@inproceedings{99813817b3e64dfa98f7827818ac56c6,
title = "Finding a needle in a haystack: Satellite detection of moving objects in marine environments",
abstract = "There is a growing need in maritime missions to monitor moving vessels with satellite sensors, in order to detect vessels that may mislead about their identity and transmit wrong identification parameters. In order to provide an efficient and cost-effective solution, vessel behavior prediction is a necessary ability. We present three models for vessel behavior prediction: Min-Max, Uniform-Walk and Normal-Walk. We use real marine traffic data (AIS, Automatic Identification System) to compare the performance of these models and their ability to predict vessel behavior in a time frame of 1-11 hours.",
author = "Natalie Fridman and Doron Amir and Han Schvartzman and Oded Stawitzky and Igor Kleinerman and Sharon Kligsberg and Noa Agmon",
note = "Publisher Copyright: {\textcopyright} Copyright 2017, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.; 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 ; Conference date: 08-05-2017 Through 12-05-2017",
year = "2017",
language = "الإنجليزيّة",
series = "Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS",
pages = "1541--1543",
editor = "Edmund Durfee and Michael Winikoff and Kate Larson and Sanmay Das",
booktitle = "16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017",
}
