Thomas W. Miller

Bio: Thomas W. Miller is an academic researcher from Raytheon. The author has contributed to research in topics: Signal & Antenna (radio). The author has an hindex of 3, co-authored 5 publications receiving 1628 citations.

Introduction to Adaptive Arrays

Abstract: This second edition is an extensive modernization of the bestselling introduction to the subject of adaptive array sensor systems. With the number of applications of adaptive array sensor systems growing each year, this look at the principles and fundamental techniques that are critical to these systems is more important than ever before. Introduction to Adaptive Arrays, 2nd Edition is organized as a tutorial, taking the reader by the hand and leading them through the maze of jargon that often surrounds this highly technical subject. It is easy to read and easy to follow, as fundamental concepts are introduced with examples before more current developments and techniques are introduced. Problems at the end of each chapter serve both instructors and professional readers by illustrating and extending the material presented in the text. Both students and practicing engineers will easily gain familiarity with the modern contribution that adaptive arrays have to offer practical signal reception systems.

System and method for subband beamforming using adaptive weight normalization

Abstract: A beamforming system and method The inventive beamforming system (100) is adapted for use with an array antenna (112) having a plurality of antenna elements (1-7) and includes an FFT (122) for transforming a signal received by an antenna into a plurality of frequency subbands A plurality of adaptive processors (800) are included for performing adaptive array processing on each of the subbands and providing a plurality of adaptively processed subbands in response thereto A normalizing processor (900) is also included for normalizing the adaptively processed subbands In the illustrative embodiment, the signal is a GPS signal and a digital multiplier (126) for applying a weight to a respective frequency subband for each of the elements of the array The weights are chosen to steer a beam in a direction of a desired signal Normalization involves adjusting the amplitude of one or more of the subbands to remove any bias distortion due to the adaptive processing thereof

Phase stabilization in adaptive arrays

Abstract: A phase-stabilized adaptive array system and method including a moving antenna array (54A-54N), a plurality of signal channels (52A-52N) coupled to the antenna array, each for producing a channel signal, each channel including adaptive signal weighting apparatus (60A-60N) for weighting the channel signal by a channel weight. The system further includes combining apparatus for combining the weighted channel signals to form a beam signal, and phase compensation apparatus (66) for applying phase compensation weights to the array signals or the beam signal which vary in dependence of the beam scan position such that the response to a signal at a known direction is held substantially constant while the antenna is moved, or as the weights are updated.

Optimum Array Processing

Abstract: Optimum array processing is an optimum multichannel filtering problem. The objective of array processing is to enhance the reception (or detection) of a desired signal that may be either random or deterministic in a signal environment containing numerous interference signals. The desired signal may also contain one or several uncertain parameters (e.g., spatial location, signal energy, phase) that it may be advantageous to estimate. Optimum array processing techniques are broadly classified as processing appropriate for ideal propagation conditions and processing appropriate for perturbed propagation conditions. Ideal propagation implies an ideal nonrandom, nondispersive medium where the desired signal is a plane (or spherical) wave and the receiving sensors are distortionless. In this case the optimum processor is said to be matched to a plane wave signal. Any performance degradation resulting from deviation of the actual operating conditions from the assumed ideal conditions is minimized by the use of complementary methods, such as the introduction of constraints. When operating under the aforementioned ideal conditions, vector weighting of the input data succeeds in matching the desired signal.

Adaptive weight calculation preprocessor

Abstract: In accordance with one aspect of the present invention, a preprocessor is provided for use in an adaptive antenna array. The purpose of the preprocessor is to modify the incoming signals received by each antenna of an antenna array in such a manner as to reduce the amount of computation necessary to compute the adaptive array weights. In an adaptive array, the weight computation process generally requires calculations using digital electronics, which tend to be computationally intensive when applied to wideband, high sample rate signals. The preprocessor of the present invention solves this problem by filtering the data in such a manner as to reduce the sample rate of the signal without losing the essential characteristics of the signal. The preprocessor includes an input terminal for receiving an electromagnetic signal from an antenna element of the adaptive antenna array, and a frequency smearer operatively coupled to the input terminal. The frequency smearer is provided in order to smear the electromagnetic signal by varying the frequency of the electromagnetic signal across a predetermined frequency band and outputting the smeared electromagnetic signal to an averaging circuit. The averaging circuit, which is operatively coupled to the output of the frequency smearer, repetitively computes and outputs an average with respect to time of the smeared electromagnetic signal.

Phased Array Antenna Handbook

Abstract: Phased Arrays in Radar and Communication Systems. Pattern Characteristics and Synthesis of Linear and Planar Arrays. Patterns of Nonplanar Arrays. Elements, Transmission Lines, and Feed Architectures for Phased Arrays. Summary of Element Pattern and Mutual Impedance Effects. Array Error Effects. Special Array Feeds for Limited Field of View and Wideband Arrays.

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

Abstract: 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.

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

Abstract: Adaptive beamforming methods are known to degrade if some of underlying assumptions on the environment, sources, or sensor array become violated. In particular, if the desired signal is present in training snapshots, the adaptive array performance may be quite sensitive even to slight mismatches between the presumed and actual signal steering vectors (spatial signatures). Such mismatches can occur as a result of environmental nonstationarities, look direction errors, imperfect array calibration, distorted antenna shape, as well as distortions caused by medium inhomogeneities, near-far mismatch, source spreading, and local scattering. The similar type of performance degradation can occur when the signal steering vector is known exactly but the training sample size is small. In this paper, we develop a new approach to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch. Our approach is based on the optimization of worst-case performance. It turns out that the natural formulation of this adaptive beamforming problem involves minimization of a quadratic function subject to infinitely many nonconvex quadratic constraints. We show that this (originally intractable) problem can be reformulated in a convex form as the so-called second-order cone (SOC) program and solved efficiently (in polynomial time) using the well-established interior point method. It is also shown that the proposed technique can be interpreted in terms of diagonal loading where the optimal value of the diagonal loading factor is computed based on the known level of uncertainty of the signal steering vector. Computer simulations with several frequently encountered types of signal steering vector mismatches show better performance of our robust beamformer as compared with existing adaptive beamforming algorithms.

Solution of the multiuser downlink beamforming problem with individual SINR constraints

Abstract: We address the problem of joint downlink beamforming in a power-controlled network, where independent data streams are to be transmitted from a multiantenna base station to several decentralized single-antenna terminals. The total transmit power is limited and channel information (possibly statistical) is available at the transmitter. The design goal: jointly adjust the beamformers and transmission powers according to individual SINR requirements. In this context, there are two closely related optimization problems. P1: maximize the jointly achievable SINR margin under a total power constraint. P2: minimize the total transmission power while satisfying a set of SINR constraints. In this paper, both problems are solved within a unified analytical framework. Problem P1 is solved by minimizing the maximal eigenvalue of an extended crosstalk matrix. The solution provides a necessary and sufficient condition for the feasibility of the SINR requirements. Problem P2 is a variation of problem P1. An important step in our analysis is to show that the global optimum of the downlink beamforming problem is equivalently obtained from solving a dual uplink problem, which has an easier-to-handle analytical structure. Then, we make use of the special structure of the extended crosstalk matrix to develop a rapidly converging iterative algorithm. The optimality and global convergence of the algorithm is proven and stopping criteria are given.

On the Capacity of Radio Communication Systems with Diversity in a Rayleigh Fading Environment

Abstract: In this paper, we study the fundamental limits on the data rate of multiple antenna systems in a Rayleigh fading environment. With M transmit and M receive antennas, up to M independent channels can be established in the same bandwidth. We study the distribution of the maximum data rate at a given error rate in the channels between up to M transmit antennas and M receive antennas and determine the outage probability for systems that use various signal processing techniques. We analyze the performance of the optimum linear and nonlinear receiver processor and the optimum linear transmitter/receiver processor pair, and the capacity of these channels. Results show that with optimum linear processing at the receiver, up to M/2 channels can be established with approximately the same maximum data rate as a single channel. With either nonlinear processing at the receiver or optimum linear transmitter/receiver processing, up to M channels can be established with approximately the same maximum data rate as a single channel. Results show the potential for large capacity in systems with limited bandwidth.