WAAS Data Independence - PowerPoint PPT Presentation

Loading...

PPT – WAAS Data Independence PowerPoint presentation | free to download - id: 127649-NzNlZ



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

WAAS Data Independence

Description:

ZETA ASSOCIATES. Signal Deformation Background ... ZETA ASSOCIATES. Example Signal Deformations. and Resulting Correlation Functions. Threat Model A: ... – PowerPoint PPT presentation

Number of Views:53
Avg rating:3.0/5.0
Slides: 15
Provided by: faa00720
Learn more at: http://www.faa.gov
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: WAAS Data Independence


1
Page 1
ZETA ASSOCIATES
SQMSBAS Workshop
21 June 2005
2
Overview
  • WAAS IOC Approach
  • Signal Deformation Background
  • WAAS FLP Approach

3
WAAS IOC Signal Deformation Approach
  • WAAS IOC signal deformation detection utilizes
    real-time and offline monitors
  • Real-time monitor protects against most likely
    signal deformation threat while offline monitor
    protects against full ICAO threat model
  • Integrity case for this threat utilized the
    maximum error range residual (MERR) approach and
    a priori event occurrence

4
Signal Deformation Background
  • Differential GPS processing from March 1993
    demonstrated that inclusion of SV-19
    significantly degraded position accuracy
  • Investigations into SV-19 performance concluded
    the satellite suffered a failure such that it
    deformed the transmitted signal
  • Signal deformation resulted in non-common range
    errors across different receiver types
  • Research into GPS signal generation failure modes
    resulted in the definition of the full ICAO
    signal deformation model
  • Signal generation failure modes represented by
    only three parameters (D, fd, s)
  • Model adopted by ICAO in 1999

5
Example Signal Deformations and Resulting
Correlation Functions
6
WAAS IOC Real-time Signal Deformation Monitor
  • Original WAAS design for signal deformation was
    specific to SV-19 fault observed in 1993
  • Little detail for threat available
  • Position error reported in the 3 to 8m range as
    function of the specific correlator spacing used
    to determine pseudorange
  • WAAS monitor relied on MEDLL, narrow and wide
    correlator pseudorange processing
  • Definition/acceptance of full ICAO model resulted
    in expanded WAAS IOC threat
  • Most Likely threat used in IOC WAAS was a
    subset of the full threat model but included the
    most similar waveforms to the SV-19 failure

7
Comparison of Full and Most Likely Threat
Regions
8
Monitor Details
  • IOC signal deformation detection utilizes the
    code-carrier coherence monitor (see reference
    list)
  • Multipath deviations (code-carrier corrected for
    dual freq iono) averaged across the network
  • Correlator data not available
  • Monitor performance and noise characteristics
    validated using 8 days of data with prototype
    algorithm
  • Detection with this monitor results in the
    satellite being set to DU for 9 hours (Remainder
    of satellite pass)

9
Integrity Case
  • Acceptance by the WIPP of a reduced threat was
    deemed sufficient provided later stages of WAAS
    would add real-time monitoring of the full ICAO
    threat model
  • Acceptance was also premised on presence of a
    robust offline monitoring capability
  • Utilization of a MERR approach and a priori event
    occurrence were carefully evaluated by the WIPP
    and deemed acceptable for the signal deformation
    threat
  • MERR concept takes advantage of system margin for
    nominal operation (sUDRE and sUIVE are well
    overbounded quantities)
  • Performance cost with MERR is floor values for
    GIVE and UDRE

10
Rationale for A PrioriSignal Deformation Threat
  • The occurrence of a signal deformation is random
  • The probability of satellite deformation failure
    is small (analysis used 10-4 but case could be
    made for even smaller event occurrence)
  • The exposure time to a signal deformation must
    not be infinite
  • When such a failure is detected the deformation
    is treated very conservatively by setting the
    satellite to DU

11
Rationale for MERRSignal Deformation Threat
  • Large errors are detected readily with high
    probability using real-time monitor
  • Small errors that are not detected with high
    probability are also small enough that they will
    not have significant impact on the User
  • The probability of satellite deformation failure
    is in itself small
  • Offline monitoring will detect the failure and
    thus limit exposure to that threat

12
WAAS IOC Offline Signal Deformation Monitor
  • Offline signal deformation monitor instituted to
    limit exposure time to undetected satellite
    failure with the real-time monitor
  • Offline processing is conducted using data from
    six to eight geographically diverse stations
  • Receivers at these stations output multipath
    correlator measurements for each satellite
    tracked
  • Current processing in transition to 24/7
    operation with analysis/reporting occurring
    during regular business hours
  • GPS satellite failure detected/confirmed with
    this monitoring would result in FAA notification
    to the GPS controlling authority

13
WAAS FLPSignal Deformation Approach
  • Full ICAO Threat Model will be monitored with
    real-time process
  • New WAAS reference receivers (G-II) with
    correlator output functionality begin
    installation this summer
  • Current offline processing is serving as
    prototype for eventual online monitor
  • FLP signal deformation monitor will significantly
    reduce the need for offline monitoring
  • Probably quarterly checks to ensure the noise
    characteristics used in design validation are
    still representative

14
Summary
  • Signal deformation threat in IOC WAAS was
    mitigated with hybrid of real-time and offline
    monitoring
  • Robust offline monitoring was leveraged heavily
    in the integrity case for this threat
  • Led to acceptance of most likely threat (subset
    of full ICAO model), MERR approach and use of a
    priori
  • References
  • P. Shloss, R. Phelts, T. Walter, P. Enge, A
    Simple Method of Signal Quality Monitoring for
    WAAS LNAV/VNAV ION GPS 2001, September 2001
  • K. Shallberg, P. Shloss, E. Altshuler, L.
    Tahmazyan, WAAS Measurement Processing, Reducing
    the Effects of Multipath ION GPS 2001, September
    2001
About PowerShow.com