Moving Target Inference With Bayesian Models in SAR Imagery

作者：Newstadt Gregory^*; Zelnio Edmund; Hero Alfred III

来源：IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(3): 2004-2018.

DOI：10.1109/TAES.2013.130123

This work combines the physical, kinematic, and statistical properties of targets, clutter, and sensor calibration as manifested in multichannel synthetic aperture radar (SAR) imagery into a unified Bayesian structure that simultaneously estimates 1) clutter distributions and nuisance parameters, and 2) target signatures required for detection/inference. A Monte Carlo estimate of the posterior distribution is provided that infers the model parameters directly from the data with little tuning of algorithm parameters. Performance is demonstrated on both measured/synthetic wide-area datasets.

• 出版日期2014-7