卡尔曼滤波器
方位(导航)
运动学
计算机科学
声纳
运动(物理)
职位(财务)
噪音(视频)
人工智能
遗传算法
算法
计算机视觉
控制理论(社会学)
机器学习
图像(数学)
控制(管理)
经济
物理
经典力学
财务
作者
Alper Aytun,Serol Bulkan
出处
期刊:Advances in logistics, operations, and management science book series
日期:2018-07-18
卷期号:: 330-346
被引量:3
标识
DOI:10.4018/978-1-5225-5513-1.ch014
摘要
The main goal of the bearing-only target motion analysis (BOTMA) is to determine the target's kinematic parameters such as position, course, and speed by only using the bearings reported by an onboard passive sensor (e.g., a sonar or an ESM [electronic support measures] device). This chapter provides a brief description of the BOTMA problem. Next, it discusses the implementation of the Kalman filtering technique to solve the problem. The authors then discuss the variations of the Kalman filtering (i.e., the extended and unscented Kalman filters). They also propose a genetic algorithm metaheuristic that incorporates a novel search space narrowing technique to solve the BOTMA problem and present numerical results for different noise conditions. They finally highlight the future research directions for modeling and solving the BOTMA problem.
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