Binary Sequences With Low Aperiodic Autocorrelation for Synchronization Purposes

Cataloged from PDF version of article.An evolutionary algorithm is used to find three sets of binary sequences of length 49–100 suitable for the synchronization of digital communication systems. Optimization of the sets are done by taking into consideration the type of preamble used in data frames and the phase-lock mechanism of the communication system. The preamble is assumed to be either a pseudonoise (PN) sequence or a sequence of 1’s. There may or may not be phase ambiguity in detection. With this categorization, the first set of binary sequences is optimized with respect to aperiodic autocorrelation which corresponds to the random (PN) preamble without phase ambiguity case. The second and third sets are optimized with respect to a modified aperiodic autocorrelation for different figures of merit corresponding to the predetermined preamble (sequence of 1’s) with and without phase ambiguity cases

Landscape statistics of the low autocorrelated binary string problem

The statistical properties of the energy landscape of the low autocorrelated binary string problem (LABSP) are studied numerically and compared with those of several classic disordered models. Using two global measures of landscape structure which have been introduced in the Simulated Annealing literature, namely, depth and difficulty, we find that the landscape of LABSP, except perhaps for a very large degeneracy of the local minima energies, is qualitatively similar to some well-known landscapes such as that of the mean-field 2-spin glass model. Furthermore, we consider a mean-field approximation to the pure model proposed by Bouchaud and Mezard (1994, J. Physique I France 4 1109) and show both analytically and numerically that it describes extremely well the statistical properties of LABSP

An Electromagnetism-Like Approach for Solving the Low Autocorrelation Binary Sequence Problem

In this paper an electromagnetism-like approach (EM) for solving the low autocorrelation binary sequence problem (LABSP) is applied. This problem is a notoriously difficult computational problem and represents a major challenge to all search algorithms. Although EM has been applied to the topic of optimization in continuous space and a small number of studies on discrete problems, it has potential for solving this type of problems, since movement based on the attraction-repulsion mechanisms combined with the proposed scaling technique directs EM to promising search regions. Fast implementation of the local search procedure additionally improves the efficiency of the overall EM system

Target detection by radar using linear frequency modulation

Range Detection is the maximum distance across which a target can detect a target. Range Resolution is the ability of the Radar to distinguish between two closely spaced targets. Range Resolution can be enhanced by using short duration pulses. But using short duration pulses results in less Range Detection. To overcome these shortcomings pulse compression techniques are used. We use a Linear Frequency Modulated (LFM) Wave for pulse compression purposes as it gives a wide operating bandwidth. It involves two types of correlation processes: matched filter processing and stretch processing. Matched Filter is used for narrow-band and Stretch Processor is used for wide-band signals. In this thesis we have analyzed both these processes and the effects of Time- Bandwidth Product, change in Doppler Frequency and effect of different kinds of windows on the LFM wave. Also masking effect is observed on the echo of a distant target due to the echo of a nearby target. The various methods to remove the masking effect are inspected