Multi-sensor Data Analysis

Academic year

2025Year

Term

First Semester

Course title

Multi-sensor Data Analysis

Class type

Lecture

Course title (ENG)

Multi-sensor Data Analysis

Class code・Class name・Teaching forms

Z1300004 Multi-sensor Data Analysis

Instructor

ASANO Futoshi

Credits

2.0Credits

Day and Time

Tue.3Period

Campus

Hachioji Remote

Location

Relationship between diploma policies and this course

A) A high degree of specialized expertise　100%
B) The skills to use science and technology　0%
C) The ability to conduct research independently, knowledge pertaining to society and occupations, and sense of ethics required of engineers and researchers　0%
D) Creative skills in specific areas of specialization　0%

Goals and objectives

By analyzing the observations from multiple sensors, informations such as the locations of signal sources and the state of the system can be estimated. The analyzing techniques taught in this course can be applied to many fields such as radar, sonar, communication, robot, seismology.

Prerequisites

None

Method Using AL・ICT

Not used

Class schedule

1. Physical model
2. Observation and Processing
3. Delay estimation
4. Statistical model and maximum likelihood
5. Spatial spectrum estimation
6. Subspace estimation
7. Adaptive filter
8. Signal source estimation
9. Independent component analysis
10. Bayes estimation
11. Target tracking
12. Supervised learning
13. Unsupervized learning
14. Review

Evaluation

Students must submit a report at the end of term.

Feedback for students

The submitted reports are reviewed and commented in the lecture.

Textbooks

Reference materials

"Array signal processing" 　ISBN978-4-339-01116-6

Office hours and How to contact teachers for questions

Mail address: asano@cc.kogakuin.ac.jp

Message for students

Course by professor with work experience

Not applicable

Work experience and relevance to the course content if applicable

Teaching profession course

Informatics Program

Syllabus data