Method for Generating a Three-Dimensional Environment Model Using GNSS Measurements

Abstract

The disclosure relates to a method for generating a three-dimensional environment model using GNSS measurements, comprising at least the following steps: a) receiving a plurality of measuring data sets, each of which describes a propagation path of a GNSS signal between a GNSS satellite and a GNSS receiver; b) selecting from the plurality of measuring data sets individual measuring data sets which meet a first selection criterion, the first selection criterion being characteristic for the presence of an object boundary along the propagation path of the GNSS signal; and c) capturing an object boundary of an object in the environment of at least one GNSS receiver using the measuring data sets selected.

Claims

1. A method for generating a three-dimensional environment model using GNSS measurements, the method comprising: a) receiving a plurality of measurement datasets that each describe a respective propagation path of a respective GNSS signal between a respective GNSS satellite and a respective GNSS receiver; b) selecting measurement datasets from the plurality measurement datasets that meet a first selection criterion, the first selection criterion being characteristic of a presence of an object boundary along the respective propagation path of the respective GNSS signal; and c) registering an object boundary of an object in an environment of a first GNSS receiver using the selected measurement datasets.

2. The method as claimed in claim 1, wherein the first selection criterion is that the each of the selected measurement datasets within a sorted succession of measurement datasets from the plurality of measurement datasets is one of a first measurement dataset and a last measurement dataset for which disturbed signal propagation is determined.

3. The method as claimed in claim 2, wherein the sorted succession of measurement datasets is sorted according to respective elevation angles.

4. The method as claimed in claim 2, wherein the sorted succession of measurement datasets is sorted according to respective timestamps.

5. The method as claimed in claim 1, wherein the plurality of measurement datasets are filtered according to a respective position of the respective GNSS receiver.

6. The method as claimed in claim 1, wherein the plurality of measurement datasets are filtered according to a respective position of the respective GNSS satellite.

7. The method as claimed in claim 1, further comprising, after the c) registering: i) selecting at least two measurement datasets from the selected measurement datasets in step b) that meet a second selection criterion, the second selection criterion being characteristic of a presence of a same object boundary along the respective propagation paths of the at least two respective GNSS signals; and ii) forming a plane in which at least sections of the respective propagation paths of the at least two respective GNSS signals of the selected at least two measurement datasets run.

8. The method as claimed in claim 7 further comprising: forming at least two planes, which are mutually different and nonparallel, each having running therein at least sections of the respective propagation paths of at least two respective GNSS signals of at least two measurement datasets that each meet the second selection criterion; and ascertaining an at least partial profile of the object boundary of the object from a line of intersection for the at least two planes.

9. The method as claimed in claim 1 further comprising: ascertaining a distance between the object and the first GNSS receiver.

10. The method according to claim 1, wherein the method is carried out by executing a computer program.

11. A non-transitory machine-readable storage medium that stores a computer program for generating a three-dimensional environment model using GNSS measurements, the computer program being configured to, when executed: a) receiving a plurality of measurement datasets that each describe a respective propagation path of a respective GNSS signal between a respective GNSS satellite and a respective GNSS receiver; b) selecting measurement datasets from the plurality measurement datasets that meet a first selection criterion, the first selection criterion being characteristic of a presence of an object boundary along the respective propagation path of the respective GNSS signal; and c) registering an object boundary of an object in an environment of a first GNSS receiver using the selected measurement datasets.

Description

[0049] The solution presented here and the technical environment for said solution are explained more thoroughly below with reference to the figures. It should be pointed out that the invention is not intended to be restricted by the exemplary embodiments shown. In particular, unless explicitly shown otherwise, it is also possible to extract partial aspects of the substantive matter explained in the figures and to combine said partial aspects with other parts and/or insights from other figures and/or the present description. In the figures:

[0050] FIG. 1: schematically shows a flowchart for the described method,

[0051] FIG. 2: schematically shows vehicles in which a method that is described here is used, in urban surroundings, and

[0052] FIG. 3: schematically shows a representative graphical illustration of the occurrence of a pseudorange error.

[0053] FIG. 1 schematically shows a flowchart for the described method. The method is used to generate a three-dimensional environment model using GNSS measurements. The order of steps a), b) and c) that is depicted by the blocks 110, 120 and 130 is merely illustrative and can arise as such for a normal operating cycle, for example.

[0054] In block 110, step a) involves receiving a multiplicity of measurement datasets that each describe a propagation path 1 (not depicted here, cf. FIG. 2) of a GNSS signal between a GNSS satellite 2 and a GNSS receiver 3. In block 120, step b) involves selecting single instances of the measurement datasets that meet a first selection criterion from the multiplicity of measurement datasets, wherein the first selection criterion is characteristic of the presence of an object boundary 4 along the propagation path 1 of the GNSS signal. In block 130, step c) involves registering an object boundary 4 of an object 5 in the environment of at least one GNSS receiver 3 by using the selected measurement datasets.

[0055] FIG. 2 schematically shows vehicles 10 in which a method that is described here is used, in urban surroundings.

[0056] The measurement datasets that are recorded, and subsequently received by a central data processing device, for example, each comprise: the actual position of the reception antenna, or of the GNSS receiver 3, which can be ascertained for example by means of an on-vehicle environment sensor system (not depicted here) using the position of the respective vehicle 10; the satellite position of the GNSS satellite 2; the measured pseudorange (cf. FIG. 3); and the measured signal strength of the GNSS signal. By way of illustration, the measurement datasets here are first collected over a relatively long period, e.g. 10 days, and using crowdsourcing (i.e. the measurements of different measurement instances are collated). Three vehicles 10 are shown by way of illustration here as an example of different measurement instances for crowdsourcing.

[0057] By way of illustration, the first selection criterion here is that the measurement dataset to be selected within a sorted succession of measurement datasets is the first or last measurement dataset for which disturbed signal propagation can be determined. The sorted succession of measurement datasets is sorted according to elevation angle 6 by way of illustration here. Alternatively, however, it is also conceivable for the sorted succession of measurement datasets to be sorted according to timestamp. Furthermore, the measurement datasets are filtered according to the position of the GNSS receiver 3 by way of illustration here. Alternatively, however, it is also conceivable for the measurement datasets to be filtered according to the position of the GNSS satellite 2.

[0058] The variant embodiment of step b) that is implemented by way of illustration here can be described as follows: the measurement datasets are first filtered according to the position of the GNSS receiver 3 (for example by applying a quantization of one meter). For each GNSS receiver position, the measurement datasets are filtered according to azimuth angle 11. To simplify matters, this can be accomplished by quantizing the measurement datasets according to azimuth angle 11 and elevation angle 6 (for example with an angular degree). The quantization can entail the measurement datasets with identical or very similar azimuth angle 11 and elevation angle 6 being statistically combined (for example averaging).

[0059] For each azimuth angle 11, the measurement datasets in this regard are now sorted according to elevation angle 6 (beginning with high elevation angle 6). The data sorted according to elevation angle 6 are searched for the elevation angle 6 at which the following traits occur for the first time: check on the pseudorange and/or signal strength for significant change in the event of decreasing elevation angle and/or whether the PR error exceeds a sensitivity limit (i.e. the state concerning whether a PR error can be measured changes from negative to positive). The “pseudorange” in this scenario describes the total length, ascertained on the basis of propagation delay measurement, of the propagation path 1 (if applicable reflected at least once) from satellite 2 to receiver 3.

[0060] Measurement data that have had a positive check are “marked” accordingly. They are used as a hypothesis for there being a building edge 4 at a point along the path 1 (the connecting line) between reception antenna, or GNSS receiver 3, and GNSS satellite 2. This is also referred to as an “edge hypothesis” here. The described search of the data sorted according to elevation angle 6 can then be carried out, or repeated, for all other azimuth angles 11.

[0061] In this regard, to also render the pseudorange and signal powers of different GNSS satellites 2 comparable if need be, it is moreover possible to calibrate the applicable offsets beforehand under LOS conditions. Alternatively, the offsets can also be calculated from the known satellite orbits and known transmission powers of the individual GNSS satellites 2. In this example, the sensitivity limit describes a threshold value (e.g. the standard deviation of the noise of the PR measurement) above which a PR error 12 (cf. FIG. 3) can be considered to be measurable.

[0062] Moreover, FIG. 2 is used to illustrate that at least the following intermediate steps can be carried out in step c): [0063] i) selecting at least two of the measurement datasets that meet a second selection criterion from the measurement datasets selected in step b), wherein the second selection criterion is characteristic of the presence of the same object boundary 4 along the propagation paths 1 of the at least two GNSS signals, [0064] ii) forming a plane 7 in which at least sections of the propagation paths 1 of the at least two GNSS signals run.

[0065] Following on from the illustrative variant embodiment of step b) that is described above, the variant embodiment of step c) that is implemented by way of illustration here can be described as follows: the elevation angle 6 and the azimuth angle 11 of the marked measured values (hypothesis for building edge 4) are now processed further and can subsequently be referred to as hypothesis vectors 1. A hypothesis vector 1 in this scenario generally forms a straight line between the GNSS receiver position 3 and the GNSS satellite 2 whose measurement data have been marked from the receiver position currently under consideration. Two hypothesis vectors 1 that are adjacent in the azimuth direction 11 are connected to form area elements 7 (as a result of which the latter span the plane 7) if the following traits (1) and (2) exist: (1) The marked measured values corresponding to the hypothesis vectors 1 originate from measurements that are adjacent in the azimuth direction 11 (i.e. if there is, for example between the two azimuth angles 11 of the two hypothesis vectors 1 under consideration, an azimuth angle 11 for which, although measurement data are available, no marking was performed for them, then the two hypothesis vectors 1 under consideration are not connected to form an area element 7). (2) The two hypothesis vectors 1 in question have an elevation angle difference<E.sub.thr (with for example E.sub.thr=) 5°. This is intended to ensure that buildings 5 are able to be separated more easily upward of certain height or position differences.

[0066] Moreover, FIG. 2 illustrates that at least two mutually different, nonparallel planes 7 are formed, running in each of which there are at least sections of the propagation paths 1 of at least two GNSS signals whose measurement datasets each meet the second selection criterion, and wherein an at least partial profile of the object boundary 4 is ascertained from the line of intersection 8 for the at least two planes 7.

[0067] Following on from the illustrative variant embodiments of steps b) and c) that are described above, the variant embodiment in this regard that is implemented by way of illustration here can be described as follows: the connected area elements of two adjacent hypothesis vectors 1 can subsequently be referred to as hypothesis areas 7. The search for edge hypotheses is repeated for different reception antenna positions, or GNSS receiver positions. This takes place for example until the measurement data for a defined region (for example for a road) have been examined. The different hypothesis areas 7 for the examined measurement data are processed further. The hypothesis areas 7 of different positions 3 are examined for lines of intersection 8. Lines of intersection 8 are interpreted as building edges 4. They therefore represent the position and height of the building facade.

[0068] FIG. 3 schematically shows a representative graphical illustration of the occurrence of a pseudorange error 12. FIG. 3 is also used to illustrate that a distance 9 between the object 5 and the GNSS receiver 3 can be ascertained.

[0069] In this regard, the collected measurement data can be used for example to obtain statements relating to the distance 9 of a building wall from the reception antenna, or the GNSS receiver 3. As FIG. 3 illustrates, the PR error 12 (symbol: ε) is obtained on the basis of the distance 9 (symbol: X) (collinear with respect to the normal vector of the reflecting area) between reception antenna and reflecting wall to produce ε=2*X*cos (θ), or X=ε/(2 cos (θ)). θ is the elevation angle here.

[0070] The distance 9 collected from the PR error 12 can be used to adapt the position of the generated building wall (e.g. by shifting). This can optionally take place in a post-processing (that is to say after steps a) to c)). Alternatively, the distance between receiver position and reflecting object can also be taken into consideration during calculation of the building walls already (that is to say during steps a) to c)).