The Experts below are selected from a list of 405153 Experts worldwide ranked by ideXlab platform
Jiongqi Wang - One of the best experts on this subject based on the ideXlab platform.
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maximum correntropy unscented kalman filter for ballistic missile navigation System based on sins cns deeply integrated mode
Sensors, 2018Co-Authors: Bowen Hou, Haiyin Zhou, Jiongqi WangAbstract:Strap-down inertial navigation System/celestial navigation System ( SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation System is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation System is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the System Equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter.
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Maximum Correntropy Unscented Kalman Filter for Ballistic Missile Navigation System based on SINS/CNS Deeply Integrated Mode
MDPI AG, 2018Co-Authors: Bowen Hou, Haiyin Zhou, Jiongqi WangAbstract:Strap-down inertial navigation System/celestial navigation System (SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation System is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation System is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the System Equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter
Bowen Hou - One of the best experts on this subject based on the ideXlab platform.
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maximum correntropy unscented kalman filter for ballistic missile navigation System based on sins cns deeply integrated mode
Sensors, 2018Co-Authors: Bowen Hou, Haiyin Zhou, Jiongqi WangAbstract:Strap-down inertial navigation System/celestial navigation System ( SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation System is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation System is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the System Equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter.
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Maximum Correntropy Unscented Kalman Filter for Ballistic Missile Navigation System based on SINS/CNS Deeply Integrated Mode
MDPI AG, 2018Co-Authors: Bowen Hou, Haiyin Zhou, Jiongqi WangAbstract:Strap-down inertial navigation System/celestial navigation System (SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation System is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation System is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the System Equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter
Haiyin Zhou - One of the best experts on this subject based on the ideXlab platform.
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maximum correntropy unscented kalman filter for ballistic missile navigation System based on sins cns deeply integrated mode
Sensors, 2018Co-Authors: Bowen Hou, Haiyin Zhou, Jiongqi WangAbstract:Strap-down inertial navigation System/celestial navigation System ( SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation System is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation System is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the System Equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter.
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Maximum Correntropy Unscented Kalman Filter for Ballistic Missile Navigation System based on SINS/CNS Deeply Integrated Mode
MDPI AG, 2018Co-Authors: Bowen Hou, Haiyin Zhou, Jiongqi WangAbstract:Strap-down inertial navigation System/celestial navigation System (SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation System is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation System is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the System Equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter
Hassan K Khalil - One of the best experts on this subject based on the ideXlab platform.
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asymptotic regulation of minimum phase nonlinear Systems using output feedback
IEEE Transactions on Automatic Control, 1996Co-Authors: Nazmi A Mahmoud, Hassan K KhalilAbstract:We consider a single-input/single-output (SISO) nonlinear System which has a well-defined normal form with asymptotically stable zero dynamics. We allow the System's Equation to depend on constant uncertain parameters and disturbance inputs which do not change the relative degree. Our goal is to design an output feedback controller which regulates the output to a constant reference. The integral of the regulation error is augmented to the System Equation, and a robust output feedback controller is designed to bring the state of the closed-loop System to a positively invariant set. Once inside this set, the trajectories approach a unique equilibrium point at which the regulation error is zero. We give regional as well as semiglobal results.
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asymptotic regulation of minimum phase nonlinear Systems using output feedback
American Control Conference, 1993Co-Authors: Nazmi A Mahmoud, Hassan K KhalilAbstract:We consider a single-input single-output (SISO) nonlinear System which has a well defined normal form with asymptotically stable zero dynamics. We allow the System's Equation to depend on bounded uncertain parameters which do not change the relative degree. Our goal is to design an output feedback controller which regulates the output to a constant reference in the presence of constant unkown input disturbances. The disturbance vector fields satisfy geometric conditions which ensure that the System is transformable into the so called disturbance-strict-feedback form. The integral of the regulation error is augmented to the System Equation and a robust output feedback controller is designed to bring the state of the closed-loop System to a positively invariant set. Once inside this set, the trajectories approach a unique equilibrium point at which the regulation error is zero. We give regional as well as semi-global results.
Nazmi A Mahmoud - One of the best experts on this subject based on the ideXlab platform.
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asymptotic regulation of minimum phase nonlinear Systems using output feedback
IEEE Transactions on Automatic Control, 1996Co-Authors: Nazmi A Mahmoud, Hassan K KhalilAbstract:We consider a single-input/single-output (SISO) nonlinear System which has a well-defined normal form with asymptotically stable zero dynamics. We allow the System's Equation to depend on constant uncertain parameters and disturbance inputs which do not change the relative degree. Our goal is to design an output feedback controller which regulates the output to a constant reference. The integral of the regulation error is augmented to the System Equation, and a robust output feedback controller is designed to bring the state of the closed-loop System to a positively invariant set. Once inside this set, the trajectories approach a unique equilibrium point at which the regulation error is zero. We give regional as well as semiglobal results.
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asymptotic regulation of minimum phase nonlinear Systems using output feedback
American Control Conference, 1993Co-Authors: Nazmi A Mahmoud, Hassan K KhalilAbstract:We consider a single-input single-output (SISO) nonlinear System which has a well defined normal form with asymptotically stable zero dynamics. We allow the System's Equation to depend on bounded uncertain parameters which do not change the relative degree. Our goal is to design an output feedback controller which regulates the output to a constant reference in the presence of constant unkown input disturbances. The disturbance vector fields satisfy geometric conditions which ensure that the System is transformable into the so called disturbance-strict-feedback form. The integral of the regulation error is augmented to the System Equation and a robust output feedback controller is designed to bring the state of the closed-loop System to a positively invariant set. Once inside this set, the trajectories approach a unique equilibrium point at which the regulation error is zero. We give regional as well as semi-global results.
