Synthetic aperture laser
radar (inverse) combines the technology of laser radar with synthetic aperture,
which has high imaging resolution, strong anti-interference, and good
concealment. Due to the short laser wavelength and fast imaging time, the tiny vibrations
of the moving target may achieve the target inverse synthetic aperture (range
-Doppler) imaging in a very short time, which increases identification
characteristics compared to the traditional optical remote point target
detection and recognition; it reduces the complexity of data processing
compared to radar, and optical imaging is easier to understand. Therefore,
synthetic aperture laser radar has the advantages of both optics and radar, and
has attracted more and more attention in long-distance target detection and
recognition. Since 1960's, MIT Lincoln Laboratory has conducted research on the
long-range target tracking and identification using laser radar. In this paper,
the micro-motion feature extraction and recognition method for inverse synthetic
aperture laser radar after target imaging is studied. The target images of
different micro-motion form are analyzed by range-Doppler imaging model, and
the geometric features of the target are extracted by the optical target
segmentation algorithm. The Hough transform theory is used to extract the
characteristics of the micro-motion period, and the micro-motion angle is
inversed through the change of the target geometric features. The simulation
test in field shows that this method can effectively extract the micro-motion
characteristics of the target and lay a foundation for the micro-motion target
recognition of synthetic aperture laser radar
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