Recursive Bayesian synthetic aperture geoacoustic inversion in the presence of motion dynamics

摘要: A low signal to noise ratio (SNR), single source/receiver, broadband, frequency-coherent matched-field inversion procedure recently has been proposed. It exploits coherently repeated transmissions improve estimation of the geoacoustic parameters. The long observation time improves SNR and creates a synthetic aperture due relative source-receiver motion. To model constant velocity source/receiver horizontal motion, waveguide Doppler theory for normal modes is necessary. However, performance degrades when acceleration exists. Furthermore processing train pulses all at once does not take advantage natural incremental acquisition data along with ability assess temporal evolution parameter uncertainty. Here recursive Bayesian approach developed that processes pulse by incrementally updates estimates also approximates assuming piecewise but linearly changing velocities. When exists, it shown modeling can reduce further biases uncertainties. method demonstrated in simulation analysis SNR, 100–900 Hz linear frequency modulated (LFM) from Shallow Water 2006 experiment.