Target classification with low-resolution radar based on dispersion situations of eigenvalue spectra

Abstract

Most low-resolution radar systems, especially ground surveillance radar systems, work at relatively low pulse repeat frequency (PRF) and with short time-on-target (TOT) (duration in scanning). Low PRF leads to Doppler ambiguity and short TOT results in low Doppler resolution, which poses a problem to target classification with low-resolution radar based on the jet engine modulation (JEM) characteristic of radar echo. From the pattern classification viewpoint, we propose a method of using dispersion situations of JEM eigenvalue spectra to categorize aeroplanes into three kinds, namely turbojet aircraft, prop aircraft and helicopter. We analyze the mathematical model of JEM echoes consisting of a series of line spectra and regard them as a sum of several series of harmonious waves. Classification features can be extracted based on the harmonious wave sum model. Some schemes for extracting features from echoes within or between pulses are proposed. Low-dimensional features are extracted to reduce computation burden. Our methods do not compensate for the fuselage echoes and are insensitive to the variation of fuselage Doppler. The feasibility of our methods is demonstrated by simulation experiment.