EP3155373A1 - Procédé et système d'adaptation d'un système de navigation - Google Patents

Procédé et système d'adaptation d'un système de navigation

Info

Publication number
EP3155373A1
EP3155373A1 EP15729402.6A EP15729402A EP3155373A1 EP 3155373 A1 EP3155373 A1 EP 3155373A1 EP 15729402 A EP15729402 A EP 15729402A EP 3155373 A1 EP3155373 A1 EP 3155373A1
Authority
EP
European Patent Office
Prior art keywords
measured values
correction
values
navigation system
error
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.)
Ceased
Application number
EP15729402.6A
Other languages
German (de)
English (en)
Inventor
Nico Steinhardt
Daniel SUREK
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 Automotive Technologies GmbH
Original Assignee
Continental Teves AG and Co OHG
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Continental Teves AG and Co OHG filed Critical Continental Teves AG and Co OHG
Publication of EP3155373A1 publication Critical patent/EP3155373A1/fr
Ceased legal-status Critical Current

Links

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
    • 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
    • G01C21/183—Compensation of inertial measurements, e.g. for temperature effects
    • G01C21/188—Compensation of inertial measurements, e.g. for temperature effects for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems
    • 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 adjusting a navigation system according to the preamble of claim 1, a system for adjustment of a navigation system according to the preamble of An ⁇ demanding 6, and a use of the system.
  • All measurement data are subject to errors and in many cases there is no consistent availability of the measurement data.
  • the measured data are often also dependent on ambient conditions.
  • Sensor errors or measurement errors can be subdivided into quasi-stationary components, which are constant over several measurements, such as a so-called offset, and statistical components that are random from measurement to measurement, such as noise. While the random parts are in principle not deterministically correctable, quasi-stationary errors can generally be given
  • Sensor fusion methods are known, which are usually also suitable for correcting or filtering measurement data from different sensors or sensor systems. Particular requirements are to be taken into account in the automotive sector, in particular, 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. For a sensor fusion applicable in the automotive sector, the greatest possible robustness against incidental disturbances and identification and compensation of systematic errors is required. Likewise, temporal influences on the measured data must be corrected and temporary failures or the unavailability of sensors bridged.
  • DE 10 2012 216 211 A1 describes a method for selecting a satellite, wherein the satellite is a satellite of a global navigation system.
  • 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. Since the distance and the relative speed depend on each other, they can be verified against each other.
  • a verification of the particular one of the signal values against known boundary conditions can be carried out, because a vehicle usually travels within a certain Ge ⁇ schwindtechniksrahmens. It is also described that when receiving several signals from different satellites, 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 each other. Finally, it is also possible to verify 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. Provided that the signals of a satellite can not be verified, this satellite is not used for Positionsbe ⁇ humor or to the velocity determination.
  • a sensor system comprising several sensor elements.
  • the sensor elements are designed so that they are at least partially different primary measured variables capture 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 quantities thus provide redundant information which 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.
  • the 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 at least partially detect different primary measured variables or at least partially use different measuring principles.
  • 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 invention relates to a method for adapting a navigation system, wherein the navigation system comprises a base system and at least one correction system, wherein the base ⁇ system and the at least one correction system each
  • Measured values are recorded, said measured values describe navigation data, wherein the measured values are in each case subject to error values, said error values describe deviations of the measured values of the described navigation data, wherein a detection of at least the error values of the measured values of the base ⁇ system by means of the measured values of the at least one corrective - tursystems takes place and wherein the recognition taking into ⁇ actuating an availability of at least one correction system is carried out, wherein the inclusion is an adaptation of parameters of a stochastic system model and the stochastic system model in accordance with parameters, a weighting of measurements of the at least one correction system compared to measured values of the Basic system pretends.
  • an availability of at least one correction system here describes both the Er chargedsbe ⁇ conditions or ambient conditions in accordance with given by the environmental conditions for data acquisition as well as intrinsic system errors, system faults and system defects.
  • the availability of the at least one correction system is therefore characterized both by external influences as well as by internal influences.
  • the detection conditions or environmental conditions are e.g. Limitations in the measured value detection capability of the base system or of the at least one correction system, such as shadowing of a GPS system against the GPS satellites, e.g. when driving through a tunnel or a canyon.
  • Limitations in the measured value detection capability of the base system or of the at least one correction system such as shadowing of a GPS system against the GPS satellites, e.g. when driving through a tunnel or a canyon.
  • a particular advantage of the method according to the invention is also to be seen in the fact that the so-called.
  • System matrix for adapting the navigation system is not changed, but remains constant. Instead, only the so-called system noise matrix is adjusted. This means that the risk for generating a non-consistent state of the navigation system ⁇ , especially a non-consistent filter condition of a filter merger of the navigation system, is avoided.
  • the invention thus enables an adaptation of the Navigati ⁇ onssystems to each of so-called present. System noise. This .
  • Measuring noise which only describes the quality of the measured values recorded by the sensor systems.
  • the adaptation is preferably carried out while using predefined sets of parameters of the stochastic system model that can be adapted for un ⁇ ter Kunststofferie situations or availability gradually or can be adjusted continuously, for example via one or more characteristics or via one or more maps.
  • a correction of at least the error values of the measured values of the base system is carried out by means of the measured values of the at least one correction system, wherein the correction takes place taking into account the availability of the at least one correction system.
  • the error values of the measured values of the at least one correction system are detected and corrected, the error values of the measured values of the at least one correction system are particularly preferably detected by means of the measured values of the base system or the measured values of a further corrective ⁇ tursystems and corrected.
  • the error values of a suitable stochastic model the model taking into account the individual properties of the respective sensor system.
  • the base system is an inertial navigation system and that the at least one correction system is a global satellite navigation system and / or an odometry navigation system.
  • the present invention for navigation purposes and for navigation systems, preferably in motor vehicles, particularly well suited.
  • the navigation system thus determines, inter alia, the position, in particular the position of a motor vehicle, from the
  • the global navigation satellite system may be, for example, a so-called GPS navigation system.
  • the Odometrienavigationssystem first determines the speed Ge ⁇ eg with the known rolling circumference of the
  • the satellite navigation system comprises at least two satellite signal receivers. This improves the reliability and accuracy of the satellite navigation system.
  • the inertial navigation system as a basic system offers the advantage that it has the comparatively highest availability, since it has a comparatively high output rate of the measured values recorded and, moreover, works largely independently of external interference.
  • the availability of the at least one correction system is determined by means of a self-diagnostic function.
  • the self-diagnostic function is preferably designed such that it can both determine internal defects and errors and also determine external interference.
  • the detection and / or the correction by means of an error-state space filter, in particular by means of an error-state-space Kalman filter done.
  • the error state space filter represents a fusion filter for the fusion of the measured values, in particular for the fusion of normally distributed measured values.
  • the Eror State Space Filter preferably estimates or determines the error values of at least the base system.
  • the error values and possibly also unknown variables of the inertial navigation system can then be estimated or determined.
  • a special feature of the error-state space filter is therefore that instead of the sensor signals or the measured values only Error values are incrementally estimated or determined and then corrected.
  • the error values namely have a significantly lower temporal dynamics than the measurement values itself, whereby a significant decoupling of the dynamics of the error-state-space filter on the properties of the base ⁇ system or the at least one correction system is achieved.
  • Another peculiarity of the error-state-space Kalman filter is that, by applying a correction, the estimated or determined error values are zero after each operating cycle of the Err-State-Space Kalman filter Prediction step for predicting the error values in the following work cycle is eliminated, thus reducing the computational effort for the error-state-space Kalman filter.
  • the invention further relates to a system for adapting a navigation system, wherein the navigation system comprises a base system and at least one correction system,
  • the base system and the at least one correction system are each designed to record measured values, wherein the measured values describe navigation data, wherein the measured values are each associated with error values, wherein the error values describe deviations of the measured values from the described navigation data
  • the system is configured to perform a recognition of at least the error values of the measured values of the base ⁇ system by means of the measured values of the at least one corrective ⁇ tursystems and wherein the system is adapted to perform the detection taking into account a detection state of the at least one correction system, the consideration of a represents adaptation of parameters of a stochastic system model and the stochastic model system in accordance with the parameters a Ge ⁇ weighting of measured values of the dictates at least one correction system compared to measured values of the base system.
  • the dung OF INVENTION ⁇ proper system thus comprises all necessary for carrying out the inventive method it ⁇ devices. It is preferably provided that the system is designed to carry out the method according to the invention.
  • the invention relates to a use of the system according to the invention in a motor vehicle.
  • FIG. 1 shows an example of 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 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, the so-called basic system whose measured values are corrected by means of the so-called correction systems described below.
  • Correction systems are the odometry navigation system 103 and the satellite navigation system 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 measured values of inertial sensor navigation system 101, among other things, are converted into position data. For this purpose, the measured values of inertial sensor navigation system 101, which naturally describe accelerations, are integrated twice over time. Also, an alignment of the motor vehicle is determined by means of two ⁇ repeated integration of the corresponding measured values of inertial sensor navigation system 101 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 sensor navigation system 101.
  • the output data of strapdown algorithm unit 102 thus includes 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 from the strapdown algorithm unit 102 have the Va ⁇ rianzen as information on the quality of the above-mentioned Navigation data. These variances are not calculated in strapdown algorithm unit 102, for example, but only used and forwarded by the latter. The of
  • Strapdown algorithm unit 102 calculated o.g. Navigation data is output via output module 112 and made available to other motor vehicle systems.
  • the navigation system also includes
  • 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 exemplified Navigati ⁇ onssystem satellite navigation system 104 which is formed so that it in each case determines the distance between an associated satellite and the Kraftahr Weg and Ge ⁇ speed in each case between the associated satellite and the motor vehicle.
  • 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 sensor 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 sensor navigation system 101 The measurements of inertial sensor 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 represents the so-called basic system, represent while Odometrienavigationssystem 103 and Satellitennaviga ⁇ tion system 104, the so-called. correcting systems, the measured values for the correction of the measured values of the base system are attracted ⁇ forth. 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 comprises the quantitative errors of the base system determined by means of the plausibilized measured values of the correction systems.
  • Strapdown algorithm unit 102 is now corrected by Fu ⁇ sion data record 106, the measured values of the base system.
  • Fusion data set 106 is output from fusion filter 105
  • Fusion filter 105 is, for example according to as ER ror state-space Kalman filter is designed so as Kalman filter, which executes in particular, a linearization of the measured values and in which computes the quantitative error values of the measured values or are estimated and which se ⁇ quentiell works and thereby corrects the available in each function ⁇ onsön the sequence of measured values.
  • 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 are guided via the motor vehicle model unit 107 and the outage model unit 109.
  • Motor vehicle model unit 107 is designed such that from the measured values of odometry navigation system 103 at least the speed along a first axis, the speed is calculated along a second axis and the rate of rotation about a third axis and provides 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
  • the example according to inputs from ReifenparameterMt- wetting unit 110 are the wheel speeds and the steering angle descriptive measured values, at least partially, the output values of the strapdown algorithm unit 102, as well as certain of fusion ⁇ filter 105 variances.
  • the exemplary system also includes
  • GPS error detection and plausibility unit 111 which is designed such that, for example, it receives as input data the measured values from satellite navigation system 104 as well as at least partially measured values from strapdown algorithm unit 102 and takes them into account in their calculations.
  • GPS error detection and plausibility check unit 111 checks the measured values 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.
  • fusion filter 105 is additionally connected to fusion filter 105 at the data level and transmits the plausibility measured values to fusion filter 105.
  • GPS error detection and validation unit 111 is exemplified to provide a method for selecting of a satellite, inter alia, by means of the following method steps:
  • ⁇ 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 permissible deviation corresponds to a multiple of the standard deviation such that a probability that the position data fall within a standard deviation dependent 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 designed in such a way that it uses the measured values of the data as input data , n
  • Wheel speed sensors odometry navigation system 103 and the measurements of inertial navigation system 101 uses.
  • the sensor fusion system used, for example in accordance with a first set of measurement values which relate to a Kraft povertykoordi ⁇ natensystem and in addition a second set of measurement values 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, 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, the results of which it provides via fusion data set 106
  • Fusion filter 105 thus detects the measured values of inertial navigation system 101, the basic system, as well as of
  • Odometry navigation system 103 and satellite navigation system 104 the correction systems.
  • the self-diagnostic function is essentially a comparison of the detected Cor ⁇ rektursysteme, ie Odometrienavigationssystem 103 or satellite navigation system 104.
  • Measured values of the correction system which is only available to a limited extent, are assumed to have quantitatively greater error values and are less heavily weighted than the measurements of the base system and the measurements of the fully available correction system.
  • FIG. 2 shows by way of example a further possible embodiment of a system according to the invention, which is likewise designed to adapt a navigation system, in a motor vehicle (not shown).
  • the system includes, for example, the inertial navigation system 201, the satellite navigation system 204, and the odometry navigation system 203 as different sensor systems.
  • Inertial navigation system 201, Satellitennavigati ⁇ onssystem 204 and Odometrienavigationssystem 203 give measured values which describe directly or indirectly navigation data, namely a position, a velocity, an acceleration, an orientation, a yaw rate or a yaw acceleration of fusion filter 205.
  • the output of the measured values takes place via a vehicle data bus, for example via a so-called CAN bus.
  • Satellitennavigati ⁇ onssystem 204 its measurement data in raw form to.
  • 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 distance covered 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 measured values to preprocessing unit 206 of inertial sensor navigation system 201 off. Pre-processing unit 206 now corrects the
  • the pre-processing unit 206 receives from Fusi ⁇ onsfilter 205.
  • the thus corrected measured values or the navigation data described therein are passed on to strapdown algorithm unit 207.
  • Strapdown algorithm unit 207 now makes a position determination based on the corrected measured values from preprocessing unit 206.
  • This position determination is a so-called dead reckoning on the basis of inertial navigation system 201.
  • the corrected measured values output by pre-processing unit 206 or the navigation data described therein are continuously integrated or added up over time.
  • Strapdown algorithm unit 207 compensates white ⁇ terhin acting on inertia sensor navigation system 201 Coriolis force, which may affect the measurement data from inertial navigation system ⁇ two hundred and first
  • strapdown algorithm unit 207 performs a two-fold integration of those detected by inertial navigation system 201
  • Measured values which 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 leads
  • Strapdown algorithm unit 207 a simple integration of the measured values acquired by inertial sensor navigation system 201 over time. Further corrected
  • the running of strap-down algorithm unit 207 so-called. Strapdown algorithm is computationally very little complex and therefore can be used as real-time capable base system reali ⁇ Sieren.
  • Inertial navigation system 201 pre-processing unit 206 of inertial sensor navigation system 201 and
  • Strapdown algorithm unit 207 form, by way of example, the so-called basic system, to which additionally proportionately also fusion filter 205 is counted.
  • Output module 212 relays the navigation data 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 Satellitenna ⁇ vigationssystem 204 measured values, which
  • satellite navigation system 204 determines a relative speed of the motor vehicle to the GPS satellites, of which GPS signals be received.
  • preprocessing unit 208 corrects a time error of a receiver clock of satellite navigation system 204 caused by drift of the receiver clock in the measured values and, by means of a correction model, the changes in the signal propagation time and of the GPS signals 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 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 plausibility check the output from the preprocessing unit 208 ⁇ readings of the navigation data, that is, the position and the speed of the motor vehicle.
  • the measured values 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 the measured values acquired by odometry navigation system 203 via the CAN bus.
  • the recorded measured values are the measured values of the individual wheel speed sensors as well as the measured values 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 measured values output by odometry navigation system 203 in accordance with a so-called dead reckoning method. Furthermore, the speed n Trent the accelera-, determines the rotation rate and the rotational acceleration of the motor ⁇ vehicle, also in the vehicle coordinates ⁇ system. In addition, corrected pre-processing unit 210 the measurement values obtained from Odometrienavigationssystem 203 by means obtained from Fusion filter 205 correction values.
  • Odometrienavigationssystem 203 is further plausibility check module 211 associated with which the measured values output from preprocessing ⁇ unit 210, so the position Alignment, the speed, the acceleration, the rotation rate and the spin of the motor vehicle, plausibility. Since the disturbances of the measured 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 determined by means of Satellitennavigati ⁇ onssystem 204 measured values in order to check the plausibility of the measured values of Odometrienavigationssystem 203rd First, the measured values against them sensor-individual model are also here but assigned, matched that Messunsi ⁇ uncertainties as noise influences into account. If the measured values correspond to the model within the given limit values or tolerance ranges, a first occurs here
  • the plausibility check and the plausibility of the values 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 measured values of the base system, ie of inertial navigation system 201, by means of measurements 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.
  • the measurements of inertial navigation system 201 are exclusively white noise.
  • fusion filter 205 is a so-called Eror State Space Kalman filter, only the quantitative error values of the measured values are determined and corresponding corrections are carried out. This simplifies and accelerates fusion of measured values 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 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, 203 and satellite-Odometrienavigationssystem tennavigationssystem 204th On the basis of the output data or outputs is not clear what sensor systems are powered ⁇ connected into the system.
  • an adaptation of parameters of a stochastic system model namely the so-called noise matrix of the system
  • the change in the availability of satellite navigation system 204 according effected, for example caused by a tunnel driving of the motor ⁇ vehicle so that satellite navigation system 204 can not receive signals more of the associated navigation satellites.
  • This circumstance is recognized on the one hand by means of a self- diagnostic function of satellite navigation system 204 and reported to fusion filter 205 and on the other hand recognized by means of a digital road map present in the navigation system and also reported to fusion filter 205.
  • the system according to the invention now loads from a digital memory a parameter set for weighting the different measured values, which is specially adapted to a tunnel drive.

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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Navigation (AREA)

Abstract

L'invention concerne un procédé d'adaptation d'un système de navigation qui comprend un système de base et au moins un système de correction, le système de base (101, 201) et au moins un système de correction acquérant chacun des valeurs de mesure qui décrivent des données de navigation. Ces valeurs de mesure s'accompagnent à chaque fois de valeurs d'erreur qui décrivent des écarts des valeurs de mesure par rapport aux données de navigation décrites. Les valeurs de mesure du ou des systèmes de correction sont utilisées pour identifier au moins les valeurs d'erreur des valeurs de mesure du système de base. Cette identification se fait en prenant en compte la disponibilité du ou des systèmes de correction. Cette prise en compte constitue une adaptation de paramètres d'un modèle de système stochastique. En fonction des paramètres, ce modèle de système stochastique prédéfinit une pondération des valeurs de mesure du ou des systèmes de correction par rapport aux valeurs de mesure du système de base. L'invention concerne en outre un système correspondant ainsi qu'une utilisation de ce système.
EP15729402.6A 2014-06-11 2015-06-09 Procédé et système d'adaptation d'un système de navigation Ceased EP3155373A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102014211164.1A DE102014211164A1 (de) 2014-06-11 2014-06-11 Verfahren und System zur Anpassung eines Navigationssystems
PCT/EP2015/062790 WO2015189180A1 (fr) 2014-06-11 2015-06-09 Procédé et système d'adaptation d'un système de navigation

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EP3155373A1 true EP3155373A1 (fr) 2017-04-19

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US (1) US10267638B2 (fr)
EP (1) EP3155373A1 (fr)
CN (1) CN107076559B (fr)
DE (1) DE102014211164A1 (fr)
RU (1) RU2667667C2 (fr)
WO (1) WO2015189180A1 (fr)

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CN110873888B (zh) 2018-09-04 2022-05-06 腾讯大地通途（北京）科技有限公司 定位方法、定位装置、定位设备和计算机存储介质
CN110658542B (zh) * 2019-10-10 2021-07-20 安徽江淮汽车集团股份有限公司 自动驾驶汽车定位识别方法、装置、设备及存储介质
CN112729288B (zh) * 2020-12-23 2023-07-14 北京机电工程研究所 一种重力梯度-地形异源数据匹配的导航定位系统
CN112762924B (zh) * 2020-12-23 2023-07-14 北京机电工程研究所 基于重力梯度-地形异源数据匹配的导航定位方法

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Also Published As

Publication number Publication date
RU2016147904A3 (fr) 2018-07-12
RU2667667C2 (ru) 2018-09-24
CN107076559A (zh) 2017-08-18
RU2016147904A (ru) 2018-07-12
WO2015189180A1 (fr) 2015-12-17
US10267638B2 (en) 2019-04-23
DE102014211164A1 (de) 2015-12-17
US20170089705A1 (en) 2017-03-30
CN107076559B (zh) 2021-09-03

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