april 10, 2008 “gps data processing methods using sw tools and the gps receiver sw simulator for...

April 10, 2008 “GPS DATA PROCESSING METHODS USING SW TOOLS AND THE GPS RECEIVER SW SIMULATOR FOR PRECISE RELATIVE POSITIONING OF FORMATION FLYING SATELLITES” of Michelangelo Ambrosini

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All rights reserved, 2008, Thales Alenia Space

Chapter of Rome

M.Sc. in Advanced Communication and

Navigation Satellite Systems

AFCEA’s International Student Conference 2008

“GPS DATA PROCESSING METHODS USING SW TOOLS AND THE GPS RECEIVER SW

SIMULATOR FOR PRECISE RELATIVE POSITIONING OF FORMATION FLYING

SATELLITES”

Brussels, April 10 2008 of Michelangelo Ambrosini


Observation Systems & Radar Business Unit – Satellite System Engineering – Integrated Control Systems

M.Sc. IN ADVANCED COMMUNICATIONS AND NAVIGATION SATELLITE SYSTEMSM.Sc. IN ADVANCED COMMUNICATIONS AND NAVIGATION SATELLITE SYSTEMS

“GPS DATA PROCESSING METHODS USING SW TOOLS AND THE GPS RECEIVER SW SIMULATOR FOR PRECISE RELATIVE POSITIONING OF FORMATION FLYING SATELLITES” of Michelangelo Ambrosini

April 10, 2008

Introduction to the study

1. Master of Science (M.Sc.) in Advanced Communications and Navigation Satellite Systems of the University of Rome “Tor Vergata” achieved in February 2008

2. Internship in the Observation Systems & Radar B.U. – Satellite Systems Engineering – Integrated Control Systems of Thales Alenia Space Italy S.p.A. (TAS-I) based in Rome, Italy

3. Study of a future TAS-I/ASI (Italian Space Agency) Low Earth Orbit Satellite in Formation Flying with COSMO Sky-Med Constellation Satellites for Remote Sensing and Earth Observation

4. High Accuracy Levels in the Relative Baseline Determination between COSMO Sky-Med Satellites and the future Formation Flying Satellite for reasons of High Level of SAR images Resolution using Interferometric Techniques and GPS Carrier Phase Data Processing Methods





April 10, 2008

Mission Requirements High Accuracy Levels in the Relative Baseline Determination between COSMO Sky-Med Satellites

and the future Formation Flying Satellite for reasons of High Level of SAR images Resolution using Interferometric Techniques

Main Arguments Mission Accurate Baseline Determination On-Board Processing Models & Algorithms using GPS

Carrier Phase Data Theory and SW Tooling Implementation & Testing of the GPS Data Processing Methods Overview & Synthesis of the GPS Orbital Receiver SW Simulator GPS Receiver SW Simulator Architecture, Performances & Test Campaign Results Simulations Numerical Results & Test Performances

Targets Simulations Results near to Real On-Board GPS Receiver Physical behaviour Simulations Results near to Real GPS Signal Degradation & Delay Sources High level of Accuracy in the Formation Flying Satellites Receivers Baseline Determination

Next Steps SW Tools integration in the Satellite System & Subsystems Platform SW Simulator Algorithms Tests SW Performances: From Post-Processing to On-Board Real-Time SW

implementation

Main topics





April 10, 2008

Spacecraft formation flying is commonly considered as:- a key technology for advanced space missions

The distribution of sensor systems to multiple platforms offers:

- improved flexibility and redundancy- shorter times to mission- the prospect of being more cost-effective

compared to large individual spacecraft

Satellite formations in Low Earth Orbit provide:- advanced science opportunities that cannot (or less easily) be realized

with single spacecraft (such as):- measuring small scale variations in the Earth’s gravity field- higher resolution imagery and interferometry

Spacecraft formationflying missions





April 10, 2008

Fundamental issues of spacecraft formation flying:

- the determination of the relative state (position and velocity) between the satellite vehicles within the formation

- knowledge of these relative states in (near) real-time is important for operational aspects

- some of the scientific applications, such as high resolution interferometry, require an accurate post-facto knowledge of these states instead

- therefore a suitable sensor system needs to be selected for each mission

Spacecraft formationflying missions





April 10, 2008

Formation Flying forEarth Remote Sensing





April 10, 2008

Classification of active microwave formations

Formation Flying forEarth Remote Sensing





April 10, 2008

Mission Objectives & Scenario

The Program is an experimental Mission both for scientific contribution and for the innovative technological aspects

The Program shall operate in strict coordination with COSMO-SkyMed, without any impact at Space and Ground level

The Program will be developed in order to guarantee a maximum level of commonality with COSMO in terms of synergies, developments, operations and maintenance

The Mission objectives are:

to provide additional products wrt the COSMO-SkyMed ones to realize a “demonstrator” for the testing of Interferometric, Bistatic,

Radargrammetric techniques to fly in formation with one satellite of the COSMO-SkyMed

constellation, avoiding to interfere with COSMO-SkyMed mission and operations





April 10, 2008


Selected Configurations for Interferometric and Bistatic acquisitions from the Reference COSMO-SkyMed orbit

Leader-Follower Cartwheel Pendulum





April 10, 2008


COSMO (master)

BISSAT (slave)

(zenith-nadir) Radial-vector

(velocity-vector) Along-Track

Across-Track

Reference: Hill’s coordinate frame





April 10, 2008

Simulated Physical Quantities

The SW Simulator reproduces two different main scenarios:

- The first one is represented by the Simulated Operative Behaviour Physics in which the GPS Receiver operates that is the Orbital Mechanics and the Physical Degradations and Delays which affect the In-Space GPS Signal transmitted from GPS Satellites to the In-Orbit GPS Receiver.

- The second one is about the GPS Receiver Behaviour and Performances as far as:

Receiver estimations and measures of the GPS Signal Degradations due to the Received GPS Signal (Code and Phase) Acquisition and Tracking Processes;

Pseudo-range and Pseudo-range-Rate Equations Systems Resolution for the In-Orbit Receiver Position and Velocity determination;

GPS Receiver SWSimulator Overview





April 10, 2008

SIMULATION STARTING DATA

RECEIVERS SPS POSITION AND VELOCITY SOLUTION

RECEIVERS ORBITAL PROPAGATION

GPS SATELLITES ORBITAL PROPAGATION

RECEIVERS SIGNAL DEGRADATIONS MEASUREMENTS

RECEIVERS SIGNAL DEGRADATIONS ESTEEMS

RECEIVERS INNER LOOPS DEGRADATIONS

MEASUREMENTS

POST PROCESSING (RTK & MLAMBDA METHOD)

FORMATION SPS POSITION AND

VELOCITYBASELINE SOLUTION

RECEIVERS EXACT POSITION AND VELOCITY

SOLUTIONS

FORMATION EXACTPOSITION AND

VELOCITYBASELINE SOLUTION

FORMATIONBASELINE ACCURACY

SW Simulator Logical Scheme






April 10, 2008

3D ECI Propagated Receiver Position & Velocity Dynamics

Receiver 3D Orbital Position Receiver 3D Orbital Velocity






April 10, 2008

3D ECI NORAD Propagated GPS Satellites Position & Velocity Dynamics

GPS Satellites 3D Orbital Position GPS Satellites 3D Orbital Velocity






April 10, 2008

GPS Signal Degradation & Delay Models (1)

Receiver Clock Bias Delay EffectMeasures Dynamic

Ionospheric Delay Effect Measures Dynamic

Receiver 1st Order Relativistic DelayEffect Measures Dynamic

GPS SAT PRN N°1 2nd Order RelativisticDelay Effect Measures Dynamic






April 10, 2008

GPS Signal Degradation And Delay Models (2)

GPS SAT PRN N°1 L1 and L2 Carrier FrequenciesSignal to Noise Ratio (SNR) Measures Dynamic

GPS SAT L1 Carrier FrequencyMultipath Delay Effect Measures Dynamic

GPS SAT PRN N°1 C/A Code GainPattern Delay Effect Measures Dynamic

GPS SAT L1 Carrier Frequency Relativistic Doppler Delay Effect Measures Dynamic






April 10, 2008

Receiver Measures Determination

GPS SAT PRN N°1 Free Space GPS SignalPropagation Time Delay Dynamic

GPS SAT PRN N°1 L1 Carrier FrequencyPseudo-range Measures Dynamic

GPS SAT PRN N°1 L1 Carrier FrequencyPseudo-range Rate Measures Dynamic

GPS SAT PRN N°1 L1 Carrier FrequencyIntegrated Pseudo-range Measures Dynamic

GPS SAT PRN N°1 L1 Carrier PhaseIntegrated Doppler Measures Dynamic

GPS SAT PRN N°1 L1 Carrier Phase IntegratedDoppler Rate Measures Dynamic






April 10, 2008

GPS Satellites Visibility Determination

GPS PRN Satellites Visibility Dynamic

Visibility: Mean Value and Standard Deviation

Number of GPS SatellitesVisibility Dynamic




Page 20M.Sc. IN ADVANCED COMMUNICATIONS AND NAVIGATION SATELLITE SYSTEMSM.Sc. IN ADVANCED COMMUNICATIONS AND NAVIGATION SATELLITE SYSTEMS


April 10, 2008

Receiver SPS Position & Velocity Solutions Accuracy

Receiver SPS 3D ECI Position Components (X,Y,Z) Error Dynamics

Receiver SPS 3D ECI Velocity Components (U,V,W) Error Dynamics






April 10, 2008

Navigation Solution Performance Requirements (Laben Test Report)






April 10, 2008

Relative positioning models:- Single difference model- Double difference model

Relative Spacecraft Positioning:

- Integer ambiguity resolution:- Integer ambiguity estimation- Integer ambiguity validation

- Proposed processing strategy:- Sequential kinematic filter (Real Time Kinematic/RTK

approach)

GPS Observations & Relative Spacecraft Positioning





April 10, 2008

Relative positioning models: Single & Double difference models

Overall viewing geometry for relative (spacecraft) positioning using differenced GPS observations. GPS satellites j and k are commonly observed by both receivers and thus SD and DD observations can be formed. This is not the case for GPS satellites h and m, which are only observed by one receiver






April 10, 2008

Integer ambiguity resolution (estimation & validation)

Distribution of a double difference ambiguity as real-valued (float) and accompanying integer (fixed) solution. In the left figure the probability mass for the correct value (4) is still low, in the right figure this might already be high enough to neglect the stochastic nature of the ambiguity






April 10, 2008

Overall Processing And Positioning Strategy:

• Complete initialization of all DD ambiguities

• Partial (re)initialization of new DD ambiguities

• Relative positioning with DD carrier phase observations and known integer ambiguities






April 10, 2008

STEP 1: Measures initialization & acquisition processes

STEP 2: Observables double difference DD and covariance matrices construction

STEP 3: Initial differential ambiguities determination: the MLAMBDA method- Floating point solution- Reduction and de-correlation processes- Search process

STEP 4: Ambiguities fixing & ionosphere free combination processes

STEP 5: Relative positioning & ambiguity-fixed-ionosphere free DD carrier phases






April 10, 2008

The LAMBDA method:

- Reduction process:- Integer Gauss transformations- Permutations- The reduction algorithm- Discrete search process

Modifying the LAMBDA method: (MLAMDA)

- Modified reduction- Symmetric pivoting strategy- Greedy selection strategy - Lazy transformation strategy- Modified reduction algorithm

- Modified search process

MLAMBDA: A Modified LAMBDA methodfor Integer Least-squares Estimation





April 10, 2008

Numerical simulations

Satellite B Orbital Position 3DECI components

Baseline between sat A and B3D ECI components






April 10, 2008


Satellite B Orbital PositionX ECI component esteem

solution accuracy

Satellite B Orbital PositionY ECI component esteem

solution accuracy

Satellite B Orbital PositionZ ECI component esteem

solution accuracy






April 10, 2008


Baseline error X ECI component

Baseline error Y ECI component

Baseline error Z ECI component

Baseline ECI error norm






April 10, 2008


Satellite B error norm PDOP for Satellite A

PDOP for Satellite B

ECI 3D errorComponents

Mean values(meters)

1σ(meters)

Δx (1°) 0.0149 0.0138

Δy (2°) 0.0237 0.0114

Δz (3°) 0.0375 0.0460

ECI satellite B 3D vector componentsaccuracy Mean Value and Standard Deviation






April 10, 2008

Conclusions

- From a careful statistical study and from an accurate comparison between the SW Simulator Data Graphics and those reported in the Laben Lagrange Test Reports we can conclude that the GPS SW Simulator supplies statistically the same results of the real Lagrange Receiver (ENEIDE Mission)

- The SW Simulator also reconstructs the Lagrange Mission Operative Environment simulating the physics which governs both the Receiver Orbital Dynamic and the GPS Constellation Orbital Dynamic considering all types of orbital perturbations

- The simulations of the GPS data processing with the SW tools for the accurate baseline determination have reached the requested preliminary mission performances which are accuracies on each ECI component in space of the order of 1 cm as Standard Deviation in very short computational time for simulations time periods of 1 orbit

Conclusions & Future Developments





April 10, 2008

Future Developments

- Now the work is to develop new strategies and algorithms to make more robust and accurate the data processing performances and integrate these SW tools in the Mission Satellite Platform SW Simulator in Matlab which will be used for the simulations of the Satellite System and Subsystems in the preliminary mission requirements design phase

- The future step will be to decode all these SW tools from Fortran and Matlab to the ADA code in which the Satellite On-Board SW is implemented and try to reach the target of obtaining the same statistical real-time GPS data processing performances On-Board and higher level of accuracy (of the order of 1 mm) in the ground-based post-processing

Conclusions & Future Developments





April 10, 2008

Michelangelo Ambrosini

Thank you very much for your attention!Do you have any question?

Brussels, April 10 2008

Michelangelo AmbrosiniThales Alenia Space Italia

S.p.A. (TAS-I)Observation Systems & Radar

Business UnitSatellite System EngineeringIntegrated Control SystemsVia Saccomuro, 24 - 00131 -

Rome, Italy

Mobile: (0049)3382376754E-mail:

[email protected] Profile URL: http://

www.linkedin.com/in/michelangeloambrosiniOn-line Curriculum Vitae URL: http://ctif.uniroma2.it/mastercv/ambrosinim/CV_Ambrosini_ENG.pdf

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