Fast Algorithm of the ML Estimator for Passive Synthetic Arrays

To reduce the heavy computation load of maximum likelihood bearing estimator for passive synthetic arrays(pasaML), a fast algorithm is proposed. This method combines Gibbs sampling with pasaML method, resulting in a frequency-azimuth joint estimation method(called Gibbs-pasaML) to estimate the frequencies and directions of multiple sources at the same time. The method regards the power of pasaML spectrum function as target distribution up to a constant of proportionality, and uses Gibbs sampling technique to sample from it. Simulations show that the new method not only keeps the high-resolution performance of pasaML method but also reduces the computation and storage costs when the number of signal sources is small.