Space based radar tracking filter

1995 ◽  
Author(s):  
A.M. Walton
Keyword(s):  
Radar Tracking ◽  
Tracking Filter

Identification of object's movement models in a radar tracking filter

2003 ◽  
Vol 36 (16) ◽  
pp. 1059-1064
Author(s):  
Miroslaw Sankowski ◽  
Zdzislaw Kowalczuk
Keyword(s):  
Radar Tracking ◽  
Movement Models ◽  
Tracking Filter

A Low Power and Low Noise On-Chip Active RF Tracking Filter for Digital TV Tuner ICs

2011 ◽  
Vol E94-C (10) ◽  
pp. 1698-1701
Author(s):  
Yang SUN ◽  
Chang-Jin JEONG ◽  
In-Young LEE ◽  
Sang-Gug LEE
Keyword(s):  
Low Power ◽  
Digital Tv ◽  
Low Noise ◽  
On Chip ◽  
Tracking Filter

Development of Radar Tracking Technique for the Short -Term Rainfall Field Forecasting-

2015 ◽  
Vol 48 (12) ◽  
pp. 995-1009
Author(s):  
Tae-Jeong Kim ◽  
◽  
Dong-Ryul Lee ◽  
Hyun-Han Kwon
Keyword(s):  
Short Term ◽  
Radar Tracking ◽  
Tracking Technique

A Strong Tracking Cubature Kalman Filter for Nonlinear Estimation

2013 ◽  
Vol 313-314 ◽  
pp. 1115-1119
Author(s):  
Yong Qi Wang ◽  
Feng Yang ◽  
Yan Liang ◽  
Quan Pan
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Scaling Factor ◽  
Estimation Accuracy ◽  
Nonlinear State Estimation ◽  
Cubature Kalman Filter ◽  
Novel Method ◽  
Simulation Results ◽  
Tracking Filter ◽  
Nonlinear State

In this paper, a novel method based on cubature Kalman filter (CKF) and strong tracking filter (STF) has been proposed for nonlinear state estimation problem. The proposed method is named as strong tracking cubature Kalman filter (STCKF). In the STCKF, a scaling factor derived from STF is added and it can be tuned online to adjust the filtering gain accordingly. Simulation results indicate STCKF outperforms over EKF and CKF in state estimation accuracy.

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