Many concepts for future robotic Mars lander missions require landing heavier payloads than those landed to date. Mars lander architectures to date have relied on a parachute to help slow the lander; however, the effectiveness of a parachute in the thin Martian atmosphere is diminished with heavier payloads unless the diameter of the parachute is increased or it is deployed at a higher Mach number, both of which are significant technical challenges. In addition, the parachute can be successfully deployed only within a specific Mach number and dynamic pressure range. Targeting the entry trajectory to hit this "Mach-Q box" imposes constraints on the entry ballistic coefficient, limiting it to similar to 150-200 kg/m(boolean AND)2. Eliminating the parachute from the design requires descent engine ignition at supersonic speeds (Supersonic Retropropulsion, or SRP). SRP increases the propellant requirement, but also allows entry ballistic coefficients of similar to 600 kg/m(boolean AND)2 or more, with the consequence of significantly increased entry mass and landed payload mass.

A feasibility study was conducted to investigate the potential performance advantages of Supersonic Retro-Propulsion in support of future high-mass Mars robotic landing missions. A notional reference architecture for a potential future Mars Sample Return formed the basis for assuming a 4.7 m diameter SRP entry vehicle containing the Mars Ascent Vehicle element. Configuration analysis was conducted to ensure that the payload and required SRP components (including engines and propellant) fit within in the capsule volume. Optimized trajectory analysis highlighted several key performance sensitivities of SRP for ballistic coefficients of 150, 300, and 450 kg/m2. These results indicated a broad SRP ignition envelope (1-4 km altitude, 300-750 m/s velocity), as well as relatively small propellant mass fraction sensitivities to SRP thrust/weight, landing site elevation, and the application of a 4-g entry deceleration constraint (relevant for future crewed mission trajectories). Finally, mass-sizing was performed to assess sensitivities to ballistic coefficient and entry velocity, and showcased the ability of the SRP system to land payload masses on the order of twice that of MSL.

We present the JUpiter MagnetosPheric boundary ExploreR, JUMPER, a Jupiter orbiting SmallSat mission concept to explore the planet's upstream solar wind environment and magnetospheric boundaries and measure the energetic neutral atom (ENA) emissions from its space environment. JUMPER's instrument payload consists of a plasma sensor, a magnetometer, and a neutral atom imager. Measurements from these instruments will complement simultaneous observations of Jupiter's magnetosphere, radio emissions, and/or aurora from a Jupiter orbiting spacecraft (e.g. Europa Clipper, Io Observer, JOLT) and/or Earth-based observatories, providing simultaneous, multi-point observations to study the dynamics of this system. JUMPER's science objectives drive several top-level requirements on mission design. The most important is an orbit that extends beyond Jupiter's bow shock and magnetopause on the planet's dayside. Mission design is also constrained by the necessity to ride share on a primary vehicle, preferably until after Jupiter orbit insertion. The JUMPER spacecraft design derives heritage from SmallSats developed for Southwest Research Institute (SwRI)-led missions such as those on the Cyclone Global Navigation Satellite System (CYGNSS) mission. The spacecraft design consists of a frame supporting four triple-deployed solar array panels, a propulsion system, and three science instruments positioned to accommodate their field-of-views (FOVs). Embedded within the frame is an radiation vault that will house a majority of the electronics for the spacecraft avionics and payload subsystems. The spacecraft consists of 5 systems: 1) Mechanical, Structural and Thermal (MST) 2) Flight Avionics System (FAS), 3) Electrical Power System (EPS), 4) Communication and Data System (CDS), and 5) Hydrazine Propulsion System (OPS). JUMPER was funded for full mission concept development through NASA's Planetary Science Deep Space SmallSat Studies (PSDS3) program. This paper describes some of the concept study results.

Nguyen Xuan Vinh (born January 1930 in Yen Bai, Vietnam) is a noted Vietnamese-American aerospace scientist and educator whose seminal work on the guidance, dynamics and optimal control of space vehicles and their interaction with the atmosphere has played a fundamental role in space exploration. Vinh is Professor Emeritus of Aerospace Engineering at the University of Michigan, where he taught for nearly thirty years. Among his many publications was "Hypersonic and Planetary Entry Flight Mechanics" (1980. Vinh, N. X.; Busemann, A.; Culp, R. D. University of Michigan Press) which contains equations for hypersonic flight that came to be known as "the Vinh equations."

Over the last 15 years, NanoSpacecraft have grown remarkably in capability while early technical demonstrations utilized passive magnetic control, or tumbled freely, today's CubeSats are able to maintain 3-axis stabilization, point precisely, and even perform propulsive maneuvers. In this paper a brief discussion of current attitude determination and control capabilities is provided, as well as the possibilities for small spacecraft to maneuver. One mission taking advantage of these capabilities is MarCO (Mars Cube One), which will independently cruise to Mars in support of the InSight mission. Here we provide some description of the mission as they relate to GNC.

The Lander Vision System (LVS) is a tightly integrated bolt-on smart sensor system that provides real-time terrain relative position, velocity, attitude and altitude while also detecting landing hazards. The LVS can increase access to scientifically rich landing sites and is a low mass, volume and cost alternative to radar-based landing sensors. The LVS hardware fuses measurements from a visible camera, flash lidar and inertial measurement unit using a terrain relative navigation filter operating on a high performance compute element. This paper describes the design of an LVS prototype created from commercial components with a path to flight implementation and describes initial terrain relative navigation results produced on the computing hardware.

G-FOLD, Guidance for Fuel Optimal Large Divert, is an algorithm that is developed to compute, onboard in real-time, fuel optimal trajectories for large divert maneuvers necessary for planetary pinpoint or precision landing. The algorithm incorporates all relevant mission constraints and computes the global optimal trajectory. It is based on a mathematical result known as "lossless convexification" of the associated optimal control problem, which allowed us to formulate the problem as a convex optimization problem and to guarantee obtaining the global optimal solution when a feasible solution exists. Hence the algorithm ensures that all physically achievable diverts are also computable in real-time. This paper reports the first three flight test results of G-FOLD generated trajectories. The goal of these tests were to test pre-flight computed G-FOLD trajectories to demonstrate that they are computed with relevant mission constraints and appropriate vehicle dynamics accounted for. The results showed good agreement with the desired ideal trajectories with mismatches below expected bounds, which validated that the desired outcome that the trajectories were computed by using the right problem description and the resulting trajectories are flyable.

A next-generation Mars landing goal is precise and safe landing with less than 1 km uncertainty to reach targets of scientific interest within hazardous terrain. This goal can be achieved by enhancing the SkyCrane Entry, Descent and Landing (EDL) architecture debuted successfully by the Mars Science Laboratory [1], by adding: (i) Terrain Relative Navigation (TRN) during the parachute phase to determine the vehicle position and attitude relative to the landing site; (ii) capability to maneuver the spacecraft to reach the exact target site, requiring a course correction of multiple kilometers during the powered descent phase; and (iii) Hazard Detection and Avoidance (HDA) in the landing area [2]. JPL is developing key technologies to enable such landings at Mars, including Guidance for Fuel-Optimal Large Divert (G-FOLD) [3][4], a trajectory optimizer suitable for on-board execution, and the Mars Lander Vision System (LVS) [5] for TRN and hazard detection. Reliable operation at Mars necessitates earth-based, end-to-end closed loop testing of these technologies as an integrated system. ADAPT (Autonomous Ascent and Descent Powered-Flight Testbed) is a testbed for this purpose. In ADAPT, JPL Mars Lander Vision System and a payload computer will be integrated into the Xombie vehicle built by Masten Space Systems, Inc. In flight, the JPL payload will perform TRN, and execute G-FOLD [6] to calculate a fuel-optimal trajectory to the landing site. The Xombie vehicle will follow the trajectory to the landing site. System engineering is performed collaboratively by JPL and Masten Space Systems, Inc. We began ADAPT development by first flying with Xombie three Mars-representative large-divert trajectories generated before launch using G-FOLD. This first phase was highly successful. The Xombie vehicle diverted 750-m laterally during descent from 500-m initial altitude with high precision and set a new record for the lateral flight distance performed by a vertical-take-off-vertical-landing vehicle, and set new altitude and distance records for Xombie vehicle. In upcoming flights, we will continue to add features to the testbed and demonstrate a fully autonomous Mars-like precise and safe landing with TRN, G-FOLD and HDA. This paper details the ADAPT testbed design and the planned set of experiments.

Prior to Mars Science Laboratory (MSL), Mars landers flew ballistic entry trajectories. Improvements in landing accuracy (from ~150 km from the target for Mars Pathfinder to ~30-40 km for Mars Exploration Rover and Phoenix) were solely due to improved approach navigation. MSL will fly the first guided-entry trajectory to Mars, further improving accuracy to ~10-12 km from the target by modifying the trajectory in the atmosphere using a lift created by slightly offsetting the vehicle center-of-mass. EDL systems of future Mars lander missions are likely to substantially resemble MSL to maximize heritage and minimize cost. Further improvements in landing accuracy are desired for these missions, motivating an investigation into improvements in landing accuracy with minimal impact to the MSL EDL system architecture.

The Stardust-NExT (New Exploration of Tempel) mission, a follow-on to the Stardust prime mission, successfully completed a flyby of comet Tempel-1 on 2/14/11. However there were many challenges along the way, most significantly low propellant margin and detection of the comet in imagery later than anticipated. These challenges and their ramifications forced the project to respond with flexibility and ingenuity. As a result, the flyby at an altitude of 178 km was nearly flawless, accomplishing all its science objectives. Lessons learned on Stardust-NExT may have relevance to other spacecraft missions.

Mars landers to date have flown ballistic entry trajectories with no trajectory control after the final maneuver before entry. 12Improvements in landing accuracies (from ~150 km from the target for Mars Pathfinder to ~30-40 km for MER and Phoenix) have been driven by approach navigation improvements. MSL will fly the first guided-entry trajectory to Mars, further improving accuracy to ~10-12 km from the target. For future missions, landing within ~100m is desired to assure landing safety close to a target of high scientific interest in irregular terrain, or to land near a previously landed asset. Improvements in approach navigation alone are not sufficient to achieve this requirement. If approach navigation error and IMU error are eliminated, the dominant error source is wind drift on the parachute, with map-tie error also significant. Correcting these errors requires terrain-relative navigation (TRN), which can be accomplished with passive imaging supplemented by radar for terrain sensing (with onboard navigation capable of processing measurements from IMU, imaging, and radar). Additionally, near-optimal-ΔV powered descent guidance is needed to minimize the amount of propellant required to reach the target. The capability to land within 100m can be applied in different landing modes depending on how much fuel is carried.

The PDG (Powered Descent Guidance) algorithm provides a numerical method for onboard generation of guidance profiles for use during the powered-descent phase of Mars pinpoint or precision landing. The algorithm incorporates both state and control constraints, including minimum and maximum thrust limits, glideslope constraints to avoid impacting the surface, and speed and attitude constraints. These constraints are particularly important for powered-descent scenarios requiring large-divert capabilities to achieve pinpoint or precision landing. Additionally, the constraints ensure that guidance profiles are physically achievable. For instance, the thrust limits are particularly relevant for spacecraft that implement rocket engines that cannot be throttled off after ignition. The formulation of PDG poses the problem as a SoCP (Second-order Cone Program) that can be solved with numerically-efficient interior-point solvers in a finite time to within a prescribed accuracy. This feature is ideal for onboard implementation during powered descent where total flight time is short, thus guidance methods must guarantee convergence to an achievable solution within a short time. If a spacecraft can physically perform maneuvers to achieve pinpoint or precision landing (i.e., the problem is feasible), then the SoCP formulation of PDG will find the solution. Further, this solution will satisfy the prescribed constraints on position, fuel, thrust, speed and attitude.

Ground-based optical navigation (OpNav) using pictures taken by the Naviga-tion camera on the Stardust spacecraft provided the target-relative information needed to design maneuvers during its approach to comet Tempel 1. Hardware problems, limited downlink bandwidth, and changes in the flight profile affected the OpNav picture schedule, sometimes in near-real time. The Stardust naviga-tion camera and attitude control presented challenges. Picture-processing techniques were developed during approach that included background estimation, co-addition, and co-registration. These techniques, along with adaptive picture scheduling, successfully addressed the challenges.

This paper presents trajectory reconstruction of the ST-9 (space technology) sounding rocket experiment using the onboard inertial measurement unit data and descent imagery. The raw inertial measurement unit accelerometer measurements are first converted into inertial acceleration and then used in trajectory integration. The descent images are preprocessed using a map-matching algorithm and unique landmarks for each image are created. Using the converted inertial measurement unit data and descent images, the result from dead-reckoning and the kinematic-fix approaches are first compared with the global positioning system measurements. Then, both the inertial measurement unit data and landmarks are processed together using a batch least-squares filter and the position, velocity, stochastic acceleration, and camera orientation of each image are estimated. The reconstructed trajectory is compared with the global positioning system data and the corresponding formal uncertainties are presented. The result shows that inertial measurement unit data and descent images processed with a batch filter algorithm provide the trajectory accuracy required for pinpoint landing.