WO2015189144A1 - Procédé et système de correction de données de mesure et/ou de données de navigation d'un système de détection de base - Google Patents

Procédé et système de correction de données de mesure et/ou de données de navigation d'un système de détection de base Download PDF

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Publication number
WO2015189144A1
WO2015189144A1 PCT/EP2015/062694 EP2015062694W WO2015189144A1 WO 2015189144 A1 WO2015189144 A1 WO 2015189144A1 EP 2015062694 W EP2015062694 W EP 2015062694W WO 2015189144 A1 WO2015189144 A1 WO 2015189144A1
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Prior art keywords
data
measurement data
navigation
vehicle
sensor
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PCT/EP2015/062694
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German (de)
English (en)
Inventor
Nico Steinhardt
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Continental Teves Ag & Co. Ohg
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Priority to EP15728488.6A priority Critical patent/EP3155372A1/fr
Publication of WO2015189144A1 publication Critical patent/WO2015189144A1/fr

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    • 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
    • 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

Definitions

  • the invention relates to a method for the correction of measurement data and / or navigation data of a sensor base system according to the preamble of claim 1, a system for the correction of measurement data and / or navigation data of a sensor base system according to the preamble of claim 11 and a use of the system.
  • sensor fusion methods are already known in this context, which are usually also suitable for correcting or filtering measurement data from different sensors or sensor systems.
  • automotive sector in particular, special requirements have to be taken into account, since a large number of different sensors have a common environment or situation. detects a motor vehicle condition by means of different measuring principles and this environment situation or this motor vehicle state by means of a Variety of different measurement data describes.
  • sensor fusion applicable in the automotive sector the greatest possible robustness against incidental disturbances and identification and compensation of systematic errors is required.
  • temporal influences on the measured data must be corrected and temporary failures or the unavailability of sensors bridged.
  • DE 10 2012 216 215 A1 describes a sensor system which comprises a plurality of sensor elements and a signal processing device.
  • the signal processing device is designed so that it evaluates the sensor signals of the sensor elements at least partially together. Furthermore, the signal processing device is designed such that the
  • Measurement data of physical quantities each time information is assigned, which includes information about the time of each measurement directly or indirectly, wherein the signal processing device takes into account this time information at least in the generation of a fusion data set in a fusion filter.
  • measurement data are used which either have matching time information or-if no measurement data with matching time information is available-a corresponding measured value with the required time information is created by means of interpolation.
  • the fusion filter assumes that error values of the measured data change only negligibly over a defined period of time.
  • a sensor system comprising several sensor elements.
  • the sensor elements are formed so that they cover at least partially different primary measured variables and at least partially under use ⁇ Kunststoffliche measuring principles. From the primary measured variable of the sensor elements, at least in part further measured quantities are derived.
  • the sensor system comprises a signal processing device, an interface device and a plurality of functional devices.
  • the sensor elements as well as all functional devices are connected to the signal Processing device connected.
  • the primary measured variables thus provide redundant information that can be compared with one another in the signal processing device or can support one another. From the comparison of the observables calculated on different ways, conclusions can be drawn on the reliability and accuracy of the observables.
  • the signal processing device qualifies the accuracy of the observables and makes the observables, together with an accuracy specification, available to various functional devices via an interface device.
  • DE 10 2012 216 211 A1 describes a method for selecting a satellite, wherein the satellite is a satellite of a global navigation system. Before such a satellite is used to determine the position or of a vehicle, the received GNSS signals are plausibilized in different ways. Each un ⁇ ter Kunststofferie redundancies or known relationships from ⁇ be used for this verification.
  • DE 10 2012 216 211 A1 discloses, for example, determining from the signal of a satellite both the distance of the vehicle to the satellite and the relative speed of the vehicle to the satellite. The distance can be determined by means of the transit time of the signal, while the Relativge ⁇ speed can be determined by means of a phase measurement of the signal.
  • the distance and the relative speed depend on each other, they can be verified against each other. Furthermore, a verification of the values determined from the signal can take place against known boundary conditions, since a vehicle usually travels within a certain speed frame. It is also described that when several signals from different satellites are received, the distances to several satellites are determined and these distances are simultaneously verified by means of trigonometric correlations and the known distance of the satellites from one another. Finally, a verification of the distance determined from the signal or the speed determined from the signal by means of other sensors, which likewise permit a position determination or speed determination, is also possible. possible. Provided that the signals of a satellite can not be verified, this satellite is not used for Positionsbe ⁇ humor or to the velocity determination.
  • the invention relates to a method for correcting measurement data and / or navigation data of a sensor-based system
  • the sensor base system and at least another Sen ⁇ sorsystem Measurement data acquisition wherein the measurement data describe directly and / or indirectly navigation data, the navigation data from the measurement data and / or from known physical and / or mathematical relationships indirectly described are calculated, wherein the navigation data of at least a Speed, wherein by means of the measurement data and / or the navigation data of the at least one further sensor system a determination of error values of the measurement data and / or the navigation data of the sensor base system takes place, the error values being corrected by applying corrections,
  • the at least one further sensor system also detected in vehicle-fixed or in topocentric coordinates and wherein the determination of the error values of at least the speed takes place in vehicle-fixed coordinates.
  • vehicle-fixed coordinates means that an orientation-independent attachment of speeds measured in vehicle-fixed coordinates becomes possible and the uncertainties of the measured data or navigation data are still correctly described.
  • Ver ⁇ applicability of fixed to the vehicle measured and measured in topocentric corrections j edem operating state is reached.
  • a particular advantage of the invention is thus in particular that error values for a speed can be determined better and more reliable and corrections for the speed or be ⁇ can be taken within more reliable.
  • Topocentric coordinates are understood to mean coordinates that correspond to a given surface, e.g. the whole world, are fixed.
  • Vehicle-fixed coordinates are understood to mean coordinates that always have the observer in their origin.
  • the vehicle-fixed coordinates represent a Cartesian coordinate system.
  • the corrections preferably correspond to the negative error values.
  • the variances of the error values are also calculated.
  • the attachment of the corrections of the error values of at least the speed takes place in vehicle-fixed coordinates.
  • the topocentric coordinates are local topocentric coordinates aligned along the geographic directions.
  • the sensor base system comprises an inertia navigation system
  • the inertial navigation system as a sensor base system has the advantage that it has the comparatively highest availability, since it has a ver ⁇ comparatively high output rate of the detected input data and also works largely independently of external disturbances.
  • the at least one further sensor system is an odometry navigation system which detects the speed in vehicle-fixed coordinates.
  • Odometry navigation system determines the speed e.g. About the known rolling circumference of the motor vehicle tires and thus enables a position determination taking into account the steering angle in the context of a dead reckoning.
  • a second further sensor system is a global satellite navigation system which outputs the speed in topocentric coordinates.
  • Satellite navigation system may be, for example, a so-called GPS navigation system, which detects the speed in earth-fixed Cartesian coordinates and converts them into topocentric coordinates in a multistage method known to those skilled in the art. It is particularly expedient that the satellite navigation system comprises at least two satellite signal receivers. Thus it improves the quality of the acquired satellite signals and thus the reliability and accuracy of the satellite navigation system.
  • the navigation data further comprise at least one position and one orientation.
  • This navigation information generally allows a comparatively good navigation guidance.
  • a speed can also be included, which allows a further improved navigation guidance.
  • the navigation data of the sensor base system and of the at least one further sensor system are merged to form a fusion data set.
  • a common merger record is relative to the individual navigation information is generally reliable and accurate, and in particular it allows using an error estimate a ver ⁇ tively reliable assessment of the accuracy or reliability ⁇ to the merged input data or navigation information.
  • the error values are determined by means of an eror-state-space filter, in particular by means of an eror-state-space Kalman filter.
  • the erorr State-space filter represents a fusion filter for the fusion of the output data or navigation information, in particular for the fusion of normally distributed output data or navigation information.
  • a special feature of ER- ror state-space filter is to be estimated, or instead of Sen ⁇ sorsignale and the input data only error values domestic krementell determined and then corrected.
  • the error values namely have a signi ficantly lower ⁇ temporal dynamics than the output data itself, whereby a significant decoupling of the dynamics of the ER- ror state-space filter on the characteristics of Sensorba ⁇ sissystems or the at least one correction system
  • the invention further relates to a system for correcting measurement data and / or navigation data of a sensor base system comprising a sensor base system, at least one further sensor system and a fusion filter, wherein the sensor base system and the at least one further sensor system are designed to acquire measurement data.
  • the measurement data directly and / or indirectly describe navigation data
  • the fusion filter is configured to calculate indirectly described navigation data from the measurement data and / or from known physical and / or mathematical relationships, the navigation data comprising at least one speed
  • the Fusion filter is adapted to make a determination of error values of the measured data and / or the navigation data of the sensor base system by means of the measurement data and / or the Na ⁇ vigationsteil the at least one further sensor system
  • the fusion filter is adapted to the error values by means of a mounting corrections to correct
  • the sensor base system is adapted to detect in vehicle-fixed or in topocentric coordinates
  • the at least one further sensor system is adapted to also detect in vehicle-fixed or in topocentric coordinates
  • the Fusio nsfilter is designed to make the determination of the error values of at least the speed in vehicle-fixed coordinates.
  • the system according to the invention thus comprises all devices necessary for carrying out the method according to the invention.
  • the invention relates to a use of the system according to the invention in a motor vehicle. 1
  • Fig. 1 by way of example a possible embodiment of a system according to the invention, which is designed for position ⁇ determination, in a motor vehicle and
  • FIG. 2 shows by way of example a further possible embodiment of a system according to the invention, which is likewise designed for position determination, in a motor vehicle.
  • Fig. 1 shows a schematic representation of an embodiment of the system according to the invention, which is provided for arrangement and use in a motor vehicle (not shown).
  • the illustrated system is designed, for example according to the positi ⁇ onsbetician of the motor vehicle.
  • the system includes inertial navigation system 101 configured to sense at least the accelerations along first, second, and third axes and at least the yaw rates about the first, second, and third axes.
  • the first axis corresponds, for example according to the longitudinal axis of the motor vehicle
  • the second axis corresponds to the transverse axis of the motor vehicle
  • the third axis corresponds to the vertical axis of the motor vehicle.
  • Inertial navigation system 101 forms, for example, the so-called sensor-based system, the measured data of which are described below be corrected described further sensor systems or the so-called. Correction systems.
  • the correction systems are Odometrienavigationssystem 103 and Satellitennavigationssys ⁇ tems 104th
  • the system also has a so-called.
  • Strapdown algorithm unit 102 in which a so-called. Strapdown algorithm is performed, by means of which the measurement data of inertial navigation system 101, among other things, in position data are converted. For this, the measurement data from inertial navigation system 101, which naturally describe Accelerat ⁇ fixing certificates, integrated twice over time. Also, an alignment of the motor vehicle is determined by means of simple Integ ⁇ ration of the respective measurement data of Trägheitsnavigati- onssystem 101 over time. By means of a single ⁇ integration over time, the orientation and speed of the motor vehicle can be further determined. In addition, strap-down algorithm unit 102 compensates for acting on Träg ⁇ integrated navigation system 101 Coriolis force.
  • the speed, the acceleration and the rate of rotation of the motor vehicle for example according to said three axes of the motor vehicle coordinate system and, for example, additionally in each case based on a topocentric Koordina ⁇ tensystem, which is suitable for describing the orientation or of dynamic variables of the motor vehicle in the world.
  • the said topocentric coordinate system is a GPS coordinate system.
  • the output data from strapdown algorithm unit 102 includes the position with respect to the vehicle coordinate system and the orientation with respect to the topocentric coordinate system.
  • Strapdown algorithm unit 102 the variances as information about the data quality of the above physical quantities or navigation information. For example, these variances are not included in strapdown algorithm unit 102. but only used by this and forwarded.
  • the values calculated by the strapdown algorithm unit 102 og phy sical ⁇ sizes or navigation information is output via output module 112 and provided to other vehicle systems.
  • the system also includes odometry navigation system 103 in the form of wheel speed sensors for each wheel of the motor vehicle.
  • odometry navigation system 103 is a four-wheeled motor vehicle with four wheel speed sensors, each detecting the speed of their associated wheel and its direction of rotation.
  • odometry navigation system 103 comprises a steering angle sensor element which detects the steering angle of the motor vehicle.
  • Satellite navigation system 104 which is designed so that it determines the distance between each associated satellite and the vehicle and the speed between the associated satellite and the vehicle.
  • satellite navigation system 104 for example according ⁇ fusion filter 105, a start position or start position information providing, or at least at the start. Turn on the system.
  • the system also includes fusion filter 105.
  • Fusion filter 105 provides a fusion data set 106 as the measurement data from the odometry navigation system 103, satellite navigation system 104, and inertial navigation system 101 are shared. Fusion data set 106 has the acquired measurement data of the different sensor systems, wherein fusion data set 106 includes, for example, additional error values and variances associated with the error values which describe the data quality.
  • Inertial navigation system 101 represents the so-called sorbase system, while odometry navigation system 103 and satellite navigation system 104 represent the so-called correction systems whose measurement data or navigation information is used to correct the values of the sensor-based system, provided they have been made plausible.
  • the measured data or Navigation information of the sensor base system ie the measurement data or navigation information of the inertial navigation system 101, stored for 25 measurement periods.
  • the required measurement data or navigation information is interpolated from the stored measurement data or navigation information.
  • the measurement data or navigation information of the correction systems ie of satellite navigation system 104 and of
  • Odometry navigation system 103 are not stored.
  • fusion data set 106 provided by fusion filter 105 includes that which has been checked for plausibility
  • Measurement data or navigation information of the correction systems determined quantitative error of the sensor base system, by means of the measurement data or navigation information of the sensor base system.
  • Strapdown algorithm unit 102 is now corrected by Fu ⁇ sion data record 106, the measurement data or navigation information of the sensor base system.
  • Fusion data set 106 is calculated by fusion filter 105 from the measurement data or navigation information from odometry navigation system 103, satellite navigation system 104 and inertial navigation system 101.
  • fusion filter 105 is embodied as an Errator-State-Space Kalman filter, that is to say as a Kalman filter, which in particular carries out a linearization of the measured data or navigation information and in which the quantitative error values of the measured data or navigation information are calculated or estimated and which operates se ⁇ quentiell and thereby the measurement data or values available in the respective functi ⁇ onsön the sequence.
  • Fusion filter 105 is designed to always be asynchronously the most recent of inertial navigation system 101,
  • Odometrium navigation system 103 and satellite navigation system 104 available measured data or values.
  • the measured data or values are thereby routed via motor vehicle model unit 107 and alignment model unit 109.
  • the motor vehicle model unit 107 is configured to derive from the measurement data or navigation information of
  • At least the velocity along a first axis, the velocity along a second axis and the rate of rotation about a third axis calculates and provides these fusion filters 105.
  • the system also includes tire parameter estimation unit 110, which is designed such that it calculates at least the semia ⁇ knife, for example, the dynamic radius of all wheels and additionally calculates the slip stiffness and the slip stiffness of all wheels and this Kraft ⁇ vehicle model unit 107 beit Rail as additional input variables , Tire parameter estimation unit 110 is further configured to use a substantially linear Rei ⁇ fenmodell for calculating the tire sizes.
  • the example according to inputs from ReifenparameterMt- wetting unit 110 are the wheel speeds and the steering angle descriptive data, at least partially, the output values of the strapdown algorithm unit 102, as well as certain of fusion ⁇ filter 105 variances.
  • the system also includes
  • GPS error detection and plausibility unit 111 which is designed such that, for example, it receives as input data the measurement data or navigation information from satellite navigation system 104 as well as at least partial measurement data or
  • GPS error detection and-plausibilization 111 examines the measurement data or navigation information to a tellitennavigationssystem to Sa- 104 adapted stochastic Mo ⁇ dell. If the measured data or navigation information corresponds to the model within the framework of a tolerance that takes account of the noise, then it is checked for plausibility. In this case, GPS error detection and plausibility check unit 111 is additionally connected to data-level fusion filter 105 and transmits the plausible measured data or navigation information to fusion filter 105. GPS error detection and plausibility check unit 111 is configured by way of example to provide a method for selecting a satellite inter alia by means of the following method steps:
  • the predetermined condition is a maximum permissible deviation of the position data from the reference position data
  • - the maximum allowable deviation from a standard deviation depends ⁇ , which is calculated based on a sum of a reference variance for the reference position data and a measurement variance for the position data
  • the maximum allowable deviation corresponds to a multiple of the standard deviation such that a probability that the position data fall in a dependent of the Standardab ⁇ scattering interval falls below a predetermined threshold.
  • the system also has standstill detection unit 108, which is designed such that it can detect a stoppage of the motor vehicle and, in the event of a detected standstill of the motor vehicle, at least fusion filter 5 provides information from a standstill model.
  • standstill detection unit 108 which is designed such that it can detect a stoppage of the motor vehicle and, in the event of a detected standstill of the motor vehicle, at least fusion filter 5 provides information from a standstill model.
  • the standstill detection unit 108 is designed in such a way that it uses as input data the sensor signals of the wheel speed sensors of
  • Odometry navigation system 103 and the sensor signals of inertial navigation system 101 uses.
  • the system uses a first group of measurement data or navigation information relating to a motor vehicle coordinate system, ie vehicle-fixed coordinates, and additionally a second group of measurement data or navigation information relating to a topocentric coordinate system.
  • topocentric coordinates are determinable.
  • an independent, but also a simultaneous, usability of vehicle-measured and in topocentrically measured corrections in each operating state is achieved.
  • the uncertainty of the orientation angles and the resulting increase in the uncertainty of the position is determined correctly and can be applied as a correction.
  • Alignment model unit 109 uses all of the output data from strapdown algorithm unit 102.
  • Alignment model unit 109 is, for example according formed so that they have an in ⁇ formation calculated in addition to the orientation angle on the quality of the orientation angle in the form of a variance and provides fusion filter 105th
  • Fusion filter 105 uses the orientation angle and the variance of the orientation angle in its calculations, which it passes via fusion data set 106 to strapdown algorithm unit 102.
  • Fusion filter 105 thus acquires the measurement data or navigation information from inertial navigation system 101, the
  • Fig. 2 shows an example of another possible embodiment of a system according to the invention, which is also designed for Posi ⁇ tion determination, in a motor vehicle (not shown).
  • the system comprises, for example according to Trägheitsna ⁇ vigationssystem 201, GPS 204, and 203 Odometrienavigationssystem as different sensor systems.
  • Inertial navigation system 201, Satellitennavigati ⁇ onssystem Odometrienavigationssystem 204 and 203 provide data that describe, directly or indirectly navigation data, namely a position, a speed, a Accelerat ⁇ n Trent, an orientation, a yaw rate or a
  • the output of the measurement data or navigation information takes place via a vehicle data bus.
  • satellite navigation system 204 outputs its measurement data or navigation information in raw data form.
  • Motor vehicle inertial navigation system 201 which is a so-called MEMS IMU
  • Inertial navigation system 201 comprises three yaw rate sensors which mutually register orthogonally and three acceleration sensors which detect each other orthogonally in each case.
  • Sa ⁇ tellitennavigationssystem 204 includes a GPS receiver, which initially carries out over the satellite signal propagation time Entfer ⁇ voltage measurements to the receivable GPS satellites and also stretch out the change of the satellite signal transit time as well as additionally from the change in the number of wavelengths of the satellite signals, a distance traveled by the vehicle path ⁇ certainly.
  • Odometrienavigationssystem 203 includes depending ⁇ wells a wheel speed sensor at each wheel of the motor vehicle, and a Lenwinkelsensor. The wheel speed sensors each determine the Radcardgschwindmaschine their associated wheel and the steering angle sensor determines the chosen steering angle.
  • Inertial navigation system 201 outputs its measurement data or navigation information to preprocessing unit 206 of inertial navigation system 201.
  • Pre-processing unit 206 now corrects the measurement data or navigation information by means of correction values, which pre-processing unit 206 receives from fusion filter 205.
  • Strapdown algorithm module 207 now makes a position determination based on the corrected measurement data or navigation information from preprocessing unit 206.
  • This Po ⁇ sitionsbetician is a so-called.
  • Dead reckoning based on inertial navigation system 201.
  • Strapdown algorithm module 207 further compensates for a Coriolis force acting on inertial navigation system 201, which affects the measurement data or Navigation information from inertial navigation system 201. To determine the position leads
  • Strapdown algorithm module 207 a two-fold integration of the measurement data captured by the inertial navigation system 201 or navigation information that describe accelerations over time. This allows an updating of a previously known position as well as an updating of a previously known orientation of the motor vehicle. To determine a speed or a rotation rate of the motor vehicle, strapdown algorithm module 207 performs a simple integration over time of the measurement data or navigation information acquired by inertial navigation system 201. Furthermore, strapdown algorithm module 207 also corrects the determined position by means of corresponding correction values of fusion filter 205. Fusion filter 205 in this example performs the
  • the so-called strapdown algorithm module 207 performs.
  • Strapdown algorithm is computationally only slightly complex and can therefore be realized as a real-time capable sensor base system. It represents a procedure for integrating the measurement data or navigation information from inertial navigation system 201 into speed, orientation and position and contains no filtering, so that an approximately constant latency and group delay result.
  • sensor base system describes the one sensor system whose measurement data or navigation information is corrected by means of the measurement data or navigation information of the other sensor systems, the so-called correction systems.
  • the correction systems are Odometrienavigationssystem 203 and to satellite navigation system ⁇ 204th
  • Inertial navigation system 201, preprocessing unit 206 of inertial navigation system 201 and strapdown algorithm module 207 form, by way of example, the so-called sensor-based system, to which fractionally also fusion filter 205 is counted.
  • Output module 212 relays the measured data or navigation information determined and corrected by strapdown algorithm module 207 to any other systems of the motor vehicle.
  • the measurement data acquired by satellite navigation system 204 are, for example, in the form of sensor signals via a so-called UART data connection, first forwarded to preprocessing unit 208 of satellite navigation system 204.
  • Pre-processing unit 208 determines from the output from satnav ⁇ gationssystem 204 measuring data representing raw GPS data, and also include a description of the orbit of each GPS signal transmitting GPS satellite, a position and a speed of the motor vehicle
  • satellite navigation system 204 determines a relative speed of the motor vehicle to the GPS satellites from which GPS signals are received.
  • preprocessing unit 208 corrects a time error of a receiver clock of satellite navigation system 204 caused by drift of the receiver clock contained in the measurement data, and by means of a correction model, the changes in the signal propagation time and the caused by atmospheric influences on the GPS signals transmitted by the GPS satellites pathway.
  • the correction of the time error as well as the atmospheric influences take place by means of correction values obtained by fusion filter 205.
  • Satellite navigation system 204 is still approximately feasibility check module 209 associated with which the measurement data or Navigationsinforma- output by preprocessing unit 208 ⁇ tions, ie the position and the speed of the vehicle ⁇ , plausibilinstrument.
  • the plausibility data or navigation information plausibilized by plausibility module 209 are then output to fusion filter 205.
  • the system further comprises preprocessing unit 210 of odometry navigation system 203, which includes those of
  • Odometrienavigationssystem 203 receives recorded measurement data or navigation information.
  • the acquired measurement data or navigation information are the measurement data or navigation information of the individual wheel speed sensors as well as the measurement data or navigation information of the steering angle sensor.
  • Pre-processing unit 210 now determines the position and orientation of the motor vehicle in the motor vehicle coordinate system from the measured data or navigation information output by odometry navigation system 203 in accordance with a so-called coupling navigation method . Furthermore, the speed, the acceleration, the yaw rate and the
  • Pre-processing unit 210 corrects the measurement data or navigation information obtained by odometry navigation system 203 by means of correction values obtained by fusion filter 205.
  • Odometrienavigationssystem 203 is associated with further plausibility check 211 which plausibility check the measurement data output from preprocessing ⁇ unit 210 or navigation Informa ⁇ functions, that is, the position, orientation, velocity, acceleration, the rate of rotation and the rotational acceleration of the motor vehicle. Since the error values of
  • Odometrienavigationssystem often random 203, environmental disturbances that do not correspond white noise, for example when a comparatively large wheel slip are used, the integrated navigation system by means of inertia 201, and by means Satellitennavigati ⁇ onssystem 204 specific measurement data or navigation information to the measured data and navigation information from Odometrienavigationssystem 203 to make it plausible.
  • the measured data or navigation information is compared with a sensor-specific model assigned to it, which takes into account measurement uncertainties such as noise influences. If the measurement data or navigation information corresponds to the model within the given limit values or tolerance ranges, one takes place here
  • Plausibilization and the plausibility-related measurement data or navigation information are further processed.
  • the plausibility measurement data or navigation information is then forwarded to fusion filter 205. If a plausibility check of these measurement data or navigation information can not take place, the corresponding measurement data or navigation information is rejected and not further processed.
  • Fusion filter 205 is embodied, for example, as an Eror State Space Kalman filter.
  • the main task of fusion filter 205 is such as, measurement data or Na ⁇ vigations on the sensor base system, ie from
  • Inertial navigation system 201 by means of measurement data or
  • Odometrienavigationssystem 203 and satellite navigation system 204 which represent the correction systems, or output corresponding correction values to strapdown algorithm module 207. Since inertial navigation system 201, for example, as free of random
  • the measurement data or navigation information from inertial navigation system 201 subject exclusively to white noise. Due to the different signal output delays of inertial navigation system 201, odometry navigation system 203 and satellite navigation system 204, the measurement data or navigation information from inertial navigation system 201 is stored over a period of 25 measurement periods in an electronic data memory, not shown. It is thus ensured that measured data or navigation information from inertial navigation system 201 is always used for the measurement data or navigation information from odometry navigation system 203 and also from navigation satellite system 204 There are comparisons that have been recorded, for example, at an identical point in time.
  • Odometry navigation system 203 and satellite navigation system 204 to a common fusion data set.
  • a real-time capable position determination and correction of the position determination is possible.
  • FIG. 2 represents a so-called virtual sensor, wherein inertial navigation system 201,
  • Odometry navigation system 203 and satellite navigation system 204 are not components of the virtual sensor.
  • a virtual sensor is a system which, regardless of the type of integrated sensor systems - always produces the same output data or outputs - here so Trägheitsnaviga ⁇ tion system 201, Odometrienavigationssystem 203 and satellite navigation system 204th On the basis of the output data or outputs is not clear what sensor systems are powered ⁇ connected into the system.
  • the system exemplified in FIG. 2 also uses a first group of measurement data or navigation information relating to a motor vehicle coordinate system, ie vehicle-fixed coordinates, and additionally a second group of measurement data or navigation information relating to a topocentric coordinate system, ie topocentric Coordinates, refer.
  • the measurement data or navigation information relating to the motor vehicle coordinate system is measurement data or navigation information of the inertial navigation system 201 and of the measurement data or navigation information relating to the vehicle
  • the determination according to the invention of the error values of the velocity in vehicle-fixed coordinates makes it possible for an orientation-independent application of corrections to speeds measured in vehicle-fixed coordinates to be made possible and the uncertainties of the Measurement data or navigation data of inertial navigation system 201 will continue to be described correctly.
  • the fusion filter determines the states or physical variables alignment errors, velocity errors, position errors, intercept errors, gyroscopes, intercept errors, accelerometers, scale factor errors
  • Gyroscopes scale factor error accelerometer
  • GPS receiver clock error and GPS receiver clock error drift The intersection error is also known as so-called offset error.
  • accelerometer refers to acceleration sensors. Inertial sensors. The following table shows by way of example an overview of error values determined by the fusion filter, their commonly used symbolism, the commonly used measuring unit as well as the commonly used coordinate system:
  • the cross-product-forming matrix [p x] of a 3x1 vector p is defined as:
  • Partial derivative alignment error rate according to axial section error of the gyroscope:
  • Partial derivative alignment error rate according to axial section error of the accelerometer:
  • Partial derivative position error rate according to axial section error of the gyroscope:
  • Partial derivative position error rate according to axial section error of the accelerometer:
  • the great advantage of the code measurement is quick and un ⁇ complicated calculation which is why it is especially used in the navigation of the position.
  • To determine the time of the signal travel he must know when the radio signal left the satellite, the signal being modulated by two codes, the C / A code and the P code
  • the satellite sends the C / A signal with help the highly accurate atomic clocks.
  • the receiver also has a clock with which it can generate its own C / a code. the receiver now shifts both codes (received and self-produced code) until they are de ⁇ congruent addition, they must each other.
  • the C / A code is a pseudorandom digital code. In reality, it is repeated a thousand times per second. In this way, the receiver can determine the duration of the signal travel.
  • z PSR is the pseudo orange measured by the GPS and z PSR is the computational pseudo orange from the strapdown algorithm:
  • the so-called pseudoranges describe distances, which are used for location determination. They deviate from the true distances by a constant, but for the time being unknown amount. First, therefore, the duration of the radio signals from the satellite used to the receiver of the observer measured. This results in the current distances to the satellites, which are still associated with errors of the clocks (satellite, receiver) and other influences. However, if the satellite clocks are exactly synchronized with each other, then all measured transit times are practically only affected by the synchronization error of the receiver clock - ie all falsified by almost the same amount. These distances, which are too long or too short by a constant, are called pseudo ranges (pseudo ranges).
  • GPS antenna phase center
  • Receiver clock error already converted over the speed of light to a distance
  • unit vector in navigation coordinates pointing from the antenna toward the respective satellite is defined as:
  • the carrier phase measurement is a purely geodetic method with which a very high resolution accuracy in the millimeter range can be achieved.
  • This measurement requires a high-quality receiver, which can measure at least the carrier phase LI and possibly also the carrier phase L2.
  • the carrier phase measurement is much more complex and time-intensive. In this observation, not the codes, but the carrier waves are compared. By determining the phase ambiguity, the number of whole waves between satellite and receiver can be determined.
  • the wavelength of the LI Signal is 19.05 cm and the L2 signal is 24.45. But since the signal does not arrive at the receiver with a whole wavelength, the length of this phase remainder piece still has to be determined.
  • Geodetic receivers can do this down to the millimeter.
  • z DPH is the differential velocity measured by the GPS to the satellite and z DPH is the differential speed calculated from the strapdown algorithm:
  • Measuring model Gyroscope intersection error for GPS carrier phase measurement Measurement model intercept error of accelerometer for GPS carrier phase measurement:
  • Measuring model Speed error for odometry measurements Measuring model position error for odometry measurements:

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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)
  • Navigation (AREA)

Abstract

L'invention concerne un procédé de correction de données de mesure et/ou de données de navigation d'un système de détection de base. Le système de détection de base et au moins un autre système de détection acquièrent des données de mesure qui décrivent directement et/ou indirectement des données de navigation, les données de navigation décrites indirectement étant calculées à partir des données de mesure et/ou à partir de relations physiques et/ou mathématiques connues. Les données de navigation comprennent au moins une vitesse. Au moyen des données de mesure et/ou des données de navigation du ou des autres systèmes de détection, on détermine des valeurs d'erreur des données de mesure et/ou des données de navigation du système de détection de base et on corrige ces valeurs d'erreur en appliquant des corrections. L'acquisition par le système de détection de base se fait dans des coordonnées fixes par rapport au véhicule ou dans des coordonnées topocentriques. De même, l'acquisition par le ou les autres systèmes de détection se fait dans des coordonnées fixes par rapport au véhicule ou dans des coordonnées topocentriques et la détermination des valeurs d'erreur au moins pour la vitesse se fait dans des coordonnées fixes par rapport au véhicule. L'invention concerne en outre un système correspondant ainsi qu'une utilisation de ce système.
PCT/EP2015/062694 2014-06-11 2015-06-08 Procédé et système de correction de données de mesure et/ou de données de navigation d'un système de détection de base WO2015189144A1 (fr)

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CN105783921A (zh) * 2014-12-17 2016-07-20 高德软件有限公司 一种校正汽车姿态数据的方法及装置
US20190235062A1 (en) * 2017-08-23 2019-08-01 Tencent Technology (Shenzhen) Company Limited Method, device, and storage medium for laser scanning device calibration
CN109932741A (zh) * 2017-12-19 2019-06-25 阿里巴巴集团控股有限公司 定位方法、定位设备、定位系统、计算设备及存储介质
CN109932741B (zh) * 2017-12-19 2024-02-27 斑马智行网络(香港)有限公司 定位方法、定位设备、定位系统、计算设备及存储介质
CN112817301A (zh) * 2019-10-30 2021-05-18 北京初速度科技有限公司 一种多传感器数据的融合方法、装置及系统
CN111562605A (zh) * 2020-04-24 2020-08-21 北京智行者科技有限公司 自适应的gps错误观测值识别方法
CN111562605B (zh) * 2020-04-24 2022-09-02 北京智行者科技有限公司 自适应的gps错误观测值识别方法
CN112710315A (zh) * 2020-12-15 2021-04-27 广州导远电子科技有限公司 一种基于智能车辆的车辆定位方法及装置

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