Inversion of range-dependent ocean environmental parameters using radiation noises of an Autonomous Underwater Vehicle

Abstract

Moving platform is playing an increasingly important role in ocean observatories. We previously reported some field testing results of using the radiation noises of an Autonomous Underwater Vehicle (AUV) as the sound source to invert the range-independent SSP. To incorporate source motion effects, the forward model based on the waveguide Doppler and normal mode theory was applied to compute the replica field, and to resolve the adjacent Doppler shifted frequencies, an analytical solution of the forward model and its simplified version were obtained for arbitrary signal integration intervals with a monochromatic source. In this paper, we reformulate the matched-field inversion problem into a state-space model to track the range-dependent environmental parameters and moving source parameters along the AUV path with the constantly updated measurement equations. Performances of several sequential filters, including extended Kalman, unscented Kalman, and particle filters, are compared. Note that at each point of the track, the estimate is the average from the source to the receiver; by doing the inversion sequentially with AUV moving, one can get the parameter estimate at individual points (sections). This process is equivalent to iteration over space, while iteration over time is considered as a solution to an under-determined inverse problem.Moving platform is playing an increasingly important role in ocean observatories. We previously reported some field testing results of using the radiation noises of an Autonomous Underwater Vehicle (AUV) as the sound source to invert the range-independent SSP. To incorporate source motion effects, the forward model based on the waveguide Doppler and normal mode theory was applied to compute the replica field, and to resolve the adjacent Doppler shifted frequencies, an analytical solution of the forward model and its simplified version were obtained for arbitrary signal integration intervals with a monochromatic source. In this paper, we reformulate the matched-field inversion problem into a state-space model to track the range-dependent environmental parameters and moving source parameters along the AUV path with the constantly updated measurement equations. Performances of several sequential filters, including extended Kalman, unscented Kalman, and particle filters, are compared. Note that at each point ...