The MUSIC algorithm-based electromagnetic target classification for isolated targets from incomplete frequency domain data

2007-06-15
Secmen, Mustafa
Sayan, Gönül
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 wires with incomplete data, which brings additional difficulty in target classification problems. It is shown that the method provides high accurate classification rates even when incomplete frequency domain data with low signal-to-noise ratio values are utilized while it needs only a few different reference aspects and small memory storage in classifier design.

Suggestions

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 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 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 Theory and Application of an Electromagnetic Target Recognition Method based on Natural-Resonance for Multi-Targets
Secmen, Mustafa; Sayan, Gönül (2008-01-01)
This paper presents the application of an electromagnetic target recognition method based on natural resonance mechanism and MUSIC algorithm to the target sets containing single amd multi-targets. The simpler case of the proposed method was applied to single targets previously and successful results were obtained [1]. However, when multi-targets are added to the test target set, the method needs crucial modifications and these modifications are mentioned in detail in this study. Owing to these modifications...
Citation Formats
M. Secmen and G. Sayan, “The MUSIC algorithm-based electromagnetic target classification for isolated targets from incomplete frequency domain data,” 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37586.