EP2243039A1 - Procédé, noeud, dispositif, programme informatique et support de données pour déterminer la position d'un noeud dans un réseau ad hoc - Google Patents

Procédé, noeud, dispositif, programme informatique et support de données pour déterminer la position d'un noeud dans un réseau ad hoc

Info

Publication number
EP2243039A1
EP2243039A1 EP08870832A EP08870832A EP2243039A1 EP 2243039 A1 EP2243039 A1 EP 2243039A1 EP 08870832 A EP08870832 A EP 08870832A EP 08870832 A EP08870832 A EP 08870832A EP 2243039 A1 EP2243039 A1 EP 2243039A1
Authority
EP
European Patent Office
Prior art keywords
node
distance
intersections
nodes
determining
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
EP08870832A
Other languages
German (de)
English (en)
Inventor
Oliver MÜLLER
Alejandro Ramirez
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.)
Siemens AG
Original Assignee
Siemens AG
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 Siemens AG filed Critical Siemens AG
Publication of EP2243039A1 publication Critical patent/EP2243039A1/fr
Ceased legal-status Critical Current

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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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0284—Relative positioning
    • G01S5/0289—Relative positioning of multiple transceivers, e.g. in ad hoc networks
    • 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/14—Determining absolute distances from a plurality of spaced points of known location

Definitions

  • the invention relates to determining geographic locations of nodes in an ad hoc network.
  • the present invention relates to a method, a node, a device, a computer program and a data carrier, each of which enable the inventive determination of geographical positions in an ad hoc network.
  • the objects can be permanently installed, resting or moving. In many situations, such as For example, in traffic (e.g., road or air), warehouses, etc., it is useful to coordinate such objects (such as vehicles, containers, etc.). For example, to support security or administration.
  • the objects can at least partially take the coordination into their own hands. That is, by matching with other objects, by receiving position-relevant data, information, the objects can evaluate the data provided, information, and make conclusions about their positioning with respect to other objects of the environment.
  • the objects (hereinafter nodes) form a network in which the objects are to be coordinated or positioned, at least partly by a corresponding system. tem and / or at least partially taken over by the objects or nodes themselves.
  • beacon nodes which know their own position
  • standard nodes which have to calculate their position on the basis of the distances to the beacon nodes.
  • the known methods can be differentiated with regard to their approaches into distanceless and distance-based approaches.
  • the distance of each network node is determined on the basis of a hop metric (i.e., the number of other nodes between two nodes) which, in a further step, is translated into geographical distances using the network topology so depicted.
  • a hop metric i.e., the number of other nodes between two nodes
  • An explicit measurement of the distances between the nodes does not take place.
  • the position of the individual node is estimated by means of direct distance measurements between individual network nodes or between nodes and beacons. Examples of this type of localization include i.a. [3], [4] and [5]. In [6] an attempt is made to compute a position estimate with the RSSI (Received Signal Strength Indication) of the signals received from the beacon nodes.
  • RSSI Receiveived Signal Strength Indication
  • distance-based position determination is considered.
  • the distance is usually determined by means of a distance or distance determination method.
  • a breadth of methods for determining distance or distance is used. For example, measurements can be made using the strength of the received signal (Received Signal
  • Fig. Ia illustrates a method according to the prior
  • Figure 1a shows how the trilateration works when there are three nodes or neighbors Bi, B 2 , B 3 in the vicinity.
  • the position of the M is estimated on the basis of measured distances di, d2 and d3 from the neighboring nodes Bi, B 2 , B 3 to the sought-after node M.
  • the trilateration is very susceptible to errors, both in terms of the positions of the beacon nodes and in the accuracy of the measured distances, since they are on a ma- thematically clear procedure in which errors are not provided. As explained above, however, the problem lies in the fact that in practice the measured distances are always estimated and thus inaccurate values.
  • Fig. Ib shows the typical problems of locating by multilateration. If the distance measurements are not perfect and accurate, the position will be calculated incorrectly.
  • Multilateration is an advanced form of trilateration. While the trilateration with three neighbor nodes can determine the position of a node, all available neighboring nodes of the node to be located are used for the multilateration.
  • multilateration can from the measured distances di + derr, i 'd2 + d er r, 2 and d3 + d er r, 3 of several adjacent nodes Pi, P 2 , P 3 to the unknown node M and their known position, the position of the unknown node M are estimated. Compared to trilateration, multilateration can also handle inaccurate position or distance measurements. In Fig. 1b, the estimated positions P es t ⁇ m, i / Pestim, 2, P e stim, 3 deviate from the real positions of the nodes Pi, P 2 , P 3 .
  • the measured distances are di + he d r, i 'd 2 + d err, 2 and d 3 + d err, 3 with errors he d r, i' th e r, 2, d err, 3-prone. Accordingly, it can be seen in FIG. 1 b that the calculated position M est differs from the actual or real position of the node M.
  • multilateration has the disadvantage that it is very susceptible to error if multicollinearity of the neighboring nodes is present.
  • an error in the position determination by means of multilateration increases, even if there are errors in the input data (the positions of the adjacent nodes and the corresponding distances). Even small capture errors can cause or produce very large errors in the calculated result position.
  • Another known method is the bounding box method [5], [8], which allows the location of nodes in the network, as soon as distance measurements can be made.
  • Fig. 2a shows an example of this method when the measurements are very accurate.
  • the sought node M has three adjacent nodes Pi, P 2 , P3.
  • the delimiting areas or boxes are defined by the positions (xi, yi), (xi, yi), (xi, yi) of the neighboring nodes Pi, P 2 , P 3 and the distances di, d 2 , d 3 of the neighboring nodes determined to the desired node M.
  • M estim is the estimated position of node M.
  • Figure 2b illustrates pictorially this problem, ie the extent of the difficulties that the method may have if the user does not have neighbors in one direction or on one side (eg at the edge of the network).
  • the bounding box method does not succeed in such situations to capture or frame the node sought. It comes to serious misjudgments regarding the position of the node sought.
  • the calculated position M estim and the actual position of the searched node M are very far from each other.
  • An object of the present invention is to provide an improved position determination.
  • the object is achieved by a method having features of claim 1, by a node having features of claim 15, by a device having features of claim 29, by a computer program having features of claim 1. Proposition 30 or by a data carrier with features of claim 32.
  • the object is achieved by a method for determining a geographical position of a node in an ad hoc network, the method comprising the following steps:
  • Determining distance circles of at least two neighboring nodes of the node Determining intersections of the distance circles of the at least two adjacent nodes of the node;
  • Determining a majority of intersections the majority comprising intersection points proximate an estimated position of the node; and determining the geographical position of the node by means of the majority of intersection points.
  • a distance circle is a circle around a given account with a predetermined radius d.
  • the radius is the distance between a neighbor node and the searched node or node for which the position is determined.
  • the distance is determined or determined by means of a distance or distance determination method.
  • the present invention is not limited to any of the distance or distance determination methods. A wide variety of methods for determining the distance can be used (e.g., RSS, ToA, TDoA, RToF, etc.), and combined application of these techniques is also possible. Thus, the present invention allows flexible implementation.
  • Intersections are those points where two or more distance circles overlap.
  • the positions of the neighboring nodes may be predetermined or estimated and thus inaccurate (eg by a Global Positioning System GPS).
  • GPS Global Positioning System
  • the present invention enables an omnidirectional determination of the position, in particular, since circles are used as search objects. Furthermore, the determination of the position by means of the intersections of the distance circles allows on the one hand fast and effective and on the other hand clearly more precise determination of the position of a node in comparison with the known methods of the prior art.
  • a distance circle of the neighboring node can be determined by means of a position indication of the neighboring node and a distance indication.
  • the distance indication indicates the distance between the adjacent node and the node for which the position is determined or determined according to the invention. In the following, this node will also be referred to as the node sought.
  • the distance specification can be an inaccurate distance specification. That is, determining a position of a node according to the present invention is prepared for inaccurate distance indication and has an error margin.
  • the position indication may also be an inaccurate position indication.
  • the present invention thus also has an error tolerance with regard to details of positions of other nodes. This may be the case, for example, when the position information is provided by GPS measurements.
  • the position information can also be an exact position indication.
  • the position data to the neighboring nodes can be specified by exact or exactly functioning measurement method or be given. The latter is z. B. be the case when the object representing a neighboring node, is permanently installed or attached.
  • the distance indication can be determined by means of a distance measuring method.
  • intersection points of the distance circles can be determined based on a subtraction and a transformation of circle equations of two distance circles each.
  • a threshold may be used in determining the majority of intersections, and the intersections lying within the threshold (e.g., not exceeding this threshold) may be used in the calculation of the final result.
  • mean values of x and y components of the intersections may be used to determine the majority of intersection points.
  • intersections may be determined by backward regression according to an embodiment of the present invention.
  • the method may be performed by the node for which the geographical position is determined.
  • the node may be a mobile node of the ad hoc network. He can z. B. be a vehicle in the transport network.
  • a node in an ad hoc network wherein the node has means for determining a geographical position of the node, wherein the means for determining a geographical position of the node are configured: To determine distance circles of at least two adjacent nodes of the node;
  • the node and thus the means for determining a geographical position of the node, is configured to perform the steps of the method outlined above and detailed below.
  • the means for determining a geographical position of the node are configured to determine for each adjacent node of the at least two neighboring nodes a distance circle of the neighboring node by means of a position specification of the neighboring node and a distance indication.
  • the node may have means for receiving the position information of the neighboring node. That is, in such a case, the node can obtain the position information of the neighboring node on request.
  • the distance indication may be an inaccurate distance indication.
  • the position specification can be an inaccurate position specification. So z.
  • the position indication may be a position indication provided by a GPS measurement.
  • the position indication can also be an exact position indication. This is z. This is the case, for example, when the position relates to a permanently installed node of the network.
  • the distance indication can be a specific distance indication by means of a distance measuring method.
  • the means for determining a geographical position of the node may be configured to determine the intersection points of the distance circles based on a subtraction and a transformation of circle equations of each two distance circles.
  • the means for determining a geographical position of the node may be configured to use a threshold in determining the majority of points of intersection and to use intersections lying within the threshold for the calculation of the final result.
  • the means for determining a geographical position of the node may be configured to use mean values of x and y components of the intersection points for determining the majority of intersection points.
  • the means for determining a geographical position of the node may be configured to be the main set of
  • the node may be a mobile node of the ad hoc network. So z.
  • the node may be a vehicle.
  • the above object is also achieved by means of a device having means for determining a geographical position of a node in an ad hoc network, wherein the means are designed: To determine distance circles of at least two adjacent nodes of the node;
  • intersections of the distance circles of the at least two adjacent nodes of the node To determine intersections of the distance circles of the at least two adjacent nodes of the node, to determine a majority of intersection points, the majority comprising intersections close to an estimated position of the node;
  • the device as a whole is configured to perform the steps of the method outlined above and described in more detail below.
  • the device can be installed anywhere in the ad hoc network. So z. For example, it may be included in a node of the ad hoc network. In particular, it may be part of a node for which the geographic location is to be determined. That is, it may, for example, be installed in a vehicle of a traffic network if the node is a vehicle, perform the position determination directly in the vehicle and thus contribute to the coordination of the traffic, i. h., support the safety or management of the transport network.
  • the above object is achieved by means of a computer program having a coding which is designed such that it carries out steps of the method outlined above and described in more detail below.
  • the computer program can be stored on a data carrier.
  • Fig. Ia illustrates a prior art method (trilateration) for position determination
  • FIG. 1 b illustrates a method according to the prior art (multilateration) for position determination and thereby illustrates the disadvantages of the method
  • Figure 2a illustrates a prior art method (Bounding Box Method) for position determination
  • Fig. 2b illustrates a prior art method (Bounding Box method) for position determination, illustrating the disadvantages of the method
  • FIG. 3 illustrates a position determination according to an embodiment of the present invention
  • Fig. 4 shows a comparison of the results of the method according to the invention and the methods according to the prior art, wherein the average dRMS of the methods is given in the RWP model;
  • Fig. 5 shows a further comparison of the results of the method and the prior art methods, wherein the mean dRMS of the methods is given in the RWP model and the comparison of the methods is shown by means of neighboring nodes further away from the center;
  • Fig. 6 shows a scheme of a column simulation;
  • Fig. 8 shows a detail of a simulation field with a column travel simulation with least squares multilateration (LSL) and the method (MDL) according to the invention
  • Fig. 9 shows a schematic of a crossing simulation
  • Fig. 10 shows results of the crossing simulation, indicating an average dRMS of the method of the invention and the prior art methods in the crossing model
  • FIG. 11 shows results of the crossing simulation, wherein the dRMS of the method according to the invention and the method according to the prior art is displayed as a function of the distance to the center of the crossing.
  • the present invention will be explained using the example of a traffic network, for the sake of simplicity being considered as objects or nodes of the (traffic) network vehicles. It should be noted that the present invention is not limited to an application in the traffic network, but that other fields of application of the present invention are possible. As objects or nodes of a network, various objects or devices can serve.
  • Fig. 3 illustrates position determination according to an embodiment of the present invention.
  • the network consists of nodes P 1 , P 2 , P 3 , P 4 and M, where M is the node sought, ie, the node for which the position determination is performed, and wherein the nodes P 1 , P 2 , P 3 , P4 are adjacent nodes of the M node.
  • the network may, for example, be a traffic network in which the nodes Pi, P 2 , P 3 , P 4 and M represent vehicles.
  • the vehicles can communicate with each other and by determining their position by means of positions of the nearby vehicles and / or other objects in the transport network and by appropriate communication with the nearby vehicles and / or other objects in the traffic network critical situations avoid.
  • the scope of the present invention is by no means limited to such traffic situations or traffic altogether.
  • the present invention is flexible and can be applied in various fields in which problems arise with regard to the positioning and / or coordination of objects.
  • a present distance information d ⁇ + d er r, i is made up of the actual distance d x and the error d err / 1 which is present through the estimation.
  • the values of the errors d err , i are real numbers. Thus, t he r, i have both a positive and a negative value. For better illustration, the errors d er , i of FIG. 3 have positive values.
  • intersection points of the distance circles of neighboring nodes are calculated separately. The majority of these intersections will be near the actual position of the node being searched. From this main set of estimated positions of the intersections Then, the final result position of the searched node M is calculated.
  • intersection points of the distance circles of adjacent nodes Pi and P2 of a node M to be calculated or searched can be found as set out below.
  • (X 1 , Y 1 ) is the position of the node P 1 .
  • the position statement (X 1 , Y 1 ) can be an estimated or inaccurate or even an exact or precise position specification, (x, y) is the searched position of the node M.
  • the set of intersection points of the distance circles of two neighbors of a node can be obtained or found.
  • the amount of solution can not have or include one, one, or two points.
  • each neighbor pair of a node usually two intersections are generated. One of these intersections may be in the vicinity of the desired node M, the other intersection may in turn be far away from the M. In order to eliminate those points of intersection which are far away from the position of the desired node M, it is expedient to introduce a threshold or a threshold value, starting from the farther away
  • the threshold value is z. B. a maximum distance or a maximum distance, the / may be given between two intersections. In this way, a majority of points of intersection is determined or detected having such intersection points which are in the vicinity of the actual or searched position of the searched node M. This is done according to the present embodiment based on the own measured position of the searched point. In this case, according to the present invention It is also possible to use still existing cluste ring processes. For example, a selection via a backward regression would be conceivable.
  • all x-values of all intersections are summed, and the sum is divided by the number of intersections. Accordingly, the y values are also treated. So all y values of all intersections are summed, and the sum is divided by the number of intersections. This gives you a central point between the intersections.
  • All points of intersection are considered from this central point of the intersections, it being determined for each intersection whether the distance between the central point and the intersection is below the predetermined threshold. If so, is the intersection in the set al ler intersections recorded and thus considered for further positioning.
  • FIG. 3 illustrates the approach of the approach of the present invention according to an embodiment of the present invention.
  • all the intersection points of the respective neighbor pairs considered are calculated, and then a data set for the final result is selected (here, based on a fixed circumference around the measured position of M).
  • the mean value of these intersections forms the sought result position of the node M.
  • the set of all intersections is marked in FIG. 3 by stars.
  • the unfilled or white stars indicate the points of intersection which are not used for the calculation or determination of the sought result position of the node M.
  • the solid or black stars in turn point to the intersections of the majority of points of intersection, d. h., those intersections that are not used for the calculation or determination of the sought result position of the node M.
  • the localization problem is divided into individual estimates. This has the advantage that single strong outliers can be effectively and easily excluded from the final position estimate.
  • the present invention can effectively counteract and effectively and effectively handle the multicolor linearity which causes positioning problems in the known methods.
  • a clustering of the intersection points is carried out, as stated above, for example by an averaging of the determined intersections. This results in a much more accurate estimate.
  • the accuracy by the position determination according to the present invention increases again, because then the intersections of the distance circles are almost symmetrical at right angles to the line.
  • the mean value of the intersections approximates the real or actual position of the searched node M.
  • the present invention relates to methods of the second category, i. h., on distance-based methods, since it is assumed that at least approximate distance measurements are present as input data.
  • the measurement of the distances between the nodes can be carried out, for example, by means of the runtime of incorporating distance or distance determination methods.
  • the present invention is not limited to such distance determination methods.
  • other methods can be used or used, eg. B. Methods based on ultrasound measurements, light measurements or measurements by radio waves.
  • the present invention generally requires that a distance determination method provide information on the distance between a searched node and at least one neighboring node of the searched node, which is expected to result in a possible inaccuracy of the distance information. Of course, this does not exclude accurate distance information. Thus, a fault tolerance with respect to the determined distance between the searched node and the adjacent node is ensured.
  • the known methods necessarily distinguish between beacon nodes and normal nodes, ie between nodes whose position is either known or completely unknown.
  • the neighboring nodes have position estimation in the form of GPS measurements or other position measurements and / or exact position information. Such estimates are used in a cooperative manner for positionalization in accordance with the present invention.
  • Another advantage with respect to prior art methods is the proportion of network beacon nodes and the density of the network. In known methods, relatively high proportions of beacon nodes are assumed (5-10%).
  • the present invention also enables positioning in those networks that have a low proportion of beacon nodes because, based on the total number of nodes, e.g. B. Vehicles in traffic, the number of RSUs with a known position is rather small. As a reference for the determination of the position of a node serve therefore its neighboring nodes, ie those nodes that are within its radio range. Looking at the example of a transport network, so z. For example, in a WAVE network, the number of vehicles is rather small and may vary considerably in density. Not least because of the mobile character, the topology changes constantly.
  • the nodes can be referred to as general network nodes (eg vehicles) or as RSU nodes (eg road side units).
  • the first category has only an inaccurate measurement of its own position, for example, by GPS, and is mobile.
  • the second category has an exact position, but is immobile. Nodes that are mutually within their radio range are called neighbor nodes.
  • the division into the first category mentioned above and the second category mentioned above is not mandatory. There can be nodes of both categories or nodes of one of the categories.
  • the vertical axis indicates the measured dRMS and the horizontal axis indicates the number of neighboring nodes.
  • MDL multidilateration
  • BB has a high degree of inaccuracy at the network edge. Due to the relatively high number of neighbors per node, LSL achieves significantly better values, but here too an increased dRMS can be observed, especially at edge nodes.
  • MDL works best in this environment. With only a few adjacent nodes, a good accuracy of the position estimation, clearly below the accuracy of the input data of 12.5 m, can be observed. By averaging the intersections of the neighboring distance circles a good estimate also comes about at the edges of the network, because unlike z. B. at BB no minimization of the largest distances takes place.
  • the number of network nodes is no longer fixed but variable. They enter the simulation in an adjustable, equally distributed probability of occurrence.
  • a newly entering node appears at a fixed point on the edge of the simulation field and moves within a certain corridor in the X or Y direction to the opposite side of the simulation field.
  • the movement is only in the specified direction, "reversing" is not possible.
  • a sideward movement is also carried out whose deflection is equally distributed in the interval [-2.5m, 2.5m].
  • RWP simulation partially changed significantly. It shows the vertical axis the average dRMS and the horizontal axis the number of neighboring nodes.
  • the left side of the picture is a screenshot of LSL and the right side is for comparison with MDL.
  • the large positioning errors are clearly visible. Since the imaginary line passes through the positions in the Y direction, the localization errors in the X direction are
  • the MDL method is only marginally better than BB.
  • this scenario is not very different from the Column scenario, as only two corridors are crossed orthogonal to each other. Nevertheless, there are clear differences in the network topology, as between the
  • the average dRMS of the network is plotted with the various methods over the average neighbor per node. That is, the vertical axis indicates the average dRMS and the horizontal axis indicates the number of adjacent nodes.
  • the LSL method falls significantly over the other two. Although its performance is better than in the previous scenario, even at high node densities its average dRMS is significantly higher than that of the GPS
  • Position measurement The improvement is explained by the fact that within the circle described in FIG. 9 there are further nodes as neighbors that are not collinear with the neighbors in the same corridor. However, since these new neighbors also have high collinearity with each other, the improvement is not as great as desired.
  • the BB process can not improve in comparison to the column scenario.
  • the dRMS is clearly higher and at high density it is still significantly higher.
  • An improvement of the dRMS over the The dRMS of the GPS measurement is only achieved with an average of approx. 20 neighboring nodes, whereas in the column scenario this is already the case with approx. 11 neighbors.
  • BB achieves the highest performance in the pseudo-one-dimensional scenario of the almost collinear column.
  • neighbors with different positions in both coordinate components are included in the calculation, the values deteriorate.
  • the performance of the MDL method is the best.
  • the dRMS has even improved a bit, especially for low neighbor numbers. Even with large node densities, in contrast to the column simulation, a clear difference between MDL and BB can now be seen.
  • MDL Multidilator Action
  • the present invention relates to determining a geographic location of a node in an ad hoc network. For this, distance circles are determined by at least two adjacent nodes of the node. Furthermore, intersections of the distance circles of the at least two adjacent nodes of the node are determined. From the set of determined or determined intersections, a majority of intersections are determined, the majority comprising intersections close to an estimated position of the node. The geographical position of the node is then determined by means of the majority of intersection points.
  • intersections of the respective neighbor pairs are calculated. From this, a data set (at intersections) is selected for the final result (eg, based on a fixed perimeter (for example, given by threshold) around the measured position of the node being searched for). The center of these intersections is the result position, d. h., the position of the searched node.

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

Abstract

L'invention concerne un procédé et un dispositif destinés à la détermination de la position géographique d'un noeud dans un réseau ad hoc. Des cercles de distance d'au moins deux noeuds voisins dudit noeud sont déterminés. Des points d'intersection des cercles de distance des deux noeuds voisins dudit noeud sont déterminés. Le nombre de points d'intersection déterminé permet de définir un nombre principal de points d'intersection, ce nombre principal présentant des points d'intersection qui se trouvent à proximité d'une position estimée dudit noeud. La position géographique dudit noeud est alors déterminée au moyen du nombre principal des points d'intersection.
EP08870832A 2008-01-14 2008-12-22 Procédé, noeud, dispositif, programme informatique et support de données pour déterminer la position d'un noeud dans un réseau ad hoc Ceased EP2243039A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
DE102008004257 2008-01-14
DE102008021614.3A DE102008021614B4 (de) 2008-01-14 2008-04-30 Verfahren, Vorrichtung, Knoten und Computerprogramm zum Bestimmen einer Position eines Knotens in einem Ad-Hoc-Netzwerk
PCT/EP2008/068162 WO2009089989A1 (fr) 2008-01-14 2008-12-22 Procédé, noeud, dispositif, programme informatique et support de données pour déterminer la position d'un noeud dans un réseau ad hoc

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EP2243039A1 true EP2243039A1 (fr) 2010-10-27

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US (1) US8369869B2 (fr)
EP (1) EP2243039A1 (fr)
CN (1) CN101910863A (fr)
DE (1) DE102008021614B4 (fr)
WO (1) WO2009089989A1 (fr)

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DE102009033603A1 (de) 2009-07-17 2011-01-20 Siemens Aktiengesellschaft Verfahren zur Kalibrierung eines laufzeitbasierten Lokalisationssystems
US8938231B2 (en) * 2011-12-12 2015-01-20 Maxlinear, Inc. Method and system for femtocell positioning using low earth orbit satellite signals
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US20110045844A1 (en) 2011-02-24
DE102008021614B4 (de) 2015-09-24
US8369869B2 (en) 2013-02-05
DE102008021614A1 (de) 2009-07-23
CN101910863A (zh) 2010-12-08

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