A Fast Algorithm for Underwater Passive Synthetic Arrays
Yu Li, Yunshan Hou · 2009
To reduce the heavy computation load of maximum likelihood parameter estimator for passive synthetic arrays(pasaML), a fast algorithm is proposed. This method combines Metropolis-Hasting Sampling with pasaML method, resulting in a frequency-azimuth joint estimation method(called MH-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 Metropolis-Hasting 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.