Showing papers by "John J. Shynk published in 2011"
TL;DR: This paper proposes a blind adaptive GPS receiver that is based on a new despreader and the one-stage constant modulus (CM) array, which together modify the received signal so that the CM array can extract the GPS signal of interest.
Abstract: The Global Positioning System (GPS) utilizes low-power spread-spectrum signals and thus is vulnerable to various types of high-power interference sources. It requires at least four satellites for estimating three-dimensional user positions and the receiver clock bias. In this paper, we propose a blind adaptive GPS receiver that is based on a new despreader and the one-stage constant modulus (CM) array. The despreader consists of a conventional GPS despreader and a so-called null despreader, which together modify the received signal so that the CM array can extract the GPS signal of interest. The beamformer not only rejects jammers and extracts the GPS signal of interest without explicit direction-of-arrival (DOA) information of any of the signals but also it has a low computational complexity compared with conventional techniques, such as minimum-variance distortionless-response (MVDR) beamforming. As a conventional despreader can recover only one GPS signal, multiple despreaders are usually required for separating multiple GPS signals. We also explore an extension of the proposed null despreader to detect multiple GPS signals. Computer simulation examples are presented to illustrate the performance of the receiver for different types of jammer signals. Copyright © 2010 John Wiley & Sons, Ltd.
4 citations
01 Nov 2011
TL;DR: A modified system-based MSB algorithm is proposed that not only has good performance for white and non-white input signals, but also has a reduced computational complexity compared with conventional approaches such as the previous cross-correlation-based (CCB) and system- based (SB) algorithms.
Abstract: Adaptive algorithms can be an important component of a sparse reconfigurable adaptive filter (SRAF) for photonic switches In this paper, we propose a modified system-based (MSB) algorithm that not only has good performance for white and non-white input signals, but also has a reduced computational complexity compared with conventional approaches such as the previous cross-correlation-based (CCB) and system-based (SB) algorithms In order to improve the convergence rate of the system, the MSB algorithm separately updates each row or column of the switch weight matrix We also consider a specific structure for the intermediate desired signals, and present a computer simulation example to demonstrate the performance of the proposed SRAF algorithm for a system identification application
1 citations