A Resonance Region Method for Recognition of Multiple Targets Using the MUSIC Algorithm and a Time Correlation Technique

Date

2008-07-11

Author

Secmen, Mustafa
Ekmekci, Evren
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 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 variations in target-to-target separation distances in the case of multiple targets. A challenging special case of multiple and identical targets is also handled in the suggested method by investigating the time correlation of a given scattered test signal as a part of the decision mechanism. A simpler ldquosingle target classifierrdquo version of this method was suggested recently in (Seemen et al., 2007) and shown to be very successful in recognizing isolated targets of various geometries and material compositions even in high-noise scenarios. Extraction of the FMSM, which is closely related to the discrete version (a matrix) of the multi-aspect fused power spectrum of a given target, is explained in detail in (Seemen et al., 2007). System poles of a given target coincide with the peak points of this FMSM map plotted in the discrete complex frequency domain. This same feature extraction procedure is used for the recognition of single targets in the present paper but crucial modifications are made in the design procedure for the characterization of multiple targets as to be explained.

Subject Keywords

Classification algorithms, Distance measurement, Target recognition, Electromagnetic scattering , Electromagnetics, Feature extraction

URI

https://hdl.handle.net/11511/54644

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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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...
A novel method for electromagnetic target classification using the music algorithm: Applied to small-scale aircraft targets Secmen, Mustafa; Sayan, Gönül (2006-01-01) 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...
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...
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...

Citation Formats

M. Secmen, E. Ekmekci, and G. Sayan, “A Resonance Region Method for Recognition of Multiple Targets Using the MUSIC Algorithm and a Time Correlation Technique,” 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54644.