Entity

Time filter

Source Type


Yu Z.,Beijing Institute of Technology | Yu Z.,Key Laboratory of Dynamics and Control of Flight Vehicle | Yu Z.,Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration | Cui P.,Beijing Institute of Technology | And 3 more authors.
Aerospace Science and Technology | Year: 2016

In order to compute the sequential state estimation of Mars entry dynamic system from noisy observations, a deterministic square-root Kalman filter is developed with the implementation of polynomial chaos expansion. The filter allows for the nonlinearity of dynamic system and observation model without the need for assumption about the Gaussian distribution of state. In the algorithm, a minimum variance based data assimilation scheme is developed. The resulting Kalman type updates of state's mean and deviations are performed separately and the square-root formulation of coefficients of polynomial chaos can be computed directly from the polynomial chaos expansion of forecasted states and observations. Two autonomous navigation scenarios based on the Mars Network are considered to quantify the benefits of polynomial chaos based square-root Kalman filter over the other usual nonlinear filters. Additionally, the contrastive analysis of propagations with non-Gaussian states is conducted. Simulation results show that a more accurate estimation and faster convergence can be achieved from the proposed nonlinear filter. Finally, the accuracy and time efficiency of the polynomial chaos based square-root Kalman filter are further analyzed and the optimal order of polynomial chaos is recommended. © 2016 Elsevier Masson SAS. Source


Hu H.,Beijing Institute of Technology | Hu H.,Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration | Hu H.,Key Laboratory of Dynamics and Control of Flight Vehicle | Zhu S.,Beijing Institute of Technology | And 5 more authors.
Aerospace Science and Technology | Year: 2016

This paper aims at desensitizing the optimal trajectory for landing on the small bodies with reduced landing error in the presence of initial state error, parameters uncertainties of the target body (the gravity and the body's rotation rate) and thrust error (the error in thrust magnitude and direction). The motion of the lander is expressed in the body-fixed coordinate frame, and the thruster is considered to be variable. Instead of directly optimizing the landing trajectory, this paper propagates the linear covariance of the stochastic landing dynamics equations, and minimizes the fuel consumption as well as the covariance. Firstly, the stochastic state equations including the effects of these uncertainties are constructed. The rotation rate is augmented as the new state of the state equations, and the uncertainties in gravity and thruster are modeled as the stochastic process noise acting on the lander. Then, the closed-loop linear covariance is derived and optimized with the fuel consumption performance index as a penalty factor. Finally, several sets of simulations are performed in the scenarios of Eros 433 and Vesta. The open-loop trajectory is firstly performed in the scenario of Eros 433 and the result shows that these uncertainties contribute greatly to the trajectory dispersions. The 3σ trajectory dispersions for tracking the optimal and desensitized optimal trajectory show that the desensitized approach reduces the landing error effectively. And the statistic landing velocities show that the desensitized approach meets the requirement of soft and stable landing on small bodies. To especially discuss the fuel consumption of optimal and desensitized optimal trajectory, the simulation in the scenario of Vesta is performed. The results show that the desensitized optimal approach takes only about 1.01kg more fuel for the lander of 800kg size. And the landing error of desensitized trajectory is reduced significantly compared to that of the optimal trajectory. The total simulations in the scenario of Eros 433 and Vesta indicate that the desensitized approach is fuel-saving, and can reduce the landing error effectively for landing on small bodies. © 2015 Elsevier Masson SAS. All rights reserved. Source


Ge D.,Beijing Institute of Technology | Ge D.,Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration | Ge D.,Key Laboratory of Dynamics and Control of Flight Vehicle | Gao A.,Beijing Institute of Technology | And 5 more authors.
2016 AIAA Guidance, Navigation, and Control Conference | Year: 2016

In Mars landing process, smaller hazards like rocks and craters can only be detected when the vehicle is near the surface. The original landing point might be found dangerous and thus the onboard selection of a new landing site and a real-time trajectory generation become the key to the success of the whole mission. In this paper, an autonomous online safe landing site selection considering maneuverability constraint during powered descent phase is proposed. The new landing site is selected based on a novel criterion called Landing Site Selection Index (LSSI). The index includes not only factors like safety of the terrain in view and terminal motion state, but also the maneuverability of the vehicle. A real-time slidingmode guidance is adopted to transfer the vehicle to the updated destination. The online selection and transfer process ensures the safety of the landing mission from multiple aspects. Further Monte Carlo simulations show the effectiveness and robustness of the scheme. © 2016, (publisher). All rights reserved. Source


Cui P.,Beijing Institute of Technology | Cui P.,Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration | Cui P.,Key Laboratory of Dynamics and Control of Flight Vehicle | Wang S.,Beijing Institute of Technology | And 6 more authors.
Advances in Space Research | Year: 2016

The performance of the navigation system during the Mars final approach phase determines the initial accuracy of Mars entry phase, which is critical for a pin-point landing. An X-ray pulsars/Doppler integrated navigation strategy is proposed to improve the estimation accuracy of the spacecraft's entry state, as well as to enhance the autonomy, real-time and reliability. The navigation system uses the X-ray pulsar measurements and Doppler velocity measurements which are complementary to each other. The performance degradation in velocity estimation at the end of the final approach phase for X-ray pulsar based navigation can thus be eliminated. The nonlinearity of the system and the performance of Extended Kalman Filter are analyzed in this paper. Furthermore, in order to optimize the navigation scheme, a principle for navigation beacons selection based on the Fisher information matrix is used. Finally, a navigation scenario based on the 2012 encounter at Mars of Mars Science Laboratory spacecraft is considered to demonstrate the feasibility and accuracy of the proposed scheme. Simulation results also indicate that the proposed navigation scheme has reference value for the design of the future Mars explorations. © 2016 COSPAR. Source


Yu Z.,Beijing Institute of Technology | Yu Z.,Key Laboratory of Dynamics and Control of Flight Vehicle | Yu Z.,Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration | Zhao Z.,Beijing Institute of Technology | And 5 more authors.
2016 AIAA Guidance, Navigation, and Control Conference | Year: 2016

Atmospheric entry guidance is a necessary technology for a Mars pin-point landing in the future. For a preferred reference-tracking guidance, trajectory optimization is an indispensable prerequisite. In order to account for the disturbance of initial states and atmospheric density which is a practical situation for Mars atmospheric entry as well as to improve the navigation performance, an observability-based robust trajectory optimization method is proposed. The determinant of Fisher information matrix is used to quantify the degree of observability, and the integration of the degree of observability is chosen as the objective function. Meanwhile, by introducing the polynomial chaos theory, the uncertainty propagation of states and path constraint functions can be characterized. Then the traditional trajectory optimization problem is transformed and solved by pseudospectral method. A Mars entry navigation scenario is considered and the entry trajectory is optimized. Simulation results demonstrate the efficiency and accuracy of the proposed method. Meanwhile, the accuracy of polynomial chaos and linearization approaches is also discussed. It is concluded that the proposed robust trajectory optimization method is more suitable for the scenario design of Mars atmospheric entry. © 2016, (publisher). All rights reserved. Source

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