scholarly journals Fuzzy modeling, maximum likelihood estimation, and Kalman filtering for target tracking in NLOS scenarios

2014 ◽  
Vol 2014 (1) ◽  
Author(s):  
Jun Yan ◽  
Kegen Yu ◽  
Lenan Wu
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Target Tracking ◽  
Kalman Filtering ◽  
Likelihood Estimation ◽  
Fuzzy Modeling

A Simaplied Adaptive Kalman Filtering Algorithm

2014 ◽  
Vol 1037 ◽  
pp. 378-382
Author(s):  
Lei Bo ◽  
Xin Yan Zhu
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Unmanned Aerial Vehicle ◽  
Kalman Filtering ◽  
Likelihood Estimation ◽  
Simplified Model ◽  
Filtering Algorithm ◽  
Aerial Vehicle ◽  
Kalman Filtering Algorithm ◽  
The Moment

The adaptive Kalman filtering algorithm was adopted in the online estimate of navigation state of unmanned aerial vehicle (UAV) as the simplified model often used. At the moment, the alogorithms those usually applied in this territory are not perfect. Analysed the adaptive Kalman filtering based on Maximum-Likelihood Estimation and Sage-Husa Kalman filtering, take advantage the characteristics of residue, choose the estimation windows, a simplified adaptive Kalman filtering algorithm was gived.

Sign in / Sign up

Export Citation Format

Share Document