A novel method for electromagnetic target classification using the music algorithm: Applied to small-scale aircraft targets

Date

2006-01-01

Author

Secmen, Mustafa
Sayan, Gönül

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper introduces a novel target classification method based on the extraction of target features by using natural response related late-time electromagnetic scattered field data. In the feature extraction stage, the use of multiple signal classification (MUSIC) algorithm together with a simple but effective feature fusion approach leads to a significant reduction in the sensitivity of classification accuracy to both aspect angle variations and the signal-to-noise ratio (SNR) levels of the data. Another advantage of the proposed method is that the scattered target data is needed at only a few different target aspects in the stage of classifier design. Furthermore, real time classification within a small fraction of a second is feasible due to computational simplicity offered by this method in the final decision stage. When applied to geometrically complicated targets such as small-scale aircraft, this method provides high accuracy rates even for extremely noisy data.

Subject Keywords

Multiple signal classification , Bandwidth, Signal to noise ratio, Aerospace electronics, Testing , Spatial databases, Feature extraction , Data mining , Electromagnetic scattering , Aircraft

URI

https://hdl.handle.net/11511/56724

DOI

https://doi.org/10.1109/eucap.2006.4584916

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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A new electromagnetic target classification method with MUSIC algorithm Secmen, Mustafa; Sayan, Gönül (2006-01-01) This paper introduces a novel method for aspect invariant electromagnetic target recognition based on the use of multiple signal classification (MUSIC) algorithm to extract late-time resonant target features from the ultra-wideband scattered data. This method is mainly based on the usage of MUSIC spectra obtained from electromagnetic scattered data as the target features. This approach achieves very high accuracy rates even at very low signal-to-noise ratio (SNR) values although it needs scattered data for ...
A novel electromagnetic target recognition method by MUSIC algorithm Secmen, Mustafa; Sayan, Gönül (2006-12-01) This paper introduces a novel method for aspect invariant electromagnetic target recognition based on the use of multiple signal classification (MUSIC) algorithm to extract late-time resonant target features from the ultra-wideband scattered data. This approach achieves very high accuracy rates even at very low signal-to-noise ratio (SNR) values although it needs scattered data for classifier design at only a few different aspects and makes use of the MUSIC algorithm in a simple and computationally efficien...
A Radar Target Recognition Method with MUSIC Algorithm: Application to Aircraft Targets with Measured Scattered Data Secmen, M.; Turhan-Sayan, G.; Sayan, Gönül (2008-05-30) This paper demonstrates the usefulness of an ultra wideband target recognition method in the case of realistic and complicated target geometries at resonance region. The method utilizes the MUSIC algorithm to extract the natural resonance-related scattering features of targets. The resulting features give the power distribution maps of targets. These maps are called as fused MUSIC spectrum matrices and used as the main target recognition feature in the method. The fusion process is needed to reduce the aspe...
The MUSIC algorithm-based electromagnetic target classification for isolated targets from incomplete frequency domain data Secmen, Mustafa; Sayan, Gönül (2007-06-15) This paper investigates the performance of a new electromagnetic target classification method to recognize isolated targets in the presence of scattered frequency domain data which may be severely incomplete at low frequencies. The suggested method utilizes multiple signal classification (MUSIC) algorithm to construct approximate pole location maps of the targets without determining the exact pole values. In this work, this method is validated for small-scale aircraft targets modeled by thin, conducting wir...
A Resonance Region Method for Recognition of Multiple Targets Using the MUSIC Algorithm and a Time Correlation Technique Secmen, Mustafa; Ekmekci, Evren; Sayan, Gönül (2008-07-11) This paper presents, for the first time in literature, a natural resonance based electromagnetic target classification method that is useful not only for single target recognition but also for the recognition of multiple targets. In this method, the scattered wide-band electromagnetic signals are processed over an optimal late-time region by using the MUSIC algorithm to extract target features called fused MUSIC spectrum matrices (FMSM). These features are almost invariant to aspect variations and to the va...

Citation Formats

M. Secmen and G. Sayan, “A novel method for electromagnetic target classification using the music algorithm: Applied to small-scale aircraft targets,” 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56724.