Multi-sensors search for lost moving targets using unrestricted effort
Keywords:
Available resources, Lost targets, Multi-sensors, Probability of undetection, Search plan.
Abstract
This paper addresses the problem of searching for multiple targets using multiple sensors, where targets move randomly between a limited number of states at each time interval. Due to the potential value or danger of the targets, multiple sensors are employed to detect them as quickly as possible within a fixed number of search intervals. Each search interval has an available search effort and an exponential detection function is assumed. The goal is to develop an optimal search strategy that distributes the search effort across cells in each time interval and calculates the probability of not detecting the targets throughout the entire search period. The optimal search strategy that minimizes this probability is determined, the stability of the search is analyzed, and some special cases are considered. Additionally, we introduce the $M$-cells algorithm.
Published
2024-06-17
How to Cite
Teamah, A.-E. A. M., Kassem, M. A., & Elebiary , E. Y. (2024). Multi-sensors search for lost moving targets using unrestricted effort. Statistics, Optimization & Information Computing, 12(6), 1812-1825. https://doi.org/10.19139/soic-2310-5070-1975
Issue
Section
Research Articles
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).