Results from the Phoenix Atmospheric Structure Experiment

Similar documents
Mars Entry and Descent. Dr. Scott Striepe NASA Langley Research Center

ASTRIUM Space Transportation

Trajectory Matching Procedure/Practice for a Guided Projectile using MATLAB/Simulink

Innovative Visual Navigation Solutions for ESA s Lunar Lander Mission Dr. E. Zaunick, D. Fischer, Dr. I. Ahrns, G. Orlando, B. Polle, E.

Satellite Attitude Determination

Comparison of Wind Retrievals from a. Scanning LIDAR and a Vertically Profiling LIDAR for Wind Energy Remote Sensing Applications

GEOG 4110/5100 Advanced Remote Sensing Lecture 4

DEVELOPMENT OF A TOOL FOR OFFSHORE WIND RESOURCE ASSESSMENT FOR WIND INDUSTRY

INTEGRATED TECH FOR INDUSTRIAL POSITIONING

DeepCore Veto Methods

Simulation and Optimization of Spacecraft Re-entry Trajectories

AIAA ANERS Radar Trajectory Processing Technique for Merged Data Sources. April 21, 2017 Prepared by Bao Tong. Federal Aviation Administration

Interactive comment on Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals by S. Noël et al.

Interactive comment on Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals by S. Noël et al.

Model-based Programming: From Embedded Systems To Robotic Space Explorers

Inertial measurement and realistic post-flight visualization

Camera Drones Lecture 2 Control and Sensors

Selection and Integration of Sensors Alex Spitzer 11/23/14

HG4930 INERTIAL MEASUREMENT UNIT (IMU) Installation and Interface Manual

DriftLess Technology to improve inertial sensors

INSTALLATION GUIDE Ultrasonic Sensors Series UFP

INSTALLATION GUIDE Ultrasonic Sensors Series UPA

Error Simulation and Multi-Sensor Data Fusion

Creating Situational Awareness with Spacecraft Data Trending and Monitoring

Estimation of Altitude and Vertical Velocity for Multirotor Aerial Vehicle using Kalman Filter

SSC15-XI-2 SmallSat Conference

Wake Vortex Tangential Velocity Adaptive Spectral (TVAS) Algorithm for Pulsed Lidar Systems

Yu Tao, Panos Sidiropoulos, Jan-Peter Muller Imaging group, Mullard Space Science Laboratory, University College London BiDS 17 March 2016

Lecture 13 Visual Inertial Fusion

Navigation for Future Space Exploration Missions Based on Imaging LiDAR Technologies. Alexandre Pollini Amsterdam,

EEN118 LAB FOUR. h = v t - ½ g t 2

IMAGE DE-NOISING IN WAVELET DOMAIN

Egyptian Space Science and Technology Educational Project Based on Can-Sat Program (CLTP)

Navigational Aids 1 st Semester/2007/TF 7:30 PM -9:00 PM

Guidance, Navigation and Control issues for Hayabusa follow-on missions F. Terui, N. Ogawa, O. Mori JAXA (Japan Aerospace Exploration Agency )

Development Of Computational Tools For Analysis And Evaluation Of Autonomous Parafoil Systems

inter.noise 2000 The 29th International Congress and Exhibition on Noise Control Engineering August 2000, Nice, FRANCE

Mass-flux parameterization in the shallow convection gray zone

YDEA C5 User Manual. Welcome to use products of YDEA! We are appreciated if our user. manual offers help and convenience to you when you are using or

Lecture 24. Lidar Simulation

Thermal Design Tool for Outdoor Space Based on a Numerical Simulation System Using 3D-CAD

fraction of Nyquist

PSI Precision, accuracy and validation aspects

Towards a Lower Helicopter Noise Interference in Human Life

Lecture 14. Lidar Data Inversion and Sensitivity Analysis

IR-Signature of the MULDICON Configuration Determined by the IR-Signature Model MIRA

Strapdown Inertial Navigation Technology

ITTC Recommended Procedures and Guidelines. ITTC Quality System Manual. Recommended Procedures and Guidelines

FAA EDR Performance Standards

Workhorse ADCP Multi- Directional Wave Gauge Primer

Use of Image aided Navigation for UAV Navigation and Target Geolocation in Urban and GPS denied Environments

REFLIGHT OF THE METRIC CAMERA ON THE ATLAS-1 MISSION. M. Schroeder, R. Statter DFVLR, FR Germany

Since a projectile moves in 2-dimensions, it therefore has 2 components just like a resultant vector: Horizontal Vertical

Collaboration is encouraged among small groups (e.g., 2-3 students).

Angles-Only Autonomous Rendezvous Navigation to a Space Resident Object

ATS22D75Q soft starter-ats22-control 220V-power 230V(18.5kW)/ V(37kW)

Inertial Measurement for planetary exploration: Accelerometers and Gyros

Lecture: Autonomous micro aerial vehicles

P. Bilsby (WesternGeco), D.F. Halliday* (Schlumberger Cambridge Research) & L.R. West (WesternGeco)

TOA RADIANCE SIMULATOR FOR THE NEW HYPERSPECTRAL MISSIONS: STORE (SIMULATOR OF TOA RADIANCE)

New paradigm for MEMS+IC Co-development

On the flow and noise of a two-dimensional step element in a turbulent boundary layer

Measuring Turbulence with Lidars

TES Algorithm Status. Helen Worden

EEN118 LAB FOUR. h = v t ½ g t 2

Background and Accuracy Analysis of the Xfactor7 Table: Final Report on QuikScat X Factor Accuracy

TOPOGRAPHY - a LIDAR Simulation

RAPTR SAT-X. University of Northern Colorado. Conceptual Design Review. Shiely, Woods, Aken, Adamson 10/4/2011

HIGH SPEED PROJECTILE RECORDING SYSTEM

GEOG 4110/5100 Advanced Remote Sensing Lecture 2

Wide-area kinematic GNSS

LAB 2: DATA FILTERING AND NOISE REDUCTION

USER MANUAL. Specifications. 0.1 m/s for wind speed degrees for wind direction -30 C to +80 C for temperature

Information Content of Limb Radiances from MIPAS

Exterior Orientation Parameters

ATS22D62Q soft starter-ats22-control 220V-power 230V(15kW)/ V(30kW)

Monte-Carlo Analysis of Object Reentry in Earth s Atmosphere Based on Taguchi Method

Building Software to Translate

Lecture 13. Lidar Data Inversion

EEN118 LAB FOUR. h = v t ½ g t 2

ifp Universität Stuttgart Performance of IGI AEROcontrol-IId GPS/Inertial System Final Report

Patching Flight Software on Mars

M-Navigator-EX User Guide

Orientation Capture of a Walker s Leg Using Inexpensive Inertial Sensors with Optimized Complementary Filter Design

Airborne LiDAR Data Acquisition for Forestry Applications. Mischa Hey WSI (Corvallis, OR)

Dealing with Scale. Stephan Weiss Computer Vision Group NASA-JPL / CalTech

navigation Isaac Skog

ATV310HU30N4E variable speed drive ATV310-3 kw - 4 hp V - 3 phase

ATV12P075M3 variable speed drive ATV kW - 1hp V - 3ph - on base plate

CARBON NANOTUBE FLAT PLATE BLACKBODY CALIBRATOR. John C. Fleming

Visual Odometry. Features, Tracking, Essential Matrix, and RANSAC. Stephan Weiss Computer Vision Group NASA-JPL / CalTech

Martian Unmanned Science Skimmer - Simulation

Deconvolution in the radial trace domain

ATV310H075N4E variable speed drive ATV kw - 1 hp V - 3 phase

Analysis Ready Data For Land (CARD4L-ST)

High-performance mean currents and turbulence, wave height and direction

Lecture 13.1: Airborne Lidar Systems

INTEGRATED MODEL-BASED SYSTEMS ENGINEERING (MBSE) APPLIED TO THE SIMULATION OF THE OSIRIS-REx MISSION

EEN118 LAB FOUR. h = v t ½ g t 2

Getting Started Processing DSN Data with ODTK

Transcription:

Results from the Phoenix Atmospheric Structure Experiment Paul Withers 1 and David Catling 2 (1) Center for Space Physics, Boston University, USA (withers@bu.edu) (2) University of Washington, USA International Planetary Probe Workshop 2010.06.15 Barcelona, Spain

Outline Overview of trajectory and atmospheric structure reconstruction for Phoenix Highlight selected aspects of Phoenix reconstruction that offer lessons for future missions Demonstration of real-time reconstruction technique using direct-to-earth radio link (Opportunity EDL) 2/25

Outline Overview of trajectory and atmospheric structure reconstruction for Phoenix Highlight selected aspects of Phoenix reconstruction that offer lessons for future missions Demonstration of real-time reconstruction technique using direct-to-earth radio link (Opportunity EDL) 3/25

Phoenix atmospheric entry JPL figure 25 May 2008 Landing site at 68.2N, 234.3E -4.1 km (MOLA) Ls=77, LST ~16:30 Ballistic entry with many similarities to Pathfinder and MER Accelerometers and gyroscopes on board IMU specifications, location, etc, etc fixed without scientific input 200 Hz data (good), but noisy (bad) 4/25

200 Hz accelerations Noisy data (poor above 65 km) Digitized data Entry (3522.2 or 143 km) at t=1857.733 seconds 5/25

Smoothed accelerations All data smoothed with 64-point or 0.32 sec window Data before 1900 sec smoothed with variable window (0.32 to 20 sec) Useful data to ~128 km now 6/25

Reconstructed trajectory Reconstruction process essentially same as used for Spirit and Opportunity, with exception of gyroscope data 5600 m/s to 6.1+-/3.6 m/s with design value of few m/s! Attitude found directly using gyroscopes, angle of attack is well behaved Parachute deployment at 13.5 km and 391 m/s (Mach 1.7) First ground contact at 1.10 +/- 1.49 km above ground level and 6.1 +/- 3.6 m/s 7/25

Reconstructed thermal structure Reconstruction process essentially same as used for Spirit and Opportunity, but with updated aerodynamics and known attitude Much warmer than CO 2 condensation curve Mesopause Tides Gravity waves 8/25

Comparison with MCS profiles Solid line is PHX Dashed line is MCS Blue = Night Red = Day 45-50N Summer Lee et al. (2009) 90 km MCS = Mars Climate Sounder instrument on MRO Good agreement at low altitudes, gets worse as altitude increases Strong signature of diurnal thermal tide 0 km 9/25

Gravity waves Black solid line is PHX profile Black dashed line is 10 km running mean Grey lines show temperature difference, offset by 180 K Vertical wind speeds of ~5 m/s associated with these 5 K oscillations with 7 km wavelength 10/25

Comparison with general circulation models Solid line = PHX Dashed line = LMD Grey line = Ames Both are OK at low altitudes, but fail to reproduce tides correctly 11/25

Success of project s empirical model Solid black line = PHX Grey line is low dust empirical model Dashed line is dusty empirical model Low dust model was very accurate 12/25

Outline Overview of trajectory and atmospheric structure reconstruction for Phoenix Highlight selected aspects of Phoenix reconstruction that offer lessons for future missions Demonstration of real-time reconstruction technique using direct-to-earth radio link (Opportunity EDL) 13/25

Challenges for smoothing accelerations Exponential increase at high altitudes Discontinuities appear when width of averaging window is changed Mean of an exponential function does not equal desired central value Can t use mean of log(a) because noisy data varies sign 14/25

Solution Use two averages Calculate long average al from t = -2ts to t = +2ts Calculate short average as from t = -ts to t = +ts Ratio gives desired tau 15/25

Grey dots are normal smoothing with 1024 point running mean Black dots are normal smoothing with 2048 point running mean Difference indicates the problem How do you transition from one averaging window to another? Grey dots are 1024 point running mean corrected using ratio to 2048 point running mean Black dots are 2048 point running mean corrected using ratio to 4096 point running mean Overlap of two series enables easy transition from one averaging window to the next 16/25

Transformation from IMU frame into spacecraft frame One source, as built M = [ 0 0.4226 0.9063 ] [ 0.8660-0.4532 0.2113 ] [ 0.5 0.7849-0.3660] Another source, as designed Differences seem small, but effects are not 17/25

Effects of frames on trajectory As designed As designed As built Differences of a few km in altitude at parachute deployment and landing, differences of tens of m/s in speed at landing 18/25

Angle of attack Black line is value from gyros Grey line is value from acceleration ratios Results of two different methods for finding the angle of attack are inconsistent by 1-2 degrees. This is SEPARATE issue from predicted/reconstructed differences 19/25

Outline Overview of trajectory and atmospheric structure reconstruction for Phoenix Highlight selected aspects of Phoenix reconstruction that offer lessons for future missions Demonstration of real-time reconstruction technique using direct-to-earth radio link (Opportunity EDL) 20/25

Entry reconstructions What if done in real time? Rapid estimate of landing site location Rapid assessment of accuracy of predicted environmental conditions Engage public during EDL event Don t need mission to survive after EDL for subsequent data transmission Direct-to-Earth radio link offers alternative approach 21/25

Doppler shift during Opportunity EDL Johnston et al. (2004) This only gives one component of velocity. Assuming that the aerodynamic deceleration is parallel to velocity gives 3D velocity. Demonstrate using scanned version of this figure (not real data). 22/25

Reconstructed trajectory Grey line = Usual reconstruction method Black line = Doppler reconstruction method Time discrepancy of about 10 seconds, but results look acceptable 100 km 50 km 23/25

Reconstructed temperature Grey line = Usual reconstruction method Black line = Doppler reconstruction method Plausible temperatures between 20 km and 60 km. This technique works, but should be validated using real data. Uncertainty analysis also needed to estimate expected accuracy. 24/25

Conclusions Trajectory and atmospheric structure reconstruction for Phoenix successful Results available in PDS Future atmospheric entry probes might consider: Reduction of noise by smoothing Sensitivity to mundane engineering details, like relationships between reference frames Why two different angles of attack? Potential of rapid reconstruction using radio link 25/25

Backup Material 26/25

Why bother? Independent reconstruction of trajectory Rapid results for: Engineers (Where did we land? Nominal?) Public (See results immediately) Science (What are atmospheric conditions?) Get results even if lander explodes when reaching ground 27/25

Detailed approach Measured: Obvious: Re-arrange: Re-arrange: Big assumption: Outcome is expression for a-aero using known quantities 28/25