Application of self-organizing neural networks to multiradar data fusion

Wann, C-D; Thomopoulos, SCA

dc.contributor.author	Wann, C-D	en
dc.contributor.author	Thomopoulos, SCA	en
dc.date.accessioned	2014-03-01T01:45:53Z
dc.date.available	2014-03-01T01:45:53Z
dc.date.issued	1997	en
dc.identifier.issn	00913286	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24775
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-3643111473&partnerID=40&md5=e6134080f1d968f06e2c30aa4d03358d	en
dc.subject	Clustering	en
dc.subject	Data fusion	en
dc.subject	Dignet	en
dc.subject	Neural networks	en
dc.subject	Self-organization	en
dc.subject	Sensor fusion	en
dc.subject	Signal processing	en
dc.subject	Target detection	en
dc.title	Application of self-organizing neural networks to multiradar data fusion	en
heal.type	journalArticle	en
heal.publicationDate	1997	en
heal.abstract	The self-organizing neural network Dignet is used in the design of a two-stage parallel data fusion system. The data fusion is applied to target detection problems in a multichannel moving target indication (MTI) system. Features of the received data from three different radar channels are extracted via digital signal processing techniques. Pulse compression, clutter canceling, and the fast Fourier transform (FFT) are used to transform data from the time-range domain to the range-Doppler domain for feature processing. A first-stage Dignet module on each channel is used for feature clustering and prefiltering. The clustering results from each channel Dignet module are passed on to the fusion Dignet for the second-stage clustering. Map regularization, circular metric, and contrast enhancement are used to resolve the misalignment problem of features on the range-Doppler maps from sensors on different channels. Each first-stage Dignet module performs feature extraction and clustering as a filter-upon-demand module that generates adaptiveness as it is required by the data clustering. Experimental results on field data have shown that a Dignet-based multiradar data fusion system successfully detects a moving target embedded in clutter. © 1997 Society of Photo-Optical Instrumentation Engineers.	en
heal.journalName	Optical Engineering	en
dc.identifier.volume	36	en
dc.identifier.issue	3	en
dc.identifier.spage	799	en
dc.identifier.epage	813	en