DocumentCode
3580410
Title
One intelligent algorithm for estimation of TDOA and FDOA
Author
Zhi yu Lu ; Jian Hui Wang ; Da Mng Wang ; Yue Wang
Author_Institution
China Nat. Digital Switching Syst. Eng. & Technol. R&DCenter, NDSC, Zhengzhou, China
fYear
2014
Firstpage
492
Lastpage
496
Abstract
The calculation is large to estimate the TDOA and FDOA with cross ambiguity function. Existing algorithms which are based on the ergodic theory have poor real-time performance. To solve this problem, the genetic algorithm is proposed with improvements based on the characteristics of cross ambiguity function. With the self-adapting mutation probability by following the convergence extent of the population and multiple population initializations, the diversity of the population is effectively improved to prevent the algorithm into a local optimum. The simulation results show that the computational efficiency of the improved algorithm, compared with the existing algorithms, is greatly improved, and the TDOA/FDOA estimation results can quickly be obtained.
Keywords
convergence; direction-of-arrival estimation; genetic algorithms; probability; time-of-arrival estimation; FDOA estimation; Intelligent Algorithm; TDOA estimation; computational efficiency; cross ambiguity function; ergodic theory; frequency difference of arrival; genetic algorithm; multiple population initializations; population convergence extent; population diversity; self-adapting mutation probability; time difference of arrival; Algebra; Algorithm design and analysis; Convergence; Estimation; Genetic algorithms; Sociology; Statistics; FDOA; TDOA; cross ambiguity function; genetic algorithm; passive location;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Artificial Intelligence Conference (ITAIC), 2014 IEEE 7th Joint International
Print_ISBN
978-1-4799-4420-0
Type
conf
DOI
10.1109/ITAIC.2014.7065099
Filename
7065099
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