EP2366116A1 - Hybridization device with segregated kalman filters - Google Patents
Hybridization device with segregated kalman filtersInfo
- Publication number
- EP2366116A1 EP2366116A1 EP09771565A EP09771565A EP2366116A1 EP 2366116 A1 EP2366116 A1 EP 2366116A1 EP 09771565 A EP09771565 A EP 09771565A EP 09771565 A EP09771565 A EP 09771565A EP 2366116 A1 EP2366116 A1 EP 2366116A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- measurements
- filter
- bank
- satellite
- state
- Prior art date
- Legal status (The legal status 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 status listed.)
- Withdrawn
Links
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
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
Definitions
- the field of the invention is that of the carriers using information provided both by an inertial unit and by a satellite navigation system, such as a GPS system.
- the invention relates to a closed-loop hybridization device, and relates more particularly to performing hybridization with protection in the sense of integrity of the output data.
- Carriers such as aircraft or boats have many navigation systems. These systems include a hybrid INS / GNSS (Inertial Navigation System and Global Navigation System).
- INS / GNSS Inertial Navigation System and Global Navigation System.
- An inertial unit provides noisy and accurate information in the short term.
- the localization performance of an inertial unit degrades (more or less quickly depending on the quality of the sensors, accelerometers or gyroscopes for example, and treatments used by the plant).
- information acquired from a satellite navigation system is very unlikely to drift in the long term, it is often noisy and variable in accuracy.
- inertial measurements are always available when GPS information is not available or is likely to be deceived and scrambled.
- Hybridization consists of combining the information provided by the inertial unit with the measurements provided by the satellite navigation system to obtain hybrid position and speed information by taking advantage of both systems.
- the accuracy of the measurements provided by the GNSS receiver makes it possible to control the inertial drift and the low noise inertial measurements make it possible to filter the noise on the measurements of the GNSS receiver.
- Modern navigation systems calculate protection radii around the calculated position that can contain the error from true position to a given integrity risk, that's what defines the integrity of a system.
- these protection radii can be calculated by means of a Kalman filter bank which makes it possible to protect against the appearance of a single failure.
- filters hybridize information from the satellite navigation system to that from the inertial unit.
- One of the filter bank filters referred to as the main filter, uses all GNSS measurements consisting of pseudo-measurements and quality information.
- the other filters called secondary filters, use only a part of the available GNSS measurements. If a failure occurs at a satellite measurement, it will not be seen by the filter not receiving this measurement: this filter will remain unpolluted. In the state of the art, integrity is based on the fact that in the event of a satellite failure, one of the bank's filters is not affected by the failure.
- N closed-loop filters are used on N virtual platforms.
- This architecture has the advantages of being insensitive to inertial drift and to present high-performance outputs at high frequency. However, it is expensive in terms of computing load due to the integration of N virtual platforms.
- N closed-loop filters are used on a virtual platform.
- the advantages are the low cost of computing due to the integration of a single virtual platform, while the disadvantages are the sensitivity to inertial drift and the fact that the outputs are performing at the frequency of the filters.
- a satellite failure detection must be implemented in order to select the Kalman filter whose output (state vector) will be applied (as stabilization vector) to the inertial measurements from the virtual platform to recalibrate it.
- this document provides for selecting the main Kalman filter when no failure of one of the satellites is detected, or, when a failure is detected, to select the secondary Kalman filter not affected by the failure.
- the corrections thus come from a single filter (the stabilization vector of the inertial measurements thus being a copy of the state vector estimated by the selected Kalman filter) and where this filter is not affected by a failure.
- satellite one does not come to apply to the inertial measurements of erroneous corrections by propagation of information corrupted by a satellite failure.
- a hybridization device comprising a virtual platform calculating inertial measurements, a Kalman filter bank each developing a hybrid navigation solution to from the inertial measurements of the virtual platform and measurements of signals emitted by a constellation of satellites delivered by a satellite positioning system, characterized in that it comprises, for each filter of the bank, a satellite measurements correction module delivering to the filter the measurements of the satellite positioning system which are used by the filter after correction using the hybrid navigation solution developed by the filter.
- the satellite measurement correction module receives as input the hybrid navigation solutions developed by the filters and the measurements corresponding to the entire constellation delivered by satellite positioning system;
- the measurements of the satellite positioning system which are used by a filter are pseudo-measurements
- the device generates a hybrid output corresponding to the inertial measurements calculated by the virtual platform corrected by a stabilization vector
- the stabilization vector corresponds to a state vector estimated by a filter of the bank not affected by a satellite failure.
- each component of the stabilization vector is developed according to the corresponding components of the set of state vectors estimated by the filters of the bank;
- the device comprises a module for generating the stabilization vector configured, for each component of the stabilization vector (dC [state]), so as: o to analyze the sign of the set of corresponding components of the state vectors; when the set of these corresponding components are not of the same sign, to develop a component of zero value for the stabilization vector; when the set of these corresponding components are of the same sign, to develop a non-zero value component for the stabilization vector, determined according to the value of each of these components of the state vectors.
- the non-zero value of the component of the stabilization vector corresponds to the minimum of the set of corresponding components of the state vectors when all of these components corresponding are positive, and corresponds to the maximum of the set of corresponding components of the state vectors when all of these corresponding components are negative;
- the non-zero value of the component of the stabilization vector corresponds to the average of the P plus, corresponding small components of the state vectors, taken in absolute value;
- the stabilization vector is applied to the input of all the filters of the filter bank
- the Kalman filter bank comprises a main Kalman filter receiving the measurements of the signals emitted by n satellites corrected with the main hybrid navigation solution that it develops, and n secondary Kalman filters each receiving the measurements of the signals emitted by the n satellites excluding a satellite corrected using the secondary hybrid navigation solution that it develops.
- the invention proposes an INS / GNSS hybridization method implementing a bank of Kalman filters each developing a hybrid navigation solution from the inertial measurements calculated by a virtual platform and from measurements of signals transmitted by a satellite constellation delivered by a satellite positioning system, characterized in that the satellite measurements used by each filter of the bank are pre-corrected using the hybrid navigation solution developed by the filter.
- Figure 1 is a diagram illustrating a possible embodiment of a device according to the first aspect of the invention.
- a hybridization device 1 according to a possible embodiment of the first aspect of the invention, intended to be embedded in a carrier such as an aircraft.
- the hybridization device 1 uses information provided by an UMI inertial measurement unit and by a GNSS satellite navigation system.
- the device 1 comprises a single virtual platform 2 and a bank 3 of Kalman filters in parallel.
- the virtual platform 2 receives inertial increments from the sensors (gyroscopes, accelerometers) of a unit of inertial measurements.
- the inertial increments correspond in particular to angular increments and to increments of speed.
- Inertial navigation information (such as the orientation, speed or position of the carrier) is calculated by the virtual platform from these increments. This inertial navigation information is designated PPVI inertial measurements thereafter.
- inertial measurements PPVI are transmitted to a device for calculating pseudo-distances estimated a priori (not shown in Figure 1) which also receives data on the position of the satellites.
- the device for calculating pseudo-distances estimated a priori calculates the pseudo-distances a priori between the carrier and the different visible satellites of the carrier. .
- the hybridization device 1 also receives from the GNSS satellite navigation system the pseudo-measurements between the carrier and the different visible satellites.
- the discrepancies (called observations) are then classically calculated between the pseudo-measurements estimated a priori and the pseudo-measurements delivered by the GNSS system.
- the hybridization device 1 further comprises a Kalman filter bank 3 which hybridises between the inertial information coming from the inertial unit and the information from the satellite navigation system.
- the role of the filters is to maintain the virtual platform 2 in a linear operating area image of that modeled in the Kalman filter each estimating a state vector dXO-dXn (generally having the order of 30 components).
- the filterbank 3 comprises several Kalman filters in parallel.
- One of the filters is called the main Kalman filter 8: it takes into account all the observations (and receives all the measurements from the GNSS system) and elaborates a main hybrid navigation solution.
- the other filters 9i, 9n are called secondary filters: they take into account only a part of the observations, for example (n-1) observations among the n observations relating to the n visible satellites so that the i-th Kalman filter Secondary 6i receives from the GNSS system the measurements of all satellites except the i-th, and each develop a secondary hybrid navigation solution.
- FIG. 1 shows only a single module for correcting the satellite measurements 4. It will be understood, however, that the hybridization device 1 according to the first aspect of the invention comprises a satellite measurements correction module. 4 by bank filter.
- the device 1 comprises a bench of summators 10, where each summator is positioned at the output of the filter bank to add to the state vector dXO-dXn elaborated by a filter the hybrid output SH which will be presented in more detail later.
- the reference navigation (hybrid output SH) produced by the device 1 is only used internally. It is thus the information delivered at the output of the summator bank 7 that provides the optimal navigation solutions (main navigation solution NAV INS / GPS 0 from the main Kalman filter, secondary navigation solution NAV INS / GPS i "derived from the secondary Kalman filter of index i).
- the raw measurement correction module 4 associated with a filter of the bank receives as input the satellite measurements (typically pseudo matters) used by the filter corresponding to all (main Kalman filter) or part (secondary Kalman filter) of the all of the constellation delivered by GNSS satellite positioning system, and outputs for each of the filters of the bank 3 said satellite measurements used by the filter after implementation of a deterministic error correction model developed from the hybrid navigation solution estimated by the filter. The calculation of the observations is then made on the basis of these satellite measurements corrected from the information of the filter, and not from the information of the GNSS system as is conventionally the case.
- the pseudo-measurements performed by a GNSS receiver are corrected inside this same receiver. Indeed deterministic errors can be corrected largely by using models that require positioning information to be calculated. It is proposed in the context of the invention to make this correction not in the receiver but for each filter of the bank, on the basis of the position estimated by the filter. Specifically, the errors that affect GNSS raw measurements are modeled. The modeling of atmospheric errors is dependent on the estimated navigation parameters. By adding (positively or negatively according to the errors and the type of measurement) the value of the error calculated by model to the gross measurement, we correct in part the error which is modeled. The error residue is then modeled statistically and characterized by a standard deviation calculated from the navigation parameters.
- the addition (positive or negative) of errors calculated by model to gross measurements is performed by the GNSS receiver, so that the entire filter bank receives corrected measurements and error residual modeling. It follows that the calculation of the error models and standard deviations of the residuals is then dependent on the position calculated by the GNSS receiver.
- the invention proposes to deport this calculation of the error models and the standard deviations of the residues, as well as the application of the models to the raw measurements in the module correction of the satellite measurements 4, and to perform the calculations for each filter from the navigation parameters specific to each filter. In this way, the corrected measurements received by a filter are no longer dependent on the navigation parameters estimated by the GNSS receiver. Therefore, in the event of a satellite failure, the corrected measurements received by the filter that does not use the failed satellite are not affected.
- the main Kalman filter receives from module 4 all the pseudo-measures, corrected with the aid of the main navigation solution that it develops.
- the secondary Kalman filter of index i 9i receives meanwhile from module 4 all the pseudo-measurements with the exception of that corresponding to the satellite of index i, corrected using the secondary navigation solution that it develops.
- the filter which does not use the pseudo-measure polluted by the appearance of a failure is not affected by the failure (its solution of unpolluted navigation the failure makes it possible to correct the pseudo matters that it uses), and consequently it remains unpolluted.
- the hybridization device 1 produces a hybrid output SH corresponding to the PPVI inertial measurements calculated by the virtual platform 2 and corrected by a stabilization vector dC.
- the corrections to be applied to the inertial measurements come from a single Kalman filter.
- the stabilization vector is equal to the correction vector estimated by the selected Kalman filter.
- the selection is effected for example according to EP1801539 A by detecting a possible satellite failure.
- the stabilization vector is elaborated component by component, using for each component the set of state vectors estimated by the Kalman filters.
- the device 1 comprises for this purpose a development module of the correction 5 configured to develop each of the components dC [state] of the stabilization vector dC according to the set of corresponding components dXO [state] -dXn [state] of the correction vectors dXO-dXn.
- the correction elaboration module 5 is configured, for each component dC [state] of the stabilization vector dC, so as to: analyzing the sign of the set of corresponding components dXO [state] -dXn [state] of the correction vectors estimated by the Kalman filters; and
- the correction elaboration module 5 is configured in such a way that the non-zero value of the component of the stabilization vector dC [state] corresponds to the minimum of the set of corresponding components dXO [state] -dXn [ state] of the correction vectors when these components dXO [state] -dXn [state] are all positive, and corresponds to the maximum of the set of components dXO [state] - dXn [state] of the correction vectors when these components dXO [ state] - dXn [state] are all negative.
- the correction elaboration module 5 can be configured in such a way that the non-zero value of the component of the stabilization vector dC [state] corresponds to the average of the smaller Ps (P being, for example, equal to 2) corresponding components dXO [state] - dXn [state] of the correction vectors, taken in absolute value.
- the stabilization vector developed in accordance with this possible embodiment of the invention makes it possible to minimize the estimated errors for all the filters.
- the stabilization vector proves judicious insofar as it is not constrained by a fault detection and exclusion mechanism (FDE mechanism according to the English terminology "Fault Detection and Exclusion”), and where the validity of the protection radii is not constrained by an EDF.
- FDE mechanism fault detection and exclusion mechanism
- EDF error Detection and Exclusion
- the stabilization vector dC thus produced by the module 5 or simply selected from the state vectors of the filters makes it possible to correct, with a delay 6, the PPVI inertial measurements calculated by the virtual platform, using conventionally known per se a subtractor 7.
- the hybrid output SH is looped back to the input of the virtual platform.
- the stabilization vector dC can be applied to the input of all the filters of the filter bank. In this way, the Kalman filters adjust by subtracting from their estimate (correction vector dX) the correction dC, and are thus kept consistent with the virtual platform.
- the architecture proposed by the invention has the following advantages.
- the filters of the bank are completely segregated; the calculation of the stabilization control of the platform is not constrained by a fault detection method.
- the invention is also not limited to a hybridization device according to its first aspect, but also extends to an INS / GNSS hybridization method implementing a bank of Kalman filters each developing a navigation solution. hybrid based on the inertial measurements calculated by a virtual platform and measurements of signals emitted by a constellation of satellites delivered by a satellite positioning system, characterized in that the satellite measurements used by each filter of the bank are corrected beforehand. help of the hybrid navigation solution developed by the filter.
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- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
- Navigation (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR0858726A FR2939901B1 (en) | 2008-12-17 | 2008-12-17 | KALMAN SEGREGES FILTER HYBRIDIZATION DEVICE |
PCT/EP2009/067333 WO2010070011A1 (en) | 2008-12-17 | 2009-12-16 | Hybridization device with segregated kalman filters |
Publications (1)
Publication Number | Publication Date |
---|---|
EP2366116A1 true EP2366116A1 (en) | 2011-09-21 |
Family
ID=40911014
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP09771565A Withdrawn EP2366116A1 (en) | 2008-12-17 | 2009-12-16 | Hybridization device with segregated kalman filters |
Country Status (4)
Country | Link |
---|---|
US (1) | US8625696B2 (en) |
EP (1) | EP2366116A1 (en) |
FR (1) | FR2939901B1 (en) |
WO (1) | WO2010070011A1 (en) |
Families Citing this family (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10746881B2 (en) * | 2017-08-09 | 2020-08-18 | Rohde & Schwarz Gmbh & Co. Kg | Measuring device and measuring method for testing a location tracking employing real time kinematics |
US11402514B2 (en) | 2020-07-10 | 2022-08-02 | Samsung Electronics Co., Ltd. | Geographical feature/artificial structures detection and application for GNSS navigation with map information |
CN113156999B (en) * | 2021-05-08 | 2022-11-11 | 一飞(海南)科技有限公司 | Cluster formation airplane abnormal fault level processing method, system and application |
FR3130399B1 (en) | 2021-12-14 | 2024-01-26 | Safran Electronics & Defense | Satellite navigation method with detection of broken satellite by statistical processing of cross innovation |
Family Cites Families (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5991691A (en) * | 1997-02-20 | 1999-11-23 | Raytheon Aircraft Corporation | System and method for determining high accuracy relative position solutions between two moving platforms |
FR2866423B1 (en) * | 2004-02-13 | 2006-05-05 | Thales Sa | DEVICE FOR MONITORING THE INTEGRITY OF THE INFORMATION DELIVERED BY AN INS / GNSS HYBRID SYSTEM |
US7373223B2 (en) * | 2004-02-13 | 2008-05-13 | The Boeing Company | Global navigation satellite system landing systems and methods |
US7317977B2 (en) * | 2004-08-23 | 2008-01-08 | Topcon Positioning Systems, Inc. | Dynamic stabilization and control of an earthmoving machine |
JP5127128B2 (en) * | 2004-12-21 | 2013-01-23 | 韓國電子通信研究院 | Camera position and orientation information correction method and apparatus |
US7609204B2 (en) * | 2005-08-30 | 2009-10-27 | Honeywell International Inc. | System and method for dynamically estimating output variances for carrier-smoothing filters |
FR2895073B1 (en) * | 2005-12-20 | 2008-02-08 | Thales Sa | CLOSED LOOP HYBRIDIZATION DEVICE WITH MONITORING THE INTEGRITY OF MEASUREMENTS. |
US8600660B2 (en) * | 2006-09-29 | 2013-12-03 | Honeywell International Inc. | Multipath modeling for deep integration |
FR2906893B1 (en) * | 2006-10-06 | 2009-01-16 | Thales Sa | METHOD AND DEVICE FOR MONITORING THE INTEGRITY OF INFORMATION DELIVERED BY AN INS / GNSS HYBRID SYSTEM |
US20080114546A1 (en) * | 2006-11-15 | 2008-05-15 | Space Systems/Loral, Inc. | Image navigation and registration accuracy improvement using parametric systematic error correction |
US7869811B2 (en) * | 2007-05-01 | 2011-01-11 | Nokia Corporation | Determination of a relative position of a satellite signal receiver |
US9593952B2 (en) * | 2007-10-04 | 2017-03-14 | Trusted Positioning, Inc. | System and method for intelligent tuning of Kalman filters for INS/GPS navigation applications |
-
2008
- 2008-12-17 FR FR0858726A patent/FR2939901B1/en active Active
-
2009
- 2009-12-16 EP EP09771565A patent/EP2366116A1/en not_active Withdrawn
- 2009-12-16 WO PCT/EP2009/067333 patent/WO2010070011A1/en active Application Filing
- 2009-12-16 US US13/139,720 patent/US8625696B2/en active Active
Non-Patent Citations (1)
Title |
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See references of WO2010070011A1 * |
Also Published As
Publication number | Publication date |
---|---|
US8625696B2 (en) | 2014-01-07 |
US20110243194A1 (en) | 2011-10-06 |
FR2939901B1 (en) | 2011-02-18 |
WO2010070011A1 (en) | 2010-06-24 |
FR2939901A1 (en) | 2010-06-18 |
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