Advanced navigation algorithms for precision landing

A detailed analysis of autonomous navigation algorithms to achieve autonomous precision landing is presented. The problem of integrated attitude determination and inertial navigation is solved. The theoretical results are applied and tested in three different applications. Optimality conditions for constrained quaternion estimation using the Kalman filter are derived. It is common in spacecraft applications to separate the attitude determination from the inertial navigation system. While this approach has worked in the past, it inevitably degrades the navigation performance when the correlations between the two systems are not correctly accounted for. It is shown how to optimally include an attitude determination algorithm into the Kalman filter. When the conditions to achieve optimality are not met, it is shown how to achieve sub-optimality by properly accounting for the correlation. The traditional approach to inertial navigation is to employ the inertial measurement unit (IMU) outputs to propagate the estimated states forward in time, rather then use them to update the state. A detailed covariance analysis of deadreckoning Mars entry navigation is performed. The contribution of various sources of IMU errors are explicitly accounted for and the filter performance is validated through Monte Carlo analysis. The drawback of dead-reckoning is that this approach prevents the inertial measurements from reducing the uncertainty of the estimated states. While this shortcoming can be compensated by the availability of other measurements, it becomes crucial when the IMU is the only sensor to provide measurements. Such a situation arises, for example, during Mars atmospheric entry. In the second application of this work, IMU measurements from a NASA mission are processed in an extended Kalman filter, and the results are compared to dead-reckoning. It is shown that is possible to reduce the uncertainty of the inertial states by filtering the IMU. The final application is lunar descent to landing navigation. In this example the IMU is filtered and the algorithms to include an attitude estimate into the Kalman filter are tested. The design performance is confirmed by Monte Carlo analysis.Aerospace Engineering and Engineering Mechanic

Robust preliminary design for multiple gravity assist spacecraft trajectories

The development of a new spacecraft trajectory design method most often occurs because a particular capability does not exist. The invention is usually considered successful so long as it is capable of producing solutions to the problem in question, and thus satisfies a particular design requirement, or is mathematically elegant. When innovation favors the latter to the exclusion of the former, the interoperability of the new method with existent techniques, and the utility of the method in the context of the overall mission design process, from concept to fight operations, is not always realized. The concepts introduced and developed throughout this work respond to specific preliminary mission design needs, but their development is also focused on maintaining, or improving, trajectory design work flow compatibility and efficiency. The techniques described address specific contributions to the multiple gravity assist trajectory optimization state-of-the-art, however, each one is also an important component of a modern trajectory design paradigm and is valuable for its ability to be integrated with and streamline that process as a whole. The bounded-impulse approximation is a widely used method for early stage trajectory design for low and high thrust vehicles. Many previous studies involving this method of design have focused on developing new or improved trajectory transcriptions. This dissertation introduces analytic techniques for calculating the Jacobian matrix for two existing bounded-impulse trajectory models. The calculations allow for the use of a smooth spacecraft power model. One such model is introduced that handles multiple thruster on-off events and a variety of logic programs. A smooth spline-based ephemeris system is also discussed that is compatible with the analytic Jacobian formulae. Mission design activities associated with the NASA New Frontiers 4 proposal call identified a particular shortcoming of the popular Sims-Flanagan bounded-impulse model, namely that its control nodes are distributed equally in time, clustering them at apoapsis for eccentric transfers, which reduces the control authority at periapsis. In response to this, a partially regularized bounded-impulse model is introduced that distributes control nodes equally at both apses. The new transcription is capable of delivering the same mass to the target as a trajectory modeled using Sims-Flanagan, but requires far fewer control segments in the trajectory discretization to do so. A bounded-impulse trajectory is usually sufficient to generate a first order (or better) estimate of a mission's mass budget, however, these low-fidelity models can prove problematic to converge inside a flight-fidelity design tool that models fi nite-burn arcs. Low-thrust trajectories in particular suffer from this issue due to the extended period of time that the thruster operates. Analytic partial derivative computations are introduced in this work that enable the replacement of bounded-impulse maneuvers and Keplerian propagation with numerical integration arcs without reducing the runtime performance such that the model becomes unusable for preliminary design tasks. These calculations are also compatible with a smooth electric power model and accommodate final time free problems. The resulting trajectory is shown to be sufficiently accurate such that the flight heritage tool MIRAGE can track it within acceptable error limits placed on the spacecraft's state vector. Finally, improvements that this thesis makes to bounded-impulse trajectory models are leveraged to solve a challenging planetary satellite tour design problem. The robustness improvements that the analytic Jacobian formulae afford the trajectory transcription, are combined with a parallelized flyby tree path finding algorithm to produce a design framework capable of autonomously optimizing a moon tour mission similar to Galileo from launch through tour end using two-body dynamics

Alignment filtering of ICESat flight data

textICESat consisted of the Geoscience Laser Altimeter System (GLAS) and a commercial spacecraft bus. The stability of the GLAS to bus alignment was unknown and significant for GLAS pointing. Pointing control was performed by the bus, and variations of the GLAS alignment were effectively pointing control errors. There were four star trackers making measurements sensitive to this alignment, two on GLAS and two on the bus. Tracker pointing variations during samples from seven years of flight data were estimated using an alignment filter. The states of an alignment filter represent multiple independent attitudes, enabling the fusion of measurements from an arbitrary number of trackers and gyro units. The ICESat alignment filter states were equivalent to four tracker pointing vectors, expressed in both the body and celestial frames. Together with a star catalog, the four pointing vectors were equivalent to predictions of the tracker measurements. The stars provided nearly ideal reference points, but filter performance was improved by detecting and handling deterministic star errors. The primary result was evidence for relatively large pointing variations of the two GLAS trackers, on the order of fifty arcseconds, with both periodic orbital variations and trends on long time scales. There was also evidence of correlations between the variations of the two GLAS trackers, suggesting that they reflected GLAS to bus alignment variations.Aerospace Engineerin