Sparse Gauss-Hermite Quadrature Filter with Application to Spacecraft Attitude Estimation

By Bin Jia, Ming Xin, Yang Cheng. 2011

140 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Oceanography

View Paper: https://www.semanticscholar.org/paper/f8ef69e8a0731095a5f052caf9eabe8435875db7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Moriba K. Jah
2. Kyle J. Demars
3. Robert H. Bishop
4. Ming Xin
5. Bin Jia
6. Yang Cheng

In Artificial Intelligence

1. Moriba K. Jah
2. Kyle J. Demars
3. Robert H. Bishop
4. Ming Xin
5. Bin Jia
6. Yang Cheng

In Oceanography

1. Moriba K. Jah
2. Kyle J. Demars
3. Robert H. Bishop
4. Ming Xin
5. Bin Jia
6. Yang Cheng

Citations in the corpus

• Entropy-Based Approach for Uncertainty Propagation of Nonlinear Dynamical Systems (2013, methodology): “In fact, the approach is amenable to consideration of other pointbased methods, such as that of Sparse Gauss-Hermite Quadrature [28].”
• Probabilistic Initial Orbit Determination Using Gaussian Mixture Models (2013, methodology): “In fact, the approach is amenable to considerationof other pointbased methods, such as that of sparse Gauss–Hermite quadrature [16].”
• High-degree cubature Kalman filter (2013, background): “Theuse of high-degree cubature rules ismotivated by the fact that the attainable accuracy of the third-degree cubature rule and theUT aremarkedly lower than that of theGauss–Hermite quadrature (GHQ) rule in problems involving high nonlinearities and large uncertainties (Jia et al., 2011, 2012).”