Title :
Frequency-DOA joint estimation by Ant Colony Optimization
Author :
Jin, Yong ; Hou, Yunshan ; Jiang, Min
Author_Institution :
Inst. of Image Process. & Pattern Recognition, Henan Univ., Kaifeng, China
Abstract :
The Multiple Signal Classification (MUSIC) method is a typical method for high-resolution Direction Of Arrival(DOA) and frequency estimation. Usually it performs spectrum search in certain grid space, which inevitably leads to high computational cost in the multi-dimensional case, for example the search for frequency and azimuth at the same time. To overcome this problem, in this paper, we introduced Ant Colony Optimization(ACO) to work with MUSIC. A new kind of ACO for continuous domain featured by Gauss kernel function is used to sample the MUSIC spectrum, which is regarded as the fitness function in the process. The resulted estimator is called Ant Colony Optimization based MUSIC (ACO-MUSIC). Simulations show that ACO-MUSIC not only reduces the computational complexity greatly but also maintains the excellent performance of the original MUSIC estimator.
Keywords :
computational complexity; direction-of-arrival estimation; frequency estimation; optimisation; signal classification; Gauss kernel function; MUSIC method; ant colony optimization; computational complexity; direction of arrival estimation; frequency estimation; frequency-DOA joint estimation; grid space; multidimensional case; multiple signal classification; Multiple signal classification; Signal to noise ratio; ant colony optimization; computational complexity; direction of arrival; multiple signal classification;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622542