A covariance–matching criterion in the Frisch scheme identification of MIMO EIV models

2012 ◽  
Vol 45 (16) ◽  
pp. 1647-1652 ◽  
Author(s):  
Roberto Diversi ◽  
Roberto Guidorzi
Keyword(s):  
Matching Criterion ◽  
Covariance Matching

scholarly journals Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Weijian Si ◽  
Xinggen Qu ◽  
Lutao Liu
Keyword(s):  
Compressed Sensing ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Doa Estimation ◽  
Semidefinite Program ◽  
Matching Criterion ◽  
Multiple Measurement Vectors ◽  
Covariance Matching ◽  
Augmented Lagrange Method ◽  
Cramer Rao Bound

A novel direction of arrival (DOA) estimation method in compressed sensing (CS) is presented, in which DOA estimation is considered as the joint sparse recovery from multiple measurement vectors (MMV). The proposed method is obtained by minimizing the modified-based covariance matching criterion, which is acquired by adding penalties according to the regularization method. This minimization problem is shown to be a semidefinite program (SDP) and transformed into a constrained quadratic programming problem for reducing computational complexity which can be solved by the augmented Lagrange method. The proposed method can significantly improve the performance especially in the scenarios with low signal to noise ratio (SNR), small number of snapshots, and closely spaced correlated sources. In addition, the Cramér-Rao bound (CRB) of the proposed method is developed and the performance guarantee is given according to a version of the restricted isometry property (RIP). The effectiveness and satisfactory performance of the proposed method are illustrated by simulation results.

Fast Covariance Matching With Fuzzy Genetic Algorithm

2012 ◽  
Vol 8 (1) ◽  
pp. 148-157 ◽  
Author(s):  
Xuguang Zhang ◽  
Shuo Hu ◽  
Dan Chen ◽  
Xiaoli Li
Keyword(s):  
Genetic Algorithm ◽  
Covariance Matching ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic

A matching criterion for motion compensation in the temporal coding of video signal

2009 ◽  
Vol 5 (2) ◽  
pp. 133-139 ◽  
Author(s):  
Ravindra Kumar Purwar ◽  
Nupur Prakash ◽  
Navin Rajpal
Keyword(s):  
Motion Compensation ◽  
Video Signal ◽  
Temporal Coding ◽  
Matching Criterion

scholarly journals Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2372 ◽  
Author(s):  
Antônio C. B. Chiella ◽  
Bruno O. S. Teixeira ◽  
Guilherme A. S. Pereira
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Ground Truth ◽  
Adaptive Strategy ◽  
Attitude Estimation ◽  
Covariance Matching ◽  
Adaptive Unscented Kalman Filter ◽  
Unit Quaternions ◽  
Abrupt Changes ◽  
Robust Adaptive

This paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter (QRAUKF) for attitude estimation. The proposed methodology modifies and extends the standard UKF equations to consistently accommodate the non-Euclidean algebra of unit quaternions and to add robustness to fast and slow variations in the measurement uncertainty. To deal with slow time-varying perturbations in the sensors, an adaptive strategy based on covariance matching that tunes the measurement covariance matrix online is used. Additionally, an outlier detector algorithm is adopted to identify abrupt changes in the UKF innovation, thus rejecting fast perturbations. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as external magnetic field interference and linear accelerations. Comparative experimental results that use an industrial manipulator robot as ground truth suggest that our method overcomes a trusted commercial solution and other widely used open source algorithms found in the literature.

scholarly journals A SINS/BDS Integrated Navigation Method Based on Classified Weighted Adaptive Filtering

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Xuchao Kang ◽  
Guangjun He ◽  
Xingge Li
Keyword(s):  
Adaptive Filtering ◽  
Navigation System ◽  
Fault Tolerant ◽  
Hypothesis Test ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Covariance Matching ◽  
Uncertain Model ◽  
Navigation Accuracy ◽  
Navigation Method

Aiming at the problem that the accuracy and stability of SINS/BDS integrated navigation system decrease due to uncertain model and observation anomalies, a SINS/BDS integrated navigation method based on classified weighted adaptive filtering is proposed. Firstly, the innovation covariance matching technology is used to detect whether there is any abnormality in the system as a whole. Then the types of anomalies are distinguished by hypothesis test. Different types of anomalies have different effects on state estimation. Based on the dynamic changes of innovation, different adaptive weighting methods are adopted to correct navigation information. The simulation results show that this method can effectively improve the fault-tolerant performance of integrated navigation system in complex environment with unknown anomaly types. When both model anomalies and observation anomalies exist, the speed and position accuracy are increased by 42% and 24% compared with the standard KF, 38% and 22% compared with the innovation orthogonal adaptive filtering, which has higher navigation accuracy.

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