Técnica para la localización de fuentes basada en la perspectiva de reconstrucción de la señal

  1. González-Pacheco García, Raúl Óscar
Supervised by:
  1. Manuel Felipe Cátedra Pérez Director

Defence university: Universidad de Alcalá

Fecha de defensa: 22 November 2013

  1. Iván González Diego Chair
  2. Eliseo García García Secretary
  3. Raúl Fernández Recio Committee member
  4. David Escot Bocanegra Committee member
  5. Fernando Rivas Peña Committee member
  1. Ciencias de la Computación

Type: Thesis


There are many applications which make use of sensor arrays to locate signal sources and, in the majority of cases, they attempt to estimate the distance from such sources. There are a large number of methods for estimating the distance, and such methods focus on the case of narrow band signals, that is to say those where the time delay can be likened to phase scrolling. This thesis focuses on the use of super-resolution algorithms for estimating distances from narrow band sources. Specifically, it is an evaluation of the performance of the most popular super-resolution algorithms, those which enable the reduction of computing time while also increasing precision and reducing the hardware requirements. However, all these parameters vary greatly among themselves, along with the probability of resolution. This determines whether or not they can be used for applications in real time. The super-resolution methods use the concept of signal sub-space. In order to deal with broadband signals, the signals received are broken down into narrow band signals by means of a band-pass filter, and then the same algorithms are applied with some specific considerations. In synthesis, it can be said that there are two different forms of resolving the decomposed signals. The incoherent methods process each band independently, by means of a specific narrow band procedure, averaging the results afterwards. The coherent methods modulate the signals in each band so that they can be combined subsequently into a coherent form. This thesis compares the performance of the different super-resolution algorithms in terms of speed, precision and resource needs. A new method is proposed, which makes use of a single sensor and exhibits a series of desired characteristics for the majority of applications dealing with narrow band sources. The results of the application of this method to the different super-resolution algorithms are compared with each other and with those of other traditional methods.