Document Type
Conference Proceeding
Publication Date
2013
Department
Marine Science
Abstract
The CUBE (Combined Uncertainty and Bathymetry Estimator) algorithm1 is commonly used to establish a surface of likely depth from the point-cloud type data produced by multi-beam echosounders. Two fundamental inputs to the CUBE algorithm are horizontal and vertical components of Total Propagated Uncertainty (TPU)2 . The algorithm requires that TPU values closely match the performance of the sonar system. Mismatch between TPU and the actual sonar performance can cause inappropriate weighting of soundings and may result in a calculated surface that is not the best estimate of depth. Typical TPU values used for CUBE are comprised of a-priori vertical and horizontal uncertainty estimates. This a-priori estimate of TPU should compare well to the real-world performance of a particular system. However, the TPU models are not transferable between systems with fundamentally different designs. Furthermore, a-priori calculations do not account for performance degradation of systems in sub-optimal conditions or over time. This paper proposes a methodology – the “median-maximum method” – to estimate representative vertical TPU values for each beam that may be used to enhance CUBE algorithm performance. The estimation uses analysis of the median and maximum variance across sets of consecutive pings. This method produces representative vertical TPU values with the advantage of down-weighting noisy beams that are not performing to their a-priori estimates.
Recommended Citation
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