Weighted Subspace Fitting DOA Estimation Based on Shuffled Frog Leaping Algorithm

Zhi Cheng Zhang; Xiao Hui Yu; Hai Xin Sun

doi:10.4028/www.scientific.net/AMM.411-414.1049

Paper Titles

A Fast Acquisition Algorithm for GNSS Multi-System Interoperability Signals
p.1025

Doppler Radio Fuze Signal Processing Method Based on the Extraction of Instantaneous Frequency
p.1033

Data Mining Utilization for Plant Historical Processing Accumulated Data
p.1040

Collaborative Filtering Algorithm Based on User Clustering
p.1044

Weighted Subspace Fitting DOA Estimation Based on Shuffled Frog Leaping Algorithm
p.1049

A Novel Method for Deinterleaving of Radar Signals Using Blind Source Separation
p.1053

Coal Gangue Interface Recognition Based on MFCC Research
p.1058

Data Integrity and Availability in Cloud Computing Based on Megastore
p.1062

Rolling Bearing Fault Feature Extraction Based on SVD-EEMD
p.1067

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 411-414Weighted Subspace Fitting DOA Estimation Based on...

Weighted Subspace Fitting DOA Estimation Based on Shuffled Frog Leaping Algorithm

Abstract:

In this paper, shuffled frog leaping algorithm (SFLA) is used to reduce the computation load of weighted subspace fitting (WSF) method for DOA estimation. As a recently proposed meta-heuristic algorithm, SFLA is suitable to solve the nonlinear multimodal optimization problem which WSF method encounters, so it offers an excellent alternative to the conventional methods in WSF-DOA estimation. Thus, the feasibility of SFLA applying to WSF-DOA estimation is analyzed, and its performance is compared with other popular meta-heuristic methods. Simulation results demonstrate that the proposed method is more efficient in computation and statistical performance.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 411-414)

Pages:

1049-1052

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.411-414.1049

Citation:

Cite this paper

Online since:

September 2013

Authors:

Zhi Cheng Zhang, Xiao Hui Yu, Hai Xin Sun

Keywords:

Direction-of-Arrival (DOA), Meta-Heuristic, Shuffled Frog Leaping, Subspace Fitting

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] M. Viberg and B. Ottersten. Sensor array processing based on subspace fitting. IEEE Transactions on Signal Processing, vol. 39, no. 5, pp.1110-1121, (1991).

DOI: 10.1109/78.80966

Google Scholar

[2] R.O. Schmidt. Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas Propagations, vol. 34, no. 3, pp.276-280, (1986).

DOI: 10.1109/tap.1986.1143830

Google Scholar

[3] R. Roy and T. Kailath. ESPRIT-estimation of signal parameters via rotational invariance techniques. IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 37, no. 7, pp.984-995, (1989).

DOI: 10.1109/29.32276

Google Scholar

[4] C. Zhao and F. Li. Wide-Band weighted sub-space fitting direction finding algorithm based on genetic algorithm. Acta Electronica Sinica, vol. 32, no. 9, pp.1487-1490, 2004. (In Chinese).

Google Scholar

[5] Y. Jiao, J. Huang and J. Han. Continuous ant colony optimization based weighted subspace fitting fast algorithm for DOA estimation with few snapshots. Journal of Electronics and Information Technology, vol. 33, no. 4, pp.973-976.

DOI: 10.3724/sp.j.1146.2010.00783

Google Scholar

[6] M. Eusuff and K. Lansey. Optimization of water distribution network design using the shuffled frog leaping algorithm. Journal of Water Resources Planning and Management, vol. 129, no. 3, pp.210-225, (2003).

DOI: 10.1061/(asce)0733-9496(2003)129:3(210)

Google Scholar

[7] M. Eusuff , K. Lansey and F. Pasha. Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Engineering Optimization, vol. 38, no. 2, pp.129-154, (2006).

DOI: 10.1080/03052150500384759

Google Scholar