Construction of partitioned prior-control units from crossover-adjusted MLA profiles for BELA applications

The BepiColombo Laser Altimeter (BELA) is a core scientific instrument of the BepiColombo mission for measuring Mercury’s global topographic characteristics and surface shape. Compared with the Mercury Laser Altimeter (MLA) onboard the MESSENGER spacecraft, BELA and MLA differ significantly in orbital configuration, spatial coverage, and observation geometry. As a result, the existing MLA laser altimetry products may not be directly suitable as comparison benchmarks or control references for subsequent BELA orbital observations. Therefore, it is necessary to establish a prior control method based on MLA data to support high-precision quality assessment, profile deviation diagnosis, and accuracy improvement for future BELA data.

Due to systematic errors related to ranging, timing, orbit determination, and pointing, MLA laser profiles often exhibit elevation inconsistencies at crossover locations. This study first uses the elevation differences at crossover as constraints to perform crossover adjustment and consistency correction of the MLA laser altimetry data, thereby producing an MLA dataset with improved internal consistency. On this basis, we propose an adjusted-MLA-driven partitioned prior-control and profile deviation diagnosis method to support future BELA laser altimetry applications. The adjusted MLA crossover network exhibits clear spatial variations in orbital coverage density, crossover density, and elevation-difference consistency, resulting in regionally variable prior-control quality. On this basis, we establish a spatially differentiated prior-confidence evaluation framework by integrating information on crossover density, interpolation stability within crossover neighborhoods, post-adjustment residual statistics, and local terrain complexity, through which the study area is divided into high-, medium-, and low-confidence regions. When a subsequent BELA laser profile passes through a corresponding region, the prior information of that partition can be directly invoked for targeted profile deviation diagnosis. In high-confidence regions, the adjusted MLA laser profiles are used as strong reference benchmarks to evaluate the consistency between BELA profiles and the existing MLA elevation reference, and to identify overall elevation offsets and long-wavelength along-track trend errors. In medium-confidence regions, the MLA control results provide weak constraints in the form of regional statistical ranges and error bounds, which are used to assess the degree of deviation of BELA profiles and to screen for anomalous residuals. In low-confidence regions, new BELA observations are used to reversely validate the existing control results.

The prior-control unit library constructed in this study can provide prior support for BELA profile quality assessment and error-source analysis after orbital insertion. It can also support rapid validation of early BELA data, subsequent global topographic recovery, and cross-mission joint laser altimetry applications.