Emitter Location Finding using Particle Swarm Optimization

Using several spatially separated receivers, nowadays positioning techniques, which are implemented to determine the location of the transmitter, are often required for several important disciplines such as military, security, medical, and commercial applications. In this study, localization is carried out by particle swarm optimization using time difference of arrival. In order to increase the positioning accuracy, time difference of arrival averaging based two new methods are proposed. Results are compared with classical algorithms and Cramer-Rao lower bound which is the theoretical limit of the estimation error

Research on Impulse Radio Ultra - wideband Positioning Method Based on Combined BP Neural Network and SVM

Intelligent tour guide is a comprehensive service based on tourist\u27s location, which is closely related to Geographic Information System (GIS), mobile positioning technology and Location-Based Service (LBS). But the intelligent tour guide field urgently needs the integrated positioning and navigation technology inside and outside the room. IR-UWB technology is suitable for positioning, tracking, navigation and communication in complex indoor environment, and is considered as the most potential indoor positioning technology to realize seamless connection between indoor and outdoor with outdoor positioning technologies such as GPS. However, one of the main problems facing IR-UWB positioning is Non-Line-Of-Sight (NLOS) error. Based on the advantages of BP neural network and support vector machine, this paper proposes a multi-model fusion algorithm to mitigate the NLOS propagation error of the time difference of arrival (TDOA) and the angle of arrival (AOA) of IR-UWB signal, and then uses TDOA/AOA hybrid positioning that mitigates the NLOS error. Simulation results show that the combined algorithm has stronger NLOS resistance and higher positioning accuracy than the single machine learning algorithm in mitigation NLOS errors

Target localization in passive and active systems : performance bonds

The main goal of this dissertation is to improve the understanding and to develop ways to predict the performance of localization techniques as a function of signal-to-noise ratio (SNR) and of system parameters. To this end, lower bounds on the maximum likelihood estimator (MLE) performance are studied. The Cramer-Rao lower bound (CRLB) for coherent passive localization of a near-field source is derived. It is shown through the Cramer-Rao bound that, the coherent localization systems can provide high accuracies in localization, to the order of carrier frequency of the observed signal. High accuracies come to a price of having a highly multimodal estimation metric which can lead to sidelobes competing with the mainlobe and engendering ambiguity in the selection of the correct peak. The effect of the sidelobes over the estimator performance at different SNR levels is analyzed and predicted with the use of Ziv-Zakai lower bound (ZZB). Through simulations it is shown that ZZB is tight to the MLEs performance over the whole SNR range. Moreover, the ZZB is a convenient tool to assess the coherent localization performance as a function of various system parameters. The ZZB was also used to derive a lower bound on the MSE of estimating the range and the range rate of a target in active systems. From the expression of the derived lower bound it was noted that, the ZZB is determined by SNR and by the ambiguity function (AF). Thus, the ZZB can serve as an alternative to the ambiguity function (AF) as a tool for radar design. Furthermore, the derivation is extended to the problem of estimating target’s location and velocity in a distributed multiple input multiple output (MIMO) radar system. The derived bound is determined by SNR, by the product between the number of transmitting antennas and the number of receiving antennas from the radar system, and by all the ambiguity functions and the cross-ambiguity functions corresponding to all pairs transmitter-target-receiver. Similar to the coherent localization, the ZZB can be applied to study the performance of the estimator as a function of different system parameters. Comparison between the ZZB and the MSE of the MLE obtained through simulations demonstrate that the bound is tight in all SNR regions

Nouvelle méthode d'estimation des différences de temps d'arrivée pour la localisation des objets connectés haut débit

The forthcoming vision of Internet of Things (IoT) and Internet of Everything (IoE) will immerse people in so-called Smart Environments involving a great number of sectors of applications such as smart habitat, smart-cities, environment monitoring, e-health… IoT and IoE tend to make everyday objects readable, recognizable, locatable, addressable and controllable via the widespread wireless deployment and the internet. Among these capabilities, localization and more extensively the ubiquitous positioning will play, in the next future, a key role to promote another emerging vision: a spatio-temporal Internet of Places (IoP), which would be able to structure and organize, by means of wireless energy aware approaches, the spatial content of Internet. It is well known that in wireless local and personal area networks, the spectrum congestion, the low energy efficiency communications and the insufficient exploitation of the spatial resources are among the factors that may slow down its development in terms of throughput and autonomy. To overcome these unavoidable restrictions, wireless localization technology, as the mechanism for discovering spatio-temporal relationship between connected objects, appears here also as one of the key solutions. This is because dedicated localization techniques in wireless communication can help in developing more extensively the exploitation of spatial resources and allow driving optimized routing for low energy multi-hop communication and spectrum decongestion for Green ICT (Information and Communication Technology). To propose optimized systems achieving both high data rate communication and precise localization, we define a well suited TDOA (Time Difference of Arrival) based method able to perform localization based on communication signals and data only. With this technique, unlike conventional TDOA estimations, it is possible to drastically decrease the complexity of required infrastructures by using either SIMO (Single Input Multiple Output), MISO (Multiple Input Single Output) or MIMO (Multiple Input Multiple Output) configurations in connected objects. This whole study is made within the framework of the IEEE 802.11ad standard and WiGig alliance specifications, however the proposed solutions are compatible with other standards and can be extended to other context aware applications requiring localization inputs such as robotics for example or smart shopping...La vision future de l'internet des objets (IdO) et Internet du Tout (OIE) plongera les personnes soi-disant environnements intelligents impliquant un grand nombre de secteurs d'applications telles que l'habitat intelligent, smart-villes, surveillance de l'environnement, l'e-santé ... IdO et l'OIE ont tendance à faire des objets du quotidien lisible, identifiable, localisable, adressable et contrôlable via le déploiement sans fil généralisée et l'Internet. Parmi ces capacités, la localisation et plus largement le positionnement omniprésente joueront, dans un proche avenir, un rôle clé pour promouvoir une autre vision émergente: un Internet spatio-temporelle des lieux (IoP), qui serait en mesure de structurer et d'organiser, par des moyens des approches sans fil d'énergie savez, le contenu spatial d'Internet. Il est bien connu que dans les réseaux locaux sans fil et personnelles, l'encombrement du spectre, les communications à faible efficacité énergétique et l'exploitation insuffisante des ressources spatiales sont parmi les facteurs qui peuvent ralentir son développement en termes de débit et de l'autonomie. Pour surmonter ces restrictions inévitables, la technologie de localisation sans fil, comme le mécanisme pour découvrir relation spatio-temporelle entre les objets connectés, apparaît ici aussi comme une des solutions clés. Ce est parce que les techniques de localisation dédiés à la communication sans fil peuvent aider à développer plus largement l'exploitation des ressources spatiales et de permettre la conduite routage optimisé pour une faible énergie communication multi-hop et la décongestion du spectre pour Green ICT (Information et Communication Technology). Pour proposer des systèmes optimisés atteindre à la fois la communication des taux de données élevés et la localisation précise, nous définissons un TDOA bien adapté (Time Difference of Arrival) méthode basée en mesure d'effectuer la localisation basée sur des signaux de communication et de données seulement. Avec cette technique, contrairement estimations TDOA classiques, il est possible de diminuer considérablement la complexité des infrastructures nécessaires en utilisant des configurations SIMO (Single Input Multiple Output), MISO (Multiple Input Single Output) ou MIMO (Multiple Input Multiple Output) dans les objets connectés . Toute cette étude est faite dans le cadre de l'IEEE 802.11ad spécifications de l'alliance standard et WiGig, mais les solutions proposées sont compatibles avec d'autres normes et peuvent être étendues à d'autres applications de contexte courant nécessitant entrées de localisation tels que la robotique par exemple ou de shopping intelligent..

A Linear Subspace Approach to Burst Communication Signal Processing

This dissertation focuses on the topic of burst signal communications in a high interference environment. It derives new signal processing algorithms from a mathematical linear subspace approach instead of the common stationary or cyclostationary approach. The research developed new algorithms that have well-known optimality criteria associated with them. The investigation demonstrated a unique class of multisensor filters having a lower mean square error than all other known filters, a maximum likelihood time difference of arrival estimator that outperformed previously optimal estimators, and a signal presence detector having a selectivity unparalleled in burst interference environments. It was further shown that these improvements resulted in a greater ability to communicate, to locate electronic transmitters, and to mitigate the effects of a growing interference environment