Texture Analysis of Remote Sensing Imagery with Clustering and Bayesian Inference

A parametric approach algorithm based on maximum likelihood estimation (MLE) method is proposed which can be exploited for high-resolution parameter estimation in the domain of signal processing applications. The array signal model turns out to be a superposition of two-dimensional sinusoids with the first component of each frequency doublet corresponding to the direction of the target and second component to the velocity. Numerical simulations are presented to illustrate the validity of the proposed algorithm and its various aspects. Also, the presented algorithm is compared with a subspace based technique, multiple signal classification (MUSIC) to highlight the key differences in performance under different circumstances. It is observed that the developed algorithm has satisfactory performance and is able to determine the direction of arrival (DOA) as well as the velocity of multiple moving targets and at the same time it performs better than MUSIC under correlated noise. Index Terms—Direction of arrival, high resolution, two-dimensional, velocity estimation.