Reduction of decision error in track identification by utilization of data fusion

Abstract

System response times are too long and decision error too high in today's computer-missile combat systems. One of the most serious shortfalls of current combat system operations is time to perform identification tasks with reliable level of certainty when, predictably, reliable decisions are most needed time is too short and system demands are high. Automated methods of reliable information generation can reduce operator workload and the probability of decision error. Multisensor data fusion concept models that address this problem have been developed. The potential advantage of multisensor data fusion is its ability to process more kinds of sensor data and more complex variables at greater speed and with less error than human decision makers. Automation speeds the identification process and frees the operator to perform higher levels of decision making. This paper attempts to bring together a concept model of multisensor data fusion with a concept model of human-computer interaction that mutually support the system engineering effort to reduce decision error in combat system identification processes.