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Aas 19-725 Improved Atmospheric Estimation for Aerocapture Guidance

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Aas 19-725 Improved Atmospheric Estimation for Aerocapture Guidance AAS 19-725 IMPROVED ATMOSPHERIC ESTIMATION FOR AEROCAPTURE GUIDANCE Evan Roelke,∗ Phil D. Hattis,y and R.D. Braunz Increased interest in Lunar or Mars-sample return missions encourages considera- tion of innovative orbital operations such as aerocapture, which generally provides significant mass-savings for orbital insertion at Earth or Mars. Drag modulation architectures offer a straightforward approach to orbital apoapsis targeting by en- abling ballistic entry, among other benefits. A shortcoming of these architectures is the poor estimation of atmospheric density resulting in target apoapsis altitude errors. This research seeks to assess and improve upon current atmospheric den- sity estimation techniques in order to support the flight viability of discrete event drag modulated aerocapture. Three different estimation techniques are assessed in terms of estimation error and apoapsis altitude error: a static density factor, a density array interpolator, and an ensemble correlation filter. The density inter- polator achieves a 5% improvement in median apoapsis altitude over the density factor when entering at −5:9◦ and targeting a 2000km apoapsis altitude, while the ensemble correlation filter achieves a 7% improvement under identical simulation conditions. The ensemble correlation filter was found to improve with decreasing density search tolerance, achieving a 4:6% improvement in median apoapsis alti- tude for a tolerance of 1% over 5%. These improvements are dependent on entry and vehicle parameters and improve as the entry angle becomes more shallow or the target apoapsis is reduced. Errors in the density factor measurements are main contributors to the error in estimated versus true density profiles. INTRODUCTION The revitalized interest in Lunar missions as well as the drive for Mars sample-return missions in recent years encourages innovative solutions to orbital operations. One such innovation is aero- capture, which falls under the realm of aeroassist maneuvers. Aerocapture is a re-entry maneuver in which a spacecraft flies through the upper atmosphere of a planetary body from an inbound hyperbolic trajectory in order to capture into a closed orbit about the central body by means of at- mospheric deceleration.1,2 Although it has yet to be flight-proven, aerocapture has been shown to provide significant mass savings for orbital insertion. A cost-benefit analysis of aerocapture mission sets shows that this maneuver can provide mass savings of up to 15% for low-altitude orbit missions to Mars.3 Aerocapture Guidance In order to mitigate error from uncertainty in the atmospheric density, entry state, and other parameters, an active GNC system is required. Lift modulation architectures have typically been ∗Draper Laboratory Fellow, The Charles Stark Draper Laboratory, Inc. Graduate Research Assistant, Entry systems Design Lab, Colorado Center for Astrodynamics Research, 1111 Engineering Drive, Boulder, CO 80309 yThe Charles Stark Draper Laboratory Inc., 555 Technology Square, Cambridge, MA 02139 zSmead Professor of Space Technology, Dean of Engineering and Applied Science, 1111 Engineering Drive, Boulder, CO 80309 1 studied due to their flight heritage.2,4,5 These systems utilize a reaction control system (RCS) thruster framework to alter the vehicle’s bank angle, and consequently lift vector direction, to steer the vehicle through the atmosphere for range control.4,6 While flight-proven, these systems require ballast mass to enforce an off-centered center of gravity, allowing the vehicle to fly at an angle of attack (AOA) and, subsequently, with a non-zero lift force. In addition, the active bank modulation GNC algorithm is computationally intensive and prone to actuator latency.7 Drag modulation architectures offer a more straightforward re-entry architecture to lift modula- tion systems. Such systems negate the need for ballast mass, enabling the vehicle to fly in a ballistic configuration, or at an AOA of zero. These systems instead provide a control event by modifying the vehicle’s ballistic coefficient, defined in Equation1. This modification is typically performed by jettisoning a rigid drag skirt or ballute to modify the vehicle mass and reference area mid-flight.8–10 m β = (1) cDAref Changing the vehicle’s ballistic coefficient ultimately affects its energy loss rate due to atmo- spheric drag, enabling these systems to target a specific orbital energy, or geometry, based on the time and location of the jettison event during the atmospheric trajectory.9, 11 Such architectures are ideal candidates for innovative re-entry systems; the removal of propellant, propellant tanks, and ballast mass simplify the packaging in addition to providing mass savings beyond the benefit of aerocapture itself.7 Additionally, the aforementioned reduction in GNC complexity by requiring only discrete control events as opposed to continuous control reduces the risk of failure. Finally, reduction in uncertainty of flight parameters and flow field interaction are reduced with a ballistic configuration.7,8 This research is concerned with the performance of a discrete, rigid drag-skirt jettison event, de- tailed in Figure1, at Earth. The control authority allotted to the spacecraft in this event is measured by the ratio of β2 , where β refers to the ballistic coefficient of the vehicle after separation, and β β1 2 1 refers to the value before separation. Figure 1: Diagram of Discrete-Event, Drag Modulation Aerocapture with a Rigid Drag Skirt Jettison Event9 The control authority of the spacecraft affects how well the spacecraft can mitigate against at- mospheric uncertainties. If the entry conditions are off nominal and/or the atmospheric density significantly perturbed, the GNC system can adjust its jettison time to reflect these changes in order to alter the total energy lost throughout the trajectory. In doing so, the spacecraft can target a spe- cific orbit, typically by means of an orbital apoapsis altitude. Of course, errors in the jettison time due to guidance system biasing, atmospheric uncertainties, or other uncertainties can result in large apoapsis errors, surface impacts, or failure to enclose the resulting orbit in extreme cases.9 2 Atmospheric Variations There are several sources of atmospheric uncertainty in the density, temperature, pressure, and wind profiles. Solar heating causes numerous secondary perturbing effects such as geomagnetic storms, atmospheric tides by surface heating, and gravity waves resulting from jet stream shear.12, 13 The periodicity of these atmospheric disturbances ranges between short scale, primarily due to atmospheric turbulence, and seasonal up to quasi-biennial scales.14 Fortunately, the time scale of an aerocapture trajectory is small, meaning that the longer time scale perturbations are effectively held constant throughout the aerocapture trajectory. The primary sources of atmospheric uncertainty then lie with diurnal (daily) and semi-diurnal perturbations, including solar heating, geomagnetic fluctuations, gravity waves, planetary waves, and atmospheric tides. In this investigation, we will focus on accurate estimation of atmospheric density. Solar Heating. Solar heating directly affects parameters such as the geomagnetic index, and heats up water vapor in the troposphere and stratosphere, resulting in density perturbations through atmospheric tides. Many of the perturbations resulting from solar heating can be characterized by a diurnal or semi-diurnal period, making them significant to re-entry guidance atmospheric mod- els.12 The correlation between solar heating and density perturbations can also be recognized as a correlation between atmospheric temperature and density. Geomagnetism. Geomagnetism typically has low impact on the atmospheric density, particu- larly below the Thermosphere. However, geomagnetic storms due to increased solar wind pressure may influence the atmospheric density distribution, especially at lower latitudes.15 A Disturbance Storm Time (Dst) index is used to quantify the severity of the geomagnetic storm. Dst > −75nT causes minimal density disturbances, while a severe geomagnetic storm can result in a Dst of less than −200nT .15 Again, these disturbances primarily affect the Thermosphere density distribution, limiting the overall perturbations on an aerocapture trajectory. Planetary Waves. Wave patterns in the atmosphere characterized mainly as gravity waves, at- mospheric tides, and planetary waves can add both small and large-scale fluctuations in the atmo- spheric density (and other parameters).16 Planetary waves, also referred to as Rossby waves, are caused by planetary rotation, having periods of several days and are modeled as a cosine function in EarthGRAM.12 On the other hand, atmospheric tides and gravity waves produce shorter time scale perturbations due to jet stream shear or surface heating due to solar radiation. Atmospheric tide variations have also been observed to intensify with altitude, resulting in larger variations at aerocapture altitude/density ranges.12 The small-scale perturbations such as gravity waves and gen- eral atmospheric turbulence are highly irregular in nature, and must be modeled with the stochastic approach of Equation 2b. Atmospheric Modeling Earth Global Reference Atmosphere Model (EarthGRAM) is used to simulate atmospheric pa- rameters as functions of altitude. Developed at NASA Marshall Spaceflight Center, EarthGRAM pulls data from numerous data sources and empirical models over various altitude ranges such as the Marshall Thermosphere Model (MET), Jacchia
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