This paper presents three data processing techniques that offer potential improvements over common munitions response industry techniques involving(1)background subtraction and leveling,(2)peak detection and target selection,and(3)spatial coverage estimation and gap identification.These processing techniques are outlined below: 1.Background subtraction and leveling of instrument response data are performed by iteratively applying a rolling demedian filter that subtracts the median value of the window.Error induced by signal included in the median calculation is reduced by identifying and masking data with signal characteristics after each iteration.2.Peak detection and target selection are performed using an iterative method that picks the current highest response in the data,then masks data within a fixed radius of the response before subsequent iterations.This detection technique offers a reliable standard spacing for follow-on cued AGC and reduces manual review by inherently ensuring all responses above threshold are within a fixed radius of a selected target.It can be applied to profile line data,gridded/interpolated data,and dynamic-AGC informed source selection results.3.Spatial coverage estimation and gap identification are performed by rasterizing data into a high resolution,small cell-sized,grid and flagging cells that exceed a specified distance from the instrument location.Flagged cells can then be counted and grouped into polygons to obtain an accurate estimate for spatial coverage.This automated approach is faster,less prone to error,and provides more accurate estimations of spatial gaps to better meet project MQOs.
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