Radar HRRP target recognition method based on dpLVSVM model

A target recognition and radar technology, applied in the field of radar, can solve problems such as unsupervised clustering process, affecting classification performance, and difficult to ensure data separability

Active Publication Date: 2014-08-27
XIDIAN UNIV
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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 un

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  • Radar HRRP target recognition method based on dpLVSVM model
  • Radar HRRP target recognition method based on dpLVSVM model
  • Radar HRRP target recognition method based on dpLVSVM model

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Embodiment Construction

[0080] refer to figure 1 , illustrate a kind of target recognition method of the radar HRRP based on dpLVSVM model of the present invention, its concrete steps are as follows:

[0081] figure 1The flow of the entire recognition system is given, and it can be seen that the entire system includes two parts: the training phase (left part) and the testing phase (right part). Among them, the task of the training phase is to estimate the parameters of the dpLVSVM model. After the training phase, the task of the testing phase is to perform the rejection task first, then calculate the cluster to which the sample belongs according to the parameters obtained from the training, and finally output the category label of the target to complete the recognition. Task.

[0082] Step 1, the radar receives the high-resolution range profile HRRP of M categories of targets; then perform feature extraction on each high-resolution range profile to obtain the power spectrum feature x of the radar h...

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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 ...

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Application Information

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IPC IPC(8): G01S7/41
CPCG01S7/41
Inventor 陈渤张学峰陈步华王鹏辉刘宏伟
Owner XIDIAN UNIV
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