Title :
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
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;
Conference_Titel :
Radar, 1996. Proceedings., CIE International Conference of
Conference_Location :
Beijing
Print_ISBN :
0-7803-2914-7
DOI :
10.1109/ICR.1996.573792
