ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / Telemetry ground stations spread over geographically diverse areas are well suited for use in passively locating the source of a distant transmitted signal. In a favorable positioning of receive sites, the accuracy of these passive localization techniques can compete with the accuracy of radars. In these cases, use of receive only assets is a less expensive alternative than the use of a radar's scarce resources. Until recently, the major technical challenge to implementation of the passive localization techniques of time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) has been the frequency and time stability of geographically separated receivers. Advances in GPS based timing and frequency references has made the implementation of TDOA and FDOA feasible. This paper shows how these limitations have been overcome using the current telemetry assets at the Reagan Test Site in Kwajalein Atoll.

<p>This thesis considers passive localization and tracking. Here, passive refers to passive observations - the type of observations for which the full position estimate of the target cannot be obtained using a single measurement, like those are from a sonar. Hence, localizing or tracking targets based on these measurements calls for the use of multiple sensors. This poses a different set of challenges to tracking with passive observations as opposed to active observations where full target position is available from a single measurement.</p><p>We identify different issues that are related to passive localization and tracking and propose algorithmic solutions to these problems. We consider the angle of arrival (AOA), which is the passive measurement that is often considered in target tracking and time difference of arrival (TDOA) as representative passive measurements to illustrate our algorithms. Whereas, the AOA measurements from different sensors can be considered independent, TDOA measurements, on the other hand, are not independent. That is, they are correlated. We would, however, like to note that the proposed algorithms can be applied with straightforward, but simple, modifications to other types of passive measurements.</p><p>In particular, this thesis provides solutions to the following problems. First, it provides efficient and improved algorithms to the data association problem when tracking with multiple passive synchronous sensors. These solutions are based on the assignment formulation. Whereas one of the algorithms proposed, the gated assignment algorithm, uses the validation gates to reduce the computational cost, the other is a new extension to the multidimensional assignment algorithm that associates the measurements directly to the tracks. This is called the (S + 1)-D assignment-based data association, where S is the number of synchronous sensors available in the tracking system. An approximation to this new (S + 1)-D algorithm is also presented.</p> <p> In literature one finds algorithms to localize a single target using TDOA measurements. None of these algorithms considered the issues that might arise in tracking the localized targets. This thesis provides a framework to localize and track targets based on TDOA measurements. The localization algorithm uses a formulation based on the sensor-emitter geometry. This formulation is considered as a constrained optimization problem and two relaxation-based algorithms are provided to solve this optimization problem. The assignment-based data association provides an additional challenge because the TDOA measurements are correlated. This problem is identified and a solution is provided by modifying the calculation of the association cost.</p> <p> Finally, this thesis also provides an efficient algorithm to form AOA mono tracks using the fast Fourier transform (FFT) and the assignment algorithm. Formation of the mono tracks is very useful in distributed tracking and is the well-known direction of arrival tracking problem in the signal processing community.</p> / Thesis / Doctor of Philosophy (PhD)

Wireless sensor networks are composed of sensor nodes, which can monitor an environment and observe events of interest. These networks are applied in various fields including but not limited to environmental, industrial and habitat monitoring. In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to find sensor node's positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. I do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. I show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes share linearity. The more the non-linearity, the better the localization. The localization for our network design proves better when I place anchor nodes at right angles.

Cette thèse porte sur la localisation de sources acoustiques sous-marines avec application à une expérience en mer. Nous proposons une nouvelle méthode d'appariement basée sur une métrique appelée distance de Hausdorff (HD) en tant que fonction de coût à minimiser, afin d'effectuer l'inversion de localisation. La localisation 2D, en distance et en profondeur, est réalisée en faisant correspondre les schémas de différence de temps d'arrivée (TDOA) en utilisant un seul hydrophone à la réception et en faisant correspondre le TDOA et l'Angle d'arrivée (AOA) lors de l'utilisation d'un tableau des hydrophones à la réception, entre des séquences respectivement mesurées et modélisées. Le TDOA modélisé a été obtenu sur la base du modèle de propagation acoustique Ray-path. Les ensembles de données analysés ici ont été collectés dans un contexte de localisation passive en considérant une cible immobile et dans deux expériences : la cuve acoustique de GIPSA-LAB utilisant des systèmes coopératifs et non coopératifs vérifiés par des simulations du rapport signal sur bruit et sur la campagne ALMA 2015, collectée par la Direction générale de l'armement (DGA) en utilisant un système coopératif qui s'est déroulé dans un environnement en eaux peu profondes de la côte sud de la France. Au cours de l’expérience ALMA, les données acoustiques ont été mesurées sur un réseau linéaire vertical (VLA) de 10 m de haut, composé de 64 hydrophones, ce qui permet non seulement d’adapter le TDOA mais également l’angle d’arrivée (AOA). Plusieurs variantes de la distance de Hausdorff sont appliquées dans deux processus différents: premièrement, séparément dans chaque hydrophone, puis combinées pour améliorer la précision de la localisation (diversité spatiale), et la seconde où les informations des différents hydrophones sont combinées (formation de faisceaux), pour trouver l'emplacement cible. Les résultats des deux processus sont comparés et prouvés pour réduire l'ambiguïté soit la profondeur et la portée, améliorant ainsi la précision finale. Le Cramer Rao Bound montrant la variance minimale effectuée sur la base d’équations déterministes est présenté avec le meilleur résultat de chaque processus. Une performance et une précision très satisfaisantes sont obtenues. Les conclusions et les perspectives de ce travail sont discutées à la fin. / This thesis addresses an acoustic underwater source localization with application to an at-sea experiment. We propose a new matching method based on a fit-metric called as Hausdorff distance (HD) as a cost-function to be minimized, in order to perform the localization inversion. The 2-D localization, in range and depth, is performed by matching the patterns of time difference of arrival (TDOA) when using only one hydrophone at the reception and by matching the TDOA and the Angle of Arrival (AOA) when using an array of hydrophones at the reception, between respectively measured and modeled sequences. The modelled TDOA was obtained based on the Ray-path acoustic propagation model. The data sets analyzed here were collected during two experiments in a context of passive localization considering a motionless target: The tank of GIPSA-LAB using cooperative and non-cooperative systems which were verified by simulations with respect to the signal-to-noise ratio and the ALMA 2015, collected by the Direction générale de l’armement (DGA) using a cooperative system which took place in a shallow water environment of the southern coast of France. During the ALMA experiment the acoustic data were measured over a 10m-high vertical linear array (VLA), composed of 64 hydrophones, allowing not only matching the TDOA but also the Angle of Arrival (AOA). Several variants of the Hausdorff Distance are applied in two different processes: First, separately in each single hydrophone, and then combined in order to improve the localization accuracy (spatial diversity), and the second, the information from the different hydrophones are combined (beamforming) and the HD variants are applied to find the target location. The results of both processes are compared and proved to reduce the ambiguity either is depth and in range, thus improving the final accuracy. The Cramer Rao Bound showing the minimal variance performed based on deterministic equations is presented with the best result of each process. Very satisfactory performance and accuracy are obtained. The conclusions and perspectives of this work are discussed at the end.

Develop new strategies to design and operate the multilateration systems, used for air traffic control operations, in a more efficient way. The design strategies are based on the utilization of metaheuristic optimization techniques and they are intended to found the optimal spatial distribution of the system ground stations, taking into account the most relevant system operation parameters. The strategies to operate the systems are based on the development of new positioning methods which allow solving the problems of uncertainty position and poor accuracy that the current systems can present. The new strategies can be applied to design, deploy and operate the multilateration systems for airport surface surveillance as well as takeoff-landing, approach and enroute control. An important advance in the current knowledge of air traffic control is expected from the development of these strategies, because they solve several deficiencies that have been made clear, by the international scientific community, in the last years. / Mantilla Gaviria, IA. (2013). New Strategies to Improve Multilateration Systems in the Air Traffic Control [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/29688