WO2015189204A1 - Procédé et système pour une détection et/ou une compensation améliorées de valeurs d'erreur - Google Patents

Procédé et système pour une détection et/ou une compensation améliorées de valeurs d'erreur Download PDF

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Publication number
WO2015189204A1
WO2015189204A1 PCT/EP2015/062831 EP2015062831W WO2015189204A1 WO 2015189204 A1 WO2015189204 A1 WO 2015189204A1 EP 2015062831 W EP2015062831 W EP 2015062831W WO 2015189204 A1 WO2015189204 A1 WO 2015189204A1
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Prior art keywords
measured values
values
error
comparison
navigation system
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PCT/EP2015/062831
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German (de)
English (en)
Inventor
Nico Steinhardt
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Continental Teves Ag & Co. Ohg
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Publication of WO2015189204A1 publication Critical patent/WO2015189204A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D3/00—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups
    • G01D3/028—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups mitigating undesired influences, e.g. temperature, pressure
    • G01D3/032—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups mitigating undesired influences, e.g. temperature, pressure affecting incoming signal, e.g. by averaging; gating undesired signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D5/00—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable
    • G01D5/12—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable using electric or magnetic means
    • G01D5/244—Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable using electric or magnetic means influencing characteristics of pulses or pulse trains; generating pulses or pulse trains
    • G01D5/24471—Error correction
    • G01D5/24485—Error correction using other sensors

Definitions

  • the invention relates to a method for improved detection and / or compensation of error values according to the preamble of claim 1, a system for improved detection and / or compensation of error values according to the preamble of claim 14 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 multiplicity of different sensors detect a common environment situation or a motor vehicle state by means of different measurement principles and describe this environment situation or this motor vehicle state by means of a multiplicity of different measurement data.
  • a 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.
  • DE 10 2012 219 478 A1 discloses a sensor system for the independent evaluation of the integrity of its data.
  • the sensor system is preferably used in motor vehicles and comprises a plurality of sensor elements which are designed such that they cover at least partially different primary measurement parameters, or at least partially utilize different Messprin ⁇ ciples.
  • the sensor system further comprises a signal processing device which evaluates the sensor signals at least partially jointly and simultaneously assessing the Informa tion ⁇ quality of the sensor signals.
  • the Signalverar- beitungs shark also provides information about the consistency of at least a date of a physical ⁇ 's size, wherein the data of the physical quantity on the basis of the sensor signals is calculated of sensor elements, which either directly detect the physical quantity or from whose sensor signals the physical quantity can be calculated. The information about the consistency of the date is now calculated on the basis of directly or indirectly redundant sensor information.
  • 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 and all functional devices are connected to the signal ⁇ processing device.
  • 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 observables calculated in different ways, conclusions can be drawn about 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 .
  • the invention relates to a method for improved recognition and / or compensation of error values, wherein measured values are detected by a sensor system, wherein the measured values describe physical quantities, wherein the measured values are subject to Def ⁇ ler screw describing deviations of the measured values of the above physical quantities , wherein the error values detected by means of a comparison and / or com ⁇ compensated, and wherein a limit-border measured values are not used in order to detect errors values of other measured values and / or compensate.
  • the invention therefore offers the advantage that - in particular in a sensor data fusion system or.
  • creeping faults which can be calculated and compensated for by a system model, eg offset errors, scale factor errors (in particular of an inertial navigation system) ) and tires ⁇ semi-diameter error.
  • Measured values are not suitable for detecting or correcting other measured values. 2. creeping faults that can not be compensated and thus directly have a comparatively considerable negative influence on a fusion data set, eg ionospheric influences in so-called Pseudorange measurements of a satellite navigation system.
  • the limit can z. B. the specifications resp. a data sheet of the sensor system are taken.
  • the measured values describe the physical quantities by representing values of the physical quantities.
  • Faulty measured values which exceed the error limit are preferably discarded.
  • the comparison is a comparison with measured values of at least one further sensor system, wherein the measured values and the measured values of the at least one further sensor system directly or indirectly describe identical physical quantities and wherein error values detected by the comparison are determined by means of increments be continuously compensated.
  • AIME Autonomous Integrity Monitoring by Extrapolation
  • RAIM Receiveiver Autonomous Integrity Monitoring
  • a disadvantage of these methods is that only modeled errors are reliably detected.
  • a typical case of creeping errors is, for example, the time-varying disturbance in a pseudorange measurement caused by changes in the ionosphere. This takes place sufficiently slowly so that the estimated position of the fusion filter Corridor ⁇ is yaws according wrong, the amount of deviation from one measurement epoch to the next, however, not sufficient to detect an error with a so-called. SNAPS hot process.
  • creeping errors are expected for the sensors used in the following cases:
  • Inertial navigation system Due to defects or external influences, such as the ambient temperature, caused drift of offset or scale factor error.
  • Satellite navigation system pseudo-orange measurements due to ionospheric influence and multipath reception, whereas delta-range measurements are not affected by the temporal differentiation of the measured values.
  • Odometrienavigationssystem Slow variable error of the measured velocity by changes of the rolling radius, for example by temperature creep ⁇ sponding pressure loss or alteration of the of the tires.
  • Odometrial navigation systems are usually already implemented as an error model in the fusion filter, and in each measurement epoch, the raw measurements are preferably corrected by the known, continuously further estimated errors. Thus, the slow growth of these errors does not lead to significant errors in the fused data as long as the fusion filter corrects them sufficiently quickly by redundant measurements. Problematic as much about the dynamics filter out ⁇ continuous interference of the measurement data in question are against a defined detection probability and thresh recognizable both preventable by a plausibility check and by the. In so-called NIS test. Furthermore, by checking the summed absolute values of the error corrections with defined maximum values, a detection of measured values outside their specified error range can be realized.
  • Creeping faults of individual pseudo-orange measurements which are not modeled as faults in the fusion filter, lead to contradictions in the one described by the above-mentioned independent of the fusion filter.
  • Plausibilmaschine carried out geometric comparison of pseudoranges with each other, and are therefore recognizable with a defined detection threshold.
  • the physical variables described indirectly are preferably calculated from the measured values which describe them and from known physical or mathematical relationships. According to a further preferred embodiment of the invention, it is provided that only measured values with an identical time stamp are used for the comparison of the measured values. This has the advantage that - at least in error-free Measurement - match all subject to the comparison values because they write the same physical size at the same time be ⁇ . This simplifies the detection of erroneous values, since the cause of a mismatch in this case must necessarily be an erroneous value.
  • the values subjected to the comparison are generated by means of interpolation, if there are no values recorded with an identical time stamp. Since the measured data are usually acquired at different times due to different signal output delays and generally due to lack of synchronization between the sensor systems, or are output by the sensor systems at different times, the required values can be calculated by means of the interpolation. Preferably, measurement data or values of the sensor system with the lowest signal output delay are generated by means of interpolation, ie, that these measurement data or values are generated as a function of the acquisition times of the measurement data or values of the other sensor systems.
  • the two values of the sensor system with the lowest signal output delay closest in time and enclosing them to be generated are then subjected to the comparison as described.
  • the sensor system with the lowest signal output delay is most preferably the basic sensor system.
  • changes in the values for the interpolation be assumed to be proportional to the time. So therefore are used for linear INTERPO ⁇ lation. This results in the advantage that the interpolation is relatively simple and correspondingly executable with only a small amount of computation.
  • the comparison is a comparison of Measured values of one and the same sensor system with each other taking into account a sensor-specific stochastic model.
  • the sensor-specific stochastic model is used to compare the measured values from the past with the current measured values. If, for example, an unexpectedly large deviation is detected here or a limit value is exceeded, the corresponding measured value can be recognized as defective or can not be used to detect and correct error values of other measured values.
  • the current measured values can be comparatively easily compared against a limit, which was formed from the measured values of the past.
  • Such a procedure is also known as a so-called snapshot method.
  • the snapshot method is essentially the well-known NIS test, but without the consideration of covariances.
  • the snapshot method is comparatively less computationally expensive and favors real-time detection of error values.
  • the sensor system and the at least one further sensor system are an inertial navigation system global satellite navigation system and / or an odometry navigation system.
  • the present invention is particularly suitable for navigation purposes and for navigation systems, preferably in motor vehicles.
  • the sensor systems thus determine the position, in particular the position of a motor vehicle, from the output data.
  • the global navigation satellite system may be, for example, a so-called GPS navigation system.
  • the odometry navigation system initially determines the speed, for example, via the known rolling circumference of the motor vehicle tires and thus makes it possible to determine the position while taking into account the steering angle in the context of dead reckoning. It is particularly expedient that the Satellitenna ⁇ vigationssystem least two satellite signal receiver comprises is. This improves the quality of the recorded
  • Satellite signals and thus the reliability and accuracy of the satellite navigation system.
  • the inertial navigation system is the sensor base system.
  • the inertial navigation system as a sensor base system has the advantage that it has the comparatively highest availability, since it has a comparatively high output rate of the acquired input data and, moreover, operates largely independently of external interference influences.
  • the limit value of the inertial navigation system is a limit value for zero error and / or
  • the limit of the Satelli ⁇ tennavigationssystems is a limit value for frequency error of an oscillation frequency of a receiver clock oscillator.
  • the limit value of Odometer navigation system is a limit for radius error of Abrollradius of vehicle wheels.
  • the detected by comparing error values by means of an error-state-space filter, in particular ⁇ sondere are detected by means of an error-state-space Kalman filter and / or compensated.
  • the error-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.
  • the error state space filter preferably estimates or determines the error values of at least the sensor base system. By means of the at least one correction system, the error values and possibly also unknown variables of the inertial navigation system can then be estimated or determined.
  • a specifics ⁇ derheit of the error-state-space filter is that error values are incrementally estimated or determined instead of the sensor signals or the input data only and are subsequently 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 error-state-space filter on the characteristics of Sensorba ⁇ sissystems or the at least one correction system
  • Inertial Navigation System 101 forms, for example according to the so-called sensor-based system, whose measured values using the method described in the following further sensor systems, so-called. Korrektursys ⁇ systems can be corrected.
  • the correction systems are Odometrienavigationssystem 103 and Satellitennavigationssys ⁇ tems 104th
  • the system according to the invention also has a so-called.
  • Strapdown algorithm unit 102 in which a so-called. Strapdown algorithm is performed by means of which the measured values of inertial navigation system 101, among other things, are converted into position data. These are the readings of inertial navigation system 101, which naturally describe Accelerat ⁇ fixing certificates, integrated twice over time. By means of a simple integration over time, the orientation and the speed of the motor vehicle are further determined. In addition, strapdown algorithm unit 102 compensates for a Coriolis force acting on inertial navigation system 101.
  • a world coordinate system which is suitable for describing the orientation or of dynamic variables of the motor vehicle in the world.
  • the named world coordinate system is a
  • the output data from the strapdown algorithm unit 102. ⁇ clearly includes the position with respect to the vehicle coordinate system and the orientation of the world coordinate system.
  • the output data from the strapdown algorithm unit 102 have the Va ⁇ rianzen to as an information on the quality of the above navigation information. These variances are such as not be ⁇ expects strap-down algorithm unit 102, but only used by this and forwarded.
  • the values calculated by the strapdown algorithm unit 102 og Navi ⁇ gations may be output via output module 112 and provided to other vehicle systems.
  • the system according to the invention also comprises
  • 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.
  • the system also includes fusion filter 105.
  • Fusion filter 105 provides a fusion data set 106 as the odometry navigation system 103, satellite navigation system 104, and inertial navigation system 101 collectively evaluate the measurements.
  • Fusion data set 106 has the acquired measured values of the different sensor systems, wherein fusion data record 106 includes, for example, additional error values and variances associated with the error values which describe the data quality.
  • inertial navigation system 101 The measured values of inertial navigation system 101 are stored during operation of the motor vehicle in a dedicated electronic data memory 113 of fusion filter 105 for a predetermined period of time.
  • Inertial navigation system 101 represents the so-called sensor base system
  • odometry navigation system 103 and satellite navigation system 104 represent the so-called correction systems whose measured values are used to correct the measured values of the sensor base system. This ensures that measured values that were at least apparently acquired at an identical point in time can always be subjected to comparison.
  • Strapdown algorithm unit 102 is now corrected by Fu ⁇ sion data record 106, the measured values of the sensor base system.
  • Fusion data set 106 is calculated by fusion filter 105 from the measurements of 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 values and in which the quantitative error values of the measured values are calculated or estimated and which se ⁇ quentiell operates and thereby corrects the available in each function ⁇ ons intimid the sequence of output data.
  • Fusion filter 105 is designed to always be asynchronous to the most recent ones of inertial navigation system 101,
  • Motor vehicle model unit 107 is configured to calculate from the measured values of odometry navigation system 103 at least the speed along a first axis, the speed along a second axis and the rate of rotation about a third axis and provide these fusion filters 105.
  • the exemplary system also includes tire parameter estimation unit 110 configured to include at least the radius, for example, the dynamic one
  • Tire parameter estimation unit 110 is further configured to use a substantially linear tire model to calculate tire sizes.
  • the example according to inputs from ReifenparameterMt- wetting unit 110 are the wheel speeds and the steering angle describing input data, at least partially, from the output values of ⁇ strapdown algorithm unit 102 as well as the particular fusion filter 105 variances.
  • GPS error detection and plausibility unit 111 which is configured such that it receives as input data, for example, the output data from satellite navigation system 104 as well as at least partial output data from
  • Strapdown algorithm unit 102 receives and considered in their Be ⁇ calculations.
  • GPS error detection and validation unit 111 checks the output data against a stochastic model adapted to satellite navigation system 104. If the measured values correspond to the model within the framework of a tolerance that takes account of the noise, they are checked for plausibility.
  • GPS error detection and plausibility check unit 111 is additionally connected to data-level fusion filter 105 and transmits the plausibility measured values to fusion filter 105.
  • GPS error detection and plausibility check unit 111 is exemplified to provide a method for selecting a satellite, and the like. by means of the following method steps:
  • the predetermined condition is a maximum permissible deviation of the position data from the reference position data
  • ⁇ 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 exemplary system also has
  • 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
  • Strapdown algorithm unit 102 forwards.
  • Odometry navigation system 103 and satellite navigation system 104 the correction systems.
  • Odometry navigation system 203 outputs measured values which directly and indirectly describe physical variables, namely a position, a velocity, an acceleration, an orientation, a yaw rate or a yaw acceleration, to fusion filter 205.
  • the output of the measured values takes place via a vehicle data bus, for example via a so-called CAN bus.
  • satellite navigation system 204 outputs its raw data readings.
  • Motor vehicle inertial navigation system 201 which is a so-called MEMS IMU
  • Inertial navigation system 201 outputs its measured values to preprocessing unit 206 of inertial navigation system 201.
  • Pre-processing unit 206 now corrects the measured values or the physical variables described therein by means of corrections, which pre-processing unit 206 receives from fusion filter 205. The thus corrected measured values or in it described physical quantities are continued on strapdown algorithm unit 207.
  • Strapdown algorithm unit 207 now makes a position determination on the basis of the corrected measured values or the physical quantities of preprocessing unit 206.
  • This Po ⁇ sitionsbetician is a so-called.
  • Dead reckoning based on inertial navigation system 201.
  • Strapdown algorithm unit 207 further compensates for a Coriolis force acting on inertial navigation system 201, which may affect the measurements of inertial navigation system 201.
  • strapdown algorithm unit 207 performs a two-fold integration over time of input data acquired by inertial navigation system 201 describing accelerations.
  • sensor base system describes the sensor system whose measured values or. physical values are corrected by means of the measured values or the physical quantities of the other sensor systems, the so-called correction systems.
  • the correction systems are odometry navigation system 203 and satellite navigation system 204.
  • Strapdown algorithm unit 207 form, for example, to ⁇ together the so-called.
  • Sensor base system to which additionally pro rata and fusion filter 205 is counted.
  • Output module 212 relays the measured values or physical quantities determined and corrected by strapdown algorithm unit 207 to any other systems of the motor vehicle.
  • the measured values acquired by the 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 measured values, which represent 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 is still approximately feasibility check module 209 associated with which plausibility output by preprocessing unit 208 ⁇ physical quantities, that is, the position and the speed of the motor vehicle, l12.
  • the plausibility values or physical variables plausibilized by plausibility module 209 are then output to fusion filter 205.
  • Odometry navigation system 203 is further associated with plausibility module 211, which plausibilizes the measured values output by preprocessing unit 210, that is to say the position, the orientation, the speed, the acceleration, the rotation rate and the rotational acceleration of the motor vehicle. Since the error values of the measured values of In the case of comparatively large wheel slippage, the measured values determined by means of the inertial navigation system 201 and the satellite navigation system 204 are used to make the measured values of the odometry navigation system 203 plausible. First of all, however, the measured values or the physical quantities are also calibrated against a sensor-individual model assigned to them which takes into account measurement uncertainties such as noise influences. If the measured values or the physical quantities correspond to the model within the given limit values or tolerance ranges, a first occurs here
  • Fusion filter 205 is embodied, for example, as an Eror State Space Kalman filter.
  • the main task of fusion filter 205 is to correct or to measure the measured values or the physical quantities of the sensor base system, ie of inertial navigation system 201, by means of the measured values or the physical variables of odometry navigation system 203 and satellite navigation system 204, which represent the correction systems to output corresponding correction values to strapdown algorithm unit 207.
  • inertial navigation system 201 is assumed to be free from random errors and external disturbances, the measurements of inertial navigation system 201 are exclusively white noise. Since it is in merger filter 205 a so-called.
  • 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 always generates the same output data or outputs regardless of the type of sensor systems involved - in this case inertial navigation system 201, odometry navigation system 203 and satellite navigation system 204. On the basis of the output data or outputs is not clear what sensor systems are powered ⁇ connected into the system.
  • Fusion filter 205 is, for example expanded according to a two-stage signal plausibility for the detection of error values in the measured values of the correction measurements. This detected the one hand deviations Träg ⁇ integrated navigation system 201 and to the strapdown algorithm, and on the other hand deviations from the individual measured values, eg each other contradictory pseudorange measurement values within a data set with each other. Fusion filter 205 is also an integrity score according to the known one

Abstract

L'invention concerne un procédé pour une détection et/ou une compensation améliorées de valeurs d'erreur, selon lequel des valeurs de mesure d'un système de capteur (101, 103, 104, 201, 203, 204) sont acquises, lesdites valeurs de mesure décrivant des grandeurs physiques, et présentant des valeurs d'erreur décrivant des écarts par rapport aux grandeurs physiques décrites. Lesdites valeurs d'erreur sont détectées et/ou compensées au moyen d'une comparaison, et les valeurs de mesure dépassant une valeur limite ne sont pas prises en compte pour détecter et/ou compenser les valeurs d'erreur d'autres valeurs de mesure. L'invention concerne en outre un système correspondant ainsi que l'utilisation dudit système.
PCT/EP2015/062831 2014-06-11 2015-06-09 Procédé et système pour une détection et/ou une compensation améliorées de valeurs d'erreur WO2015189204A1 (fr)

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DE102014211180.3 2014-06-11
DE102014211180.3A DE102014211180A1 (de) 2014-06-11 2014-06-11 Verfahren und System zur verbesserten Erkennung und/oder Kompensation von Fehlerwerten

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DE102017108107A1 (de) 2017-04-13 2018-10-18 Volkswagen Aktiengesellschaft Verfahren, vorrichtung und computerlesbares speichermedium mit instruktionen zur schätzung einer pose eines kraftfahrzeugs
WO2018189089A1 (fr) 2017-04-13 2018-10-18 Volkswagen Aktiengesellschaft Procédé, dispositif et support d'enregistrement lisible par ordinateur comprenant des instructions servant à estimer une position d'un véhicule automobile
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