Applications of Correlation Techniques for Battlefield Identification I.
JET PROPULSION LAB PASADENA CA
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This study is the first in a series of reports involved in researching self-correlation and cross-correlation algorithms in intelligence systems. These algorithms are used to maintain a data base of current information about a battlefield. The initial view of the battlefield is stored in a central computer data base. As new data is received from the sensors on the battlefield, it is used to update the old data and formulate a new picture of the battlefield. The work on these algorithms reported here focuses on the sensitivity of the mathematical tests to changes and uncertainties in the data. The self-correlation algorithms use multivariate statistical tests to determine the equality of mean vectors from two different datasets. The statistical tests developed were variations of Hotellings T sub 2-statistics. The main results deal with the analysis of the robustness of these statistics with respect to normality and equal covariance matrices. Additional keywords Multivariate distributions Multivariate skewness Chi square tests Mathematical models Computerized Simulation.
- Statistics and Probability
- Military Operations, Strategy and Tactics