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
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;
Conference_Titel :
Information Technology and Artificial Intelligence Conference (ITAIC), 2014 IEEE 7th Joint International
Print_ISBN :
978-1-4799-4420-0
DOI :
10.1109/ITAIC.2014.7065099