Multi-aspect target detection in SAR imagery using hidden Markov models


Journal Article

It is well known that radar scattering from an illuminated object is often dependent on target-sensor orientation. In typical synthetic aperture radar (SAR) imagery, such aspect dependence is lost during image formation. We apply a sequence of directional filters to the SAR imagery to generate a sequence of images which recover the directional dependence over a corresponding sequence of subapertures. The scattering statistics associated with geometrically distinct target-sensor orientations are then used to design a hidden Markov model (HMM) for the target class. This approach explicitly incorporates the sensor motion into the model and accounts for the fact that the orientation of the target is assumed to be unknown. Performance is quantified by considering the detection of tactical targets concealed in foliage.

Duke Authors

Cited Authors

  • Runkle, P; Nguyen, L; Ybarra, G; Carin, L

Published Date

  • January 1, 1999

Published In

Volume / Issue

  • 3721 /

Start / End Page

  • 214 - 223

International Standard Serial Number (ISSN)

  • 0277-786X

Citation Source

  • Scopus