Automatic HRR target recognition based on Prony model wavelet and probability neural network

Author

Xun, Zhung ; Ronghui, Shen ; Guirong, Guo

Author_Institution

ATR Nat. Lab., Nat. Univ. of Defense Technol., Changsha, China

fYear

1996

fDate

8-10 Oct 1996

Firstpage

143

Lastpage

146

Abstract

An automatic high range resolution (HRR) target recognition algorithm is detailed and tested on a data set of five different aircraft. A super-resolution downrange profile of radar returns of HRR is obtained using the Prony model. Target features are extracted by the wavelet transform. The features consist of two parts: one reflects the detailed structure of the targets, the other shows the outline of the targets. A probabilistic neural network (PNN) with a simple data fusion technique is applied for target classification

Keywords

aircraft; feature extraction; neural nets; probability; radar cross-sections; radar target recognition; sensor fusion; signal resolution; wavelet transforms; Prony model; aircraft; automatic HRR target recognition; data fusion technique; data set; probabilistic neural network; probability neural network; radar returns; scattering centers; superresolution downrange profile; target classification; target feature extraction; target outline; target recognition algorithm; wavelet transform; Automatic testing; Data mining; Feature extraction; Frequency measurement; Laboratories; Neural networks; Polynomials; Radar scattering; Signal resolution; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 1996. Proceedings., CIE International Conference of

Conference_Location

Beijing

Print_ISBN

0-7803-2914-7

Type

conf

DOI

10.1109/ICR.1996.573792

Filename

573792