MLS system error model identification and synthesis

1992 ◽  
Vol 28 (1) ◽  
pp. 164-173 ◽  
Author(s):  
R.J. Kelly
Keyword(s):  
Model Identification ◽  
Error Model ◽  
System Error

scholarly journals Output Error Model Identification Against Unexpected Load Disturbance

2016 ◽  
Vol 49 (7) ◽  
pp. 863-868 ◽  
Author(s):  
Shijian Dong ◽  
Tao Liu ◽  
Fengwei Chen
Keyword(s):  
Model Identification ◽  
Error Model ◽  
Output Error ◽  
Load Disturbance

Speech enhancement using PCA and variance of the reconstruction error model identification

2007 ◽  
Author(s):  
Amin Haji Abolhassani ◽  
Sid-Ahmed Selouani ◽  
Douglas O'Shaughnessy ◽  
Mohamed-Faouzi Harkat
Keyword(s):  
Speech Enhancement ◽  
Model Identification ◽  
Reconstruction Error ◽  
Error Model

The Error Analysis of the Chirp Radar Waveforms Based on DDS Technology

2014 ◽  
Vol 707 ◽  
pp. 476-479
Author(s):  
Shuang Zhao ◽  
Yu Bo Yue
Keyword(s):  
Error Analysis ◽  
Error Model ◽  
Signal Source ◽  
Chirp Signal ◽  
System Error ◽  
Radar Waveforms ◽  
System Errors ◽  
Phase Truncation

Based on the chirp signal radar using DDS technology, the waveform of the wideband chirp signal source is analyzed. By analyzing the system error model, the method that selecting the chirp steps in accordance with the digits of DDS phase truncation is proposed. It reduces the system errors caused by the phase truncation.

scholarly journals Initial Self-Alignment for Marine Rotary SINS Using Novel Adaptive Kalman Filter

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Fujun Pei ◽  
Li Zhu ◽  
Jian Zhao
Keyword(s):  
Kalman Filter ◽  
Inertial Frame ◽  
Error Model ◽  
Alignment Method ◽  
Initial Alignment ◽  
Adaptive Kalman Filter ◽  
Dynamic Disturbance ◽  
System Error ◽  
Angular Velocities ◽  
Initial Attitude

The accurate initial attitude is essential to affect the navigation result of Rotary Strapdown Inertial Navigation System (SINS), which is usually calculated by initial alignment. But marine mooring Rotary SINS has to withstand dynamic disturbance, such as the interference angular velocities and accelerations caused by surge and sway. In order to overcome the limit of dynamic disturbance under the marine mooring condition, an alignment method using novel adaptive Kalman filter for marine mooring Rotary SINS is developed in this paper. This alignment method using the gravity in the inertial frame as a reference is discussed to deal with the lineal and angular disturbances. Secondly, the system error model for fine alignment in the inertial frame as a reference is established. Thirdly, PWCS and SVD are used to analyze the observability of the system error model for fine alignment. Finally, a novel adaptive Kalman filter with measurement residual to estimate measurement noise variance is designed. The simulation results demonstrate that the proposed method can achieve better accuracy and stability for marine Rotary SINS.

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