Radar Target Recognition Using the Differential Power Spectrum

Author

Guo, Zunhua ; Li, Shaohong

Author_Institution

Sch. of Electron. & Inf. Eng., Beijing Univ. of Aeronaut. & Astronaut.

fYear

0

fDate

0-0 0

Firstpage

385

Lastpage

387

Abstract

In this paper we discuss the problem about the target recognition by the high resolution radar range profiles. Several feature extraction methods for computing shift invariants are simply reviewed: such as bispectrum, differential cepstrum, then the differential power spectrum (DPS) based features are introduced to this study. A multi-layered feed-forward neural network with simulated annealing resilient propagation (SARPROP) algorithm is selected as classifier. Simulations are presented to identify the range profiles of four different aircrafts. The results demonstrated that the differential power spectrum based features are effective and robust for radar target recognition

Keywords

feature extraction; feedforward neural nets; radar resolution; radar target recognition; simulated annealing; spectral analysis; SARPROP algorithm; differential power spectrum; feature extraction method; multilayered feed-forward neural network; radar range profile; radar resolution; radar target recognition; simulated annealing resilient propagation; Cepstrum; Computational modeling; Feature extraction; Feedforward neural networks; Feedforward systems; Multi-layer neural network; Neural networks; Radar; Simulated annealing; Target recognition; feature extraction; high resolution radar; neural networks; range profiles; target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 2005 Fifth International Conference on

Conference_Location

Bangkok

Print_ISBN

0-7803-9283-3

Type

conf

DOI

10.1109/ICICS.2005.1689073

Filename

1689073