Abstract
In this part of the paper, we continue to study the problem of detecting a double subspace signal in Gaussian noise. Precisely, we address the detection problem in partially homogeneous environments, where the primary and secondary data share the same covariance matrix up to an unknown scaling factor. We derive the generalized likelihood ratio test (GLRT), Rao test, Wald test, and their two-step versions. We also introduce three spectral norm tests (SNTs). All these detectors possess the constant false alarm rate (CFAR) property. Moreover, various kinds of special cases of these detectors are given. At the stage of performance evaluation, we consider two cases. One is the case of no signal mismatch. The other is more general, namely, the case of signal mismatch, including the column-space signal mismatch and row-space signal mismatch.
Sign-in/Register to access full text options 
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.
