Abstract
Time-reversal processing (TRP) is an implementation of matched-field processing (MFP) where the ocean itself is used to construct the replica field. This paper introduces virtual time-reversal processing (VTRP) that is implemented electronically at a receiver array and simulates the kind of processing that would be done by an actual TRP during the reciprocal propagation stage. MFP is a forward propagation process, while VTRP is a back-propagation process, which exploits the properties of reciprocity and superposition and is realized by weighting the replica surface with the complex conjugate of the data received on the corresponding element, followed by summation of the processed received data. The number of parabolic equation computational grids of VTRP is much smaller than that of MFP in a range-dependent waveguide. As a result, the localization surface of VTRP can be formed faster than its MFP counterpart in a range-dependent waveguide. The performance of VTRP for source localization is validated through numerical simulations and data from the Mediterranean Sea.
Highlights
Time-reversal processing (TRP) is an implementation of matched-field processing (MFP) where the ocean itself is used to construct the replica field
When TRP is applied to source localization, known as virtual time-reversal processing (VTRP), it is unnecessary to send a signal back and forth between the source and receiver
Instead, assuming that the acoustic channel is sufficiently stable in time, the retransmission of the temporal dispersed signals in a time reversed fashion will be done by a computer
Summary
MFP deals with target localization by matching the data of the target radiated acoustic field, acquired by an array to a model-based replica vector at a test target position. The replica vector on the array for each candidate position (r, z) is normalized to the unit norm and is denoted as wMFP(r, z) here. For a Bartlett matched field processor, the ambiguity function (or surface) is given by [12]. Where d(rs, zs) is a data vector observed on the array for the real source at (rs, zs), and R is the data covariance matrix. Superscript ( )H denotes the Hermitian or conjugate transpose of the matrix
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