scholarly journals Ground Target Classification Algorithm based on Multi-Sensor Images

2012 ◽  
Vol 15 (2) ◽  
pp. 195-203
Author(s):  
Eun-Young Lee ◽  
Eun-Hye Gu ◽  
Hee-Yul Lee ◽  
Woong-Ho Cho ◽  
Kil-Houm Park
Keyword(s):  
Classification Algorithm ◽  
Target Classification ◽  
Ground Target

A Seismic-Based Feature Extraction Algorithm for Robust Ground Target Classification

2012 ◽  
Vol 19 (10) ◽  
pp. 639-642 ◽  
Author(s):  
Qianwei Zhou ◽  
Guanjun Tong ◽  
Dongfeng Xie ◽  
Baoqing Li ◽  
Xiaobing Yuan
Keyword(s):  
Feature Extraction ◽  
Target Classification ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Ground Target

An Improved Joint Target Tracking and Classification Algorithm Based on Data Fusion

2014 ◽  
Vol 904 ◽  
pp. 325-329
Author(s):  
Hong Wei Quan ◽  
Lin Chen ◽  
Dong Liang Peng
Keyword(s):  
Data Fusion ◽  
Target Tracking ◽  
Classification Algorithm ◽  
Target Classification ◽  
Tracking Accuracy ◽  
Traditional Methods ◽  
System Models ◽  
Target State ◽  
Classification Probability

This paper addresses the problem of the joint target tracking and classification based on data fusion. In traditional methods, a separate suite of sensors and system models are used, target tracking and target classification are usually treated as separate problems. In our JTC framework, the link between target state and class is considered and the feasibility of JTC techniques is discussed. The tracking accuracy and classification probability are improved to some extent with the more accurate classification results from classifier based on data fusion feedback to state filter.

Automatic ground target classification using forward scattering radar

2006 ◽  
Vol 153 (5) ◽  
pp. 427 ◽  
Author(s):  
M. Cherniakov ◽  
R.S.A.R. Abdullah ◽  
P. Jančovič ◽  
M. Salous ◽  
V. Chapursky
Keyword(s):  
Forward Scattering ◽  
Target Classification ◽  
Ground Target

A New Air and Ground Target Classification Method Based on Doppler Information

2021 ◽  
Author(s):  
Wei Han ◽  
Yan Gao ◽  
Shengxiang Zhou ◽  
WeiJian Liu ◽  
Pei Zhu ◽  
...  
Keyword(s):  
Classification Method ◽  
Target Classification ◽  
Ground Target

Toward a robust 3D-model-based ground target classification system for airborne platforms

2010 ◽  
Author(s):  
Wolfgang Ensinger ◽  
Christoph Stahl ◽  
Peter Knappe ◽  
Klaus Schertler ◽  
Jörg Liebelt
Keyword(s):  
Classification System ◽  
3D Model ◽  
Target Classification ◽  
Model Based ◽  
Ground Target

Design of a SIFT based Target Classification Algorithm robust to Geometric Transformation of Target

2010 ◽  
Vol 20 (1) ◽  
pp. 116-122 ◽  
Author(s):  
Hee-Yul Lee ◽  
Jong-Hwan Kim ◽  
Se-Yun Kim ◽  
Byung-Jae Choi ◽  
Sang-Ho Moon ◽  
...  
Keyword(s):  
Classification Algorithm ◽  
Geometric Transformation ◽  
Target Classification

scholarly journals Fractal Dimension Based on Morphological Covering for Ground Target Classification

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Kai Du ◽  
Xiang Fang ◽  
Wei-ping Zhang ◽  
Kai Ding
Keyword(s):  
Fractal Dimension ◽  
Seismic Waves ◽  
Vehicle Classification ◽  
Test Field ◽  
Target Classification ◽  
Operation Conditions ◽  
Wheeled Vehicle ◽  
Ground Target ◽  
Nonlinear Features ◽  
Mc Method

Seismic waves are widely used in ground target classification due to its inherent characteristics. However, they are often affected by extraneous factors and have been found to demonstrate a complicated nonlinear characteristic. The traditional signal analysis methods cannot effectively extract the nonlinear features. Motivated by this fact, this paper applies the fractal dimension (FD) based on morphological covering (MC) method to extract features of the seismic signals for ground targets classification. With the data measured from test field, three different schemes based on MC method are employed to classify tracked vehicle and wheeled vehicle in different operation conditions. Experiment results demonstrate that the three proposed methods achieve more than 90% accuracy for vehicle classification.

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