Evidence-C-mean radar signal class sorting method

A radar signal sorting and radar signal technology, applied to radio wave measurement systems, instruments, etc., can solve the problems of large amount of calculation, low recognition rate, and time-consuming, etc., and achieve the goal of increasing fuzzy items and accurate classification of radar signals Effect

Active Publication Date: 2016-03-16
XIDIAN UNIV
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However, these methods not only require a large amount of calculation, consume a

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  • Evidence-C-mean radar signal class sorting method
  • Evidence-C-mean radar signal class sorting method
  • Evidence-C-mean radar signal class sorting method

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Embodiment Construction

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0017] An important tool often used in image segmentation theory is fuzzy C-means (FCM), which is simple to implement, widely used and effective. Masson improved the FCM algorithm according to the D-S evidence theory, and obtained the evidence C-means (ECM) method. The biggest feature of this method is that it can generate new categories, and the classification of uncertainty is more accurate.

[0018] An embodiment of the present invention provides an ECM-bas...

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Abstract

The invention, which belongs to the technical field of radar signal sorting, especially relates to an evidence-C-mean (ECM) radar signal class sorting method. The method comprises: radar signals needing class sorting are obtained; feature elements of corresponding feature parameters of sampling sequences of the radar signals needing class sorting are extracted to form a feature vector; the feature vector is used as a computation input of an ECM, and the membership probability, belonging to a first radar signal, of each feature element, the membership probability, belonging to a second radar signal, of each feature element, and the fuzzy probability, belongs to the first radar signal and the second radar signal simultaneously, of each feature element in the feature vector are obtained; each feature element is classified; and according to the classification result of each feature parameter, a class sorting result of the radar signals needing class sorting is obtained.

Description

technical field [0001] The invention belongs to the technical field of radar signal sorting, and in particular relates to a radar signal category sorting method based on evidence C-means (ECM). Specifically, according to the characteristic parameters of different signals, the ECM method is used to estimate the membership probability of each characteristic parameter, which can be used It is used to classify different types of radar signals. Background technique [0002] The radar emitter signal will inevitably be interfered by various noises during the propagation process and the receiving process. During this period, the characteristic samples of the same type of signal are severely dispersed. If the degree of dispersion of the characteristic samples is too large, the number of radiation source signal categories for classification and identification will increase, thereby increasing the error probability of classification and identification. One of the effective measures to...

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Application Information

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IPC IPC(8): G01S7/02
CPCG01S7/02G01S7/021
Inventor 李明张鹏黄坤左磊
Owner XIDIAN UNIV
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