Subspace detection for range and Doppler distributed targets with Rao and Wald tests

For the detection problem caused by the point target broken up into the distributed target in the high-range resolution radar system, adaptive detection algorithms based on the Rao and the Wald tests are proposed. The distributed target, which is modeled as a subspace random signal, may be distributed both in range and also in Doppler frequency axes. The clutter is modeled as a spherically invariant random process (SIRP). The unknown parameters are estimated by maximum likelihood estimation only under hypothesis H0 in Rao test, while only under hypothesis H1 in Wald test. Interestingly the proposed non-adaptive detectors from different deriving progresses have the same final form, which perform an incoherent processing over all the cells under test and ensure CFAR property with respect to the unknown statistics of the clutter texture component. In the end, performances of the proposed adaptive detectors are assessed through Monte Carlo simulations and are shown to have better detection performance compared with existing similar detectors.