Based on the conclusion drawn by Li and Wang that radar with higher range resolution can provide better tolerance to aspect variation, a lot of work has been done on radar target recognition using super-resolution range profiles as features.

A new method of range super-resolution of radar is proposed ,Its basic idea is to calculate the parameters of AR model of target transfer function and to extrapolate the raw data linearly both with Adaline.

Due to the aspect sensitivity of high-resolution range profile (HRRP), the template database should include all the templates for each small aspect range.

Due to the nonlinear separability and high feature dimensionality of high-resolution range profile(HRRP),an approach based on the so called optimized kernel fisher discriminant analysis for radar target recognition is proposed.

The high resolution range profiles(HRRP) characteristics of missiles are analyzed.

The differential cepstrum properties of a radar HRR profile are presented and studied by means of a Z transform, based physically upon the fact that a radar high resolution range profile is characterized by non minimum phase and wavelet features.

Then a relationship is established between the logarithm bispectra averaged and a high resolution range profile.

Radar target recognition of the high resolution range profiles based on nonlinear transform;

Due to the aspect sensitivity of high-resolution range profile (HRRP),tradition al radar HRRP target recognition methods usually use average profile within some aspect region as aspect template.