Makale detayı · 2016
Hierarchical Reconstruction and Structural Waveform Analysis for Target Classification
- Yıl
- 2016
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı IEEE Transactions on Antennas and Propagation
- Katalog eşleşmesi (ISSN) IEEE Transactions on Antennas and Propagation
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Classification of objects from scattered electromagnetic waves is a difficult problem, as it heavily depends on aspect angle. To minimize this dependency, distinguishable features can be used. In this paper, we propose a target identification method in the resonance scattering region using a novel structural feature set based on the scattered signal waveform. To obtain robustness at low signal-to-noise ratio (SNR), a multiscale approximation is used for distortion correction prior to the feature extraction. This is achieved by an overlapping grid hierarchical radial basis function (HRBFOG) network topology, which is demonstrated to outperform existing HRBF techniques. The results obtained from the simulations and the measurements performed for various targets show high accuracy for classification with the proposed feature set, robustness through the use of HRBF at low SNR, and efficient computation in real time.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
17 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 9 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- Savitzky-Golay filtering for Scattered Signal De-noising 2018
- Automatic Detection of Emotional Changes Induced by Social Support Loss using fMRI 2023
- Automatic Detection of Emotional Changes Induced by Social Support Loss Using fMRI 2023
- Transferring Synthetic Elementary Learning Tasks to Classification of Complex Targets 2019
- Comparison of scattered signal waveform recovery techniques under low SNR for target identification 2017
- Radar target classification for resonance scattering region targets with min-norm signal processing method 2016
- Utilizing Resonant Scattering Signal Characteristics of Magnetic Spheres via Deep Learning for Improved Target Classification 2019
- The effects of geometric scattered signal waveform modeling on target identification performance 2017
- Reliability Assessment of Denoising Methods for Change Point and Activation Detection in Lack of Ground Truth from fMRI 2020