The high level of English is a standard for a top student.
1. Sometimes you missee people, not because you are blind, but because you are kind.
2. I wish there was someone in the future Hold my hands when I'm lost. Tell me firmly:''You are not alone, you and me ."
3. “It isn’t the burdens of today that drive men mad. It is the regret over yesterday and the fear of tomorrow. Regret and fear are twin thieves who rob us of today.”
4. Isolate Yourself – to reenergize. Many seemingly extroverts are introverts. If you recharge when by yourself, you need to seek out isolation from time to time.
5. Don’t be so eager to show off your strengths until it’s the perfect time to strike. If rope-a-dope worked for The Champ, it will for you too.
6. The best kind of travel experience is being deeply moved in an unfamiliar place.
7. “After the life of desolation, to reach the heart of prosperity.
8. Man has to be crazy for once, whether it is for a person,a love story, a journey or a dream.
INS Inertial Navigation System
WSN Wireless Sensor Networks
the orbital navigation method called unknown landmark tracking
Brogan - Modern Control Theory
Optimal Estimation and Control
khalil nonlinear control
Advanced Discrete Control
Introduction to a Simulation Environment – Gazebo
Introduction to Robotics
（http://www2.ece.ohio-state.edu/~zhang/RoboticsClass/index.html）
Paper
1. Fuzzy adaptive Kalman filter for indoor mobile target positioning with INS/WSN integrated method
(https://sci-hub.tw/10.1007/s11771-015-2649-9)
Abstract:
Pure inertial navigation system (INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network (WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter (KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system (FIS), and the fuzzy adaptive Kalman filter (FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.
Key words: inertial navigation system (INS); wireless sensor network (WSN); mobile target; integrated positioning; fuzzy adaptive; Kalman filter
2. A Kalman Filter-Based Framework for Enhanced Sensor Fusion
(https://ieeexplore.ieee.org/document/7001546)
Abstract:
Sensor fusion has found a lot of applications in today's industrial and scientific world with Kalman filtering being one of the most practiced methods. Despite their simplicity and effectiveness, Kalman filters are usually prone to uncertainties in system parameters and particularly system noise covariance. This paper proposes a Kalman filtering framework for sensor fusion, which provides robustness to the uncertainties in the system parameters such as noise covariance and state initialization. Two methods are developed based on the proposed approach. The effectiveness of the proposed methods is verified through numerous simulations and experiments.