Multi-Source T-S Target Recognition via an Intuitionistic Fuzzy Method

To realize aerial target recognition in a complex environment, we propose a multi-source Takagi–Sugeno (T-S) intuitionistic fuzzy rules method (MTS-IFRM). In the proposed method, to improve the robustness of the training process of the model, the features of the aerial targets are classified as the...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 15; no. 24; p. 5773
Main Authors: Zhang, Chuyun, Xie, Weixin, Li, Yanshan, Liu, Zongxiang
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.12.2023
Subjects:
Accuracy
Adaptive algorithms
adaptive weight
Aerial targets
Algorithms
Clustering
Comparative analysis
Decision making
Fuzzy algorithms
Fuzzy logic
Fuzzy sets
Fuzzy systems
Information sources
Methods
Parameter identification
Probability distribution
regression analysis
Regression models
ridge regression
Robustness (mathematics)
Sensors
T-S intuitionistic fuzzy rules
Target acquisition
Target recognition
China
ISSN:2072-4292, 2072-4292
Online Access:Get full text
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Summary:To realize aerial target recognition in a complex environment, we propose a multi-source Takagi–Sugeno (T-S) intuitionistic fuzzy rules method (MTS-IFRM). In the proposed method, to improve the robustness of the training process of the model, the features of the aerial targets are classified as the input results of the corresponding T-S target recognition model. The intuitionistic fuzzy approach and ridge regression method are used in the consequent identification, which constructs a regression model. To train the premise parameter and reduce the influence of data noise, novel intuitionistic fuzzy C-regression clustering based on dynamic optimization is proposed. Moreover, a modified adaptive weight algorithm is presented to obtain the final outputs, which improves the classification accuracy of the corresponding model. Finally, the experimental results show that the proposed method can effectively recognize the typical aerial targets in error-free and error-prone environments, and that its performance is better than other methods proposed for aerial target recognition.
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs15245773