Telecommunications and Radio Engineering

ISSN for PRINT: 0040-2508

For Online Access

Best Paper Award Selection - Editorial Board Site

2001, Volume56

Issue 4&5

210 pages

Issue price - $394.00

Victor Golikov
Universidad Autonoma del Carmen,Ciudad del Carmen, Campeche, Mexico

Olga Lebedeva
Universidad Autonoma del Carmen, Ciudad del Carmen, Campeche, Mexico

Jose Luis Orta
Director of Department of Universidad Autonoma del Carmen, Ciudad del Carmen, Campeche, Mexico

This paper proposes a method to reduce the computational complexity of the optimal digital quadratic detector, which is the optimal Neyman-Pearson detector for detecting a colored Gaussian random target signal against colored Gaussian distributed noise. The covariance matrices of the colored noise are unknown. We also presents fully adaptive detector and it exhibits an acceptable loss with respect to previously proposed adaptive detector. This detector has been constructed by replacing the covariant matrices on the appropriate block-circulant matrices in the likelihood ratio for example dyadic matrices. The performance comparison between the classical adaptive approach and the adaptive approach proposed by the authors carried out in terms of probability of detection as a function of the signal to noise ratio for a fixed probability of false alarm and in term of computational complexity.

Download article, 6 pages

Article price - $35.00

<< Previous article   Next article >>