GLRT-based adaptive detection algorithms for range-spread targets
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
The CFAR adaptive subspace detector is a scale-invariant GLRT
IEEE Transactions on Signal Processing
Signal detection in compound-Gaussian noise: Neyman-Pearson andCFAR detectors
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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The problem of adaptive detection of spatially distributed targets or targets embedded in compound-Gaussian clutter with unknown covariance matrix is studied. At first, the test decision statistic of the generalized likelihood ratio test (GLRT), Rao test and Wald test which have been widely applied to the distributed targets detection of modern Wideband radar is derived. Next, the numerical results are presented by means of Monte Carlo simulation strategy. Assume that cells of signal components are available. Those secondary data are supposed to possess either the same covariance matrix or the same structure of the covariance matrix of the cells under test. In this context, the simulation results highlight that the asymptotic properties of the three tests in different coherent train pulses, and that the performance loss of the real target length mismatches the setup in receiver.