GPS Attitude Determination by Jinsuck Kim AERO 681 Department of Aerospace Engineering Texas A&M University March 9th, 1999.

Slides:



Advertisements
Similar presentations
Ordinary Least-Squares
Advertisements

2013 Western Australia Surveying Conference
Position and Attitude Determination using Digital Image Processing Sean VandenAvond Mentors: Brian Taylor, Dr. Demoz Gebre-Egziabher A UROP sponsored research.
P. Venkataraman Mechanical Engineering P. Venkataraman Rochester Institute of Technology DETC2011 –47658 Determining ODE from Noisy Data 31 th CIE, Washington.
Limits of static processing in a dynamic environment Matt King, Newcastle University, UK.
A New Block Based Motion Estimation with True Region Motion Field Jozef Huska & Peter Kulla EUROCON 2007 The International Conference on “Computer as a.
D Nagesh Kumar, IIScOptimization Methods: M1L1 1 Introduction and Basic Concepts (i) Historical Development and Model Building.
Attitude Determination - Using GPS. 20/ (MJ)Danish GPS Center2 Table of Contents Definition of Attitude Attitude and GPS Attitude Representations.
MASKS © 2004 Invitation to 3D vision Lecture 11 Vision-based Landing of an Unmanned Air Vehicle.
Spacecraft Attitude Determination Using GPS Signals C1C Andrea Johnson United States Air Force Academy.
Space Weather influence on satellite based navigation and precise positioning R. Warnant, S. Lejeune, M. Bavier Royal Observatory of Belgium Avenue Circulaire,
Workshop EGNOS KRAKÓW GNSS RECEIVER TESTING TECHNIQUES IN A LABORATORY ENVIRONMENT Institute of Radar Technology Military University of Technology.
Navigational System For An Autonomouse Farming Vehicle Group 942.
Efficient Methodologies for Reliability Based Design Optimization
Goals of Adaptive Signal Processing Design algorithms that learn from training data Algorithms must have good properties: attain good solutions, simple.
Project Presentation: March 9, 2006
Autonomous Robotics Team Autonomous Robotics Lab: Cooperative Control of a Three-Robot Formation Texas A&M University, College Station, TX Fall Presentations.
Abstract In this project we expand our previous work entitled "Design of a Robotic Platform and Algorithms for Adaptive Control of Sensing Parameters".
Principles of the Global Positioning System Lecture 10 Prof. Thomas Herring Room A;
Sub-Nyquist Sampling DSP & SCD Modules Presented by: Omer Kiselov, Daniel Primor Supervised by: Ina Rivkin, Moshe Mishali Winter 2010High Speed Digital.
EGR 1101 Unit 7 Systems of Linear Equations in Engineering (Chapter 7 of Rattan/Klingbeil text)
Anthony Gaught Advisors: Dr. In Soo Ahn and Dr. Yufeng Lu Department of Electrical and Computer Engineering Bradley University, Peoria, Illinois May 7,
SVY 207: Lecture 4 GPS Description and Signal Structure
Introduction to Adaptive Digital Filters Algorithms
1 Cooperative STBC-OFDM Transmissions with Imperfect Synchronization in Time and Frequency Fan Ng and Xiaohua(Edward) Li Department of Electrical and Computer.
1 SVY207: Lecture 18 Network Solutions Given many GPS solutions for vectors between pairs of observed stations Compute a unique network solution (for many.
Kalman filtering techniques for parameter estimation Jared Barber Department of Mathematics, University of Pittsburgh Work with Ivan Yotov and Mark Tronzo.
Da Yan, Zhou Zhao and Wilfred Ng The Hong Kong University of Science and Technology.
Simultaneous Estimations of Ground Target Location and Aircraft Direction Heading via Image Sequence and GPS Carrier-Phase Data Luke K.Wang, Shan-Chih.
Vision-based Landing of an Unmanned Air Vehicle
High Accuracy Nationwide Differential Global Positioning System (HA-NDGPS) UPDATE Jim Arnold September, 2009.
Network Computing Laboratory Radio Interferometric Geolocation Miklos Maroti, Peter Volgesi, Sebestyen Dora Branislav Kusy, Gyorgy Balogh, Andras Nadas.
Compatibility of Receiver Types for GLONASS Widelane Ambiguity Resolution Simon Banville, Paul Collins and François Lahaye Geodetic Survey Division, Natural.
Modern Navigation Thomas Herring
SVY 207: Lecture 13 Ambiguity Resolution
On Distinguishing the Multiple Radio Paths in RSS-based Ranging Dian Zhang, Yunhuai Liu, Xiaonan Guo, Min Gao and Lionel M. Ni College of Software, Shenzhen.
ES 240: Scientific and Engineering Computation. Chapter 13: Linear Regression 13. 1: Statistical Review Uchechukwu Ofoegbu Temple University.
Ali Al-Saihati ID# Ghassan Linjawi
Surveying with the Global Positioning System Phase Observable.
Solving Linear Systems of Equations
Colorado Center for Astrodynamics Research The University of Colorado 1 STATISTICAL ORBIT DETERMINATION ASEN 5070 LECTURE 11 9/16,18/09.
Active Noise Cancellation System
PROCESS MODELLING AND MODEL ANALYSIS © CAPE Centre, The University of Queensland Hungarian Academy of Sciences Statistical Model Calibration and Validation.
Computational Time-reversal Imaging
Texas A&M University, Department of Aerospace Engineering AN EMBEDDED FUNCTION TOOL FOR MODELING AND SIMULATING ESTIMATION PROBLEMS IN AEROSPACE ENGINEERING.
A Semi-Blind Technique for MIMO Channel Matrix Estimation Aditya Jagannatham and Bhaskar D. Rao The proposed algorithm performs well compared to its training.
Goddard Space Flight Center High Earth Orbit GPS Flight Experiment AMSAT-OSCAR 40 (AO-40) Frank H. Bauer NASA Goddard Space Flight Center November 1, 2001.
5. Nonlinear Functions of Several Variables
1 SVY 207: Lecture 12 Modes of GPS Positioning Aim of this lecture: –To review and compare methods of static positioning, and introduce methods for kinematic.
Using Kalman Filter to Track Particles Saša Fratina advisor: Samo Korpar
Engineering Analysis ENG 3420 Fall 2009 Dan C. Marinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00.
Civil and Environmental Engineering and Geodetic Science This file can be found on the course web page:
SVY207: Lecture 10 Computation of Relative Position from Carrier Phase u Observation Equation u Linear dependence of observations u Baseline solution –Weighted.
Tracking Mobile Nodes Using RF Doppler Shifts
EECS 274 Computer Vision Projective Structure from Motion.
ROBOTICS 01PEEQW Basilio Bona DAUIN – Politecnico di Torino.
Impacts of Carrier Wavelength and Physical Environment on Coverage of ORBCOMM LMSS with Different Antenna Radiation Patterns Steven J. Ma,Dr. Dave Michelson.
GPS Computer Program Performed by: Moti Peretz Neta Galil Supervised by: Mony Orbach Spring 2009 Characterization presentation High Speed Digital Systems.
© 2012 Anwendungszentrum GmbH Oberpfaffenhofen Idea by: Dr. Eng. Mohamed Zayan | 1.
Limits of static processing in a dynamic environment Matt King, Newcastle University, UK.
Limits of static processing in a dynamic environment Matt King, Newcastle University, UK.
3D Array Processing Sept 8, 2016, DUGL telecon
Vision Based Motion Estimation for UAV Landing
CHAPTER OBJECTIVES The primary objective of this chapter is to show how to compute the matrix inverse and to illustrate how it can be.
KINEMATIC GPS AND AMBIGUITY RESOLUTION PROBLEM
Systems of Linear Equations in Engineering
Singular Value Decomposition
Lecture 8: Image alignment
Unfolding with system identification
Enhanced State Estimation by Advanced Substation Monitoring
Presentation transcript:

GPS Attitude Determination by Jinsuck Kim AERO 681 Department of Aerospace Engineering Texas A&M University March 9th, 1999

Outline Motivation Algorithm –GPS carrier phase –Integer ambiguity problem –Traditional and improved methods Application –Simulation –Hardware data verification

GPS equipment : Trimble TANS Vector Four antenna receiver to form three baselines Provide attitude and navigation solutions

Motivation International Space Station (ISS) –Crew return vehicle in case of emergency –“Lost-in-Space” : unknown attitude and position –Place independent pseudolites on the ISS (GPS-like transmitters) –Need the relative attitude at the first stage of escape ISS Crew return vehicle escape transmitters

Difference of carrier phase To GPS satellite Frequency = MHz, Wave length = 19cm

Integer Ambiguity Problem Static search –Finds a solution that minimizes the error residual –Provides a solution even when no motion has occurred –May converge to incorrect solutions (no unique solution) Motion based method –Collect data for a given period of time and perform batch process –Inherently highly reliable –Takes longer time and requires sufficient relative movement

Improved Algorithm Quasi-static resolution (Cohen’s method) –Method has been successfully implemented –A prior attitude estimate must be given –Large-order matrix inversion may be required New algorithm –Does not require any initial estimate –Requires less computational effort –Converge in significantly less time –Need at least three non-coplanar baselines –Minimize

Linear Least Square (Cohen’s method)

Nonlinear Least Square Result

Application Program development (current work) –Use Matlab or C compiler with fictitious S/C, GPS signal –Compare traditional methods with the improved method Hardware simulation (next semester) –Import the data from JSC lab using actual GPS receiver (by Trimble) –Simulate LEO space crafts (ISS and crew return vehicle) –Compare linearized and nonlinear least square solutions Future work : optimal pseudolites locations