Work place: School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054 China
E-mail: cloudhopping@163.com
Website:
Research Interests: Image Compression, Image Manipulation, Image Processing, Statistics
Biography
Liyun Su was born in Guang’an city, Sichuan province, Peoples’ Republic of China, in December, 1977. He received the B.S. degree in applied mathematics in 2001. The M.S’s and PH.D’s degree were received in stochastic signal processing of probability and statistics in 2004, 2007,respectively, both from the College of Mathematics, Sichuan University, P. R. China. He is now a faculty member of school of mathematics and statistics of Chongqing University of Technology in China. His research interests include statistical signal processing, weak signal detection, digital image processing, financial statistics, and communication signal processing. He has published over 20 papers including 9 SCI-indexed journal papers and over 10 EI-indexed papers. He also is a council member of Chinese engineering probability and statistics society and Chongqing Operation Research society.
By Su Liyun
DOI: https://doi.org/10.5815/ijitcs.2014.02.02, Pub. Date: 8 Jan. 2014
The Joint Probabilistic Data Association (JPDA) solves single sensor multi-target tracking in clutter, but it cannot be used directly in multi-sensor multi-target tracking (MMT) and has high computational complexity with the number of targets and the number of returns. This paper presents a hybrid method to implement MMT by combing Maximum Likelihood Estimation (MLE) with Adaptive Neuro-Fuzzy Inference System (ANFIS). The MLE is applied to classify the same source observations at one time into the same set, then the cheap JPDA(CJPDA) approach is used to calculate the data association probability, and ANFIS is used to realize the MMT. The computer simulations indicate that this scheme achieves MMT perfectly with higher precision and easy realization.
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