DocumentCode
2538994
Title
Study on emitter signal recognition based on backward cloud model and attribute similarity
Author
Li-na, Pan
Author_Institution
Dept. of Basic Sci., Naval Aeronaut. & Astronaut. Univ., Yantai, China
Volume
2
fYear
2012
fDate
21-23 May 2012
Firstpage
546
Lastpage
550
Abstract
To deal with the problem of radar emitter recognition caused by noise environment, this paper presents a new method for emitter recognition based on backward cloud model and attribute similarity. First, it constructs a radar emitter database included with noise data according with the reality, then calculates the cloud numerical characteristic based on backward cloud model, presents a method of determining recognition weight of coefficients, and a new classification implement based on backward cloud model and attribute similarity is proposed. Simulation results show that the method proposed by this article can deal with the randomicity and vagueness caused by noise environment much better and can conduct emitter recognition effectively in the adverse noise envioroment.
Keywords
radar computing; adverse noise envioroment; attribute similarity; backward cloud model; cloud numerical characteristic; emitter signal recognition; noise data; noise environment; radar emitter database; radar emitter recognition; randomicity; vagueness; Character recognition; Data models; Generators; Noise; Radar measurements; Simulation; Attribute similarity; Backward cloud model; Radar emitter recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwave Radar and Wireless Communications (MIKON), 2012 19th International Conference on
Conference_Location
Warsaw
Print_ISBN
978-1-4577-1435-1
Type
conf
DOI
10.1109/MIKON.2012.6233609
Filename
6233609
Link To Document