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A ray approach is used to simulate subcritical scattering from a buried target at low-to-high frequencies (100 Hz–15 kHz). A penetrating wave at a subcritical angle decays along the depth at the bottom (i.e., evanescent wave) and propagates horizontally at a subcritical angle-dependent speed lower than the sound speed of the bottom. The corresponding target strength (TS) is distinguished from that of a standard plane wave. Its pattern is asymmetric by the evanescent wave including for symmetric targets and is more complicated owing to the higher wavenumber induced by the lower speed of the evanescent wave. A scattered signal is simulated by considering the features of the penetrating wave with the TS and then verified using the finite element method. In the ray approach, once the TS is computed, a scattered field is efficiently derived with low computational complexity. Strong peaks are observed in the scattered signal via mid-frequency enhancement; however, their amplitudes are less than those yielded by the free-field target owing to the more diminished penetrating waves at higher frequencies. The peaks indicate the possibility of detecting the buried target using a receiver near the target (bistatic sonar) with a broadband source signal that includes low-to-mid frequencies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new calculation method for the regularization factor in sparse recursive least squares (SRLS) with l 1 -norm penalty. The proposed regularization factor requires no prior knowledge of the actual system impulse response, and it also reduces computational complexity by about half. In the simulation, we use Mean Square Deviation (MSD) to evaluate the performance of SRLS, using the proposed regularization factor. The simulation results demonstrate that SRLS using the proposed regularization factor calculation shows a difference of less than 2 dB in MSD from SRLS, using the conventional regularization factor with a true system impulse response. Therefore, it is confirmed that the performance of the proposed method is very similar to that of the existing method, even with half the computational complexity. [ABSTRACT FROM AUTHOR]