Title :
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.
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;
Conference_Titel :
Information, Communications and Signal Processing, 2005 Fifth International Conference on
Conference_Location :
Bangkok
Print_ISBN :
0-7803-9283-3
DOI :
10.1109/ICICS.2005.1689073
