Title :
Online maneuvering target tracking using neuro-fuzzy adaptive filters
Author :
Menhaj, Mohammad B. ; Amani, Soheil
Author_Institution :
Dept. of Electr. Eng., Amirkabir Univ., Tehran, Iran
fDate :
6/23/1905 12:00:00 AM
Abstract :
In this paper two nonlinear adaptive filter are proposed for maneuvering target tracking. The maneuver is considered as an inherent part of target dynamics; this makes the system nonstationary. Due to good performance of adaptive filters in nonstationary environment, two neuro-fuzzy adaptive filter with online structure and parameter learning ability has been introduced to maneuvering target tracking. Simulation results help to judge better the merit of proposed filters
Keywords :
adaptive filters; filtering theory; fuzzy neural nets; image processing; nonlinear filters; online operation; radar imaging; target tracking; neuro-fuzzy adaptive filters; noisy radar data; nonlinear adaptive filter; nonstationary system; online maneuvering target tracking; online structure; parameter learning ability; Adaptive filters; Clustering algorithms; Equations; Fuzzy systems; Kalman filters; Noise measurement; Radar measurements; Radar tracking; Signal processing algorithms; Target tracking;
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-7293-X
DOI :
10.1109/FUZZ.2001.1007238
