Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technique

Nanjing, China

Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technique

Nanjing, China
SEARCH FILTERS
Time filter
Source Type

Chen H.,Nanjing Southeast University | Chen H.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technique | Chen H.,Henan University of Technology | Cheng X.,Nanjing Southeast University | And 4 more authors.
Signal Processing | Year: 2015

In this paper, the authors analyze the stochastic stability of the H∞ Sparse-grid Quadrature Kalman Filtering (H∞-SGQKF) used in nonlinear stochastic discrete-time systems with nonlinear state dynamic equation and nonlinear transition function. Using some standard results from estimation accuracy level of multidimensional sparse-grid theories as well as stochastic stability theories, we have developed the robust stability of nonlinear SGQKF under stochastic uncertainties. It is shown that estimation errors remain bounded if the system satisfies sufficient conditions, and that it is possible to improve stochastic stability by increasing system noise covariance matrixes, adjusting the noise robustness parameter γ and demonstrating the lower bound of noise robustness parameter. Finally, the H∞-SGQKF is applied to the design of Near-space hypersonic vehicle transfer alignment. The numerical simulation of the designed filter validates the effectiveness of the proposed filtering stochastic stability. © 2015 Elsevier B.V. All rights reserved.


Chen H.,Henan University of Technology | Chen H.,Nanjing Southeast University | Chen H.,Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technique | Cheng X.,Nanjing Southeast University | And 3 more authors.
2016 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2016 | Year: 2016

In the initialization process of the strapdown initial navigation system (SINS) of a launched weapon before its release, transfer alignment (TA) uses the data from the aircraft SINS or other navigation aids. However, stochastic measurement aid information is unreliable in practical integrated navigation system. The paper is the filtering stability for a class of nonlinear stochastic systems with intermittent measurements when the arrival of the observations is described by Bernoulli independent and identically distributed process. The stochastic stability of the a novel Gaussian filter through presenting Gaussian approximate about one step posterior predictive probability density function (PDF) of the state and intermittent measurements is investigated. The estimation errors remain bounded if the system satisfies some sufficient conditions, and its error covariance matrices are statistically convergent by providing the existence of a super-threshold value for the intermittent measurement probability. Finally, a nonlinear integrated navigation method based on the proposed filter is presented, and the ground vehicle test of missile-board SINS is given to illustrate the effectiveness of the investigated techniques. © 2016 IEEE.

Loading Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technique collaborators
Loading Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technique collaborators