Application of particle swarm optimization to spacetime twodimensional parameter estimation
QIU Xin-jian1,2,SHANBAI Dalabaev1,XUE Feng-feng3
1. College of Information Science and Engineering, Xinjiang University,Urumqi Xinjiang 830046,China 2. Unit 68203 of PLA, Jiuquan Gansu 735000, China 3. Telecommunications Engineering Institute, Air Force Engineering University, Xi’an Shaanxi 710077,China
Abstract：The traditional spacetime twodimensional parameter estimation has many shortcomings, such as high computational complexity, poor robustness and generalization, and slow convergence speed. According to the spacetime equivalence and that the spatial and time domain processing algorithms can be transformed into each other, a suitable fitness function was derived, the improved particle swarm algorithm was used to search the arrival angle and frequency of signal, and the search results were classified with Kmeans clustering algorithm. Using particle swarm algorithms feature, such as global convergence, parallelism, can improve the algorithms searching capabilities. The computer simulation shows that the proposed method has better statistics and convergence performance than traditional methods.
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2012, Vol. 32 
