Engineering topics

David Geller

Publications and source records attributed to David Geller.

6 records

NASA NTRS2025

Generalized Reference Targeting for Spaceflight

For spaceflight programs to achieve some of the aggressive exploration initiatives such as visiting and landing on other celestial bodies, rendezvousing with other orbiting vehicles, and ultimately returning crew safely to Earth, an assortment of targeting algorithms to compute the necessary burns to strategically maneuver a spacecraft to a variety of destinations are required. Numerous examples exist, but rather than creating and implementing multiple targeting solutions, is it possible to have a general targeting model that can accommodate a variety of applications? Originally motivated for mission design and analysis purposes, this paper outlines a generalized reference targeting algorithm for spaceflight that may also have applications in on-orbit flight software. It accommodates arbitrary flight dynamics and both impulsive and finite burns for either absolute or relative targeting applications. It also allows for an arbitrary number of targeting design parameters such as multiple discrete correction burns or finite thrust parameters to satisfy numerous combinations of targeting constraints that can have fixed or variable time epochs. Given a reference trajectory, this targeting technique provides a general framework to quickly solve an assortment of targeting problems that may be well-defined, over-determined, or under-determined while naturally producing metrics providing insight into the controllability for a given problem formulation. Due to the derivation, speed, and accuracy of the algorithm, it lends to supporting rapid linear covariance analysis and robust trajectory design applications for a variety of flight phases such as rendezvous and docking, cislunar transfer, interplanetary flight, orbit maintenance, de-orbit, and powered descent and landing.

Targeting↗

NASA NTRSDate not supplied

Robust Cislunar Trajectory Optimization Via Midcourse Correction and Optical Navigation Scheduling

This paper presents a new approach to optimal trajectory design that considers uncertainties in the system, referred to herein as robust trajectory optimization. This approach assumes an existing reference trajectory and optimizes the locations of midcourse correction burns and utilization of onboard navigation sensors to minimize dispersions in ∆v or final position. Navigation errors, maneuver execution errors, orbit insertion errors, and environmental modeling errors are considered. The application in this paper is cislunar flight with the goal of injecting into a Near-Rectilinear Halo Orbit for rendezvous with a target vehicle. Two complementary optimization problems are proposed. One problem minimizes the total ∆v dispersion subject to a final position dispersion constraint. The other problem minimizes the final position dispersion subject to a total ∆v dispersion constraint. The results from each optimization problem are shown for a complete mission profile.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

Robust Trajectory Optimization and GN&C Performance Analysis for NRHO Rendezvous

This paper evaluates several candidate Near-Rectilinear Halo Orbits (NRHO) rendezvous trajectory designs using linear covariance (LinCov) analysis and determines the optimal locations for NRHO rendezvous translational maneuver locations. The performance of several candidate relative trajectory designs are determined as a function of relative navigation accuracy (angles only), inertial optical navigation (OpNav), range observability maneuvers, maneuver execution errors, relative maneuver targeting, and environment uncertainties. Further, the optimal locations of rendezvous maneuvers are determined for each of the candidate reference trajectories. The long-term goal of this research is to utilize LinCov and a genetic optimization algorithm (GA) to determine a complete end-to-end optimal NRHO trajectory design that is robust to navigation errors, maneuver execution errors, and environment uncertainties. This paper represents a first step toward this goal. Three candidate rendezvous trajectories with varying numbers of range-observability maneuvers are evaluated for their robustness to uncertainties, errors, and total trajectory correction delta-v performance. Some key elements of this analysis include relative navigation performance in an NRHO, relative trajectory dispersion performance, and total 3-sigma delta-v performance. This development provides the foundation to then determine an optimal and robust end-to-end NRHO rendezvous trajectory, including the determination of the optimal locations of range observability maneuvers, if needed.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

Sensitivity of Optimal Midcourse Correction Scheduling for Robust Cislunar Trajectory Design

A new approach to optimal trajectory design is the determination of optimal trajectories that are robust to initial trajectory dispersions, navigation errors, maneuver execution errors, and environment modeling errors. This paper investigates the sensitivity of cislunar robust optimal trajectory design to launch date, duration of navigation measurement passes, and navigation measurement frequency. For a given cislunar trajectory from translunar injection (TLI) to lunar orbit insertion (LOI), the optimal locations of midcourse corrections, also known as trajectory correction maneuvers (TCM) are determined by minimizing the final 3-σ ∆v subject to a final 3-σ position dispersion constraint for a given launch date, specified measurement pass duration prior to each maneuver, and measurement frequency. Optical navigation (OpNav) is assumed, and OpNav field-of-view (FOV) and lighting constraints are employed. These constraints turn out to be important elements of the problem. The sensitivity of the optimal TCM locations are then investigated by varying the launch date, duration of OpNav measurement passes, and the OpNav measurement frequency, and then re-optimizing the locations of the TCMs. Given the problem parameters provided herein, results show that while the optimal TCM locations with respect to TLI vary greatly from one launch date to another, their locations with respect to LOI are nearly invariant over a 2-month launch window. Results also show that in all cases the optimal location of the last TCM is found to be at the point where the OpNav lunar FOV constraint is first violated. For all other TCMs, OpNav measurement pass duration and measurement frequency can have a moderate to large affect on the optimal TCM locations.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

Generalized Linear Targeting For Cislunar Flight

An important element of Artemis and NASA’s campaign to explore the Moon is the autonomous onboard two-level targeter (TLT) used during all cislunar flight phases. The function of the TLT is to autonomously recompute the burn targets for the upcoming burn (or multiple burns) in response to navigation and vehicle dispersion providing a solution that meets all of the trajectory constraints. Although the TLT has been utilized previously as a ground-based planning tool, and flown onboard during the Artemis I mission, it’s complexity and iterative nature make is difficult to incorporate into and support rapid analyses such as robust optimal trajectory design applications where speed is essential. In this paper, a set of generalized linear targeting algorithms that mimics many of the properties of the TLT is derived. The generalized algorithms can handle single or multiple impulsive maneuvers, with multiple constraints at multiple fixed or variable times. A linear targeting algorithm for finite burn maneuvers is also derived. The generalized linear targeting algorithms are exceptionally fast and easy to implement in Monte Carlo analysis, linear covariance (LinCov) analysis, and robust optimal trajectory design. Several cislunar flight examples are provided.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

Generalized Augmented-State Covariance Analysis for Spaceflight

The use of linear covariance analysis techniques, also known as LinCov, has been used extensively for more than a half century for spaceflight applications. Originally, its primary purpose was to facilitate navigation analysis. For many past and current applications, the specific implementations only support navigation studies still. When the concept of an augmented-state linear covariance analysis approach was initially introduced that allowed for both navigation and trajectory dispersion analysis, the enhancement was motivated and primarily utilized to support navigation filter tuning and error budget analysis. Relatively few utilize this alternate augmented-state formulation of LinCov due to its additional complexity. The untapped potential of the augmented-state linear covariance analysis technique slowly unfolded in the past two-decades as its capability to rapidly and reliably capture the integrated closed-loop guidance, navigation, and control (GN&C) system performance became more apparent. Even with this dual purpose of generating insights to both navigation errors along with trajectory and delta-v dispersions, the core theoretical development had a heavy emphasis on the impacts of the navigation system and largely neglected the details of the actual guidance, targeting, and control systems. This paper extends the navigation-centric theoretical development by formulating a generalized augmented-state covariance analysis (GAUSCOV) technique that allows for the intricacies of a variety of targeting and control strategies along with ground planning and mission operations to be more formally included in assessing the impacts to spaceflight GN&C system performance.

Linear Covariance Analysis↗