scholarly journals Adaptive filtering algorithms in target tracking applications

2003 ◽  
Vol 16 (3) ◽  
pp. 317-326
Author(s):  
Igor Jovandic ◽  
Zeljko Djurovic ◽  
Branko Kovacevic
Keyword(s):  
Target Tracking ◽  
Adaptive Filtering ◽  
Noise Level ◽  
Estimation Error ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Error Criterion ◽  
Filtering Algorithms ◽  
Target Trajectory ◽  
Simulation Results

Comparison of several target tracking algorithms is presented. Namely discrete noise level adjustment (DNLA), variable state dimension (VSD) and interacting multiple model (IMM) algorithms are discussed. Target trajectory, target models, filtering algorithms and simulation results are given. The cumulative estimation error criterion is used in order to compare the algorithms.

Maneuvering Target Tracking Based on Radar/ESM Sensors

2015 ◽  
Vol 713-715 ◽  
pp. 672-675 ◽  
Author(s):  
Xing Xiu Li ◽  
Pan Long Wu
Keyword(s):  
Dynamic System ◽  
Target Tracking ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Maneuvering Target Tracking ◽  
Heterogeneous Sensors ◽  
System Models ◽  
Maneuvering Target ◽  
Blue Filter ◽  
Simulation Results

A novel interacting multiple model based on BLUE filter (IMM-BLUE) for tracking a maneuvering target using radar/ESM heterogeneous sensors is presented in this paper. Under the architecture of the proposed algorithm, the interacting multiple model (IMM) deals with the model switching, while the BLUE filter accounts for non-linearity in the dynamic system models. The simulation results show that the presented IMM-BLUE has higher tracking precision than the IMM-DCM, and IMM-EKF.

Sign in / Sign up

Export Citation Format

Share Document