Fundamentals of Narrowband Array Signal Processing

Array signal processing is an actively developing research area connected to the progress in optimization theory, and remains the key technological development that attracts prevalent attention in signal processing. This chapter provides an overview of the fundamental concepts and essential terminologies employed in narrowband array signal processing. We first develop a general signal model for narrowband adaptive arrays and discuss the beamforming operation. We next introduce the basic performance parameters of adaptive arrays and the second order statistics of the array data. We then formulate various optimal weigh vector solution criteria. Finally, we discuss various types of adaptive filtering algorithms. Besides, this chapter emphasizes the theory of narrowband array signal processing employed in narrowband beamforming and direction-of-arrival (DOA) estimation algorithms.

Steered Beam Adaptive Antenna Arrays

In this chapter, the performance of steered beam adaptive arrays is presented with its corresponding analytical expressions. Computer simulations are used to illustrate the performance of the array under various operating conditions. In this chapter, we ignore the presence of mutual coupling between the array elements. The principal system elements of the adaptive array consist of an array of sensors (antennas), a pattern-forming network, and an adaptive pattern control unit or adaptive processor that adjusts the variable weights in the pattern-forming network. The adaptive pattern control unit may furthermore be conveniently subdivided into a signal processor unit and an adaptive control algorithm. The manner in which these elements are actually implemented depends on the propagation medium in which the array is to operate, the frequency spectrum of interest, and the user’s knowledge of the operational signal environment.

Reconfigurable Antenna Systems for the Next Generation Devices Based on 4G/5G Standard

This article is devoted to showing the applications of innovative reconfigurable antenna systems suitable for the next generation 4G/5G devices. Microwave antenna technology can be very useful for next generation devices based on 4G/5G standards. Next generation tablets and smartphones based on 4G/5G standards will require high bandwidth and high velocity channels with respect to conventional devices. This work tries to present a complete overview of possible applications of advanced antenna technologies for 4G/5G devices and systems. Methodologies, such as phased and fully adaptive arrays, multiple-input and multiple-output (MIMO) antennas based on compact Rotman lenses or butler matrices, development of innovate reconfigurable antennas based on reconfigurable parasitic structures or new materials such as graphene, and unconventional modulation techniques have been investigated in this work. The work ends with some conclusions and considerations related to ideas for future works.

Digital antenna array calibration by adaptive algorithms of signal processing

A method of antenna array calibration, based on the using of the recursive least squares (RLS) adaptive filtering algorithms is discussed. The matrix inversion lemma, the QR-decomposition and the Householder transform based RLS algorithms with quadratic computational complexity can be used for the method implementation in the narrowband adaptive arrays. The proposed calibration method is used in the antenna arrays with digital beam forming. The method demonstrates the ability to estimate and compensate the channel gain errors that ensures the average deviation of the calibrated array radiation pattern shape relatively the radiation pattern shape of the ideal array about –20 dB.

Impact of Element Pattern on the Performance of GNSS Power-Inversion Adaptive Arrays

Power-inversion (PI) adaptive arrays are widely used in Global Navigation Satellite System (GNSS) receivers for interference mitigation. The effects of element patterns on the performance of PI adaptive arrays are investigated in this paper. To this end, the performance of adaptive arrays is investigated by Monte Carlo simulations, using CST Microwave Studio (Dassault Systems, Vélizy-Villacoublay, France) to calculate the radiation patterns of circular microstrip elements which are used to compute the adaptive weight and the adaptive array gain. It is shown that the performance of PI adaptive arrays is mainly dependent on the gain pattern of the reference antenna element rather than the non-reference elements because the algorithm essentially pushes the elements into an unequal position. Furthermore, the results show that the impact of mutual coupling on the performance of the antenna array can be associated with the radiation patterns of the reference element, which is helpful in selecting the optimum reference element without increasing computational complexity, especially for small GNSS arrays.