data processing. The model considered in this paper is that of an array consisting of N elements; the number of signal sources, which are separated in spatial location, is M and M ≥ N. In the case of narrow band signals, the pre-envelope form of the incident signal can be obtained from the original signal and its Hilbert transform. The directional bearing-angle matix G is formed in terms of the conventional beam-forming system. By using a special implementation, the inverse matrix of G is derived. Finally, a matrix transform is operated on the received signal so that the output signal is separable, i.e. each output channel has only one incident signal. In the case of wide band signals, the DFT of the input signal or heterodyne is required. The block diagrams of the signal separation technique are given and some important results of this technique are derived. The results of system simulation experiments in digital computers prove that this theory is effective for separating signals.

The Effect of the Conventional Beampattern on Adaptive Beamformer Performance

Abstract: : This report develops an expression that relates the adaptive beamformer array response function to the conventional beamformer beampattern function in the sidelobe region. Specific examples for deterministic, randomized, and random arrays are evaluated. These examples clearly indicate that sidelobes in the conventional beampattern function produce spurious peaks in the adaptive array response. The probability that a spurious peak exceeds a threshold for the adaptive array response of random arrays is developed. The probability tha a signal peak exceeds that peak spurious peak for minimum-energy adaptive beamforming with random arrays is developed. Keywords: Spurious peak; Array response; Random arrays; Adaptive arrays.

Adaptive Beamforming Using Real Arithmetic

Abstract: Two different techniques are proposed for implementing an adaptive beamformer using a systolic QR decomposition array based on real rather than complex Givens rotations. These are compared in terms of their computational requirements, sensitivity to phase and amplitude imbalance, and effect on the reception of a desired signal.

A Robust Adaptive Array Structure Using the Soft Constrained LMS algorithm

Abstract: This paper presents a new algorithm for adaptive beamforming which is robust to both desired signal misalignment and array geometry imperfections. It extends the work done by Jab-Ion and Widrow [1] by utilizing a priori knowledge of the desired signal direction to generate new soft constraints on the pattern of the array.

Adaptive Beamforming For Large Arrays

Abstract: Adaptive and high-resolution array processing techniques are usually considered for relatively small arrays in which the number of snapshots is large compared to the number of array elements. In this paper we consider the case of a large array in which the number of snapshots is smaller than the number of sensors, and therefore the sample covariance matrix is rank deficient. A numerically stable adaptive beamforming algorithm is derived for this case, and it is shown how eigenstructure based algorithms such as MUSIC need to be modified to handle the case of large arrays.

On The Role Of Adaptive Beamforming And Modern Spectral Estimation In High Resolution Microwave Imaging

Abstract: Modern spectral estimation techniques offer higher angular resolution than Fourier-based methods in microwave imaging with large phased arrays. Two problems limit the applicability of these methods. Both are solved bv data-adaptive feedback control of the weight vector of the array. The method is adaptive beamforming, developed for the radio camera. The problems are 1) intrinsic mechanical and electrical distortion in large systems of antennas and 2) the lack of spatial stationarity in the radiation field from near-field targets. The theory and experiments with aircraft imagery at X-band (3-cm wavelength) are presented.

Systolic array for 2-d adaptive beamforming

Abstract: In this paper, we describe a pinelined architecture for implementing a 2-D digital adaptive beamformer. The architecture relies heavily on a triangular systolic structure, which was described earlier in [1,2] as a means of solving recursive least-squares problems based on the QRD-algorithm. In the implementation of the 2-D beamformer, we use a manifold of triangular systolic arrays, which in the limit takes the form of a cosmic cube. With the proper time skew format for the data flow, it will be shown that the cosmic cube beamformer can concurrently and simultaneously process the data from the rows and columns of array antennas with a speed comparable to the 1-D case. As well it will be shown that data memory requirements are modest. It is felt that the 2-D adaptive beamformer has promise for real-time beamforming with planar array antennas.

A comparison of two frequency domain adaptive beamforming algorithms for sonar signal processing

Abstract: Computer simulation studies of two frequency domain adaptive beamforming algorithms are presented. The two algorithms are the frequency domain adaptive beamforming modified least-mean-square algorithm, and the proposed new frequency domain adaptive beamforming algorithm based on modified adaptive linear predictionerror filtering. The simulation studies were conducted to determine the multiple broadband target localization capability and the full angular coverage capability of the two algorithms. The number of iterations that the adaptive algorithms took to reach a minimum estimation error was determined. The algorithms were evaluated at several signal-to-noise ratios. Finally, using the results of the simulation studies a comparison between the two algorithms is performed.