Abstract
We focus on the problem of detecting a distributed target in compound-Gaussian clutter, where the texture is a random variable with Gamma distribution. The Rao and Wald tests are devised by using the two-step method: in the first step, the Rao and Wald tests are designed by assuming that the texture and covariance matrix structure are known; in the second step, the maximum a posterior probability estimate of clutter texture and the fixed point estimate of covariance matrix structure are used to replace the known texture and covariance matrix in the tests derived in the first step, respectively. The effectiveness of the proposed detectors is verified by using simulated and real data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
