Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques
Abstract
This research continues on the work by Hatzinger and Gertsman by creating a decision-based algorithm which subdivides the search region into sub-regions known as cells, decides an optimal next cell to search, and distributes the results of the search to other cooperative search assets. Each cooperative search asset stores the following four arrays in order to decide which cell to search: current estimated target density of each cell; the current number of assets in a cell; each cooperative asset's next cell to search; and the total time any asset has been in a cell. A software-based simulation based environment, AFSIM, was utilized to complete the verification process, create the test environment, and the SUT. Additionally, the algorithm was tested against various distributions of target threats or clusters. Finally, precision, recall, and F-score are introduced as new MOEs. The results show the algorithm does not have a significant effect against the original MOEs or the new MOEs. Furthermore, the results are negatively correlated to a decrease in target distributions standard deviation i.e. target clustering.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 23, 2022
- Accession Number
- AD1189067
Entities
People
- Shawn Whitney
Organizations
- Air Force Institute of Technology