Fault tolerant integrated radar/inertial altimeter based on Nonlinear Robust Adaptive Kalman filter

Hajiyev, Chingiz

doi:10.1016/j.ast.2011.03.005

Cited by 27 publications

(12 citation statements)

References 15 publications

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“…However, it is difficult to determine the performance level and the weighting matrices. In [31][32][33][34], several robust UKF algorithms have been proposed for nonlinear stochastic systems with measurement malfunctions. An adaptation scheme with multiple scale factors is used for adapting the measurement noise covariances so that only the data of the faulty sensor is scaled and any unnecessary information loss is prevented.…”

Section: Introductionmentioning

confidence: 99%

“…The main advantage of the UKF is that it does not use any linearization for calculating the state predictions and covariances. Many robust UKF variants have been proposed [30][31][32][33][34][35][36][37][38][39][40]. For instance, the H ∞ performance criterion has been combined with the UKF to improve the robustness against model errors and noise uncertainty in [30].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust unscented Kalman filter with adaptation of process and measurement noise covariances

Sun

Jia

et al. 2016

Digital Signal Processing

101

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust unscented Kalman filter with adaptation of process and measurement noise covariances

Sun

Jia

et al. 2016

Digital Signal Processing

101

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“…Doppler device is generally considered to be rigidly connected with the body [6][7][8]. Doppler velocity errors contain inherent errors of the equipment such as scale error, bias and noise, and installation errors such as structural misalignment.…”

Section: Introductionmentioning

confidence: 99%

A Novel In-flight Alignment Algorithm for Airborne Strapdown INS with Assistant of Doppler Radar

Pan¹,

Han

Nie³

2015

Proceedings of the Second International Conference on Mechatronics and Automatic Control

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In order to improve the precision of Doppler and Strapdown inertial navigation system (SINS) integrated navigation system with moving base, an in-flight alignment method is proposed by making an uniform circular motion of the aircraft according to the phenomena avaliable in the Doppler/SINS navigation system tests. The platform error-angles of the SINS can be estimated quickly and the prediction precise can be improved by this method. Experiment verifies the feasibility and validity of this method. Theoretical analysis shows that the steady state limit of the estimation can be highly reduced by proposed method, and the method is valuable for practical application.Keywords Airborne SINS · Doppler · In-flight alignment · EKF · Filtering estimation IntroductionAs limited by the status of INS equipment and the level of theoretical research, the in-flight alignment cannot be implemented effectively just by using the existing INS equipment on airborne which can finish the work of solver on its own [1]. Most scholars tend to believe that the INS resolving capability can be improved with the assistance of some airborne mission equipment, and the attitude misalignment angles can be estimated and compensated effectively by using the auxiliary information as reference as obtained from some established satellite positioning

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“…The innovation-based covariance matching technique is a popular method. It calculates the covariance estimation with limited sample in a window and attempts to make the filter theoretical covariance consistent with it [5,6].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Huber-Based Filter for Hypersonic Cruise Vehicle Navigation

Wang

Liu

Zhong

2014

Journal of Algorithms & Computational Technology

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The navigation for hypersonic cruise vehicle (HCV) is a challenging task because of the complex vehicle dynamic and sensor measurement noise it suffered. This paper proposes a kind of adaptive robust Kalman filter using Mahalanobis distance for HCV navigation. The innovation-based adaptive estimation is discussed first. Based on Mahalanobis distance theory, a kind of robust covariance matrix estimation method is used to modify the innovation-based adaptive Kalman filter. Considering that the vehicle maneuver characteristics and noise statistics parameters varies during different periods, dual-frequency tuning for unknown noise statistics is designed based on this. The algorithm proposed by this paper is applied to hypersonic cruise vehicle navigation. Simulation has been made to verify the performance of the new algorithm according to HCV flight profile and characteristics; both Gaussian and non-Gaussian simulation are included.

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Fault tolerant integrated radar/inertial altimeter based on Nonlinear Robust Adaptive Kalman filter

Cited by 27 publications

References 15 publications

Robust unscented Kalman filter with adaptation of process and measurement noise covariances

Robust unscented Kalman filter with adaptation of process and measurement noise covariances

A Novel In-flight Alignment Algorithm for Airborne Strapdown INS with Assistant of Doppler Radar

Adaptive Huber-Based Filter for Hypersonic Cruise Vehicle Navigation

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