Array of sensors: A spatiotemporal-state-space model for target trajectory tracking

In this paper, with the objective of tracking the trajectory of multiple mobile targets, a novel spatiotemporal-state-space model is introduced for an array of sensors distributed in space. Under the wideband assumption, the proposed model incorporates the array geometry in conjunction with crucial target parameters namely (i) ranges, (ii) directions, (iii) velocities and (iv) associated Doppler effects. Computer simulation studies show some representative examples where the proposed model is utilised to track the locations of sources in space with a very high accuracy

Signals and Images in Sea Technologies

Life below water is the 14th Sustainable Development Goal (SDG) envisaged by the United Nations and is aimed at conserving and sustainably using the oceans, seas, and marine resources for sustainable development. It is not difficult to argue that signals and image technologies may play an essential role in achieving the foreseen targets linked to SDG 14. Besides increasing the general knowledge of ocean health by means of data analysis, methodologies based on signal and image processing can be helpful in environmental monitoring, in protecting and restoring ecosystems, in finding new sensor technologies for green routing and eco-friendly ships, in providing tools for implementing best practices for sustainable fishing, as well as in defining frameworks and intelligent systems for enforcing sea law and making the sea a safer and more secure place. Imaging is also a key element for the exploration of the underwater world for various scopes, ranging from the predictive maintenance of sub-sea pipelines and other infrastructure projects, to the discovery, documentation, and protection of sunken cultural heritage. The scope of this Special Issue encompasses investigations into techniques and ICT approaches and, in particular, the study and application of signal- and image-based methods and, in turn, exploration of the advantages of their application in the previously mentioned areas

Active Backscattering Positioning System Using Innovative Harmonic Oscillator Tags for Future Internet of Things: Theory and Experiments

RÉSUMÉ D'ici 2020, l'Internet des objets (IoT) permettra probablement de créer 25 milliards d'objets connectés, 44 ZB de données et de débloquer 11 000 milliards de dollars d’opportunités commerciales. Par conséquent, ce sujet a suscité d’énormes intérêts de recherche dans le monde académique entier. L'une des technologies clés pour l'IoT concerne le positionnement physique intérieur précis. Le principal objectif dans ce domaine est le développement d'un système de positionnement intérieur avec une grande précision, une haute résolution, un fonctionnement à plusieurs cibles, un faible coût, un faible encombrement et une faible consommation d'énergie. Le système de positionnement intérieur conventionnel basé sur les technologies de Wi-Fi ou d'identification par radiofréquence (RFID) ne peut répondre à ces exigences. Principalement parce que leur appareil et leur signal ne sont pas conçus spécialement pour atteindre les objectifs visés. Les chercheurs ont découvert qu'en mettant en oeuvre de différents types de modulation sur les étiquettes, le radar à onde continue (CW) et ses dérivés deviennent des solutions prometteuses. Les activités de recherche présentées dans cette thèse sont menées dans le but de développer des systèmes de positionnement en intérieur bidimensionnel (2-D) à plusieurs cibles basées sur des étiquettes actives à rétrodiffusion harmonique avec une technique à onde continue modulée en fréquence (FMCW). Les contributions de cette thèse peuvent être résumées comme suit: Tout d'abord, la conception d'un circuit actif harmonique, plus spécifiquement une classe d'oscillateurs harmoniques innovants utilisée comme composant central des étiquettes actives dans notre système, implique une méthodologie de conception de signal de grande taille et des installations de caractérisation. L’analyseur de réseau à grand signal (LSNA) est un instrument émergent basé sur les fondements théoriques du cadre de distorsion polyharmonique (PHD). Bien qu'ils soient disponibles dans le commerce depuis 2008, des organismes de normalisation et de recherche tels que l’Institut national des normes et de la technologie (NIST) des États-Unis travaillent toujours à la mise au point d'un standard largement reconnu permettant d'évaluer et de comparer leurs performances. Dans ce travail, un artefact de génération multi-harmonique pour la vérification LSNA est développé. C'est un dispositif actif capable de générer les 5 premières harmoniques d'un signal d'entrée avec une réponse ultra-stables en amplitude et en phase, quelle que soit la variation de l'impédance de la charge.----------ABSTRACT By 2020, the internet of things (IoT) will probably enable 25 billion connected objects, create 44 ZB data and unlock 11 trillion US dollar business opportunities. Therefore, this topic has been attracting tremendous research interests in the entire academic world. One of the key enabling technologies for IoT is concerned with accurate indoor physical positioning. The development of such an indoor positioning system with high accuracy, high resolution, multitarget operation, low cost, small footprint, and low power consumption is the major objective in this area. The conventional indoor positioning system based on WiFi or radiofrequency identification (RFID) technology cannot fulfill these requirements mainly because their device and signal are not purposely designed for achieving the targeted goals. Researchers have found that by implementing different types of modulation on the tags, continuous-wave (CW) radar and its derivatives become promising solutions. The research activities presented in this Ph.D. thesis are carried out towards the goal of developing multitarget two-dimensional (2-D) indoor positioning systems based on harmonic backscattering active tags together with a frequency-modulated continuous-wave (FMCW) technique. Research contributions of this thesis can be summarized as follows: First of all, the design of a harmonic active circuit, more specifically, a class of innovative harmonic oscillators used as the core component of active tags in our system, involves a large signal design methodology and characterization facilities. The large signal network analyzer (LSNA) is an emerging instrument based on the theoretical foundation for the Poly-Harmonic Distortion (PHD) framework. Although they have been commercially available since 2008, standard and research organizations such as the National Institute of Standards and Technology (NIST) of the US are still working towards a widely-recognized standard to evaluate and cross-reference their performances. In this work, a multi-harmonic generation artifact for LSNA verification is developed. It is an active device that can generate the first 5 harmonics of an input signal with ultra-stable amplitude and phase response regardless of the load impedance variation

A Consistent Metric for Performance Evaluation of Multi-Object Filters

The concept of a miss-distance, or error, between a reference quantity and its estimated/controlled value, plays a fundamental role in any filtering/control problem. Yet there is no satisfactory notion of a miss-distance in the well-established field of multi-object filtering. In this paper, we outline the inconsistencies of existing metrics in the context of multi-object miss-distances for performance evaluation. We then propose a new mathematically and intuitively consistent metric that addresses the drawbacks of current multi-object performance evaluation metrics

A new Measure for Optimization of Field Sensor Network with Application to LiDAR

This thesis proposes a solution to the problem of modeling and optimizing the field sensor network in terms of the coverage performance. The term field sensor is referred to a class of sensors which can detect the regions in 2D/3D spaces through non-contact measurements. The most widely used field sensors include cameras, LiDAR, ultrasonic sensor, and RADAR, etc. The key challenge in the applications of field sensor networks, such as area coverage, is to develop an effective performance measure, which has to involve both sensor and environment parameters. The nature of space distribution in the case of the field sensor incurs a great deal of difficulties for such development and, hence, poses it as a very interesting research problem. Therefore, to tackle this problem, several attempts have been made in the literature. However, they have failed to address a comprehensive and applicable approach to distinctive types of field sensors (in 3D), as only coverage of a particular sensor is usually addressed at the time. In addition, no coverage model has been proposed yet for some types of field sensors such as LiDAR sensors. In this dissertation, a coverage model is obtained for the field sensors based on the transformation of sensor and task parameters into the sensor geometric model. By providing a mathematical description of the sensor’s sensing region, a performance measure is introduced which characterizes the closeness between a single sensor and target configurations. In this regard, the first contribution is developing an Infinity norm based measure which describes the target distance to the closure of the sensing region expressed by an area-based approach. The second contribution can be geometrically interpreted as mapping the sensor’s sensing region to an n-ball using a homeomorphism map and developing a performance measure. The third contribution is introducing the measurement principle and establishing the coverage model for the class of solid-state (flash) LiDAR sensors. The fourth contribution is point density analysis and developing the coverage model for the class of mechanical (prism rotating mechanism) LiDAR sensors. Finally, the effectiveness of the proposed coverage model is illustrated by simulations, experiments, and comparisons is carried out throughout the dissertation. This coverage model is a powerful tool as it applies to the variety of field sensors