Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
  • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/13—Receivers
  • G01S19/22—Multipath-related issues
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
  • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/396—Determining accuracy or reliability of position or pseudorange measurements
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
  • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/40—Correcting position, velocity or attitude

Definitions

• the present invention falls within the field of geographical positioning by use (alone or hybrid) of satellite positioning signals for all land, sea, river, or low-altitude aerial applications.
• satellite positioning is based on the reception by a terminal, arranged for example on the surface of the globe, of signals from at least four synchronized clocks arranged in transmitting objects whose positions are known.
• the distance between a clock and the receiver determines a signal propagation time, proportional to said distance.
• the four signal reception delays of the four clocks make it possible to calculate a solution determining the position, speed and time at the reception terminal.
• the reference objects are moving satellites in medium orbit, and a satellite positioning system usually called GPS (for “Global Positioning System”), or GNSS (for “Global Navigation Satellite System”) comprises several dozen satellites, so that at any time an object placed on the ground or in the vicinity of the ground is in sight of at least four satellites, and often significantly more.
• GPS Global Positioning System
• GNSS Global Navigation Satellite System
• the local environment is defined as the set of final propagation conditions capable of modifying or obscuring the signal received by the receiver. Among these propagation conditions, it is necessary to consider any terrestrial obstacle modifying the propagation path or the power of the received signal as well as various interference or jamming. The ionosphere and the troposphere are excluded from the local environment.
• a first problem is to characterize the local environment and its impact on the P VT triplet (Position, Speed, Time) measured by the GNSS receiver. The precision of geolocation in particular is highly sensitive to these parameters. For years, researchers in the field have set themselves the objective of being able to anticipate the shape and importance of errors likely to impact the determination of positions.
• a second problem is related to the current lack of digital data defining the obstacles to the propagation of GNSS signals, while these obstacles are an integral part of the operational conditions of any satellite positioning application.
• the EN16803-1 standard defines six main categories of local environment.
• the position errors therefore depend on the instrumental quality of the GNSS receivers and of the GNSS infrastructures, such as satellite constellations, on the one hand, and on harmful phenomena that alter the quality of the signals, on the other hand.
• Precision is defined (JCGM 200: 2012) as "the closeness of agreement between indications or measured values obtained by repeated measurements of the same object or similar objects under specified conditions". We understand that the fidelity represents the random error between different successive measurements taken at the same place under the same conditions.
• the GNSS signal propagation channels are liable to be interrupted (for example by tunnels, bridges, buildings, etc.), lengthened (for example by multipath signals on buildings ... ) and altered (for example by attenuation and diffraction of signals by foliage, interference ).
• the lengthening of the GNSS signal propagation channels cause Accuracy errors made worse by the reduction in the number of visible satellites, often due to various obstructions in the environment.
• the first method is the generation of signals by simulators. This allows the test conditions to be checked, but is not sufficiently representative of the actual operational conditions of the measurement due to the lack of sufficiently realistic and dynamic modeling of the local phenomena modifying the propagation of the signals (in terms of power and delays);
• the second method consists of recording the real GNSS radiofrequency signals collected in the field, then playing them back in the laboratory in order to recreate the measurement conditions. In this case, the reproducibility and repeatability of the tests are well obtained, the representativeness of the operational conditions is ideal.
• the object of the invention is notably to remedy these drawbacks.
• the invention relates in a first aspect to a method of producing a georeferenced database X on a zone Z which characterizes the local GNSS environment by separately measuring the biases, that is to say the systematic errors. (or “Accuracy” errors) and random errors (or “Fidelity” errors).
• These error profiles are the imprints of the local environment which can consist of obstacles obscuring, hindering and / or deviating the propagation of GNSS signals before being picked up by an antenna, such as infrastructures, terrain, vegetation, sources of parasitic radiofrequencies. Such obstacles are particularly shown in Figure 1.
• the method of characterizing a local environment by a satellite positioning system comprises the following steps:
• GNSS receiver 100 recording of data (position, speed, time, satellite measurements) supplied by a GNSS receiver, in particular a receiver of the type known to those skilled in the art under the name “professional GNSS receiver”, during at least one monitoring campaign. dynamic collection carried out in the local environment to be characterized.
• the term “professional GNSS receiver” means a receiver capable of providing the basic measurements necessary for calculating the metrics defined below in this text, and more generally a receiver having the following characteristics:
• the number of constellations processed is greater than or equal to 3 (such as GPS, Galileo, GLONASS, Beidou);
• One of the advantages of the invention is to be able to separately estimate the errors of Trueness and Fidelity from the metrics obtained from the data supplied by the receiver. These metrics are intrinsically linked to propagation phenomena caused by the local environment and practically independent of receiver performance. In other words, the method described therefore makes it possible to break down the impact of the local GNSS environment into a component of accuracy and a component of fidelity.
• the aim of the invention is to provide tangible data and tools for testing and controlling systems using GNSS by first carrying out a step of characterizing the local GNSS environment in a digital and unequivocal manner. by its impact in terms of accuracy and reliability on the geo-positioning solution.
• step 300 of the method distinguishes the impact of the local GNSS environment on the measurements provided by the satellites from that on the visibility of the satellites, whether for estimating the Accuracy or for estimate Fidelity.
• step 300 of the method comprises the following sub-steps:
• step 310 in which the validity of the data recorded by the receiver is checked and the raw measurement data is extracted; a step 320 in which an indicator A (P) is calculated for each instant of the test on the basis of the signal to noise density ratio measurements C / N0 extracted in step 310;
• step 330 in which, for each instant of the test, an indicator D (P) is calculated from the raw measurement residuals extracted in step 310;
• step 340 in which an aggravation indicator B (P) is calculated for each instant of the test from a matrix resulting from a calculation of the precision dilution (DOP) on valid measurements.
• P an aggravation indicator B
• DOP precision dilution
• a step 350 in which an indicator for the propagation of errors on the measurements in the triplet P VT C (P) is calculated for each instant of the test from the values of the sensitivity matrix S.
• This matrix gives weight to each satellite characterizing their impact on positioning errors, hence the term “sensitivity”. In particular, it makes it possible to locate the most critical satellites for accuracy.
• Step 300 of the method also comprises a step 360 in which an accuracy indicator J and a reliability indicator F are calculated from the four metrics introduced in steps 320, 330, 340 and 350.
• the loyalty indicator (F) depends on the indicators A (P) and B (P). It is calculated as follows:
• an indicator A (P) of measurement fidelity is calculated calculated as the time derivative of the average, over all the satellites whose signals are received by the professional GNSS receiver, of the received signal power to noise spectral density ratios, C / N0.
• step 330 the indicator of D (P) of the measurements is calculated at each recording time as the L1 norm of the vector of the residuals of the measurements.
• an aggravation indicator B (P) of the random errors detected on the satellite measurements is calculated for each instant, using the calculation of the precision dilution (DOP ) horizontal (HVOP), vertical (VTOP) or temporal (TDOP) from the satellite axes which provided a valid measurement.
• DOP precision dilution
• HVOP horizontal
• VTOP vertical
• TDOP temporal
• the DOP is calculated at each instant as below, from the observation matrix H constructed with the azimuths and elevations of the satellites:
• the sensitivity indicator C (P) is calculated as the smallest diagonal term of the matrix S, min ((3 ⁇ 4) ie [i; N sat ] ). This matrix which is calculated as described below from the matrix H introduced previously:
• this embodiment has three major advantages: - It separates the fidelity impacts marked by the indicators A (P) and B (P) from the accuracy impacts marked by the indicators C (P) and D (P);
• the method comprises a step 301 consisting in making accessible all the indicators A (P), B (P), C (P), D (P), of accuracy (J) and fidelity (F), without being exhaustive, in the form of a database; said indicators (J) and (F) being linked to geo-referenced coordinates and converted into a format readable by a navigation system.
• the invention also relates to the devices, essentially software, which implement the steps of the method, as well as to the services and data from these devices.
• the products derived from the method according to the present invention will essentially be translated into digital data libraries and / or software products making it possible to generate and use these libraries. Products, software, libraries, and methods that utilize these libraries are also contemplated by the present invention.
• the first concerns Metrology, the second Navigation and the third Simulation.
• the method can be used to characterize and classify categories of local environments and error models by categories.
• the method can be used to anticipate propagation phenomena and to implement error reduction strategies, in particular by having recourse to hybridization techniques.
• the system navigation will exploit the data of the local environment to be crossed previously characterized.
• the method can be used to model systematic GNSS errors (multiple paths) and to cause random GNSS errors.
• the method can be used to calculate over a given route sets of trajectories representative of a given GNSS receiver subjected to a disturbed local environment. This process is supposed to be integrated into a test bench managing the simulation of other modeled sensors. The combination of scenarios for each sensor covers all test cases for dependability and integrity analysis.
• Figure 1 illustrates the elements of the local environment likely to interfere with GNSS reception of a vehicle
• FIG. 2 illustrates the mechanisms of the impact of the local environment on the fidelity and accuracy of the satellite measurements then of the P VT triplet;
• Figure 3 illustrates the main steps of the process and the use cases
• Figure 4 is a decomposition of the step of calculating the accuracy and precision indicators (step 300);
• Figure 5 is one of the possible graphical representations of the metrics used
• FIG. 1 illustrates such a system, very schematically with several satellites 10 which transmit time data to a GNSS receiver 13, here installed in a truck.
• the GNSS receiver 13 is of the type known to those skilled in the art under the name “professional GNSS receiver”.
• environmental elements can interfere with the correct reception of data by the professional GNSS receiver 13 traveling on a road 14.
• disruptive environmental elements there may be mentioned, in a nonlimiting manner, buildings 15, transmitting antennas 16, trees 17, etc.
• the local environment causes many errors: modification of the signal path (reflection, diffraction, refraction), masking, attenuation, interference.
• Masking, attenuation, and interference cause scattering of measurements and sometimes loss of measurements.
• Masking causes a loss of observability of certain satellites from the receiver.
• the geographic position error is broken down into two components:
• Vehicle speed can have an effect that reduces the systematic effect of errors in favor of effects that appear to be random.
• the characterization of the environment developed by the present invention makes it possible to differentiate the potential impact of a local environment on the Trueness and on the Fidelity of the P VT solution.
• the GNSS measurement assumes that the propagation of the signal has taken place in a straight line on the transmitter-receiver axis of visibility (also known as the 'sight axis'). As a result, any refraction, reflection or diffraction (modification of the signal path) is an alteration of the signals. of interests, creating errors that will be qualified as systematic, because of principle. They then affect the accuracy of the measuring instrument.
• the weakening of the signals whether by attenuation, or by the presence of ambient noise out of the ordinary affects the quality of the signal processing, which results in a greater dispersion then affecting the fidelity. of the instrument.
• a use may appear, in design office and laboratory, in several stages of the development cycle of any complex geolocated application, giving in particular the dependence of GNSS performance on the operational conditions found in zone Z. Thanks to the collection From the data carried out in the first stages, certain questions specific to security analysis and the design of complex systems which will have to meet operational specifications can be answered.
• each section of the road axis in a geographical area can be associated with indicators available in a database. These indicators characterize the risks of accuracy and reliability error on the P VT triplet specific to the local environment during dynamic geolocation. The accumulation of information on a local environment then gives the possibility of defining types of environment over a wide geographical area.
• Geolocation applications integrating a GNSS receiver alone or merged with other sensors will then be able to integrate more artificial intelligence if they have a priori knowledge of the environment that is likely to be encountered. Feedback from these operational users could thus support the updating of this georeferenced database.
• a set of records is made by a professional GNSS receiver 13, on the basis of a dynamic campaign (typically travel of a vehicle on a road route), from which data is taken. recorded data 101.
• a dynamic campaign typically travel of a vehicle on a road route
• the chosen route has no limitation in terms of time or distance traveled.
• the same street can be crossed several times, in different time intervals.
• the need in this step 100 of characterizing the local GNSS environment is that the recorded data 101 include raw information from the signal processing stage of the professional GNSS receiver, such as raw measurement data on the devices.
• satellite axes :
• an ASTERX-U type GNSS terminal from the company SEPTENTRIO meets the need and constitutes a preferential implementation, but does not constitute a unique solution.
• the recording will use a digital format (ASCII for NMEA xxx and / or RINEX) and preferably binary for the proprietary format of the outputs of the device (example sbf format for SEPTENTRIO devices). Obviously, this can change over time.
• the data is necessarily dated by a GNSS or UTC time.
• a second step 200 the true trajectory 201 of said receiver 13 is determined during these recordings.
• the preferred implementation uses a reference instrumentation consisting of an inertial unit (IMU) and a high quality GNSS receiver, for example being dual-frequency, dual-constellation.
• the GNSS receiver is corrected and hybridized in post processing using the correction data from one or more reference station networks (PPK techniques (acronym for the English term “Post Processing Kinematic”) - using NRTK networks (acronym of the English term “Network Real Time Kinematic”) or PPP (abbreviation of the English term “Precise Point Positioning”).
• PPK techniques as analog for the English term "Post Processing Kinematic”
• NRTK networks analog of the English term “Network Real Time Kinematic”
• PPP abbreviation of the English term “Precise Point Positioning”.
• the inertial measurement unit makes it possible to maintain precise measurement in difficult environments, with the ability to only maintain a accuracy of a few centimeters over a period of about one minute.
• a favorable implementation of the method 200 uses PPK techniques and a hybridization from the recorded data 101 supplied by the equipment used for step 100. It can be called upon to the use of specialized software supplied by the manufacturer of the GNSS receiver and / or an inertial unit.
• the data jointly forming the true trajectory 201, that is to say here all the position data as a function of time, and of speed as a function of time. , these two parameters being referred to the phase center of the GNSS antenna of the professional GNSS receiver 13, and an estimate of the accuracy of these data as a function of time.
• the GNSS antenna used by the device specific to the trajectory is also that of the professional GNSS receiver 13.
• the method described here is based on the analysis of the metrics A (P), B (P), C (P) and D (P) and on the calculation of their potential impact on the fidelity and accuracy error on the solution P VT (position, speed, time) through the two indicators (F) and (J).
• Step 300 of the method comprises the following sub-steps:
• a step 310 in which a check is made of the validity of the data recorded by the professional GNSS receiver 13.
• the step includes the extraction at each instant of the local clock bias estimated by the professional GNSS receiver 13 and of the measurements and data raw dated for each reception channel associated with the satellites received;
• step 320 in which at least one indicator A (P) of the measurements from the signal to noise density ratio measurements C / N0 extracted by step 310 is calculated for each instant of the recorded test and relates it to the position P of the true trajectory recorded simultaneously;
• step 330 in which at least one indicator D (P) of the measurements from the raw measurement residues extracted by step 310 is calculated for each instant of the recorded test and it is related to the position P of the trajectory true reading simultaneously;
• a step 340 in which at least one indicator of aggravation B (P) of the random errors detected on the satellite measurements and consequently affecting the fidelity of an output P VT is calculated for each instant of the recorded test.
• P aggravation B
• a step 350 in which at least one sensitivity indicator C (P) to the accuracy errors of the measurements and consequently affecting the accuracy of the output P VT is calculated for each instant of the recorded test.
• This matrix gives a weight to each satellite characterizing their impact on positioning errors, hence the term sensitivity. In particular, it makes it possible to locate the most critical satellites for accuracy.
• a step 360 in which a correctness indicator J and a fidelity indicator F are calculated from the four metrics introduced in steps 320, 330, 340 and 350.
• the loyalty indicator (F) is a function of the indicators A (P) and B (P). It is calculated as follows:
• the accuracy indicator J (P) is a function of the indicators C (P) and D (P). It is calculated as follows:
• the indicators (J) and (F) will be linked to the georeferenced coordinates (P) in order to create a database. If necessary, the database can be converted into different digital formats. All or part of the indicators, as described in steps 320, 330, 340 and 350 can form part of this database.
• an indicator A (P) is calculated from the received signal power to noise spectral density ratios, called by those skilled in the art C / N0.
• the use of its time derivative increases the sensitivity of the indicator, because the instability of the C / N0 ratio is particularly characteristic of a disturbed environment (urban environment, for example) and of the difficulty in tracking the GNSS signal in synchronization.
• an average is preferably taken over all the satellites 10 whose signals are received by the professional GNSS receiver 13. Alternatively, this calculation can be carried out on the only subset of the satellites which have an elevation greater than one. configurable threshold.
• step 330 it is chosen to calculate at each recording instant the indicator D (P) of the measurements such as the L1 norm of the vector of residuals of the measurements.
• the term measurement residue is understood to mean the difference between the measurement carried out and supplied by the professional GNSS receiver 13 and the measurement which can be predicted from the known positions and speeds of the true trajectory 201, from the positions and recalculated speeds of the satellites from dating and ephemeris. It is also predicted from other knowledge of correction of systematic errors such as desynchronization errors of the clocks of the GNSS system satellites and the clock of the professional GNSS receiver 13, ionosphere and troposphere errors. The measurement residue then essentially represents the accuracy errors on the measurements.
• an aggravation indicator B (P) is calculated for each instant, using the conventional calculation of the horizontal (HDOP), vertical (VDOP) precision dilution (DOP) at from the satellite axes that provided a valid measurement.
• an observation matrix H is constructed at each instant of the recording from the azimuths and elevations of the visual axes (direct satellite transmitter-receiver axis).
• azimuths and elevations of the visual axes we use the corresponding dating of the instant of calculation, and the satellite ephemeris data to calculate the instantaneous position of the satellite corresponding to the desired visual axis, then by taking the instantaneous position of the true trajectory corresponding to the instant of calculation, one calculates in the local geographical axes the spherical coordinates of the satellite (azimuth / local geographic north axis, local elevation / horizontal plane).
• the indicator B (P) retains the appropriate indicator HDOP or VDOP.
• the indicator C (P) is calculated as the smallest diagonal coefficient of the matrix S according to the formulation:
• This matrix S characterizes the measurement errors which result in a bias on the position.
• FIG. 5 An example of a representation making it possible to characterize a local GNSS environment is given in FIG. 5.
• the path of the receiver during a path on the ground results in two curves.
• the first curve is located in the top right quarter of the figure and gives for each instant of the route a point F (P) whose coordinates are A (P) and B (P), impacting the fidelity of the triplet P VT.
• the second is located in the lower left quarter of the figure and gives a point for each moment of the course J (P) whose coordinates are D (P) and C (P), impacting the accuracy of the PVT triplet.
• the method relates to dynamic geolocation, that is to say that the method is intended to be implemented when the professional GNSS receiver 13 is installed on board a vehicle in movement.
• the issues related to static geolocation are different and are not affected by the process.
• semantic layers that can be integrated into geographic information systems are produced. Like these, they can be displayed on basemaps to create cartographic representations of standard errors of accuracy and fidelity of a GNSS positioning.
• the semantic layers are for example transformed into line thickness to visualize the fidelity and in color to visualize the accuracy error, the indicators being associated point to point with the geographical coordinates of the true trajectory established during the step 200 of the process.
• the inventive method has the merit of creating a new layer which can be easily integrated into future GIS (geographic information systems), HD map type which can be installed in navigation systems, for example connected vehicles. Addressing requests on these databases according to the current position, we can retrieve useful information on the capabilities of GNSS to provide precise and fair (safe) position information, to be taken into account for intelligent management and control of the sensors. navigation.
• GIS graphic information systems
• HD map type which can be installed in navigation systems, for example connected vehicles.
• the process can be adapted to define and segment with precision environmental categories
• the method can be adapted to inform a hybridized GNSS receiver to act on its parameter setting and weight the influence of the sensors associated with its calculation of positions with a view to increasing the navigation performance of a vehicle.
• the method can be adapted to synthesize more representative GNSS signals by slaving a constellation generator using data characterizing the local environment supposed to be reconstituted.
• the method can be adapted to calculate trajectories representative of a navigation by simulating the measurements of a given receiver in a given environment, that is to say by operating in a totally synthetic and configurable environment. .
• the application of the present method also covers the fields of GNSS metrology for the performance evaluation of GNSS terminals. More generally, the system engineering activities of the development cycles of geolocation systems and applications can benefit from the described process.

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• Engineering & Computer Science (AREA)
• Radar, Positioning & Navigation (AREA)
• Remote Sensing (AREA)
• Computer Networks & Wireless Communication (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Position Fixing By Use Of Radio Waves (AREA)

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• 2020
  • 2020-07-02 EP EP20735192.5A patent/EP3994498A1/de active Pending
  • 2020-07-02 WO PCT/EP2020/068698 patent/WO2021001489A1/fr unknown

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