Radar HRRP target recognition method based on dpLVSVM model

Abstract

The invention discloses a radar HRRP target recognition method based on a dpLVSVM model. the method includes the steps of firstly, conducting feature extraction on radar HRRP data to obtain a power spectrum feather set X; secondly, constructing the dpLVSVM model, and obtaining the probability density function of power spectrum features and the combined condition posterior distribution of all parameters; thirdly, conducting derivation to obtain the condition posterior distribution of each parameter; fourthly, conducting circulating sampling on each parameter I times; fifthly, storing the sampling result of the parameter required by the T0th test stage; sixthly, judging whether the radar HRRP is an outside-library sample or not, if yes, rejecting the judgment, and if not, executing the seventh step; seventhly, conducting sampling to obtain the cluster mark number of the power spectrum features (please see the specification); eighthly, outputting the target classification mark number (please see the specification) of the radar HRRP. The method has the advantages of being low in classifier design complexity, good in recognition performance and good in judgment rejection performance, and can be used for radar target recognition.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to a radar target recognition method, in particular to a target recognition method based on a dpLVSVM (Dirichlet process latent variable support vector machine, Dirichlet process latent variable support vector machine) model of a radar high-resolution range profile HRRP. It is used to identify targets such as aircraft and vehicles. Background technique [0002] Radar target recognition is to use the radar echo signal of the target to realize the judgment of the target type. Broadband radar usually works in the optical region, where the target can be regarded as composed of a large number of scattered points with different intensities. High-resolution range profile (HRRP) is the vector sum of the echoes of each scattering point on the target body obtained by broadband radar signals. It reflects the distribution of scattering points on the target along the radar line of sight, contains ...

AI Technical Summary

Problems solved by technology

There are two shortcomings in this type of model: one is the model selection problem, that is, how to select the number of sample subsets (clustering); the other is that the clustering process of the sample set is unsupervised and independent of the back-end classifier task, so it is relatively difficult. It is difficult to guarantee the separability of data in each cluster, thus affecting the overall classification performance

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