Array processing involves manipulation of signals induced on various antenna elements. Its capabilities of steering nulls to reduce cochannel interferences and pointing independent beams toward various mobiles, as well as its ability to provide estimates of directions of radiating sources, make it attractive to a mobile communications system designer. Array processing is expected to play an important role in fulfilling the increased demands of various mobile communications services. Part I of this paper showed how an array could be utilized in different configurations to improve the performance of mobile communications systems, with references to various studies where feasibility of apt array system for mobile communications is considered. This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them. This paper brings together almost all aspects of array signal processing.

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Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations

A compendium of recent theoretical results associated with using higher-order statistics in signal processing and system theory is provided, and the utility of applying higher-order statistics to practical problems is demonstrated. Most of the results are given for one-dimensional processes, but some extensions to vector processes and multichannel systems are discussed. The topics covered include cumulant-polyspectra formulas; impulse response formulas; autoregressive (AR) coefficients; relationships between second-order and higher-order statistics for linear systems; double C(q,k) formulas for extracting autoregressive moving average (ARMA) coefficients; bicepstral formulas; multichannel formulas; harmonic processes; estimates of cumulants; and applications to identification of various systems, including the identification of systems from just output measurements, identification of AR systems, identification of moving-average systems, and identification of ARMA systems. >

Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications

This paper presents an in-depth investigation of frequency-domain super-resolution time-of-arrival (TOA) estimation with diversity techniques for indoor geolocation applications. A methodology for performance evaluation of super-resolution techniques based on the measurements of indoor radio propagation channels is presented. The performance of super-resolution techniques is compared with the performance of conventional TOA estimation techniques. The effects of diversity techniques on the performance of super-resolution techniques are evaluated. The measurement and simulation methods presented in this paper can be used to establish empirical performance bounds for real implementation of super-resolution indoor geolocation systems.

Super-resolution TOA estimation with diversity for indoor geolocation

https://users.aalto.fi/~vorobys1/SP13.pdf

Principles of minimum variance robust adaptive beamforming design

A frequently encountered problem in signal processing is that of estimating the frequencies and amplitudes of harmonics observed in additive colored Gaussian noise. In practice, the observed signals are contaminated with spatially and temporally colored noise of unknown power spectral density. A cumulant-based approach to these problems is proposed. The cumulants of complex processes are defined, and it is shown that specific 1-D slices of the fourth-order cumulant of the noisy signal for the direction of arrival (DOA) and retrieval of harmonics in noise (RHN) problems are identical to the autocorrelation of a related noiseless signal. Hence correlation-based high-resolution methods may be used with fourth-order cumulants as well. The effectiveness of the proposed methods is demonstrated through standard simulation examples. >

Cumulant-based approach to harmonic retrieval and related problems

It is well known that signal subspace algorithms perform poorly when coherent or highly correlated signals are present. Recently, the so-called spatial smoothing technique was devised to preprocess the array covariance matrix so that signal subspace algorithms can be applied irrespective of the signal correlation. Unfortunately, the application of this technique reduces the effective aperture of the array. A modified spatial smoothing technique that is capable of increasing the effective aperture of the array over that of conventional spatial smoothing methods is explored. It is shown that under certain conditions, the modified algorithm may fail to yield the desired increase in array aperture, and some simulation results concerning the sensitivity of the modified spatial smoothing algorithm to these conditions are provided. >

An improved spatial smoothing technique for bearing estimation in a multipath environment

A method of parameter estimation is presented for a class of problems in which the desired signal is embedded in colored noise with unknown covariance. The proposed algorithm does not require multiple estimates of the signal covariance matrix; instead, it uses a priori knowledge of the structure of the noise covariance matrix to transform the array covariance matrix in a way that leaves its noise component unchanged while the signal component is transformed in some appropriate manner. The noise component is then eliminated by forming the difference of the original and transformed covariance differencing methods to be applied to a wider class of problems than was previously possible. This is illustrated by applying the algorithm to the problems of bearing estimation, resolution of overlapping echos, and transient response analysis. Simulation results demonstrate that the technique affords significant improvement in certain situations over conventional methods. >

L.H. Sibul

Papers

An improved spatial smoothing technique for bearing estimation in a multipath environment

A transform-based covariance differencing approach for some classes of parameter estimation problems