Human Engineering of Sensor Fusion Systems in Fighter Aircraft
Abstract: A pressing concern in modern fighter aircraft cockpit design is how to present and reduce large amounts of data obtained from several sensor observations of the same object. Currently, sensor observations are presented individually as overlays or in different displays requiring the pilot to control each sensor and integrate observations. The increased number of sensors and communication networks covering extensive ranges has, however, led to a situation that hampers pilots' situation awareness and decision-making. One approach to support the pilot is automatic information management. Although considerable technological research has been conducted on automatic sensor fusion and process refinement, little is known about how to integrate systems capabilities with pilots' decision-making.This thesis focuses on the factors involved in pilots' control of sensor fusion systems for tracking, classifying,and identifying objects, which are presented on the indicators in the cockpit of fighter aircraft. A cognitive systems engineering perspective was applied, since sensor fusion systems by definition automate parts of the information management. The emphasis in cognitive systems engineering is to create a complementary role for technological solutions and operator competence. A comparison of two major programs on decision support systems shows that striking the right balance between available technology and pilot expertise is important for the development of useful systems.Since little research has directly addressed pilots' control of sensor fusion systems, a conceptual model is presented based on systems characteristics and a review of factors likely to be important. The model shows how pilots' mission goals specify a desired situation awareness that determines the control of sensors. Pilots' control sensor fusion systems by designating important objects and areas, and intervening on exceptions of an essentially autonomous system. The systems support pilots' situation awareness with visualization of information and by improving their evaluation of the situation. Remaining uncertainties that delay action are reduced with suitable strategies. A High Range Resolution (HRR) radar identification system was simulated and evaluated for further understanding of the uncertainty in target identity that is important for pilots. The interface for the HRR system shows how supervisory control of system performance, levels of control, and visualization of conflicts are general factors that may be important for control of sensor fusion systems.The thesis shows that an appropriate function allocation for automatic sensor management may have to consider pilots' individual differences in minimizing goal trees and characterizing situations. Such factors may be important for pilots' expectations on sensor management that makes them use and trust system inferences appropriately. Interviews with pilots can provide some understanding of the factors involved in sensor control. However, since many of the judgments and tactical patterns involved in pilots' decision making are overlearned for efficient automatic performance, they may not be able to explain their behavior in detail. The thesis shows that analyzing pilot performance using neurofuzzy models may be a useful way to describe how situations drive responses. The linguistic form of fuzzy rules gives an intuitive understanding of the relationship in a presentational form that can be integrated with sensor management control rules.
This dissertation MIGHT be available in PDF-format. Check this page to see if it is available for download.