摘要
The missile-tracked priority assessment for the early warning system monitoring multi-missile very well, is the first task to defend them and useful to perform optimally the sensor-to-missile assignment. The problem of the missile-tracked priority assessment is of incomplete information, of multi-attribute and dynamic. To solve the dificult problem, the index system, which includes six classification indices, is established by means of reducing the target＇s primary information which the early warning system focuses on. The lack of some attributes values, which is caused by the incomplete information, is handled by the approach： first classifying each attribute as unknown one or known one, and then subdividing the latter, last using the expectation and the information entropy if the attribute is known but uncertain. With a view of reality, nine qualitative evaluation criteria are given. Based on them each index is quantified by the eigenvector method. And then based on the improved technique for order preference by similarity to ideal solution （TOPSIS）, the targets-tracked priorities are assessed and sorted by an evaluation function from three aspects： 1） the quantity of the available information, 2） the affirmative or accurate degree of the available information, 3） the classification or trait of the available information.
The missile-tracked priority assessment for the early warning system monitoring multi-missile very well, is the first task to defend them and useful to perform optimally the sensor-to-missile assignment. The problem of the missile-tracked priority assessment is of incomplete information, of multi-attribute and dynamic. To solve the dificult problem, the index system, which includes six classification indices, is established by means of reducing the target＇s primary information which the early warning system focuses on. The lack of some attributes values, which is caused by the incomplete information, is handled by the approach： first classifying each attribute as unknown one or known one, and then subdividing the latter, last using the expectation and the information entropy if the attribute is known but uncertain. With a view of reality, nine qualitative evaluation criteria are given. Based on them each index is quantified by the eigenvector method. And then based on the improved technique for order preference by similarity to ideal solution （TOPSIS）, the targets-tracked priorities are assessed and sorted by an evaluation function from three aspects： 1） the quantity of the available information, 2） the affirmative or accurate degree of the available information, 3） the classification or trait of the available information.
基金
supported by the National Ministry Foundation for the Pre-research
