WO2007096466A1 - procédé de calibrage des phases porteuses de signaux radio provenant de satellites et autres émetteurs par filtrage Fast Kalman - Google Patents

procédé de calibrage des phases porteuses de signaux radio provenant de satellites et autres émetteurs par filtrage Fast Kalman Download PDF

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Publication number
WO2007096466A1
WO2007096466A1 PCT/FI2007/000052 FI2007000052W WO2007096466A1 WO 2007096466 A1 WO2007096466 A1 WO 2007096466A1 FI 2007000052 W FI2007000052 W FI 2007000052W WO 2007096466 A1 WO2007096466 A1 WO 2007096466A1
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WO
WIPO (PCT)
Prior art keywords
values
model
carrier
sensor output
calibration parameters
Prior art date
Application number
PCT/FI2007/000052
Other languages
English (en)
Inventor
Antti Aarne Llmari Lange
Original Assignee
Antti Aarne Llmari Lange
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from FI20060198A external-priority patent/FI20060198A0/fi
Priority claimed from FI20060219A external-priority patent/FI20060219A0/fi
Application filed by Antti Aarne Llmari Lange filed Critical Antti Aarne Llmari Lange
Publication of WO2007096466A1 publication Critical patent/WO2007096466A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections

Definitions

  • the invented method relates primarily to the technological convergence of Satellite Geodesy and Meteorology.
  • the Helmert- Wolf Blocking (HWB) method known from Geodesy since 1880 is expanded to Fast Kalman Filtering (FKF) to cover all security-critical operational applications of Kalman Filtering (KF) such as Navigation, Remote Sensing and Computer Vision.
  • FKF Fast Kalman Filtering
  • Rapid fluctuations of the tropospheric water vapour and the ionospheric electron content are estimated operationally for adjusting the carrier-phases measured by a precision receiver for most reliable navigation, mobile positioning, detection of crustal movement and tsunami warning etc.
  • Local alerts of those meteorological hazards that stem from unexpected concentrations of water vapour like tornados, thunderstorm, fog, ice formation and road slipperiness are included under the general context of Global Monitoring of Environment and Security (GMES).
  • GMES Global Monitoring of Environment and Security
  • FKF Fast Kalman Filtering
  • HWB Helmert- Wolf Blocking
  • Single, Double and/or Triple Differences of the carrier-phases are used for sorting out Integer (lane) Ambiguities of the GNSS carrier-phase measurements in Real-Time Kinematic (RTK) and Virtual Reference Station (VRS) land surveying.
  • RTK Real-Time Kinematic
  • VRS Virtual Reference Station
  • Residual error variances of the carrier-phases are computed operationally using methods based on the Minimum Norm Quadratic Unbiased Estimation (MINQUE) theory for indicating the quality and usefulness of each GNSS signal.
  • MINQUE Minimum Norm Quadratic Unbiased Estimation
  • the blockwisely computed error covariance matrix (Lange, 2001) of the estimated state and calibration parameters gives accuracy information on each adjustment or indicates that Kalman's observability condition is not satisfied.
  • y of the total carrier-phases between the j 4 satellite and the k l1 receiver
  • i index of the signals (Ll, L2, L3,..., Gl,..., El,..., etc.)
  • j index of the satellites (GPS, Glonass and Galileo, etc.)
  • k index of the receivers (or receiver sites)
  • g slant-mapping of the IWV refractivity for the i th signal from the j th satellite to the k receiver at epoch t (see Slant-delay models on pages 39-49 of Kleijer (2004))
  • a t state transition matrix describing the speed and direction of IWV along mean air-flow
  • dA t matrix of those state transition errors that can be adjusted by adaptive Kalman Filter.
  • Adaptive Fast Kalman Filtering is applied to dense receiver and observing networks that are operated with high sampling rates (see Equations (23) and (24) on pages 12-13 in PCT/FI96/00621 of WO 97/18442).
  • BLUE Best Linear Unbiased Estimates
  • IWV integrated water vapour
  • TEC total value of ionospheric electron content
  • y difference of the total carrier-phases between the j th satellite and the k th receiver
  • i index of the signals (Ll, L2, L3,... , Gl,... , El,... , etc.)
  • j index of the satellites (GPS 5 Glonass and Galileo, etc.)
  • k index of the receivers (or receiver sites)
  • g vector of the slant-path 3WV refractivity values of pixel volumes from the j th satellite to the k th receiver at epoch t (see Slant-delay models on pages 39-49 of Kleijer (2004))
  • a t state transition matrix describing advection of the 3WV values in the air-mass
  • dA t matrix of the state transition errors to be adjusted by adaptive Kalman Filtering.
  • Matrix A t is a tangent-linear approximation of the Numerical Weather Prediction (NWP) model that is applied in the data assimilation of the 3WV values at epoch t for obtaining them from their previous values at epoch t-1 (see Equations (26-29) on pages 12-13 in PCT/FI93/00192 of WO 93/22625).
  • Matrix dA t is approximated by a vector r that is estimated by adaptive Fast Kalman Filtering (FKF) (see Equations (22-24) on pages 12-13 in PC17FI96/00621 of WO 97/18442).
  • FKF adaptive Fast Kalman Filtering
  • BLUE Best Linear Unbiased Estimates

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

Les informations orbitales comme celles des systèmes de navigation mondiale par satellite (GNSS) ou autres émetteurs sont collectées pratiquement en temps réel (NRT) par des centres informatiques mondiaux ou locaux comme ceux de l'IGS. Les reconstitutions de phases porteuses des signaux radio provenant de ces émetteurs sont reçues par un réseau de référence local et transmis de manière opérationnelle à un processeur à filtre Fast Kalman (FKF) pour calculer les estimations à la fois des paramètres d'état et des paramètres de calibrage avec des estimations de précision les plus fiables possibles. Ces paramètres d'états comportent typiquement la vapeur d'eau intégrée (IWV) ou la répartition en 3 dimensions de la vapeur d'eau (3WV) de la troposphère locale et la teneur totale en électrons (TEC) de la stratosphère locale. Des réglages de précision des phases porteuses avec des informations de précision nécessaires peuvent alors être produits de manière opérationnelle pour répondre aux besoins locaux et offrir une navigation, un positionnement mobile et une signalisation des dangers environnementaux etc les plus fiables possibles.
PCT/FI2007/000052 2006-02-27 2007-02-27 procédé de calibrage des phases porteuses de signaux radio provenant de satellites et autres émetteurs par filtrage Fast Kalman WO2007096466A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
FI20060198A FI20060198A0 (fi) 2006-02-27 2006-02-27 Nopea menetelmä ilmakehän kokonaiskosteuden ja -elektronitiheyden vaikutusten arvioimiseksi ja korjaamiseksi globaalien navigaatiosatelliittijärjestelmien kantoaaltojen vaiheita käytettäessä
FI20060198 2006-02-27
FI20060219A FI20060219A0 (fi) 2006-03-06 2006-03-06 Nopea menetelmä vesihöyrytomografialle käyttäen globaalien navigaatiosatelliittijärjestelmien kantoaaltojen vaiheita
FI20060219 2006-03-06

Publications (1)

Publication Number Publication Date
WO2007096466A1 true WO2007096466A1 (fr) 2007-08-30

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Application Number Title Priority Date Filing Date
PCT/FI2007/000052 WO2007096466A1 (fr) 2006-02-27 2007-02-27 procédé de calibrage des phases porteuses de signaux radio provenant de satellites et autres émetteurs par filtrage Fast Kalman

Country Status (1)

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WO (1) WO2007096466A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109001382A (zh) * 2018-09-20 2018-12-14 武汉大学 一种基于cors的区域大气水汽实时监测方法及系统
CN110568459A (zh) * 2019-08-28 2019-12-13 桂林电子科技大学 基于igs和cors站的区域电离层tec实时监测方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1993022625A1 (fr) * 1992-05-05 1993-11-11 Antti Aarne Ilmari Lange Procede de filtrage de kalman rapide dans des grands systemes dynamiques
US5323322A (en) * 1992-03-05 1994-06-21 Trimble Navigation Limited Networked differential GPS system
US5506794A (en) * 1989-04-28 1996-04-09 Lange; Antti A. I. Apparatus and method for calibrating a sensor system using the Fast Kalman Filtering formula
WO1997018442A2 (fr) * 1995-11-15 1997-05-22 Antti Aarne Ilmari Lange Procede de filtrage adaptatif de kalman dans des systemes dynamiques
US5867411A (en) * 1996-12-19 1999-02-02 The Aerospace Corporation Kalman filter ionospheric delay estimator

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5506794A (en) * 1989-04-28 1996-04-09 Lange; Antti A. I. Apparatus and method for calibrating a sensor system using the Fast Kalman Filtering formula
US5323322A (en) * 1992-03-05 1994-06-21 Trimble Navigation Limited Networked differential GPS system
WO1993022625A1 (fr) * 1992-05-05 1993-11-11 Antti Aarne Ilmari Lange Procede de filtrage de kalman rapide dans des grands systemes dynamiques
WO1997018442A2 (fr) * 1995-11-15 1997-05-22 Antti Aarne Ilmari Lange Procede de filtrage adaptatif de kalman dans des systemes dynamiques
US5867411A (en) * 1996-12-19 1999-02-02 The Aerospace Corporation Kalman filter ionospheric delay estimator

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
RANNAT K ET AL: "Water vapour tomography for ultra-reliable tracking in air-space surveillance", COST716 FINAL WORKSHOP (KNMI, DE BILT, NL), 3 September 2004 (2004-09-03), XP002434048, Retrieved from the Internet <URL:http://web.archive.org/web/20040903133951/http://www.knmi.nl/samenw/cost716/final-workshop/posters/Rml.pdf> [retrieved on 20070516] *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109001382A (zh) * 2018-09-20 2018-12-14 武汉大学 一种基于cors的区域大气水汽实时监测方法及系统
CN109001382B (zh) * 2018-09-20 2020-05-29 武汉大学 一种基于cors的区域大气水汽实时监测方法及系统
CN110568459A (zh) * 2019-08-28 2019-12-13 桂林电子科技大学 基于igs和cors站的区域电离层tec实时监测方法
CN110568459B (zh) * 2019-08-28 2022-05-10 桂林电子科技大学 基于igs和cors站的区域电离层tec实时监测方法

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