Object feature extraction method based on fractional order Fourier transform

Abstract

The invention discloses an object feature extraction method based on fractional order Fourier transform, mainly for solving the problems of single feature and poor classification effect in feature extraction of the process of extracting three kinds of airplane objects. The technical scheme is as follows: 1, performing the fractional order Fourier transform on training signals; 2, extracting features from the transformed training signals; 3, performing feature selection on the extracted features; 4, training a classifier by use of selected features; 5, performing the fractional order Fourier transform on test signals; 6, extracting the features selected from the third step from the transformed test signals; and 7, sending the features extracted from the test signals into the well trained classifier so as to finish classification of the three kinds of the airplane objects. According to the invention, conventional time domain and Doppler domain features are expanded to a fraction domain, object echo features can be better described, the classification correct rate is improved, and the method can be applied to classification of such three kinds of objects including helicopters, propeller-driven airplanes and jet aircrafts.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a method for extracting target features, which can be used to classify three types of targets: helicopters, propeller planes and jet planes. Background technique [0002] Namias proposed the fractional Fourier transform in 1980. In the following ten years, the theory and research of the fractional Fourier transform have been well developed. At present, it is mostly used in filtering and image processing of chirp signals. [0003] At present, under the narrow-band radar system, there have been many research results on the classification methods of helicopters, propeller planes and jet planes. Engine modulation characteristics are used to classify targets. For example, "Research on JEM Feature Analysis and Target Classification of Conventional Radar" published by Ding Jianjiang and Zhang Xianda extracts modulation cycle features in the time domain and frequency domain re...

AI Technical Summary

Problems solved by technology

Although these existing features can reflect the periodic characteristics of the target echo to a certain extent, the description is not comprehensive, and only the time domain spectrum and Doppler domain spectrum of the echo are analyzed, which has limitations, resulting in unsatisfactory classification results

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