Open Loop Tracking of GPS Radio Occultation for LEOs

Slides:



Advertisements
Similar presentations
Long RAnge Navigation version C
Advertisements

Unit Generators and V.I.s Patches are configurations of V.I.s Both Patches & Virtual Instruments can be broken down into separate components called Unit.
THE AUSTRALIAN NATIONAL UNIVERSITY Infrasound Technology Workshop, November 2007, Tokyo, Japan OPTIMUM ARRAY DESIGN FOR THE DETECTION OF DISTANT.
Collaboration FST-ULCO 1. Context and objective of the work  Water level : ECEF Localization of the water surface in order to get a referenced water.
Excess phase computation S. Casotto, A. Nardo, P. Zoccarato, M. Bardella CISAS, University of Padova.
DETECTION OF UPPER LEVEL TURBULENCE VIA GPS OCCULTATION METHODS Larry Cornman National Center for Atmospheric Research USA.
Atmospheric structure from lidar and radar Jens Bösenberg 1.Motivation 2.Layer structure 3.Water vapour profiling 4.Turbulence structure 5.Cloud profiling.
Digital Voice Communication Link EE 413 – TEAM 2 April 21 st, 2005.
Propagation characteristics of wireless channels
Ground-Based Altimetry Using a Single- Receiver Single-Frequency GNSS Phase Ambiguity Resolution Technique G. Stienne* S. Reboul J.-B. Choquel M. Benjelloun.
Inputs to Signal Generation.vi: -Initial Distance (m) -Velocity (m/s) -Chirp Duration (s) -Sampling Info (Sampling Frequency, Window Size) -Original Signal.
CS3502, Data and Computer Networks: the physical layer-3.
New Satellite Capabilities and Existing Opportunities Bill Kuo 1 and Chris Velden 2 1 National Center for Atmospheric Research 2 University of Wisconsin.
Use of GPS RO in Operations at NCEP
Comparison of temperature data from HIPPO-1 flights using COSMIC profiles and Microwave Temperature Profiler. Kelly Schick 1,2,3 and Julie Haggerty, Ph.D.
A New Algorithm for Improving the Remote Sensing Data Transmission over the LEO Satellite Channels Ali Payandeh and Mohammad Reza Aref Applied Science.
Different options for the assimilation of GPS Radio Occultation data within GSI Lidia Cucurull NOAA/NWS/NCEP/EMC GSI workshop, Boulder CO, 28 June 2011.
Fundamentals of Data Analysis Lecture 10 Management of data sets and improving the precision of measurement pt. 2.
1 Detection and Determination of Channel Frequency Shift in AMSU-A Observations Cheng-Zhi Zou and Wenhui Wang IGARSS 2011, Vancouver, Canada, July 24-28,
June, 2003EUMETSAT GRAS SAF 2nd User Workshop. 2 The EPS/METOP Satellite.
10. Satellite Communication & Radar Sensors
ECE 5233 Satellite Communications Prepared by: Dr. Ivica Kostanic Lecture 15: Secondary atmospheric losses effects (Section ) Spring 2011.
Experimental Results ■ Observations:  Overall detection accuracy increases as the length of observation window increases.  An observation window of 100.
Status of the assimilation of GPS RO observations: the COSMIC Mission L. Cucurull JCSDA/UCAR J.C. Derber, R. Treadon, and R.J. Purser.
Sparse Signals Reconstruction Via Adaptive Iterative Greedy Algorithm Ahmed Aziz, Ahmed Salim, Walid Osamy Presenter : 張庭豪 International Journal of Computer.
Use of GPS Radio Occultation Data for Climate Monitoring Y.-H. Kuo, C. Rocken, and R. A. Anthes University Corporation for Atmospheric Research.
Electromagnetic Spectrum
University of Electronic Science and Technology of China
GRAS SAF User Workshop June GRAS Level 1 Processing and Products Juha-Pekka Luntama and Julian Wilson EUMETSAT Am Kavalleriesand 31, D
Key RO Advances Observation –Lower tropospheric penetration (open loop / demodulation) –Larger number of profiles (rising & setting) –Detailed precision.
October 02, st IHOP_2002 Water Vapor Intercomparison Workshop Status of intercomparisons and the next steps  Characterize moisture measuring techniques.
Preliminary results from assimilation of GPS radio occultation data in WRF using an ensemble filter H. Liu, J. Anderson, B. Kuo, C. Snyder, A. Caya IMAGe.
Atmospheric phase correction at the Plateau de Bure interferometer IRAM interferometry school 2006 Aris Karastergiou.
Improved Radio Occultation Observations for a COSMIC Follow-on Mission C. Rocken, S. Sokolovskiy, B. Schreiner UCAR / COSMIC D. Ector NOAA.
ASI, February 2009 The GRAS Instrument C. Marquardt, Y. Andres, A. von Engeln, F. Sancho.
0 Earth Observation with COSMIC. 1 COSMIC at a Glance l Constellation Observing System for Meteorology Ionosphere and Climate (ROCSAT-3) l 6 Satellites.
COSMIC: Constellation Observing System for Meteorology, Ionosphere and Climate Mission Status and Results UCAR COSMIC Project FORMOSAT-3.
GPS Radio-Occultation data (COSMIC mission) Lidia Cucurull NOAA Joint Center for Satellite Data Assimilation.
NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS SURFACE PRESSURE MEASUREMENTS FROM THE ORBITING CARBON OBSERVATORY-2.
SVY207 Lecture 8: The Carrier Phase Observable
Observational Error Estimation of FORMOSAT-3/COSMIC GPS Radio Occultation Data SHU-YA CHEN AND CHING-YUANG HUANG Department of Atmospheric Sciences, National.
Fundamentals of Communications. Communication System Transmitter: originates the signal Receiver: receives transmitted signal after it travels over the.
TRANSMISION LINE PROTECTION USING GPS PRESENTED BY:- KAJAL MOR M.TECH(PS)
Chapter 10 Digital Signal and Image Processing
Serial Communications
Geodesy & Crustal Deformation
1.) Acquisition Phase Task:
GPS: Global Positioning System
TIMN seminar GNSS Radio Occultation Inversion Methods Thomas Sievert September 12th, 2017 Karlskrona, Sweden.
Improved radio data analysis with LOPES Katrin Link, for the LOPES Collaboration #0404, ICRC 2011, Beijing.
Content * Overview * Project overall * PF meter * Calculation of firing angle * Generation of firing angle * Results * Comparison * Problems.
Acoustic mapping technology
Data Assimilation Training
Spread Spectrum Audio Steganography using Sub-band Phase Shifting
CJT 765: Structural Equation Modeling
Efficient Estimation of Residual Trajectory Deviations from SAR data
Formosat3 / COSMIC The Ionosphere as Signal and Noise
FTIR multi-touch screen
Surveying Techniques II. GPS
COSMIC Data Analysis and Archival Center
Formosat3 / COSMIC The Ionosphere as Signal and Noise
UWB Receiver Algorithm
Assimilation of Global Positioning System Radio Occultation Observations Using an Ensemble Filter in Atmospheric Prediction Models Hui Liu, Jefferey Anderson,
Loran c R.Ezhilarasan( ) R.Dinesh( )
NOAA/NESDIS/Center for Satellite Applications and Research
Data Assimilation Initiative, NCAR
Effects and magnitudes of some specific errors
Scientific challenges in GPS RO assimilation for weather forecasting
Challenges of Radio Occultation Data Processing
International Civil Aviation Organization
Presentation transcript:

Open Loop Tracking of GPS Radio Occultation for LEOs Chris Bombach*, Changyong Cao, Ph.D.** * University of Texas at El Paso ** NOAA/NESDIS/STAR

Overview Radio occultation of GPS signals received by LEO satellites is an atmospheric sounding technique for retrieving atmospheric profiles from the troposphere via refractivity. This requires a high degree in accuracy to retrieve reliable data. This information is retrieved using the excess phase between the GPS satellite and a LEO satellite. GPS radio occultation shows a depiction quickly and accurately. Allows for vertical scanning of successive layers of the atmosphere.

Radio Occultation Radio occultation is atmospheric sounding technique that uses GPS signals to get a physical profile of the atmosphere a change in GPS signal.

Significance to JPSS These radio occultation profiles are important for numerical weather prediction because they are stable, accurate, and act as anchors for other types of data for assimilation. This is due to the consistency at which data can be collected and at certain times. The JPSS program is considering adding this capability to a future satellite, and STAR is developing new capabilities to support radio occultation missions in the areas of data processing, quality control and monitoring, and algorithm development.

Objective Develop a procedure and algorithm for open loop tracking of GPS signals which would enable the data processing from level 0 to level 1 and 2 to retrieve atmospheric profiles. This requires extracting the residual phase, which is the excess phase generated from refractivity in the atmosphere.

Problems There are limitations in the payload which constrains the antenna size and therefore the signal to noise ratio (SNR), and the ability to penetrate to the lower levels of atmosphere. The traditional method of locking onto a signal, a phase lock loop, is inaccurate at low SNR.

SNR’s Effect on Phase Shifts

Changing Geometry The residual phase depends heavily on the geometry. As the distance between satellites changes there will be a delay. This requires the use of interpolation and measuring the delay between transmission to receiver to get an accurate estimate of the distance between them.

Doppler Effect Since the data can’t be measured directly, more processing is required, this includes identifying the Doppler shifts in the measured phase. These shifts are the information needed to feed into further algorithms.

Doppler Effect

Tracking Methods The open loop tracking method uses received signal and compares it to independently modeled data, compensates for discontinuities, and derives the final excess phase. This is in contrast to more traditional methods. Open Loop tracking is a promising method to help alleviate the SNR problem.

Signal Discontinuities/Cycle Slips They are when there is a rapid change in data received. The reference data does not have these. These lead to bad data points and need to be detected and remedied.

Cross Correlation To check for delays and unusable data the measured and model were cross correlated and normalized.

Cross Correlation

Really Bad Errors

Error Before Correction

Full comparison

Low SNR comparison

High SNR comparison

Residual Phase This is the extracted residual phase

Conclusion Open loop tracking is a viable method for finding Doppler frequency shifts and compensating for cycle slips. At low SNRs there is still a problem but after 60 samples (1.2 seconds) discontinuities become far less of a problem and the retrieved residual phase becomes more accurate.

Future Works More investigation on how to deal with cycle slips and the effect of SNR overall. A method to compare to other instruments’ measurements. Further this information along to get bending angles and the exact refractory index. Coding Concerns: Much of the used algorithm is in Matlab and needs to be converted to C++; mostly the phase unwrapping portion and interpolation techniques Is currently taking ASCII data inputs and has hardcoded file names and paths Fortran90 implementation of cross correlated data is outright wrong and it needs a better method for calculating the boundary at where significant correlation exists.