Abstract
We dealt with the detection of signal in presence of compound-Gaussian noise. First of all, we derived the optimum Neyman-Pearson detector for a known signal to establish the limiting performance. Since the NP detector does not implement a uniformly most powerful (UMP) test, we adopt an alternative approach, namely the generalized likelihood ratio test (GLRT): the result is a completely canonical structure. Nevertheless since the implementation of such a processor requires averaging infinitely many projections of the received waveform, we also presented a sub-optimum scheme, retaining most of the characteristics, especially the CFARness, of the ideal detector. The analysis of the above detectors shows that both of them largely outperform the conventional square-law receiver and that the sub-optimum processor is practically equivalent to the GLRT receiver.
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.
