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http://dx.doi.org/10.17661/jkiiect.2017.10.2.154

A Study on Unmanned Vehicles Estimation using Steepest Descent, Wiener and Bartlett Algorithm  

Lee, Kwan-Hyeong (Division of Human IT Convergence, Major in Human Robot Convergence, Daejin University)
Song, Woo-Young (Department of Electronic Engineering, Cheongju University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.10, no.2, 2017 , pp. 154-160 More about this Journal
Abstract
In this paper, we studied the Bartlett method to correctly estimate the targets of a unmanned vehicles. The Bartlett method estimates the desired signals by making the gain constant for the received signal incident on the array antenna. In this paper, the weights of the Bartlett method are updated by applying the winner method and steepest descent method in order to estimation the accurate unmanned. The updated weights improve the resolution of the existing Bartlett method by applying optimal weights to all received signals received at the array antenna. Through simulation, we are comparative analysis about the performance of proposed method. From result of simulation, We showed the superior performance of the proposed method relative to the classical method, and Bartlett using steep descent method showed more superior than one using wiener method.
Keywords
Bartlett method; Resolution; Steepest descent; Weight value; Wiener;
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1 Li.Feng, Li Gao, and Yun Hui Li,"Research on information processing of intelligent Lane-Changing Behaviors for Unmanned Ground Vehicles" IEEE Conference 2016 9th international symposium on computational intelligence and Design, Vol.2, Dec, 2016.
2 Vindhya Devalla, and Om Prakash, " Developments in unmanned powered parachute aerial vehicle: a review", IEEE Aerospace and Electronic systems Magazine, Vol.29, No.11, pp. 6-20, May, 2014.   DOI
3 A.J.Haug and G.M.Jacyna, "Theory and analytical performance evaluation of generalized correlation beamformers", IEEE Journal of Oceanic Engineering, Vol.25, No.3, pp.314-330, Aug, 2000.   DOI
4 Jon W. Wallace and Michael A. jensen, " Sparse power angle spectrum estimation", IEEE Transactions on antennas and propagation, Vol.57, No.8, pp.2453-2460, June,2009.
5 B. Allen and M. Ghavarri, "Adaptive Array Sys tem", Wiley, Feb, 2005.
6 Shuo Chen, Yi Hong Ong, and Quan Liu,"A method to create an universal calibration dataset for roman reconstruction based on wiener estimation", IEEE Journal of selected topics in quantum electronics, Vol.22, No.3, Sept, 2015.
7 Yoshifumi Nagata, Toyata Fujioka, and Masato Abe,"Two-Dimensional DOA estimation of sund sourece based on weighted wiener gain exploiting two-directional microphones", IEEE Transaction on Audio, speech, and language processing, Vol.15, No.2, pp.416-429, Jan, 2007   DOI
8 K.Vastola," On robust wiener signal estimation", IEEE Transactions on Automatic Control, Vol.31, No.5, pp.466-467, jan, 2003.   DOI
9 Xin Cai, Xiang Wang, Zhi Tao, and Feng Hua wang, "Single channel steepest descent algorithm for the correction of cycle frequency error", IET communications, Vol.10, No.14, Sept, 2016.
10 H.D .Han and Z.Ding, "Steepest descent algorithm implementation for multichannel blind signal recovery", IET Communications, Vol.6, No.18, pp.3196-3203, Jan, 2013   DOI
11 R.Schmidt,"Multiple emitter location and signal parameter estimation", IEEE Transactions on Antennas and Propagation, Vol.34, No.3, pp.276-280, Jan, 2003.   DOI
12 M.Zoltowski, and F.Haber, " A Vector space approach to direction finding in a coherent multipath environment", IEEE Transactions on Antennas and Propagation, Vol.34, No.9, pp.1069-1079, Jan, 2003.   DOI