Array signal processing for maximum likelihood direction-of-arrival estimation

Emitter Direction-of-Arrival (DOA) estimation is a fundamental problem in a variety of applications including radar, sonar, and wireless communications. The research has received considerable attention in literature and numerous methods have been proposed. Maximum Likelihood (ML) is a nearly optimal technique producing superior estimates compared to other methods especially in unfavourable conditions, and thus is of significant practical interest. This paper discusses in details the techniques for ML DOA estimation in either white Gaussian noise or unknown noise environment. Their performances are analysed and compared, and evaluated against the theoretical lower bounds

Innovative Adaptive Techniques for Multi Channel Spaceborne SAR Systems

Synthetic Aperture Radar (SAR) is a well-known technology which allows to coherently combine multiple returns from (typically) ground-based targets from a moving radar mounted either on an airborne or on a space-borne vehicle. The relative motion between the targets on ground and the platform causes a Doppler effect, which is exploited to discriminate along-track positions of targets themselves. In addition, as most of conventional radar, a pulsed wide-band waveform is transmitted periodically, thus allowing even a radar discrimination capability in the range direction (i.e. in distance). For side-looking acquisition geometries, the along-track and the range directions are almost orthogonal, so that the two dimensional target discrimination capabiliy results in the possibility to produce images of the illuminated area on ground. A side-looking geometry consists in the radar antenna to be, either mechanically or electronically, oriented perpendicular to the observed area. Nowadays technology allows discrimination capability (also referred to as resolution) in both alongtrack and range directions in the order of few tenths of centimeters. Since the SAR is a microwave active sensor, this technology assure the possibility to produce images of the terrain independently of the sunlight illumination and/or weather conditions. This makes the SAR a very useful instrument for monitoring and mapping both the natural and the artificial activities over the Earth’s surface. Among all the limitations of a single-channel SAR system, this work focuses over some of them which are briefly listed below: a) the performance achievable in terms of resolution are usually paid in terms of system complexity, dimension, mass and cost; b) since the SAR is a coherent active sensor, it is vulnerable to both intentionally and unintentionally radio-frequency interferences which might limit normal system operability; c) since the Doppler effect it is used to discriminate targets (assumed to be stationary) on the ground, this causes an intrinsic ambiguity in the interpretation of backscattered returns from moving targets. These drawbacks can be easily overcome by resorting to a Multi-cannel SAR (M-SAR) system

Innovative Adaptive Techniques for Multi Channel Spaceborne SAR Systems

Synthetic Aperture Radar (SAR) is a well-known technology which allows to coherently combine multiple returns from (typically) ground-based targets from a moving radar mounted either on an airborne or on a space-borne vehicle. The relative motion between the targets on ground and the platform causes a Doppler effect, which is exploited to discriminate along-track positions of targets themselves. In addition, as most of conventional radar, a pulsed wide-band waveform is transmitted periodically, thus allowing even a radar discrimination capability in the range direction (i.e. in distance). For side-looking acquisition geometries, the along-track and the range directions are almost orthogonal, so that the two dimensional target discrimination capabiliy results in the possibility to produce images of the illuminated area on ground. A side-looking geometry consists in the radar antenna to be, either mechanically or electronically, oriented perpendicular to the observed area. Nowadays technology allows discrimination capability (also referred to as resolution) in both alongtrack and range directions in the order of few tenths of centimeters. Since the SAR is a microwave active sensor, this technology assure the possibility to produce images of the terrain independently of the sunlight illumination and/or weather conditions. This makes the SAR a very useful instrument for monitoring and mapping both the natural and the artificial activities over the Earth’s surface. Among all the limitations of a single-channel SAR system, this work focuses over some of them which are briefly listed below: a) the performance achievable in terms of resolution are usually paid in terms of system complexity, dimension, mass and cost; b) since the SAR is a coherent active sensor, it is vulnerable to both intentionally and unintentionally radio-frequency interferences which might limit normal system operability; c) since the Doppler effect it is used to discriminate targets (assumed to be stationary) on the ground, this causes an intrinsic ambiguity in the interpretation of backscattered returns from moving targets. These drawbacks can be easily overcome by resorting to a Multi-cannel SAR (M-SAR) system

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Target Detection in Heterogeneous Clutter with Low Resolution Radar

This thesis develops a framework for SAR target detection and super-resolution in low-resolution environments. The primary focus in this research is the background clutter heterogeneity that often accompanies low range and cross-range resolutions. A corrective model which accounts for clutter replacement is developed to define the detection and false alarm rates of the detector more accurately than a traditional model in which the radar return from the target supplements the existing clutter. In a heterogeneous clutter cell, the clutter replacement model leverages the different scattering distributions among the individual clutter types to generate a probability distribution function for the areas of each clutter type which are obstructed by a target. The location of the target can be extrapolated from the clutter replacement areas, and a multiple hypothesis detection test is conducted to determine which location estimate yields the lowest average error

Impairments in ground moving target indicator (GMTI) radar

Radars on multiple distributed airborne or ground based moving platforms are of increasing interest, since they can be deployed in close proximity to the event under investigation and thus offer remarkable sensing opportunities. Ground moving target indicator (GMTI) detects and localizes moving targets in the presence of ground clutter and other interference sources. Space-time adaptive processing (STAP) implemented with antenna arrays has been a classical approach to clutter cancellation in airborne radar. One of the challenges with STAP is that the minimum detectable velocity (MDV) of targets is a function of the baseline of the antenna array: the larger the baseline (i.e., the narrower the beam), the lower the MDV. Unfortunately, increasing the baseline of a uniform linear array (ULA) entails a commensurate increase in the number of elements. An alternative approach to increasing the resolution of a radar, is to use a large, but sparse, random array. The proliferation of relatively inexpensive autonomous sensing vehicles, such as unmanned airborne systems, raises the question whether is it possible to carry out GMTI by distributed airborne platforms. A major obstacle to implementing distributed GMTI is the synchronization of autonomous moving sensors. For range processing, GMTI processing relies on synchronized sampling of the signals received at the array, while STAP processing requires time, frequency and phase synchronization for beamforming and interference cancellation. Distributed sensors have independent oscillators, which are naturally not synchronized and are each subject to different stochastic phase drift. Each sensor has its own local oscillator, unlike a traditional array in which all sensors are connected to the same local oscillator. Even when tuned to the same frequency, phase errors between the sensors will develop over time, due to phase instabilities. These phase errors affect a distributed STAP system. In this dissertation, a distributed STAP application in which sensors are moving autonomously is envisioned. The problems of tracking, detection for our proposed architecture are of important. The first part focuses on developing a direct tracking approach to multiple targets by distributed radar sensors. A challenging scenario of a distributed multi-input multi-output (MIMO) radar system (as shown above), in which relatively simple moving sensors send observations to a fusion center where most of the baseband processing is performed, is presented. The sensors are assumed to maintain time synchronization, but are not phase synchronized. The conventional approach to localization by distributed sensors is to estimate intermediate parameters from the received signals, for example time delay or the angle of arrival. Subsequently, these parameters are used to deduce the location and velocity of the target(s). These classical localization techniques are referred to as indirect localization. Recently, new techniques have been developed capable of estimating target location directly from signal measurements, without an intermediate estimation step. The objective is to develop a direct tracking algorithm for multiple moving targets. It is aimed to develop a direct tracking algorithm of targets state parameters using widely distributed moving sensors for multiple moving targets. Potential candidate for the tracker include Extended Kalman Filter. In the second part of the dissertation,the effect of phase noise on space-time adaptive processing in general, and spatial processing in particular is studied. A power law model is assumed for the phase noise. It is shown that a composite model with several terms is required to properly model the phase noise. It is further shown that the phase noise has almost linear trajectories. The effect of phase noise on spatial processing is analyzed. Simulation results illustrate the effect of phase noise on degrading the performance in terms of beam pattern and receiver operating characteristics. A STAP application, in which spatial processing is performed (together with Doppler processing) over a coherent processing interval, is envisioned

Robust Optical Wireless Links over Turbulent Media using Diversity Solutions

Free-space optic (FSO) technology, i.e., optical wireless communication (OWC), is widely recognized as superior to radio frequency (RF) in many aspects. Visible and invisible optical wireless links solve first/last mile connectivity problems and provide secure, jam-free communication. FSO is license-free and delivers high-speed data rates in the order of Gigabits. Its advantages have fostered significant research efforts aimed at utilizing optical wireless communication, e.g. visible light communication (VLC), for high-speed, secure, indoor communication under the IEEE 802.15.7 standard. However, conventional optical wireless links demand precise optical alignment and suffer from atmospheric turbulence. When compared with RF, they suffer a low degree of reliability and lack robustness. Pointing errors cause optical transceiver misalignment, adversely affecting system reliability. Furthermore, atmospheric turbulence causes irradiance fluctuations and beam broadening of transmitted light. Innovative solutions to overcome limitations on the exploitation of high-speed optical wireless links are greatly needed.Spatial diversity is known to improve RF wireless communication systems. Similar diversity approaches can be adapted for FSO systems to improve its reliability and robustness; however, careful diversity design is needed since FSO apertures typically remain unbalanced as a result of FSO system sensitivity to misalignment. Conventional diversity combining schemes require persistent aperture monitoring and repetitive switching, thus increasing FSO implementation complexities. Furthermore, current RF diversity combining schemes may not be optimized to address the issue of unbalanced FSO receiving apertures.This dissertation investigates two efficient diversity combining schemes for multi-receiving FSO systems: switched diversity combining and generalized selection combining. Both can be exploited to reduce complexity and improve combining efficiency. Unlike maximum ratio combing, equal gain combining, and selective combining, switched diversity simplifies receiver design by avoiding unnecessary switching among receiving apertures. The most significant advantage of generalized combining is its ability to exclude apertures with low quality that could potentially affect the resultant output signal performance.This dissertation also investigates mobile FSO by considering a multi-receiving system in which all receiving FSO apertures are circularly placed on a platform. System mobility and performance are analyzed. Performance results confirm improvements when using angular diversity and generalized selection combining.The précis of this dissertation establishes the foundation of reliable FSO communications using efficient diversity-based solutions. Performance parameters are analyzed mathematically, and then evaluated using computer simulations. A testbed prototype is developed to facilitate the evaluation of optical wireless links via lab experiments