DocumentCode :
2242131
Title :
A fully-hardware-type maximum-parallel architecture for Kalman tracking filter in FPGAs
Author :
Lee, C.R. ; Salcic, Z.
Author_Institution :
Dept. of Electr. & Electron. Eng., Auckland Univ., New Zealand
fYear :
1997
fDate :
9-12 Sep 1997
Firstpage :
1243
Abstract :
The Kalman filter for linear estimation and the extended Kalman filter for nonlinear estimation are the most typical complex and precise algorithms used for target tracking. But, for multi-target tracking (MTT) radar systems, the computational time for calculating the Kalman-filter-based algorithms in software is too long to meet today´s warfare needs. The FPGA-based reconfigurable Kalman filtering coprocessor for MTT systems has been proposed. A fully-hardware-type maximum parallel FPGA-based Kalman tracking filtering coprocessor in a track-while-scan (TWS) radar system has been designed and presented. The performance gained in our approach includes two to three orders of magnitude higher speed than other implementations
Keywords :
Kalman filters; coprocessors; digital signal processing chips; field programmable gate arrays; military equipment; nonlinear filters; parallel algorithms; parallel architectures; phased array radar; radar computing; radar signal processing; radar tracking; 3D phased-array rada; FPGA; Kalman filter based algorithms; Kalman tracking filter; MTT systems; computational time; linear estimation; maximum-parallel architecture; multitarget tracking radar systems; nonlinear estimation; performance; radar computer; reconfigurable Kalman filtering coprocessor; software; target tracking; track-while-scan radar system; warfare; Coprocessors; Field programmable gate arrays; Filtering; Intelligent sensors; Kalman filters; Logic devices; Military computing; Radar tracking; Target tracking; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
Print_ISBN :
0-7803-3676-3
Type :
conf
DOI :
10.1109/ICICS.1997.652183
Filename :
652183
Link To Document :
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