Previous |  Up |  Next


Title: A simplex trained neural network-based architecture for sensor fusion and tracking of target maneuvers (English)
Author: Wong, Yee Chin
Author: Sundareshan, Malur K.
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 35
Issue: 5
Year: 1999
Pages: [613]-636
Summary lang: English
Category: math
Summary: One of the major applications for which neural network-based methods are being successfully employed is in the design of intelligent integrated processing architectures that efficiently implement sensor fusion operations. In this paper we shall present a novel scheme for developing fused decisions for surveillance and tracking in typical multi-sensor environments characterized by the disparity in the data streams arriving from various sensors. This scheme employs an integration of a multilayer neural network trained with features extracted from the multi-sensor data and a Kalman filter in order to permit reliable tracking of maneuvering targets, and provides an intelligent way of implementing an overa without any attendant increases in computational complexity. A particular focus is given to optimizing the neural network architecture and the learning strategy which are particularly critical to develop the capabilities required for tracking of target maneuvers. Towards these goals, a network growing scheme and a simplex algorithm that seeks the global minimum of the training error are presented. To provide validation of these methods, results of several tracking experiments involving targets executing complex maneuvers in noisy and clutter environments are presented. (English)
Keyword: neural network
Keyword: multi-sensor environment
Keyword: simplex algorithm
Keyword: sensor fusion operations
Keyword: Kalman filter
MSC: 68M10
MSC: 90B06
MSC: 90B40
MSC: 92B20
MSC: 93E11
idZBL: Zbl 1274.93265
idMR: MR1728471
Date available: 2009-09-24T19:28:26Z
Last updated: 2015-03-27
Stable URL:
Reference: [2] Bar–Shalom Y., Li X. R.: Estimation and Tracking.Artech House, 1993 Zbl 0853.62076, MR 1262124
Reference: [3] Bogler P. L.: Tracking a maneuvering target using input estimation.IEEE Trans. Aerospace Electron. Systems AES-23 (1987), 298–310 10.1109/TAES.1987.310826
Reference: [4] Box G. E. P., Jenkins G. M.: Time Series Analysis, Forecasting and Control.Holden Day, San Francisco 1970 Zbl 1154.62062, MR 0272138
Reference: [5] Chan Y. T., Hu A., Plant J. B.: A Kalman filter based tracking scheme with input estimation.IEEE Trans. Aerospace Electron. Systems (1979), 237–244
Reference: [9] Hagan M. T., Demuth H. B., Beale M.: Neural Network Desig.
Reference: [14] Nelder A. J., Mead R.: A simplex method for function minimizatio.
Reference: [18] Sworder D. D.: Image enhanced tracking.IEEE Trans. Aerospace Electron. Systems AES-25 (1989), 701–710 10.1109/7.42087


Files Size Format View
Kybernetika_35-1999-5_5.pdf 3.238Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo