AUTHOR: Thayaparan, S.; Abrol, S.; Riseborough, E.
Simulated results confirm that the mathematical analysis is valid. The m-D features derived from a target's vibrational/rotational motion are extracted by utilizing discrete wavelet transforms. During this process, the time domain radar signal is decomposed into a set of components that are represented by different wavelet scales. The m-D features are extracted by sorting the components that are associated with the vibrational/rotational motions of a target and is achieved by applying the inverse wavelet transform.
After the extraction of m-D features, time-frequency analysis is employed to analyze the oscillation and to estimate the motion parameters. The vibration/rotation rate is estimated by taking the autocorrelation of the time sequence data. The findings show that these results have higher precision after the m-D extraction since only vibrational/rotational components are employed.
The proposed method of the m-D extraction has been successfully applied to both simulated data and experimental helicopter and human data. The preliminary results clearly demonstrate that the m-D signatures can be observed by radar and suggest that applications of m-D should be investigated and exploited for target detection, classification and recognition.
It is recommended that the exploitation of micro-Doppler, as a new identification / recognition tool, be undertaken as it could impact all aspects of radar sensing and may enhance the effectiveness of Automatic Target Recognition (ATR) and Automatic Gait Recognition (AGR) techniques. We recommend that a new man-portable “micro-Doppler radar” be constructed for use on the battlefield or for disaster scenarios. We also propose a sequence of research work to achieve the desired technical objectives. Full report - TM2004-170
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