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Target Identification Using Harmonic Wavelet Based ISAR Imaging


A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.


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Correspondence to B. K. Shreyamsha Kumar.

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Shreyamsha Kumar, B.K., Prabhakar, B., Suryanarayana, K. et al. Target Identification Using Harmonic Wavelet Based ISAR Imaging. EURASIP J. Adv. Signal Process. 2006, 086053 (2006).

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  • Fourier
  • Fourier Transform
  • Information Technology
  • Analysis Tool
  • Quantum Information