Showing papers on "Adaptive beamformer published in 1985"

Adaptive Signal Processing

Abstract: GENERAL INTRODUCTION. Adaptive Systems. The Adaptive Linear Combiner. THEORY OF ADAPTATION WITH STATIONARY SIGNALS. Properties of the Quadratic Performance Surface. Searching the Performance Surface. Gradient Estimation and Its Effects on Adaptation. ADAPTIVE ALGORITHMS AND STRUCTURES. The LMS Algorithm. The Z-Transform in Adaptive Signal Processing. Other Adaptive Algorithms and Structures. Adaptive Lattice Filters. APPLICATIONS. Adaptive Modeling and System Identification. Inverse Adaptive Modeling, Deconvolution, and Equalization. Adaptive Control Systems. Adaptive Interference Cancelling. Introduction to Adaptive Arrays and Adaptive Beamforming. Analysis of Adaptive Beamformers.

Adaptive beamforming for coherent signals and interference

Abstract: In this paper we introduce a new adaptive array beam-former able to work well even when the desired signal and the interference are coherent. The present adaptive beamformers fail to operate in these cases. The results of simulations support the theoretical predictions.

An alternative formulation for an optimum beamformer with robustness capability

Abstract: In the paper, an alternative formulation for an optimum beamformer with a robustness capability against directional errors is presented. With this approach, the width of the main beam can be specified and a compromise can be reached between a reasonable signal acceptance angle and the ability of the beamformer to reject directional interferences. Furthermore, based on a partitioned processor interpretation, the new beam-former gives a clue to a way of reducing the complexity of a full processor.

Analysis of constrained LMS algorithm with application to adaptive beamforming using perturbation sequences

Abstract: Adaptive antenna array processing employing a constrained least mean square (LMS) algorithm requires an unbiased estimate of the gradient of the output power with respect to the array weights. There are a number of schemes for obtaining an unbiased estimate of this gradient. Though in each case the estimated gradient is unbiased, the covariance of the estimated gradient with each method is different and thus the transient and the steady state behavior of the constrained algorithm is different in each case. The transient and the steady state behavior of the weight covariancc matrix is analyzed, exact expressions for the misadjustment are derived, and a comparison of the performance of the algorithm is presented when the required gradient is estimated by different schemes. The schemes considered include gradient estimation when all the array signals are accessible as well as gradient estimation using perturbation sequences for eases when the array signals are inaccessible. The necessary and the sufficient condition for the diagonlization of the weight covarience matrix is also derived.

Adaptive antenna array

Abstract: A method and device for removing undesired jammer signals from desired signals which comprises forming a beam on the desired signal in an adaptive antenna array characterized by an orthogonalizer array (12) to receive digitised signals from the antennas, and pass signals to a beamforming array (14) and including a late jammer canceller array (16) and an intelligent controller (24) arranged to control weights (W) and select a row having the desired beamformed signal.

The Performance of an LMS Adaptive Array with Frequency Hopped Signals

Abstract: The performance of an LMS adaptive array with a frequency hopped, spread spectrum desired signal and a CW interference signal is examined. It is shown that frequency hopping has several effects on an adaptive array. It causes the array to modulate both the amplitude and the phase of the received signal. Also, it causes the array output SINR (signal-to-interference-plus-noise ratio) to vary with time and thus increases the bit error probability for the received signal. Typical curves of the desired signal modulation and the time-varying SINR at the array output are presented. It is shown how the array performance depends on hopping frequency, frequency jump size, interference frequency, signal arrival angles, and signal powers.

On beamforming in presence of multipath

Abstract: We consider a source radiated signal arriving at an array as a group of wavefronts, each having a different angle of arrival and with arbitrary amplitude, phase and inter wavefront correlation. Several such sources may be present and the measurement data is assumed to be corrupted by sensor to sensor uncorrelated noise. The task of the beamformer is to make optimal estimates of each source signal of interest by using the information in all the wavefronts generated by the source. The proposed processor begins with no apriori information about the environment and constructs the optimal beamformer by a bootstrapping approach which uses a two tier eigenstructure analysis of the array covariance. We show that this new beamformer has substantial advantages over the usual optimal beamformers and present results of computer simulation carried out to verify its performance.

An Lms Adaptive Array Using a Pilot Signal

Abstract: A least mean square (LMS) adaptive array requires a reference signal. When the desired signal contains a pilot signal, it may be used as the reference signal. In this paper the steady-state performance of an LMS adaptive array in which the pilot signal is used as the reference signal is examined. It is shown that the LMS adaptive array occasionally suppresses the desired signal. The loop gain, which is an important parameter, is also considered.

An Adaptive Beamforming Algorithm With Simultaneous Mainlobe Response And Tolerance Sensitivity Constraints

Abstract: Adaptive beamforming algorithms sometimes are very sensitive to slight errors in array characteristics Errors which are uncorrelated from sensor to sensor pass through the beamformer like uncorrelated or spatially white noise Hence, gain against white noise is a measure of robustness A new algorithm is presented which includes a quadratic inequality constraint on the array gain against uncorrelated noise while minimizing output power subject to multiple linear equality constraints It is shown that a simple scaling of the projection of the weights in a subspace can be used to satisfy the quadratic inequality constraint This leads to a simple effective robust adaptive beamforming algorithm

Adaptive beam forming in correlated interference environment

Abstract: In the presence of signal correlated interference, a conventional adaptive beamformer fails to perform satisfactorily due to the signal cancellation effects. This paper suggests a new technique based signal interpolation followed by spatial correlation smoothing to de-correlate the signal from the interference for avoiding signal cancellation.

Selective Reverberation Cancellation via Adaptive Beamforming

Abstract: : This thesis applies the adaptive beamforming concept to the problem of selective reverberation cancellation, with an emphasis on experimental verification. Oceanic reverberation is often a limiting form of interference in echo detection applications. It may also be the signal of interest conveying valuable information about the scatterers or physical processes influencing their dynamical behavior. Because of stringent limitations imposed by the oceanic medium on the directional characteristics of sonar systems, reverberation is often composite in nature with two or more unrelated reverberation types contributing to the acoustic return. In that setting it would be desirable to selectively cancel the unwanted reverberation component(s) while preserving the component of interest. This signal processing problem whereby both signal and noise are constituent components of the received reverberation process is the focus of this thesis. The related problem of extracting reflector echoes from a reverberation backround is also considered.

Empirical observations of a sonar adaptive array

Abstract: The responses of adaptive and conventional acoustic array processors using data acquired from an underwater environment are compared. The data from a horizontal planar array with omnidirectional elements are processed using frequency-domain and element-space techniques to estimate the azimuthal noise anisotropy and to contrast the effectiveness of each processor. Three beamformers are represented: the uniform amplitude shaded beamformer, a nonuniformly shaded beamformer and a fully adaptive processor which seeks to optimise array response by minimising the beampower.

A solid state transmitter with adaptive beamforming

Abstract: Utilisation d'amplificateurs a l'etat solide dans les reseaux d'antennes emettrices equiphases

Inversion of modified beamformed array data

Abstract: The separation of transient plane-waves as a function of their velocity and time-of-arrival can be performed by a time domain beamformer. Modifications in the beamformer output domain, such as masking out coherent interfering signals while taking into account both velocity and time information, are more straightforward than with traditional (k-ω) velocity filtering methods. We describe three methods of inverting the beamformer output to reconstruct the space-time samples. Of the three, one method, a block matrix inversion technique, is new. It is exact when operating on the original data, but fails when the beamformer output is modified. This problem can be alleviated by reducing the dimensionality of the inversion matrix using a singular value decomposition.

Error analysis of eigenvector preprocessors used in adaptive beamforming

Abstract: Perturbation analysis and Weyl's inequality are used to determine second order statistics of eigenvalues and eigenvectors of an estimated covariance matrix that arises in an adaptive array processor. An expression for excess mean square error which is caused by the eigenvalue errors is derived. This expression shows that small eigenvalues of the underlying true covariance matrix result in large contributions to the excess mean square error. Closely spaced eigenvalues can cause large errors in eigenvector determination.

A Computer-Controlled Adaptive Antenna System

Abstract: The problem of active pattern control in multibeam or phased array antenna systems is one that is well suited to technologies based upon microprocessor feedback control systems. Adaptive arrays can be realized by incorporating microprocessors as control elements in closed-loop feedback paths. As intelligent controllers, microprocessors can detect variations in arrays and implement suitable configuration changes. The subject of this paper is the application of the Howells-Applebaum power inversion algorithm in a C-band multibeam antenna system. A proof-of-concept, microprocessor controlled, adaptive beamforming network (BFN) was designed, assembled, and subsequent tests were performed demonstrating the algorithm's capacity for nulling narrowband jammers.

A General Framework For Analysis Of Fir Beamforming Structures

Abstract: A framework for analyzing linearly constrained adaptive beamforming structures is developed using factored state variable descriptions The framework simplifies comparison of different structures and illustrates relationships between them It provides insight into the eflect of structure on performance and complexity and suggests development of new structures The framework arise!; by factoring the procesmr impulse response into an adaptive weight vector times a structure matrix parameterizing the processor structure It is shown that, identical optimum performance results for dl processors having nonsingular structure matrix An adaptive algorithm for structures with arbitrary structure matrices is presented and it is proved that all processors with orthogonal structure matrices have identical output during adaptive operation Existence of structures which synthesize arbitrary structure matrices is also established