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

Published

Journal Article

Radar scattering from an illuminated object is often highly dependent on the target-sensor orientation. In typical synthetic aperture radar (SAR) imagery, the information in the multi-aspect target signatures is diffused in the image-formation process. In an effort to exploit the aspect dependence of the target signature, we employ a sequence of directional filters to the SAR imagery, thereby generating a sequence of subaperture images that recover the directional dependence of the target scattering. The scattering statistics are then used to design a hidden Markov model (HMM), wherein the orientation-dependent scattering statistics are exploited explicitly. This approach fuses information embodied in the orientation-dependent target signature under the assumption that both the target identity and orientation are unknown. Performance is assessed by considering the detection of tactical targets concealed in foliage, using measured foliage-penetrating (FOPEN) SAR data.

Full Text

Duke Authors

Cited Authors

  • Runkle, P; Nguyen, LH; McClellan, JH; Carin, L

Published Date

  • January 1, 2001

Published In

Volume / Issue

  • 39 / 1

Start / End Page

  • 46 - 55

International Standard Serial Number (ISSN)

  • 0196-2892

Digital Object Identifier (DOI)

  • 10.1109/36.898664

Citation Source

  • Scopus