阅读说明：本技术 使用电子测距设备进行地理定位优化的方法 (Method for geolocation optimization using electronic ranging devices ) 是由 D·帕拉托夫 M·甘瑙纳 P·斯大帕尼 于 2019-08-29 设计创作，主要内容包括：本发明主要涉及一种确定节点n的新位置的方法,所述节点具有测距无线电,所述方法包括以下步骤：a)获取多个相邻节点的位置列表；b)分析所述列表中的位置与节点n的预测位置的几何关系；c)从所述列表中选择小于所述列表中节点总数的节点子集；d)执行从节点n到所述节点子集中的每个节点的电子距离测量；e)利用在步骤d)中获取的距离来确定节点n的新位置。(The present invention generally relates to a method of determining a new position of a node n, said node having a ranging radio, said method comprising the steps of: a) acquiring a position list of a plurality of adjacent nodes; b) analyzing the geometric relationship between the positions in the list and the predicted position of the node n; c) selecting a subset of nodes from the list that is less than the total number of nodes in the list; d) performing an electronic distance measurement from node n to each node in the subset of nodes; e) determining a new position of node n using the distance obtained in step d).)

1. A method of determining a new location of a node n, the node having a ranging radio, the method comprising the steps of:

a) acquiring a position list of a plurality of adjacent nodes;

b) analyzing the geometric relationship between the positions in the list and the predicted position of the node n;

c) selecting a subset of nodes from the list that is less than the total number of nodes in the list;

d) performing an electronic distance measurement from node n to each node in the subset of nodes; and

e) determining a new position of node n using the distance obtained in step d).

2. The method according to claim 1, wherein the selection in step c) is based on the most favorable geometrical relationship of the nodes in the list to the predicted position of node n.

3. The method of claim 1, wherein step a) further comprises: obtaining a corresponding confidence measure for each of the locations in the list, and the selecting in step c) is based at least in part on the confidence measure.

4. The method of claim 1, wherein: the number of nodes selected in step c) is at most 3.

5. The method of claim 1, further comprising: step f) transmitting the measured distances to the subset of nodes.

6. The method of claim 1, wherein step a) further comprises: receiving previously measured distances from at least one of a plurality of neighbouring nodes and comprising the step d) of performing an electronic distance measurement from node n to each of the subset of nodes for which a previously measured distance was not received in step a).

7. The method of claim 1, wherein: if the node n is moving, performing steps a) to e); otherwise, if node n is not moving, no measurement is made and the predicted location of node n is used as the new location of node n.

Technical Field

The invention relates to a method for geographic positioning by using electronic distance measuring equipment.

Background

Geolocation using ranging devices employs multiple distance measurements from a node to other nearby nodes with known locations to determine the location of a local node. Many such systems are known in the art. Known methods typically attempt to obtain as many such measurements as possible in order to reduce errors by averaging, filtering, and other statistical and numerical techniques. As the number of nodes increases, the accuracy of the location in such systems improves, making it desirable to obtain as many nodes as possible.

With known point-to-point ranging techniques, a node can only measure the distance to another node at a time. Furthermore, unless multiple channels are used, only a pair of nodes within radio transmission range may measure the distance between them at any given time to avoid interference from other nodes using the same radio spectrum. Various scheduling and arbitration techniques are known and practiced in the art, including TDMA, CDMA, etc.

In a system that attempts to collect all possible distance measurements, (N x (N-1))/2 measurements need to be scheduled and executed when there are N nodes. This means that radio usage requirements grow exponentially with the number of nodes. In some cases, using multiple radio channels may improve system response, but this can make scheduling very complex and not solve the problem at all. In some implementations, the results of such measurements then need to be collected and distributed to all participating nodes in order for each node to determine its location, potentially further increasing bandwidth requirements. As a result, the common methods do not scale well and system response times can degrade significantly as the number of nodes increases.

As the number of nodes decreases, the accuracy of the conventional method also decreases, and the system becomes more prone to errors and outright failures.

In the above-referenced co-pending application, a method of geolocation is disclosed that selects only a small subset of the most favorable measurements among all available measurements based on the confidence measures of the available nodes disclosed and the geometry of the relative locations. In many embodiments, according to the disclosed method, a maximum of only three measurements are used to determine the location of any given node, while the remaining measurements are discarded. In embodiments with N nodes, only (N x 3)/2 measurements at most are actually used, providing potential linear scalability as opposed to the exponential of conventional approaches.

There is a need for a way to predetermine which measurement values are likely to be most advantageous and to perform only the requested measurements, as a result of which the use of the radio is greatly reduced. The present invention teaches methods of providing the desired means.

Disclosure of Invention

The terms "invention," "the present invention," and "the present invention" as used in this patent are intended to refer broadly to all subject matter of this patent and the following patent claims. Statements containing these terms should be understood as not limiting the subject matter described herein or limiting the meaning or scope of the following patent claims. Embodiments of the invention covered by this patent are defined by the following claims, not this summary. This summary is a high-level overview of various aspects of the invention and is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter alone. The subject matter should be understood by reference to the entire specification of this patent, any or all of the drawings, and appropriate portions of each claim.

The main object of the present invention is to significantly reduce the radio utilization required for accurate point-to-point geolocation of multiple nodes in order to improve scalability and overall system response.

The present invention achieves its objects by disclosing a method comprising a series of steps that begins with determining which node of a set of available neighboring nodes will provide the most favorable distance measurement value to determine the location of the node, selecting only those nodes for distance measurement, and then performing only the selected distance measurement.

More specifically, the invention relates to a method of determining a new position of a node n, the node having a ranging radio, the method comprising the steps of:

a) a list of locations of a plurality of neighboring nodes is obtained,

b) analyzing the geometric relationship of the positions in the list to the predicted position of node n,

c) selecting from the list a subset of nodes that is less than the total number of nodes in the list,

d) performing an electronic distance measurement from node n to each node in the subset of nodes,

e) determining a new position of node n using the distance obtained in step d).

According to a particular embodiment, the selection in step c) is based on the most favorable geometrical relationship of the nodes in the list to the predicted position of node n.

According to a particular embodiment, step a) further comprises: obtaining a corresponding confidence measure for each of the locations in the list, and the selecting in step c) is based at least in part on the confidence measure.

According to a particular embodiment, the number of nodes selected in step c) is at most 3.

According to a particular embodiment, the method further comprises the step f) of transmitting the measured distances to the subset of nodes.

According to a particular embodiment, step a) further comprises: receiving previously measured distances from at least one of a plurality of neighbouring nodes and comprising the step d) of performing an electronic distance measurement from node n to each of the subset of nodes for which a previously measured distance was not received in step a).

According to a particular embodiment, steps a) to e) are performed if node n is moving, otherwise, if node n is not moving, no measurements are made and the predicted position of node n is used as the new position of node n.

Drawings

The invention is described herein with reference to the following drawings:

fig. 1 shows the main functional blocks of the illustrative embodiment, and the data flow between them.

FIG. 2 is a schematic diagram of an embodiment of the process of the present invention.

Fig. 3 illustrates the ambiguity of distance measurements in the case of only one available reference node, resulting in an infinite number of candidate positions along the circumference of the circle.

Fig. 4 shows ambiguity reduction in case of two available reference nodes with advantageous geometry, resulting in two candidate positions at the intersection of a circle and a circle.

Fig. 5 shows that when three reference nodes with favorable geometry are available, the ambiguity is further reduced to a single candidate position.

Detailed Description

The illustrative embodiments presented herein make use, in part, of the methods disclosed in the above-referenced co-pending applications, particularly methods for selecting a subset of nodes based on geometry and confidence, and methods for determining the location of a node n having two or three distance measurements to other nodes. These methods are included in the following description for reference, but they are not within the scope of the present invention.

The scope of the invention relates in particular to the following sequence: a subset of nodes is first selected from a plurality of available nodes by any known or future method, then distance measurements are performed only on the selected nodes, and then the positions of the nodes are determined based on the measurements by any known or future method.

Fig. 1 is a schematic diagram of the overall data flow for an exemplary embodiment of the present invention.

To determine the location of a node, information is collected from various sensors. In the context of the illustrated embodiment, the location data of neighboring nodes and the measured distances to such nodes are considered sensor inputs. Other typical sensors include Inertial Measurement Units (IMU), magnetometers, altimeters, and the like.

In the illustrated embodiment, the IMU and altimeter are contained within the hardware portion of the node.

Information about the location of the neighboring node is transmitted to the node via data radio. In some embodiments, a single node will be designated as a Neighborhood manager responsible for periodically collecting and distributing this information among the nodes. In other embodiments, this information may be transferred in a coordinated point-to-point fashion. Many methods of transferring information between multiple nodes are known. The details of such methods are outside the scope of the present invention.

The distance measurement between the nodes is performed by ranging radio. Many such methods are known. The illustrated embodiment utilizes a Decawave DW1000 ranging radio, but many other methods are readily available.

A sensor:

-altimeterProviding a relative height.

-IMU: an inertial measurement unit (such as BNO 080) consists of a 3-axis accelerometer, gyroscope, and magnetometer. They are typically fused together (internally in most modern IMUs) to provide virtual sensors such as linear acceleration and step counters and rotation vectors to convert linear acceleration with magnetic north.

-Distance measurement: a ranging module (such as a UWB radio) provides the range from the current node to nearby nodes.

-Neighborhood zone: in the context of the illustrated embodiment, a neighborhood is a collection of nodes managed by a node that acts as a neighborhood manager (NHM). Each node broadcasts its location information via XNet. The NHM maintains a neighborhood database (NHDB) of nodes in its neighborhood. Each node in a neighborhood receives location information for each of its neighborhoods. The information includes:

-X, Y, Z coordinates, wherein:

x is the west (negative) and east (positive) axis,

y is the north (positive) and south (negative) axes,

-Z is the altitude.

-role:

-an anchor point: a fixed node with an accurately measured position.

-a label: mobile or fixed nodes whose position is calculated via positioning.

The fixed label is called Breadcrumb (break navigation).

-a state: the movement or the fixation of the device can be realized,

-a confidence level.

Confidence level: the key location values (such as coordinates and distances) have associated confidence values ranging from 0.0 to 1.0, where 0.0 represents no confidence and 1.0 represents absolute confidence. Other numerical dimensions may be used in different embodiments. Whenever a position fix selects among the node data to compute a position estimate, the position fix uses the confidence of the data to select the best (most confident) data.

Only anchors have a pre-assigned and constant confidence level set to 1.0. The confidence of a tag is calculated based on the confidence of the data received from the sensors, distance measurements, and neighboring nodes used to calculate the location of the tag.

The positional confidence of the tag may decrease over time due to data errors, lack of precision, and time lag between data updates; confidence may decrease with age of the data. As mentioned above, confidence is never increased alone, only if the confidence of the incoming new data is higher than the currently available data.

A module:

the positioning consists of the following modules:

-an Inertial Navigation System (INS): given a starting position, the INS module takes inertial input from the IMU and converts it to X and Y offsets to calculate a predicted position.

-geometry: given the locations and distances of the neighboring nodes, the geometry module computes one or more candidate locations for the local node.

-movement: given the inertial input, the motion module calculates whether the local node is in motion and calculates the direction of travel.

Geometry module (GEO):the GEO uses the locations and distances of neighboring nodes to compute one or more candidate locations for the local node. The NHM provides a proximity location and provides a distance to a nearby node through a distance measurement; both delivered as sensor readings. These are merged into a list of proximity descriptors (NDs).

The GEO recalculates the estimated position at the same rate that the range measurements can provide range updates. Each node implementation may have a different ranging technique and therefore the update rate varies from node to node.

The GEO location calculation is shown in the flow chart shown in fig. 2 and summarized as follows:

1. unsuitable neighbors are removed from the ND list. Ideal neighbors are those with high confidence, closest location and distance data, and favorable locations.

2. The interpolated position of the tag neighbors is calculated.

3. The ND list is sorted by confidence.

4. Up to three best neighbors are selected based on role (anchor over non-mobile tags over mobile tags) and confidence.

5. Distance measurements are made only for selected nodes.

6. If there are only two neighbors, then an attempt is made to compute two candidate locations using bilateral measurements.

7. If there are three neighbors, an attempt is made to compute a single candidate location using trilateration. If trilateration fails, several pairs of candidate locations are attempted to be computed using bilateral measurements for each neighbor pair combination.

8. The list of candidate locations is reported to the INS module. Each of the above steps may end the calculation due to the insufficient number of available neighbors. In such a case, the GEO will report the previously calculated position with reduced confidence. Thus, over time, without sufficient neighbors, the position confidence of the GEO report decreases.

Trilateration/bilateral measurement

Given an anchor point and a tag and the distance d1 between them, all that is possible is that the tag is located somewhere on a circle with its center at anchor point 1 and radius d1 (see fig. 3). This information is not sufficient to compute a limited list of candidate locations. However, in case the predicted position pP is obtained from the INS module, the confidence of the association may be adjusted. The confidence may increase if the pP is located on or near the circle. If pP is far from the circle, its confidence may be reduced.

Given two anchors and tags and distances d1 and d2 to anchors, we can calculate two possible candidate positions cP1 and cP2 at the intersection of two circles around an anchor, as shown in fig. 4. In the case where the predicted position pP is obtained from the INS module, a closer candidate position (cP 2 in the illustrated case) may be selected. As in the previous embodiment, the magnitude of the distance between cP2 and pP can be used as the basis for adjusting the confidence.

Using three anchor points, a single candidate position cP for a tag may be calculated as being at the center of the intersection of all three circles. Fig. 5 illustrates such a scenario. As in the previous embodiments, the size of the distance between cP and pP can be evaluated, especially when compared to the inherent accuracy of the ranging technique used, to adjust the confidence.

Inertial navigation module (INS)

The INS takes inertial input from the IMU and converts it to X and Y offsets and adds it to previous positions to calculate new predicted positions and associated confidence levels. In some embodiments, a large amount of inertial activity may decrease confidence, while increasing confidence in the case of little or no inertial activity.

The second function of the INS is to receive a list of geometric candidate locations from the GEO module and select among them based on distance and relative confidence from the predicted location. In some scenarios, the predicted location may be selected over all candidate locations. In other scenarios, a new location may be calculated that is a weighted average of the closest candidate location and predicted location, wherein the weights are at least partially proportional to the respective confidence levels.

Sports Module (MOT)

The MOT takes inertial input from the INS and calculates whether the local node is in motion, and calculates the direction of travel (bearing). The results of the motion calculations can be used to adjust the confidence of the node location and also to switch the node role between anchor, breadcrumb and tag. The GEO module uses the node role as a criterion to select the most favorable set of distance measurements, where the highest priority is given to the anchor, then the breadcrumb, then the label. In the context of the illustrated embodiment, breadcrumbs are tags that have been fixed for an extended period of time. In the illustrated embodiment, the main difference between an anchor and a breadcrumb is that the location of an anchor is explicitly known and assigned when it is placed. The position of the breadcrumb is calculated as it moves as a tag, but because it is already fixed and takes into account the benefit of repeating the measurement multiple times over time to reduce errors, it has a higher confidence than a moving tag.

According to a particular embodiment, a method of determining a new position of a node n, the node having a ranging radio, the method comprising the steps of:

a) calculating a predicted position pP and an associated predicted confidence pC starting from a previously determined previous position P having a previously determined confidence C, the calculation using data from at least 3-axis inertial sensors,

b) if the data from the inertial sensors indicates that node n has not moved, then the previous location is taken as the new location and all subsequent steps are skipped.

c) A list of available neighboring nodes, their associated locations, and associated confidence measures is obtained.

d) For each pair of available neighboring nodes in the list, the geometric relationship between Pn1, Pn2, and pP is evaluated

e) If the evaluation of step d) shows a favorable geometry, nodes N1 and N2 are added to the selected subset of nodes.

f) In step e) three nodes are selected from the selected subset of nodes, said three nodes having the highest confidence associated with their positions.

g) Electronically measuring at least a first distance Dn1 to at least a first further node n1, at least a second distance Dn2 to at least a second further node n2, and at least a third distance Dn3 to at least a second further node n3,

h) the value of Dn1 is transmitted to node N1, the value of Dn2 is transmitted to node N2, and the value of Dn3 is transmitted to node N3.

i) Obtaining a current position Pn1 of the first other node, a position Pn2 of the second other node, and a position Pn3 of the third other node, the positions including at least X, Y, Z coordinates and confidence measures Cn1, Cn2, and Cn3,

j) trilateration is used with the positions Pn1, Pn2, and Pn3 and the corresponding measured distances Dn1, Dn2, and Dn3, to determine at least a candidate position cP,

k) determining the candidate confidence, cC, as the lesser of Cn1, Cn2, and Cn3, and then adjusting the confidence, cC, based on the geometry calculated in step d),

l) selecting the candidate position cP as a new position P and having cC as a new confidence C if the confidence cC is greater than pC, otherwise selecting the predicted position pP as a new position P and having the prediction confidence pC as a new confidence C.

According to another particular embodiment, a method of determining a new location of a node n, the node having a ranging radio, the method comprising the steps of:

a) calculating a predicted position pP and an associated predicted confidence pC starting from a previously determined previous position P having a previously determined confidence C, the calculation using data from at least 3-axis inertial sensors,

b) if the data from the inertial sensors indicates that node n has not moved, then the previous location is taken as the new location and all subsequent steps are skipped.

c) A list of available neighboring nodes, their associated locations, and associated confidence measures is obtained.

d) For each pair of available neighboring nodes in the list, the geometric relationship between Pn1, Pn2, and pP is evaluated

e) If the evaluation of step d) shows a favorable geometry, nodes N1 and N2 are added to the selected subset of nodes.

f) Selecting two nodes from the selected subset of nodes in step e), the two nodes having the highest confidence associated with their locations.

g) At least a first distance Dn1 to at least a first further node n1, and at least a second distance Dn2 to at least a second further node n2 are electronically measured,

h) the value of Dn1 is transmitted to node N1 and the value of Dn2 is transmitted to node N2.

i) Geometrically projecting the distances Dn1 and Dn2 onto a common horizontal plane to determine projected distances pDn1 and pDn2,

j) calculating the intersection of the circle of projected distances with the circle to determine two candidate positions cPa and cPb,

k) determining the candidate confidence, cC, as the lesser of Cn1 and Cn2, and then adjusting the confidence, cC, based on the geometry calculated in step e),

l) determining an error distance eDa between pP and cPa, and an error distance eDb between pP and cPb,

m) selecting a candidate position with a smaller error distance as the candidate position cP, and selecting a corresponding error distance as the error distance eD,

n) calculating a new position P as a weighted interpolation between at least said predicted position pP and the candidate position cP,

o) calculating the new confidence C as a weighted interpolation of the prediction confidence pC and the candidate confidence cC.

The embodiments disclosed herein are illustrative and not restrictive; other embodiments will be apparent to those skilled in the art based on the disclosure herein without departing from the scope of the invention.