Detection performance analysis of tests for spread targets in compound-Gaussian clutter

Abstract

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. © 2012 Springer-Verlag.