《多傳感器信息融合》課程介紹
多傳感器信息融合是物聯網工程專業的專業選修課，它是為滿足物聯網工程的理論研究和應用實踐需要而設置的。這是一門既涉及一些基礎理論又能同應用實踐緊密結合的課程。
多傳感器信息融合技術是信息科學領域的一項高新技術。是對多種信息的獲取、傳輸與處理的基本方法、技術和手段，以及對信息的表示、内在聯系和運動規律進行研究的技術。多傳感器信息融合技術的理論和技術涉及了多個學科，是新一代智能信息技術的核心基礎之一。
通過本課程的學習，學生将掌握如下知識：
1． 數據融合的理論基礎
2． 多傳感器目标檢測的基本理論
3． 多傳感器目标檢測的性能評估
4． 目标跟蹤與數據關聯概論
5． 相互作用多模型—概率數據關聯算法
6． 多傳感器多目标跟蹤的一般理論
7． 身份識别
通過本課程的學習，使學生掌握多傳感器信息融合的基本理論和基本知識，培養學生在對涉及多傳感器的實際場景中，分析問題和解決問題的能力。
The introduction of course --- Information Fusion of Multi-Sensors
Information Fusion of Multi-Sensors is a optional specialty course of web of things engineering. This course is provided for the need of the application and theoretical study for the web of things engineering.
Multi-sensor information fusion technology is a high-tech field of information science. It studies the variety of information acquisition, transmission and processing of the basic methods, techniques and tools, as well as the information that the movement of internal relations and research technology. Multi-sensor information fusion technology theory and techniques involved in a number of disciplines. It is a key foundation of the new generation of intelligent information technology.
Through this course, students will learn the following knowledge:
1. Data fusion theory
2. Basic theories for multi-sensor target detection
3. Performance evaluation for multi-sensor target detection
4. Target tracking and data association
5. Interacting multiple model - probabilistic data association algorithm
6. Basic theories for multi-sensor multi-object tracking
7. Identification
After the study of this course, students will master the basic theory and basic knowledge of multi-sensor information fusion. The analyzing and problem-solving abilities for the multi-sensor scene will be greatly improved after this course.
