Investigation of Flexure Effect on Transfer Alignment Performance

Transfer Alignment (TA) is the initialisation process of the Inertial Navigation System (INS) of an air-launched weapon before its release by using the data from the aircraft INS. The aim of this paper is to improve the TA performance by taking into account the aircraft flexures deterministically. The developed procedure neither requires captive carry tests for determination of flexures nor increases the size of the problem, and can be used in real-time missions of any type of military aircraft. The procedure is evaluated for the Velocity Match (VM) method as well as the Velocity and Attitude Match (VAM) method, which are applied through a Kalman Filter (KF). Using a short-time Wing-Rock (WR) manoeuvre, the results of both methods are compared to each other for two cases in which either the flexures are taken into account deterministically, or modelled as noise by assuming that they are unknown. Standard deviations of the errors and the Circular Error Probable (CEP) variations have shown that the TA performance of the VAM method can be much improved if aircraft flexures are incorporated deterministically into the method. The improved performance makes possible target of opportunity missions at shorter weapon ranges, and it decreases target strike errors.

Hawaii Environmental Sensitivity Index (ESI) Maps and the Spatial Accuracy of ESI Mapping Methodology

ABSTRACT Environmental Sensitivity Index (ESI) maps and digital databases have been generated for the Hawaiian Islands. ESI atlases integrate the most recent data available in three general categories: shoreline habitats, biological resources, and human-use resources, to provide spill responders with a synopsis of critical information. The new Hawaii atlas was prepared using standardized ESI data collection and analysis methods. For the first time, the spatial accuracy of the ESI shoreline classification method has been quantitatively measured using GPS. Shoreline classification methodology consisted of low-altitude overflights during the 2.5 hours preceding and following low-tide. Aerial classifications were then checked on the ground throughout the study area. USGS 7.5 minute basemaps were used in the field and shoreline segmentation annotation was transcribed from scanned field maps to a digital shoreline provided by the State. ESI surveys in August of 2000 resulted in nineteen shoreline classes for the Hawaiian chain. The GPS field study was conducted simultaneously with shoreline classification. During GPS surveys boundaries between ESI shoreline segments were located in the field and their position recorded with a hand held GPS. The coordinates of the segment boundary as located on the final ESI map were compared to those recorded with the GPS. Data for over 60 locations were analyzed statistically using three commonly accepted error-reporting methodologies. A Root Mean Squared (RMS) error of 33.5 meters, a Circular Error Probable (CEP) of 28 meters, and a 95% error bound of 58.2 meters were found. Error occurred unsystematically and was attributed to various factors, including inaccuracies in basemap shorelines, human error in the field and cartography, and error expected when mapping natural gradations as discreet points.