ADAPTIVE SUBSPACE DETECTION OF RANGE DISTRIBUTED TARGETS IN COMPOUND-GAUSSIAN CLUTTER

This paper addresses adaptive high resolution radar detection of range-distributed target embedded in compound-Gaussian clutter modeled as a spherically invariant random process (SIRP). Echoes backscattered from range-distributed target are modeled as a subspace random signal by using multiple dominant scattering models. At the design stage we resort to the so-called two-step GLRT-based design procedure and assume that a set of secondary data is available. A sub-optimal adaptive detector for range-distributed target is devised. More over the analytical closed-form expression for the probability of false alarm of the proposed detector is derived. The proposed adaptive detector ensures fully constant false alarm rate (CFAR) property in SIRP clutter Performance of the proposed CFAR adaptive detector is assessed through Monte Carlo simulations and is shown to have better detection performance compared with existing similar detector