Robust Spread-Spectrum Communications Over Non-Gaussian Channels. Adaptive Disturbance Suppression With Small Data Support PDF Download

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Get Book

Book Description
Based on the theory of locally optimum detection we identified a spread-spectrum receiver architecture that consists of an adaptive non-linear chip-level pre-processor followed by an adaptive linear filter post-processor. The non-linear front-end protects against impulsive, non-Gaussian disturbance. The adaptive linear filter post-processor suppresses unknown highly correlated spread-spectrum (SS) interference. To achieve adaptive, rapid, and effective SS interference suppression from a small number of input observations, we defined a new class of linear filters that we called Auxiliary-Vector (AV) filters. We view this development as a breakthrough in the field of adaptive signal processing theory. When the input autocorrelation matrix is unknown and estimated from a limited set of input data (as in all real-life adaptive signal processing applications), Auxiliary-Vector filters are shown to outperform all other filter estimator means in the literature. We addressed successfully the critical problem of determining an automated, theoretically derived, rule for the selection of the best number of auxiliary vectors (AV's) for a given data record of input observations. We anticipate that this development will attract a great deal of interest in the Auxiliary-Vector filtering technique. Based on the principles of AV-filtering we proposed and analyzed theoretically structures that are self-synchronized in the sense that adaptive synchronization and demodulation are viewed and treated as an integrated receiver operation. As a major application, we addressed the problem of navigation data demodulation by an adaptive jam-resistant GPS receiver that utilizes a bank of linear-tap-delay filters and employs antenna-array reception (one space-time.