Aplicação de Algoritmos Bioinspirados à Otimização da Estimação da Direção de Chegada
Resumo
Este trabalho apresenta implementações rápidas de algoritmos bio-inspirados para a estimação da direção de chegada de sinais incidindo em um arranjo linear de sensores. Resultados experimentais mostram uma significativa redução no tempo de execução dispendido por eles, porém, ainda apresentando um robusto desempenho de estimação mesmo em baixas relações sinal-ruído.
Referências
Alves, C. A. (2004). Análise Teórica e Experimental de Métodos de Estimação de DOA e de Estimação de Freqüência com Alta Resolução. PhD thesis, State University of Campinas.
Boccato, L., Krummenauer, R., Attux, R., and Lopes, A. (2012). Application of natural computing algorithms to maximum likelihood estimation of direction of arrival. Signal Processing, 92(5):1338–1352.
Boccato, L., Krummenauer, R., Attux, R., and Lopes, A. (2013). Improving the efficiency of natural computing algorithms in doa estimation using a noise filtering approach.
Circuits, Systems, and Signal Processing, 32:1991–2001.
Carvalho, M. H., Cerioli, M. R., Dahab, R., Feofiloff, P., Fernandes, C. G., Ferreira, C. E., Guimarães, K. S., Miyazawa, F. K., de Pina Jr., J. C., Soares, J. A. R., and Wakabayashi, Y. (2001). Uma Introdução Sucinta a Algoritmos de Aproximação. Instituto de Matemática Pura e Aplicada, Rio de Janeiro, RJ.
Chen, S., Sun, S., Xu, G., Su, X., and Cai, Y. (2020). Beam-space multiplexing: Practice, theory, and trends-from 4g td-lte, 5g, to 6g and beyond.
de Castro, L. N. and Von Zuben, F. J. (2002). Learning and optimization using the clonal selection principle. IEEE Transactions on Evolutionary Computation, 6(3):239–251.
Ferreira, Y. R. and Lemos, R. P. (2005). A new DOA estimation algorithm based on angle search through the difference between the principal singular values. In Proceedings of the International Microwave and Optoelectronics Conference, volume 5, pages 283–286, Brası́lia, Brazil.
Forster, P. and Vezzosi, G. (1987). Application of spheroidal sequences to array processing. In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’87), pages 2268–2271, Dallas, USA.
Fujitsu and Cisco (2008). Beamforming boosts the range and capacity of WiMAX networks. Technical report.
Gershman, A. B. and Stoica, P. (1999). New MODE-based techniques for direction finding with an improved threshold performance. Signal Processing, 76:221–235.
Hawkes, M., Nehorai, A., and Stoica, P. (2001). Performance breakdown of subspace-based methods: Prediction and cure. In Proceedings of 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’01), pages 4005–4008, Salt Lake City, USA.
Haykin, S. (2001). Adaptive Filter Theory. Prentice-Hall, Englewood Cliffs, NJ, 4th edition edition.
Kennedy, J. and Eberhart, R. (1995). Particle swarm optimization. In IEEE International Conference on Neural Networks, pages 1942–1948.
Krishnaveni, V., Kesavamurthy, T., and Aparna, B. (2013). Beamforming for direction-of-arrival (DOA) estimation – a survey. International Journal of Computer Applications, 61(11):4–11.
Krummenauer, R., Cazarotto, M., Lopes, A., Larzabal, P., and Forster, P. (2010). Improving the threshold perfomance of maximum likelihood estimation of direction of arrival. Signal Processing, 90(11):1582–1590.
Lemos, R. P., e Silva, H. V. L., Flôres, E. L., Kunzler, J. A., and Beltrán, D. F. B. (2016). Spatial filtering based on differential spectrum for improving ML DOA estimation performance. IEEE Signal Processing Letters, 23(12):1811–1815.
Li, F. and Vaccaro, R. J. (1991). Unified analysis for DOA estimation algorithms in array signal processing. Signal Processing, 25:147–169.
Li, M. and Lu, Y. (2007). A refined genetic algorithm for accurate and reliable DOA estimation with a sensor array. Wireless Personal Communications, 43(2):533–547.
Liberti, J. C. and Rappaport, T. S. (1999). Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA. Prentice-Hall, Upper Saddle River, NJ.
Lopes, A., Bonatti, I. S., Peres, P. L. D., and Alves, C. A. (2003). Improving the MODEX algorithm for direction estimation. Signal Processing, 83(9):2047–2051.
National Instruments (2018). The road to realizing 5g technologies. Technical report. Pappa, G. L. (2015). Notas de aula em Conceitos e Aplicações em Aprendizado de Máquina. Departamento de Ciência da Computação da Universidade Federal de Minas Gerais.
Starer, D. (1990). Algorithms for Polynomial-Based Signal Processing. PhD thesis, Yale University.
Stoica, P. and Nehorai, A. (1990). Performance study of conditional and unconditional direction-of-arrival estimation. IEEE Transactions on Acoustic, Speech and Signal Processing, 38(10):1783–1795.
Stoica, P. and Sharman, K. C. (1990). Novel eigenanalysis method for direction estimation. IEE Proceedings F Radar and Signal Processing, 137(1):19–26.
Storn, R. and Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11:341–359.
Boccato, L., Krummenauer, R., Attux, R., and Lopes, A. (2012). Application of natural computing algorithms to maximum likelihood estimation of direction of arrival. Signal Processing, 92(5):1338–1352.
Boccato, L., Krummenauer, R., Attux, R., and Lopes, A. (2013). Improving the efficiency of natural computing algorithms in doa estimation using a noise filtering approach.
Circuits, Systems, and Signal Processing, 32:1991–2001.
Carvalho, M. H., Cerioli, M. R., Dahab, R., Feofiloff, P., Fernandes, C. G., Ferreira, C. E., Guimarães, K. S., Miyazawa, F. K., de Pina Jr., J. C., Soares, J. A. R., and Wakabayashi, Y. (2001). Uma Introdução Sucinta a Algoritmos de Aproximação. Instituto de Matemática Pura e Aplicada, Rio de Janeiro, RJ.
Chen, S., Sun, S., Xu, G., Su, X., and Cai, Y. (2020). Beam-space multiplexing: Practice, theory, and trends-from 4g td-lte, 5g, to 6g and beyond.
de Castro, L. N. and Von Zuben, F. J. (2002). Learning and optimization using the clonal selection principle. IEEE Transactions on Evolutionary Computation, 6(3):239–251.
Ferreira, Y. R. and Lemos, R. P. (2005). A new DOA estimation algorithm based on angle search through the difference between the principal singular values. In Proceedings of the International Microwave and Optoelectronics Conference, volume 5, pages 283–286, Brası́lia, Brazil.
Forster, P. and Vezzosi, G. (1987). Application of spheroidal sequences to array processing. In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’87), pages 2268–2271, Dallas, USA.
Fujitsu and Cisco (2008). Beamforming boosts the range and capacity of WiMAX networks. Technical report.
Gershman, A. B. and Stoica, P. (1999). New MODE-based techniques for direction finding with an improved threshold performance. Signal Processing, 76:221–235.
Hawkes, M., Nehorai, A., and Stoica, P. (2001). Performance breakdown of subspace-based methods: Prediction and cure. In Proceedings of 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’01), pages 4005–4008, Salt Lake City, USA.
Haykin, S. (2001). Adaptive Filter Theory. Prentice-Hall, Englewood Cliffs, NJ, 4th edition edition.
Kennedy, J. and Eberhart, R. (1995). Particle swarm optimization. In IEEE International Conference on Neural Networks, pages 1942–1948.
Krishnaveni, V., Kesavamurthy, T., and Aparna, B. (2013). Beamforming for direction-of-arrival (DOA) estimation – a survey. International Journal of Computer Applications, 61(11):4–11.
Krummenauer, R., Cazarotto, M., Lopes, A., Larzabal, P., and Forster, P. (2010). Improving the threshold perfomance of maximum likelihood estimation of direction of arrival. Signal Processing, 90(11):1582–1590.
Lemos, R. P., e Silva, H. V. L., Flôres, E. L., Kunzler, J. A., and Beltrán, D. F. B. (2016). Spatial filtering based on differential spectrum for improving ML DOA estimation performance. IEEE Signal Processing Letters, 23(12):1811–1815.
Li, F. and Vaccaro, R. J. (1991). Unified analysis for DOA estimation algorithms in array signal processing. Signal Processing, 25:147–169.
Li, M. and Lu, Y. (2007). A refined genetic algorithm for accurate and reliable DOA estimation with a sensor array. Wireless Personal Communications, 43(2):533–547.
Liberti, J. C. and Rappaport, T. S. (1999). Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA. Prentice-Hall, Upper Saddle River, NJ.
Lopes, A., Bonatti, I. S., Peres, P. L. D., and Alves, C. A. (2003). Improving the MODEX algorithm for direction estimation. Signal Processing, 83(9):2047–2051.
National Instruments (2018). The road to realizing 5g technologies. Technical report. Pappa, G. L. (2015). Notas de aula em Conceitos e Aplicações em Aprendizado de Máquina. Departamento de Ciência da Computação da Universidade Federal de Minas Gerais.
Starer, D. (1990). Algorithms for Polynomial-Based Signal Processing. PhD thesis, Yale University.
Stoica, P. and Nehorai, A. (1990). Performance study of conditional and unconditional direction-of-arrival estimation. IEEE Transactions on Acoustic, Speech and Signal Processing, 38(10):1783–1795.
Stoica, P. and Sharman, K. C. (1990). Novel eigenanalysis method for direction estimation. IEE Proceedings F Radar and Signal Processing, 137(1):19–26.
Storn, R. and Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11:341–359.
Publicado
11/11/2020
Como Citar
S. NETO, Adı́lio; FERNANDES, Kátia; SOUSA, Daniel; KUNZLER, Jonas; LEMOS, Rodrigo; SILVA, Hugo.
Aplicação de Algoritmos Bioinspirados à Otimização da Estimação da Direção de Chegada. In: ESCOLA REGIONAL DE INFORMÁTICA DE GOIÁS (ERI-GO), 8. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 45-58.
DOI: https://doi.org/10.5753/erigo.2020.13861.
