Non-Linear DSGE Models, the Central Difference Kalman Filter, and the Mean Shifted Particle Filter

2008 ◽  
Author(s):  
Martin M. Andreasen
Keyword(s):  
Kalman Filter ◽  
Particle Filter ◽  
Dsge Models ◽  
Central Difference ◽  
Non Linear ◽  
The Mean ◽  
Central Difference Kalman Filter

A SLAM algorithm based on the central difference Kalman filter

2009 ◽  
Author(s):  
Jihua Zhu ◽  
Nanning Zheng ◽  
Zejian Yuan ◽  
Qiang Zhang ◽  
Xuetao Zhang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Central Difference ◽  
Slam Algorithm ◽  
Central Difference Kalman Filter

scholarly journals Moving State Marine SINS Initial Alignment Based on High Degree CKF

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yong-Gang Zhang ◽  
Yu-Long Huang ◽  
Zhe-Min Wu ◽  
Ning Li
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Alignment Method ◽  
Misalignment Angle ◽  
Initial Alignment ◽  
Central Difference ◽  
Angle Condition ◽  
Cubature Kalman Filter ◽  
High Degree ◽  
Central Difference Kalman Filter

A new moving state marine initial alignment method of strap-down inertial navigation system (SINS) is proposed based on high-degree cubature Kalman filter (CKF), which can capture higher order Taylor expansion terms of nonlinear alignment model than the existing third-degree CKF, unscented Kalman filter and central difference Kalman filter, and improve the accuracy of initial alignment under large heading misalignment angle condition. Simulation results show the efficiency and advantage of the proposed initial alignment method as compared with existing initial alignment methods for the moving state SINS initial alignment with large heading misalignment angle.

An Array Nonlinear Kalman Tracker for Indoor GPS Signal

2010 ◽  
Vol 44-47 ◽  
pp. 3864-3868
Author(s):  
Ji Cheng Ding ◽  
Lin Zhao ◽  
Jia Liu ◽  
Shuai He Gao
Keyword(s):  
Dynamic Programming ◽  
Kalman Filter ◽  
Detection Probability ◽  
Viterbi Algorithm ◽  
Signal Quality ◽  
Tracking Loop ◽  
Central Difference ◽  
Signal Tracking ◽  
High Detection ◽  
Central Difference Kalman Filter

To implement indoor GPS signal tracking in standalone mode when the tracking loop is unlocked and data bit edge is unknown, the paper develops a modified Viterbi Algorithm (MVA) based on dynamic programming, and it was applied for GPS bit synchronization. Besides, two combination carrier tracking schemes based on Central Difference Kalman Filter (CDKF) and MVA module were designed for indoor GPS signal. The testing results indicate that the methods can successful detect bit edge position with high detection probability whether or not the tracking loop is locked. The co-operational tracking scheme is still able to perform when the signal quality deteriorate.

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