|Table of Contents|

One-dimensional Range Profile Recognition Based on FSVM

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2009年03期
Page:
375-378
Research Field:
Publishing date:

Info

Title:
One-dimensional Range Profile Recognition Based on FSVM
Author(s):
LUAN Ying-hongLI Yue-hua
School of Electronic Engineering and Optoelectronic Technology,NUST,Nanjing 210094,China
Keywords:
vectors radars radar target recognition support vector machine membership functions affinity
PACS:
TN957.52
DOI:
-
Abstract:
Based on the discussion of membership functions computed by distance and affinity among samples,a new membership function is introduced which can reflect the distribution of radar echo signal in feature space,in order to avoid the influence of noise and isolated points in millimeter-wave radar one-dimensional range profile recognition.Super-ellipse is introduced to improve membership function and applied to fuzzy support vector machine(FSVM) to distinguish support vectors with outliers or noise.Compact super-ellipse is used to surround samples and its direction radius can measure the affinity between samples.The experimental results show that the recognition rate of support vector machine drops down rapidly with the decrease of signal-noise-ratio for echo waves,but only one percent of FSVM reduces,which reduces the influence of noise on recognition results of one-dimensional range profiles effectively.

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Last Update: 2012-11-19