Fast solver for J2-perturbed Lambert problem using deep neural network

@article{Yang2021FastSF,
  title={Fast solver for J2-perturbed Lambert problem using deep neural network},
  author={Bin Yang and Shuang-quing Li and Jinglang Feng and Massimiliano Vasile},
  journal={ArXiv},
  year={2021},
  volume={abs/2201.02942}
}
This paper presents a novel and fast solver for the J2-perturbed Lambert problem. The solver consists of an intelligent initial guess generator combined with a differential correction procedure. The intelligent initial guess generator is a deep neural network that is trained to correct the initial velocity vector coming from the solution of the unperturbed Lambert problem. The differential correction module takes the initial guess and uses a forward shooting procedure to further update the… 
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References

SHOWING 1-10 OF 29 REFERENCES
Multiple Revolution Solutions for the Perturbed Lambert Problem using the Method of Particular Solutions and Picard Iteration
TLDR
This study reveals that solving the perturbed Lambert’s problem using the method of particular solutions with modified Chebyshev-Picard iteration is about an order of magnitude faster compared with the classical shooting method and a tenth-twelfth order Runge-Kutta integrator.
On the solution to every Lambert problem
  • R. Russell
  • Computer Science
    Celestial Mechanics and Dynamical Astronomy
  • 2019
TLDR
A concise, improved vercosine formulation of the Lambert problem is presented, including new singularity-free and precision-saving equations and the 2D interpolation scheme stands to benefit all Lambert problem formulations.
New Solutions for the Perturbed Lambert Problem Using Regularization and Picard Iteration
A new approach for solving two-point boundary value problems and initial value problems using the Kustaanheimo–Stiefel transformation and Modified Chebyshev–Picard iteration is presented. The first
Partial Derivatives of the Solution to the Lambert Boundary Value Problem
Two methods for deriving first-order partial derivatives of the outputs with respect to the inputs of the Lambert boundary value problem are presented. The first method assumes the Lambert problem is
Higher Order Algorithm for Solving Lambert’s Problem
This work presents a high-order perturbation expansion method for solving Lambert’s problem. The necessary condition for the problem is defined by a fourth-order Taylor expansion of the terminal
Real-Time Optimal Control for Spacecraft Orbit Transfer via Multiscale Deep Neural Networks
TLDR
A real-time optimal control approach is proposed using deep learning technologies to obtain minimum-time trajectories of solar sail spacecraft for orbit transfer missions and three deep neural networks are designed and trained offline by the obtained optimal solutions to generate the guidance commands in real time during flight.
Homotopic Perturbed Lambert Algorithm for Long-Duration Rendezvous Optimization
L AMBERT’s problem has been discussed over the years bymany researchers [1–3]. Gauss [1] first developed an iterative method to solve Lambert’s problem, which is efficient and converges rapidly for
Regularized Integration of Gravity-Perturbed Trajectories-A Numerical Efficiency Study
NINE methods for predicting the motion of a particle in a perturbed gravity field, many of which are based upon regularizing transformations and some of which are newly developed, are numerically
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