GENETIC ALGORITHMS IN SEARCH AND ANALYSIS OF LOWAUTOCORRELATION BINARY SEQUENCES

摘要

The design of sequences that have low side-lobes andpeaky autocorrelation functions are desirable in spreadspectrum communication and efficient radar reception.The search of such sequences becomes extremely difficultwhen the length of the sequence is increased. In this paperGenetic Algorithm is used to search Low AutocorrelatedBinary Sequences (LABS). Three objective functionsGolay merit factor, low sidelobe energy, low values ofautocorrelation coefficients other than zero-lag) can betreated separately by Genetic Algorithm and anexhaustive search is done on the final population. Thenumber of generations is controlled so that the populationgenerated will have different sequences with desiredobjective functions. In this analysis it is found that onlysome objective functions, like minimum sidelobe energy,plays a prominent role in the overall performance. Thesefindings provide useful information on the solution spacewhich can enhance the search process.