Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

Author

Patnaik, L.M. ; Nair, Hema ; Abraham, Varghese ; Raghavendra, G. ; Singh, Shishir Kumar ; Srinivasan, Rajan ; Ramchand, K.

Author_Institution

Microprocessor Applications Lab., Indian Inst. of Sci., Bangalore, India

Volume

1

fYear

1996

fDate

3-6 Jun 1996

Firstpage

223

Abstract

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Keywords

aircraft instrumentation; backpropagation; neural nets; radar signal processing; radar tracking; sensor fusion; RPROP algorithm; airborne track-while-scan radar; multisensor data fusion; neural network algorithms; performance evaluation; single target scenario; standard backpropagation; Airborne radar; Aircraft; Azimuth; Backpropagation algorithms; Intelligent networks; Neural networks; Radar applications; Radar tracking; Sensor fusion; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1996., IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-7803-3210-5

Type

conf

DOI

10.1109/ICNN.1996.548895

Filename

548895