1. Applying the Analytical Hierarchy Process to determine the optimal
sensor pair for use in aerial surveillance
John Uncangco
Mentored by Richard LeClaire and Faraz Nathaniel
Introduction
Methods and Materials (continued)
Results (continued)
The surveillance industry has changed dramatically over the last 50 years. From the use of the SR-71 to the use of unmanned drones currently the entire industry has changed. In addition to the changes to the types of vehicles performing the surveillance, the sensors have changed as well. While manned aircraft like the SR-71 have room for many sensors and lots of power available to use, aircraft, like drones, have low spatial capacity and limited power resources, making carrying and utilizing several sensors simultaneously either wasteful or impossible. This poses a problem for possible threat detection, as well as a question regarding which sensors should be prioritized. Ideally, only one sensor would be required to detect all threats, but each sensor has its own strengths and weaknesses. By using pairs of sensors, it may be possible to put two sensors together that will complement each other as well as provide for adequate coverage of all areas of data collection. If such a pair could be found, the aircraft’s surveillance versatility worldwide would increase dramatically. Effective pairs would also reduce resource usage, which would benefit the environment and save funding.
Choosing the most optimum sensor pair to span a world of different environments without experimental data was too subjective, but with the Analytical Hierarchy Process it can be made easier for hypothesis purposes, using relative knowledge of each sensor in relation to one another. The Analytical Hierarchy Process is a decision making tool that makes use of pairwise comparison values, matrix Eigenvalue eigenvalue math, and several factors of decision to produce a decision more accurate to what the user values (Saaty & Katz, 1990). With the research limitations of the project, it was an effective decision making method.
Then a similar process was done for the criteria, but with all alternatives pairwise compared under each criteria separately. This part of the process produces several Eigenvalue matrices where they are then combined into one matrix by placing them side by side, making sure that the rows’ alternative titles align properly with the column’s alternative titles. This combined eigenvalue matrix is then multiplied with the criteria weight matrix, with the criteria weight matrix on the right during the multiplication process. The final matrix produced will then have the raw ratings of the sensors, which are then interpreted from highest value to lowest value to give the highest rated to the lowest rated, thus completing the process.
Two separate methods were practiced side by side, using the Analytical Hierarchy Process. The method centered around educated discussion involved direct comparisons between each sensor in each environmental condition separately, yielding SIGINT and EO-IR as shown in Graph 1, while the method centered around assigning scores to the sensors individually in each environmental discussion involved more of a look at each sensor separately, yielding SIGINT and Radar as shown in Graph 2, by using those scores for the pairwise comparisons.
Conclusions
It was expected that the individual scoring method would provide the least subjectivity, considering that each sensor was given a score, instead of trying to gauge comparison ratios of superiority, as practiced by the educated discussion method. Although this expectation seemed reasonable, the educated discussion method captured one of the most commonly used surveillance pairs, SIGINT and EO-IR, as the optimal pair, while the individual scoring method captured the more unheard of SIGINT and Radar optimal pair, thus pointing to the idea that the educated discussion method was more reasonable in hypothesizing the optimal aerial sensor pair.
Considering the general subjectivity in the Analytical Hierarchy Process and its reliance on the user’s knowledge and opinions on the matter, it makes sense that the educated discussion method, being the more subjective, produced the more commonly used sensor pair. Based on the more reasonable results from Graph 1, the educated discussion method with the Analytical Hierarchy Process appears most effective.
Results
Graph 1: The following final eigenvalue scores for comparative discussion of the sensors were calculated as the final part to the Analytical Hierarchy Process, and revealed SIGINT and EO-IR as the optimal pair.
Methods and Materials
References
The data used to conduct the Analytical Hierarchy Process was collected through research of publicly available data on these sensors. Several sites and databases were utilized to interpret and produce educated assessments of the importance of each sensor in relation to the other sensors.
The Analytical Hierarchy Process begins with creating a set of criteria to help judge each of the possible decisions in those specific criteria. The criteria are then pairwise compared, meaning that each criteria to be so much more important than the other by a chosen ratio and placed in a matrix. The final matrix produced is the criteria weight matrix to be used during the final step of the Analytical Hierarchy Process.
Graph 2: The following final eigenvalue scores for table scoring discussion of the sensors were calculated as the final part to the Analytical Hierarchy Process, and revealed SIGINT and Radar as the optimal pair.
Saaty, T. L. & Katz, J. M. (1990). How to make a decision: The Analytical Hierarchy Process. European Journal of Operational Research, 48, 9-26.
Acknowledgements
I would like to thank my faculty adviser, Mr. Sloan, for his help in this process, and my friends and family for comfort and encouragement along the way.