Desensitized Optimal Filtering and Sensor Fusion Toolkit

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations

Flyby Geometry Optimization Tool

The Flyby Geometry Optimization Tool is a computer program for computing trajectories and trajectory-altering impulsive maneuvers for spacecraft used in radio relay of scientific data to Earth from an exploratory airplane flying in the atmosphere of Mars

Reconstruction of the Advanced Supersonic Parachute Inflation Research Experiment Sounding Rocket Flight Test

The Advanced Supersonic Parachute Inflation Research and Experiments project is a flight test program for development of supersonic parachutes for potential future use at Mars. The flight tests are designed to reduce risk for the Mars 2020 mission. The flight tests involve two Disk-Gap-Band parachute designs to be tested at relevant Mach number and dynamic pressure conditions for the Mars 2020 entry capsule. The first of these parachutes is a built-to-print design that was successfully employed by the Mars Science Laboratory lander at Mars in August 2012, and the second is a design that is strengthened in material properties and construction methods but has the same geometry as that used by Mars Science Laboratory. The first flight test of the built-to-print parachute took place on October 4, 2017 at NASA's Wallops Flight Facility. This paper describes the instrumentation, data analysis techniques, and atmospheric and trajectory reconstruction results from this flight test

Reconstruction of the Adaptable Deployable Entry and Placement Technology Sounding Rocket One Flight Test

The Adaptable Deployable Entry and Placement Technology Sounding Rocket One flight test is a demonstration experiment for deployable atmospheric decelerator technologies. The suborbital flight test occurred on 12 September 2018, at the White Sands Missile Range. Data from on-board and ground-based sensors were collected, from which the as-flown trajectory was reconstructed using an iterative extended Kalman filter-smoother. This paper describes the methodology, test vehicle instrumentation, and data analysis results from the flight test trajectory reconstruction

Mars Phoenix EDL Trajectory and Atmosphere Reconstruction Using NewSTEP

This document describes the trajectory and atmosphere reconstruction of the Mars Phoenix Entry, Descent, and Landing using the New Statistical Trajectory Estimation Program. The approach utilizes a Kalman filter to blend inertial measurement unit data with initial conditions and radar altimetry to obtain the inertial trajectory of the entry vehicle. The nominal aerodynamic database is then used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state. The reconstructed atmosphere pro le is then blended with pre-flight models to construct an estimate of the as-flown atmosphere

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms

Mars Science Laboratory Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

On August 5th 2012, The Mars Science Laboratory entry vehicle successfully entered Mars atmosphere and landed the Curiosity rover on its surface. A Kalman filter approach has been implemented to reconstruct the entry, descent, and landing trajectory based on all available data. The data sources considered in the Kalman filtering approach include the inertial measurement unit accelerations and angular rates, the terrain descent sensor, the measured landing site, orbit determination solutions for the initial conditions, and a new set of instrumentation for planetary entry reconstruction consisting of forebody pressure sensors, known as the Mars Entry Atmospheric Data System. These pressure measurements are unique for planetary entry, descent, and landing reconstruction as they enable a reconstruction of the freestream atmospheric conditions without any prior assumptions being made on the vehicle aerodynamics. Moreover, the processing of these pressure measurements in the Kalman filter approach enables the identification of atmospheric winds, which has not been accomplished in past planetary entry reconstructions. This separation of atmosphere and aerodynamics allows for aerodynamic model reconciliation and uncertainty quantification, which directly impacts future missions. This paper describes the mathematical formulation of the Kalman filtering approach, a summary of data sources and preprocessing activities, and results of the reconstruction

Aerodynamics for the ADEPT SR-1 Flight Experiment

Adaptable, Deployable, Entry, and Placement Technology (ADEPT) is a combination of a heatshield and an aerodynamic decelerator for atmospheric entry applications. The ADEPT Sounding Rocket (SR)-1 mission was a suborbital flight experiment of an 0.7 m-diameter ADEPT to verify system-level performance and to characterize dynamic stability behavior. The aerodynamic database for ADEPT SR-1 was constructed from non-continuum and continuum flowfield computations, along with data from recent ADEPT ground testing and the IRVE-3 flight test vehicle. High-altitude (free-molecular and transitional regimes) data were generated using DSMC methods. Pre-flight predictions of continuum static aerodynamics coefficients were derived from Reynolds-Averaged Navier-Stokes solutions at conditions along a design trajectory, with comparisons to available ground test data of the nano-ADEPT geometry. Dynamic pitch damping characteristics were taken from functional forms developed for the IRVE-3 flight test vehicle through ballistic range testing. Comparison of pre-flight predictions to post-flight reconstruction of aerodynamic force and moment coefficients is presented

Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results

The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012

Modeling Multibody Stage Separation Dynamics Using Constraint Force Equation Methodology

This paper discusses the application of the constraint force equation methodology and its implementation for multibody separation problems using three specially designed test cases. The first test case involves two rigid bodies connected by a fixed joint, the second case involves two rigid bodies connected with a universal joint, and the third test case is that of Mach 7 separation of the X-43A vehicle. For the first two cases, the solutions obtained using the constraint force equation method compare well with those obtained using industry- standard benchmark codes. For the X-43A case, the constraint force equation solutions show reasonable agreement with the flight-test data. Use of the constraint force equation method facilitates the analysis of stage separation in end-to-end simulations of launch vehicle trajectorie