Fast DOA estimation for widebandsources based on perfect sampling

In DOA estimation of wideband sources, Approximated Maximum Likelihood estimator (AML) has been shown to have the best performance. However, the computational load of AML is very high. In order to reduce its computational complexity, Markov Monte Carlo method with perfect sampling is introduced by the author to work with AML. And it results in a novel Approximated Maximum Likelihood DOA Estimator based on Perfect Sampling (PAML). PAML regards the power of the AML spectrum function as the target distribution up to a constant proportionality, and uses Perfect sampler to sample from it. Simulations show that PAML not only keeps the excellent performance of the original AML but also reduces the computational complexity to a great extent.