EP3155371A1 - Procédé et système pour corriger des données de sortie d'un système de base de capteur - Google Patents

Procédé et système pour corriger des données de sortie d'un système de base de capteur

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Publication number
EP3155371A1
EP3155371A1 EP15727973.8A EP15727973A EP3155371A1 EP 3155371 A1 EP3155371 A1 EP 3155371A1 EP 15727973 A EP15727973 A EP 15727973A EP 3155371 A1 EP3155371 A1 EP 3155371A1
Authority
EP
European Patent Office
Prior art keywords
output data
error
sensor
sensor base
data
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Withdrawn
Application number
EP15727973.8A
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German (de)
English (en)
Inventor
Jens Martin
Nico Steinhardt
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Continental Teves AG and Co OHG
Original Assignee
Continental Teves AG and Co OHG
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Publication date
Application filed by Continental Teves AG and Co OHG filed Critical Continental Teves AG and Co OHG
Publication of EP3155371A1 publication Critical patent/EP3155371A1/fr
Withdrawn legal-status Critical Current

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Classifications

    • 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 invention relates to a method for correcting output data of a sensor based system according to the preamble of claim 1.
  • An ⁇ a system for correcting output data of a sensor based system according to the preamble of claim 9 and a use of the system.
  • All output data are in principle subject to error and in many cases a continuous availability of Ausga ⁇ bequel is also not given.
  • the output data are often also dependent on environmental conditions.
  • Sensor errors or measurement errors can be subdivided into quasi-stationary components that are constant over several measurements, such as a so-called offset error, as well as a so-called scale factor error, and statistical components that are random from measurement to measurement, such as noise.
  • the scale factor error is a multiplicative error, ie a slope error in the sensor characteristic.
  • the random parts are not deterministically correctable in principle, quasi-stationary errors can generally be corrected with a given observability. Uncorrectable significant errors can usually be avoided, given the detectability.
  • 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 observable and provides the observables together with an accuracy specification via an interface device to various functional devices.
  • 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.
  • the signal processing device is designed so that the output data of physical quantities are each assigned a time information which directly or indirectly includes information about the time of the respective measurement, wherein the signal processing device at least this time information taken into account in the generation of a fusion record in a fusion ⁇ filter.
  • output data are used which either have matching time information or-if there are no output data with matching time information-a corresponding measured value with the required time information is created by means of interpolation.
  • the fusion filter assumes that error values from ⁇ with output data change only negligibly over a defined period of time.
  • 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 ⁇ processing device also provides information about the consistency of at least one date of a physi ⁇ cal size, wherein the date of the physical quantity is calculated based on the sensor signals from sensor elements that either directly detect the physical quantity or from their sensor signals, the physical size is calculable. The information about the consistency of the date is now calculated on the basis of directly or indirectly redundant sensor information.
  • the invention relates to a method for correcting output data of a sensor base system, wherein the sensor base system and at least one further sensor system detect input data and output this as output data,
  • the output data of the at least one further sensor system is used to determine error values of the output data of the sensor base system, wherein the error values are corrected by applying corrections, and wherein the determination of the error values comprises a determination of an error value of a slope of a characteristic of the sensor base system, wherein the characteristic curve describes a dependence of the output data of the sensor base system of the input data of the sensor base system.
  • the invention thus proposes to monitor the slope of a characteristic curve or to determine an error value of the slope of the characteristic curve.
  • This type of error value is also known as so-called.
  • At least two input data of the at least one further sensor system are required for the scale factor error.
  • the so-called correction system are required for the scale factor error.
  • the slope is calculated for the characteristic of the basic system or for their error value.
  • the corrections preferably correspond to the negative error values.
  • the dependence of the output data of the sensor system based on the input data of the sensor base system is preferably a function of the error value of the output data of the Sensorba ⁇ sissystems from the input data of the sensor base system.
  • the error values are determined as such, but also their variances and, alternatively or additionally, also the variances of the output data.
  • the input data in the sense of the invention are the physical quantities which are detected by the sensor base system or by the at least one further sensor system.
  • the output data describe the detected physical quantities and are generally associated with error values that are caused by the sensor base system or by at least one other sensor system.
  • the output data directly and / or indirectly describe navigation information, whereby indirectly described navigation information is calculated from the output data and / or from known physical and / or mathematical contexts.
  • indirectly described navigation information is calculated from the output data and / or from known physical and / or mathematical contexts.
  • the navigation information comprising at least position information, a speed ⁇ information and orientation information. These Navigation information generally enables a comparatively good navigation guidance.
  • the output data of at least output data of an inertial navigation system, output data of a global satellite navigation system and / or Ausga ⁇ beoire are a Odometrienavigationssystems.
  • the present invention is particularly suitable for navigation purposes and for navigation systems, preferably in motor vehicles.
  • Odometrienavigationssystem so therefore determine the position, in particular the position of a motor vehicle, with output data from the off ⁇ .
  • the global navigation satellite system may be, for example, a so-called GPS navigation system.
  • the odometry navigation system first determines the speed, for example, over the known rolling circumference of the
  • the Sa ⁇ tellitennavigationssystem comprises at least two satellite signal receiver. Thus it improves the quality of the acquired 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 disturbing influences.
  • the navigation information is merged into a fusion data record.
  • a common fusion data set is usually more reliable and precise than the individual navigation information, and in particular it allows by means of an error estimate, a comparatively reliable evaluation of the accuracy or reliability of the merged input data or navigation information.
  • the error values are determined by means of an error-state-space filter, in particular by means of an eror-state-space Kalman filter.
  • the Eror 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
  • the error state-space filters the error values to ⁇ least the base system.
  • the at least one Cor ⁇ rektursystems the error values and possibly also un- known quantities of the inertial navigation system can then be estimated or determined.
  • a special feature of He ⁇ ror state-space filter it is then that estimated or instead of Sen ⁇ sorsignale or the input data only error values domestic krementell determined and subsequently corrected.
  • the error values have a signi ⁇ fikant lower temporal dynamics than the output data itself, whereby a substantial decoupling of the dynamics of the error-state space filter of the properties of the base system and the at least one correction system
  • the invention further relates to a system for correcting output data of a sensor based system comprising a sensor ⁇ base system, at least one further sensor system, and a Fusion filter, wherein the sensor base system and a further sensor system being adapted at least to detect input data and output them as output data, wherein the fusion filter is designed to be read by means of the output data of the vorzu ⁇ take at least one further sensor system, a determination of error values of the output data of the sensor base system, wherein the fusion filter is adapted when attempting to correct by means of an application of corrections, the error values, and wherein the fusion filter is adapted, in determining the error values and a determination an error value of a slope of a characteristic of the sensor base ⁇ system make
  • the system according to the invention thus comprises all devices necessary for carrying out the method according to the invention. It is preferably provided that the system is designed to carry out the method according to the invention. This leads to the advantages already described.
  • the invention relates to a use of the inventive system in a motor vehicle.
  • 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.
  • the illustrated system is designed according to the example for the correction of output data of a sensor base system and is suitable for determining the position of the motor vehicle.
  • the system illustrated elements or components or sensor systems as function blocks and their together ⁇ men breathe shown with one another.
  • the navigation 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.
  • These three axes form a Cartesian coordinate system, the so-called motor vehicle coordinate system.
  • Inertial Navigation System 101 forms, for example according to the so-called.
  • Sensor base system whose output data by means of the so-called described below further sensor systems,. Korrektursys ⁇ systems can be corrected.
  • the correction systems are odometry navigation system 103 and satellite navigation systems 104.
  • 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 input data of inertial navigation system 101, among others, are converted into position data. For this purpose, the input data of inertial navigation system 101, which naturally describe accelerations, are 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. The output data from strapdown algorithm unit 102 to ⁇ therefore consider the following physical quantities:
  • 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 of strapdown algorithm unit 102 has the variances as information about the data quality of the above-mentioned navigation information. These variances are such as not be ⁇ expects strap-down algorithm unit 102, but only used by this and forwarded.
  • the above-mentioned navigation information calculated by strapdown algorithm unit 102 is output via output module 112 and made available to other motor vehicle systems.
  • the system according to the invention also comprises
  • Odometry navigation system 103 in the form of wheel speed sensors for each wheel of the motor vehicle.
  • it 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 in the form of wheel speed sensors for each wheel of the motor vehicle.
  • it is a four-wheeled motor vehicle with four wheel speed sensors, each detecting the speed of their associated wheel and its direction of rotation.
  • Odometrienavigationssystem 103 a steering angle sensor element that detects the steering angle of the motor vehicle.
  • the exemplary system includes satellite navigation system 104, which is configured to determine the distance between an associated satellite and the vehicle and the speed between the associated satellite and the motor vehicle, respectively.
  • the system also includes fusion filter 105.
  • Fusion filter 105 provides a fusion data set 106 as the input data from odometry navigation system 103, satellite navigation system 104, and inertial navigation system 101 are shared.
  • Fusion data set 106 comprises the acquired input 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 The input data of inertial navigation system 101 are stored during operation of the motor vehicle in a dedicated electronic data storage 113 of fusion filter 105 for a predetermined period of time. Inertial navigation system 101 provides thereby the so-called. Base system, whereas Odometrienavigationssystem represent 103 and Satellitennaviga ⁇ tion system 104, the so-called. Correcting systems, whose output data are used to correct the output data of the basic system. This ensures that values that were at least apparently captured at an identical time can always be subjected to comparison.
  • fusion data set 106 provided by fusion filter 105 includes the quantitative errors of the base system determined by means of the plausibilized output data of the correction systems.
  • Strapdown algorithm unit 102 is now corrected by Fu ⁇ sion data set 106, the output data of the basic system.
  • Fusion data set 106 is output from fusion filter 105
  • Input data from the odometry navigation system 103, satellite navigation system 104 and inertial navigation system 101 is calculated.
  • Fusion filter 105 is designed, for example, as an Eror-State-Space-Kalman filter, that is to say as a Kalman filter, which in particular has a linearization of the output. performs beoire and in which the quantitative error values of the output data 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,
  • Odometry navigation system 103 and satellite navigation system 104 detected available output data.
  • the output data is thereby passed over the motor vehicle model unit 107 and the alignment model unit 109.
  • Motor vehicle model unit 107 is adapted to calculate from the input DataN of Odometrienavigationssystem 103 at least the speed along a first axis, the Ge ⁇ speed along a second axis as well as the rate of rotation about a third axis and this fusion filter be riding provides ⁇ 105th
  • the exemplary system also includes tire parameter estimation unit 110, which is configured to include at least the radius, for example, the dynamic
  • 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.
  • the exemplary system also includes
  • GPS error detection and plausibility unit 111 which is designed such that it can be used as input data, for example 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 output data corresponds to the model within the framework of a noise tolerance, they will be made plausible.
  • GPS error detection and plausibility check unit 111 is additionally connected to data-level fusion filter 105 and transmits the plausibilized input data to fusion filter 105.
  • GPS error detection and validation 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
  • 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, and - Where 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
  • Standstill detection unit 108 which is designed so that it can detect a stoppage of the motor vehicle and in the case of a detected stoppage of the motor vehicle to ⁇ at least fusion filter 105 information from a
  • Stability model provides.
  • the information from a standstill model describes that the rotation rates around all three axes have the value zero and the velocities along all three axes have the value zero.
  • Standstill detection unit 108 is, for example, designed in such a way that it uses the output data of the wheel speed sensors of odometry navigation system 103 and the input data of inertial navigation system 101 as input data.
  • the example contemporary system used, for example in accordance with a first set of input data relating to a Kraft povertyko ⁇ ordinate system and additionally a second group of input data relating to a world coordinate system, the world coordinate system is used to describe the orientation and dynamic variables of the motor vehicle.
  • alignment model unit 109 is determined ⁇ an alignment angle between the motor vehicle coordinate system and the world coordinate system.
  • Alignment model unit 109 uses all of the output data from strapdown algorithm unit 102.
  • Alignment model unit 109 is designed, for example, such that it additionally calculates information about the data quality of the orientation angle in the form of a variance and provides fusion filter 105 in addition to the orientation angle.
  • Fusion filter 105 uses the orientation angle and the variance of the orientation angle in its calculations, the results of which it provides via fusion data set 106
  • Strapdown algorithm unit 102 forwards.
  • Fusion filter 105 thus detects the output data from inertial navigation system 101, the base system, as well as from
  • Odometry navigation system 103 and satellite navigation system 104 the correction systems.
  • the scale factor error is next to the offset error of significant systematic error of inertial navigation system 101 and leads therefore if it is not corrected to acceleration and rotation-rate-dependent drift of direction and speed, and in addition to significant Feh ⁇ ler79 the position. In particular, if no corrections of orientation, speed and position are available by, for example, satellite navigation system 104, a rapid increase in the error values is observable.
  • Odometer navigation system 103 and satellite navigation system 104 a characteristic used, which describes the vehicle dynamics-dependent error value of the inertial navigation system 101. This improves accuracy and reliability determining the respective error value of inertial navigation system 101.
  • the scale factor error is a relatively slowly varying error value relative to the driving dynamics of the vehicle.
  • a steady state estimation of these two error values is therefore capable, in a system according to the invention, even if temporary corrections (e.g.
  • the method according to the invention achieves generally lower deviations (residuals) in fusion filter 105 and a clearer assignment of error values to the respective output data, whereby the quality of fusion data set 106 is improved even with available correction measurements or correction systems.
  • FIG. 2 shows, by way of example, a further possible embodiment of a system according to the invention, which is likewise designed to correct output data of a sensor base system, in a motor vehicle (not shown).
  • the system according to the example includes inertial navigation system 201, Satellitenna ⁇ vigationssystem Odometrienavigationssystem 204 and 203 as different sensor systems.
  • Odometry navigation system 203 outputs output data directly and indirectly describing navigation information, namely, position, velocity, acceleration, orientation, yaw rate, and yaw acceleration to fusion filter 205.
  • the output of the output data is carried out via a vehicle data bus, for example via a so-called CAN bus.
  • satellite navigation system 204 outputs its raw data output data.
  • 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.
  • Satellite navigation system 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 from 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 ⁇ distance determined.
  • 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 Radcardgschwindtechnik their associated wheel and the steering angle sensor determines the chosen steering angle.
  • Inertial navigation system 201 outputs its output data to preprocessing unit 206 of inertial navigation system 201.
  • Pre-processing unit 206 now corrects the output data or the navigation information described therein by means of corrections, which pre-processing unit 206 receives from fusion filter 205.
  • the thus corrected output data or the navigation information described therein are passed on to strapdown algorithm unit 207.
  • Strapdown algorithm unit 207 takes on the basis of the corrected output data from preprocessing unit 206 before a Posi ⁇ tion determination. This position determination is a so-called. Dead reckoning based on inertial navigation system 201. For this, the pre-processing unit 206 by being passed ⁇ corrected output data or the navigation information described therein are continuously over time
  • Strapdown algorithm unit 207 further compensates for a Coriolis force acting on inertial navigation system 201, which may affect the output data 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. This allows an updating of a previously known position as well as an updating of a previously known orientation of the motor vehicle.
  • strapdown algorithm unit 207 For determining a speed of the motor vehicle, strapdown algorithm unit 207 performs a simple integration of the input data acquired by inertial navigation system 201 over time. Further corrected
  • strapdown algorithm executed by strapdown algorithm unit 207 is only comparatively computationally complex and can therefore be realized as a real-time capable basic system. It represents a procedure for integrating the input data of inertial navigation system 201 to speed, orientation and position and does not include any Filtering, resulting in an approximately constant latency and group delay.
  • the term basic system describes the one sensor system whose input data by means of the output data of the other
  • correction systems to be corrected.
  • the correction systems are odometry navigation system 203 and satellite navigation system 204.
  • Inertial navigation system 201 preprocessing unit 206 of inertial navigation system 201 and
  • Strapdown algorithm unit 207 form, for example, to ⁇ together the so-called.
  • Basic system to which in addition proportionally and fusion filter 205 is counted.
  • Output module 212 relays the navigation information determined and corrected by strapdown algorithm unit 207 to any other systems of the motor vehicle.
  • the input data acquired by satellite navigation system 204 are, for example, initially forwarded to preprocessing unit 208 of satellite navigation system 204 in the form of sensor signals via a so-called UART data connection.
  • Preprocessing beitungstician 208 is now determined from the output from satnav ⁇ gationssystem 204 output data
  • GPS raw data and also include a description of the orbit of each GPS satellite transmitting the GPS signals, a position and a speed of the vehicle in the GPS coordinate system.
  • 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 contained in the output data, which is caused by a drift of the receiver clock, and by means of a correction model caused by atmospheric influences on the GPS signals transmitted by the GPS satellites Changes in signal transit time and signal path.
  • the correction of the time error as well as the atmospheric influences are carried out by means of correction filters obtained by means of Fusionsfilter 205 via the CAN bus.
  • Satellite navigation system 204 is still approximately feasibility check module 209 associated with which the input data output from preprocessing ⁇ unit 208 of the navigation information, so the position and the speed of the
  • the input data 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 receives via the CAN bus the input data acquired by odometry navigation system 203 as output data.
  • the detected input data in this case are the output data of the individual wheel speed sensors and the input data of the steering angle sensor.
  • Preprocessing unit 210 now determines the position and orientation of the motor vehicle in the motor vehicle coordinate system from the input data output by odometry navigation system 203 in accordance with a so-called dead reckoning method. Furthermore, the speed, the acceleration, the rate of rotation and the rotational acceleration of the motor vehicle are determined, also in the motor vehicle coordinate system.
  • pre-processing unit 210 corrects the output data obtained from odometry navigation system 203 by means of correction values obtained by fusion filter 205.
  • Odometrienavigationssystem 203 remains approximately feasibility check module assigned 211 which plausibility check the output from the preprocessing unit 210 ⁇ output data, that is, the position, orientation, velocity, acceleration, the rate of rotation and the rotational acceleration of the motor vehicle.
  • the error values of the output data of odometry navigation system 203 are often random, environmental disturbances that do not correspond to white noise, eg at comparatively large wheel slip is that utilized by Träg ⁇ integrated navigation system 201 and by means of Satellitennavigati ⁇ onssystem 204 determined output data in order to check the plausibility of the output data from Odometrienavigationssystem 203rd First of all, however, the output data are also compared with a sensor-individual model assigned to them which takes into account measurement uncertainties such as noise influences. If the output data corresponds to the model within the given limit values or tolerance ranges, a first plausibility check is carried out here and the values that have been checked for such a degree are further processed. The plausibilized values are then forwarded to fusion filter 205. If one
  • Fusion filter 205 is embodied, for example, as an Eror State Space Kalman filter.
  • the main task of fusion filter 205 is, for example, to correct the output data of the base system, ie of inertial navigation system 201, by means of output data from odometry navigation system 203 and satellite navigation system 204, which represent the correction systems, or output corresponding correction values to strapdown algorithm unit 207.
  • inertial navigation system 201 is assumed to be free from accidental errors and external disturbances, the output data from inertial navigation system 201 is exclusively subject to white noise.
  • Fusion Filter 205 is a so-called Eror State Space Kalman Filter, only the quantitative error values of the output data are determined and corresponding corrections are made. This simplifies and speeds up the merger of the output data from inertial navigation system 201 made by fusion filter 205,
  • 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 allows.
  • 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.
  • the scale factor error represents the most significant systematic error value of the inertial navigation system 201.
  • the size of the scale factor error or the error value of the scale factor error is dependent on the respective driving dynamic state of the vehicle.
  • a characteristic is stored which describes a dependence of the Ausga ⁇ bechrist from inertial navigation system 201 from the input data from inertial navigation system 201. According to the invention, this characteristic describes the error value of the output data of the inertial navigation system 201 as a function of the input data of the inertial navigation system 201.
  • Satellite navigation system 204 the characteristic used to determine the error values of the output data of inertial navigation ⁇ system 201.
  • the fusion filter determines the states or physical quantities alignment errors, velocity errors, position errors, intercept errors Gyroscopes, intercept error
  • 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 or inertial sensors. The following table exemplifies an overview of some of the fusion ⁇ filter error values, the commonly used symbols, the measuring unit commonly used as well as the coordinate system commonly used:
  • the cross-product-forming matrix [px] 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: dib
  • 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:
  • 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).
  • unit vector in navigation coordinates pointing from the antenna toward the respective satellite is defined as:
  • H P s R [hg 0 / ⁇ ⁇ 0 0 0 0 / ⁇ ⁇ 0]
  • 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 consuming.
  • the codes but the carrier waves are compared.
  • the phase ambiguity the number of whole waves between satellite and receiver can be determined.
  • the wavelength of the L1 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:
  • H DPH [h s K 0 0 ⁇ ⁇ 0 h Ai 0] Furthermore, will be described below by way of example a model for Na ⁇ vigieren by means of odometry.
  • the ancillary variables WM and v ⁇ o d o are both combined in the prediction vector z odo , and the measurement vector z odo is set to zero:
  • Measurement model Axis error of the accelerometer for odometry measurements
  • H 0D0 [o K o ⁇ ⁇ 0 ⁇ ⁇ ooh rdyn ]

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
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Abstract

L'invention concerne un procédé pour corriger des données de sortie d'un système de base de capteur (101, 201), le système de base de capteur (101, 201) et au moins un autre système de capteur (103, 104, 203, 204) détectant des données d'entrée et émettent celles-ci comme données de sortie, une détermination de valeurs d'erreur des données de sortie du système de base de capteur (101, 201) ayant lieu au moyen des données de sortie du au moins un autre système de capteur (103, 104, 203, 204), les valeurs d'erreur étant corrigées au moyen d'une mise en place de corrections et la détermination des valeurs d'erreur comprenant une détermination d'une valeur d'erreur d'une pente d'une courbe caractéristique du système de base de capteur (101, 201), la courbe caractéristique décrivant une dépendance des données de sortie du système de base de capteur (101, 201) selon les données d'entrée du système de base de capteur (101, 201). L'invention concerne en outre un système correspondant ainsi qu'une utilisation du système.
EP15727973.8A 2014-06-11 2015-06-09 Procédé et système pour corriger des données de sortie d'un système de base de capteur Withdrawn EP3155371A1 (fr)

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DE102014211172.2A DE102014211172A1 (de) 2014-06-11 2014-06-11 Verfahren und System zur Korrektur von Ausgabedaten eines Sensorbasissystems
PCT/EP2015/062797 WO2015189183A1 (fr) 2014-06-11 2015-06-09 Procédé et système pour corriger des données de sortie d'un système de base de capteur

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CN107942364A (zh) * 2016-10-13 2018-04-20 阿里巴巴集团控股有限公司 车辆定位方法和车辆定位系统
DE102017108107A1 (de) 2017-04-13 2018-10-18 Volkswagen Aktiengesellschaft Verfahren, vorrichtung und computerlesbares speichermedium mit instruktionen zur schätzung einer pose eines kraftfahrzeugs
DE102017108130B4 (de) 2017-04-13 2024-02-29 Volkswagen Aktiengesellschaft Verfahren zur Datenfusion eines Datensatzes, entsprechende Recheneinheit und Fahrzeug welches mit einer entsprechenden Recheneinheit ausgestattet ist sowie Computerprogramm
DE102018205205A1 (de) * 2018-04-06 2019-10-10 Continental Teves Ag & Co. Ohg Verfahren zur Ermittlung der Position eines Fahrzeugs
CN114383610B (zh) * 2021-12-24 2024-07-16 郑州恒达智控科技股份有限公司 一种基于移动三维扫描技术的抖动检测分段滤波方法

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DE10238061B4 (de) * 2002-08-20 2005-06-02 Litef Gmbh Verfahren zur Bestimmung und Kompensation des durch Wellenlängenänderung verursachten Skalenfaktorfehlers in einem GPS-gestützten INS-System
US8447517B2 (en) * 2008-11-06 2013-05-21 Texas Instruments Incorporated Tightly-coupled GNSS/IMU integration filter having speed scale-factor and heading bias calibration
DE102010063984A1 (de) 2010-02-11 2011-08-11 Continental Teves AG & Co. OHG, 60488 Fahrzeug-Sensor-Knoten
WO2013037850A1 (fr) 2011-09-12 2013-03-21 Continental Teves Ag & Co. Ohg Système capteur à correction temporelle
DE102012219478A1 (de) 2011-10-24 2013-04-25 Continental Teves Ag & Co. Ohg Sensorsystem zur eigenständigen Bewertung der Integrität seiner Daten
CN103575299B (zh) * 2013-11-13 2016-09-21 北京理工大学 利用外观测信息的双轴旋转惯导系统对准及误差修正方法

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DE102014211172A1 (de) 2015-12-17

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