Seabed Backscattered Signal Peak Shift and Broadening Induced by Multiple Scattering in Bathymetric Lidar

Bathymetric lidar, with its deep penetration, continuous day-and-night operation, and high accuracy, is an important tool for remotely sensing bottom depths. However, the strong forward scattering of the laser beam during transmission in water introduces substantial multiple scattering components into the lidar signal reflected by sea bottom, leading to a peak shift and signal broadening. The peak shift leads to an overestimation of the bottom depth, while the signal broadening makes peak extraction more challenging. To quantitatively study this impact, a semianalytic Monte Carlo (MC) simulation is applied to model seabed reflected signals. By statistically analyzing the peak position bias (termed as Bias) and full-width at half-maximum (termed as FWHM) of the seabed lidar reflected signals across four platforms—spaceborne, airborne, shipborne, and underwater—empirical models are established to relate Bias and FWHM to scattering efficient (b), bottom depth ( $z_{\mathbf {m}}$ ), and lidar receiver footprint ( $r_{\mathbf {s}}$ ). Here, $r_{\mathbf {s}}$ represents the radius of the footprint of the lidar receiver on the water surface. Furthermore, the effects of different scattering phase functions and the absorption coefficient are analyzed. This study shows that the Bias and FWHM are influenced by $b, z_{\mathbf {m}}$ , and $r_{\mathbf {s}}$ . For lidar systems with an $r_{\mathbf {s}}$ of dozens of meters, measuring deeper depths in water with higher b can result in a bottom depth overestimation of nearly 4% and an FWHM broadening exceeding 28 ns solely due to multiple scattering effects. This article provides a theoretical basis for correcting and evaluating bathymetric lidar data, thereby improving the accuracy and applicability of bathymetric lidar results.