Application of the Hough transform to Doppler-time image processing

Doppler-time images (DTIs) of a rotating object were formed from the returns of high resolution radars by expressing the Doppler values as a function of time over a span of ranges. Returns from scatterers on the object yielded a characteristic signature of the object´s rotation: a section of a sinusoid centered about the negatively sloped zero-crossing. As several scatterers are usually present, these signatures may overlap. The return from each scatterer is noisy and, more importantly, may be missing (falling below the detection threshold) or may be multi-valued (yielding several values exceeding the detection threshold). The Hough transform-the extraction of parametrically expressible features-was used to extract straight line approximations to the return signatures. This algorithm is shown to be insensitive to missing or extraneous values. Quantization in Hough transform computation is shown to determine the sensitivity of the calculation to noisy values. Parameters of the signatures were extracted using a data-dependent clustering algorithm designed to be insensitive to quantization and feature parameterization