Abstract
This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT) for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT’s performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated) pulse radar, SAR (Synthetic aperture radar), or ISAR (Inverse synthetic aperture radar), for improving the probability of target recognition.
Highlights
For a complicated movement target with a translational movement, the target itself or the structure it carries may have rotation, precession, nutation, or other micro movement features.These features could be used to help determine the “identity” of the target
Experiment data experiment data are used to demonstrate the high time-frequency resolution performanceare of used to demonstrate the high time-frequency resolution performance when dealing with multi-component micro Doppler signal. of short-time fractional order Fourier transformation (STFRFT) when dealing with multi-component micro Doppler signal
As with STFT, STFRFT is a kind of windowed transformation; alternatively, it may be interpreted as an expansion of a signal on the basis of time-fractional order domain frequency interpreted as an expansion of a signal on the basis of time-fractional order domain frequency location location function
Summary
For a complicated movement target with a translational movement, the target itself or the structure it carries may have rotation, precession, nutation, or other micro movement features. Second-order Cohen class time-frequency distribution offers a higher time-frequency resolution but its downside is the cross terms being tainted by multi-component signals [4,10,11,12,13,14,15,16,17,18]. FRFT a global transformation technique cannot unveil the time-varying features of the target [26,27,28,29,30]asinvestigates the performance of STFRFT (short-time fractional order Fourier transformation) signal. Experiment data experiment data are used to demonstrate the high time-frequency resolution performanceare of used to demonstrate the high time-frequency resolution performance when dealing with multi-component micro Doppler signal. Experiment data experiment data are used to demonstrate the high time-frequency resolution performanceare of used to demonstrate the high time-frequency resolution performance when dealing with multi-component micro Doppler signal. of STFRFT when dealing with multi-component micro Doppler signal
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