CN113132935B - Distributed cooperative positioning method and device, electronic equipment and storage medium - Google Patents
Distributed cooperative positioning method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a distributed cooperative positioning method, a distributed cooperative positioning device, electronic equipment and a storage medium, wherein the method comprises the following steps: when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance; then, double centralization is carried out on the dissimilarity matrix, singular value decomposition is carried out on the dissimilarity matrix obtained after the centralization, and the eigenvalue and the eigenvector of the matrix obtained after the centralization are decomposed according to the singular value; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; finally, the relative position coordinate is used as the relative position coordinate of the reference wireless sensor; based on the relative position coordinates of the reference wireless sensor, the relative position coordinates of the other wireless sensors are determined. Thereby, the determination of the relative position coordinates of the wireless sensors in the wireless sensor network can be realized.
Description
Technical Field
The present invention relates to the field of wireless positioning technologies, and in particular, to a distributed cooperative positioning method and apparatus, an electronic device, and a storage medium.
Background
The wireless sensor network is a multi-hop self-organizing network formed by a large number of wireless communication connections, the emergence of the wireless sensor network enables a plurality of applications which cannot be realized or are difficult to realize before, and research related to the sensor network becomes a research hotspot in academia and industry in recent years due to the potential application value of the sensor network. In many applications of sensor networks, the positioning of the wireless sensor itself is important, and the wireless sensor usually needs to report its own position coordinates when transmitting data, and in many routing algorithms based on position coordinates, it is also necessary to know the position coordinates of the wireless sensor, including relative position coordinates and absolute position coordinates.
However, since the wireless sensor network is usually deployed in a complex environment (such as indoors or in a hilly area), it is difficult to determine absolute position coordinates of each wireless sensor in the wireless sensor network by using a GPS (Global Positioning System) technology; also, since wireless sensors often have limited computational resources and energy supply, it is not possible to determine absolute position coordinates of individual wireless sensors in a wireless sensor network by equipping the wireless sensors with higher power GPS receivers.
Therefore, how to determine the relative position coordinates of the wireless sensors in the wireless sensor network becomes an urgent problem to be solved.
Disclosure of Invention
Embodiments of the present invention provide a distributed co-location method and apparatus, an electronic device, and a storage medium, so as to determine a relative position coordinate of a wireless sensor in a wireless sensor network.
The specific technical scheme is as follows:
in a first aspect, an embodiment of the present invention provides a distributed cooperative positioning method, which is applied to a wireless sensor network, and the method includes:
when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
taking the relative position coordinates of the wireless sensors with the first preset number as the relative position coordinates of the reference wireless sensors;
based on the relative position coordinates of the reference wireless sensor, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor are determined.
Optionally, the obtaining a distance between any two adjacent wireless sensors in the wireless sensor network includes:
acquiring the delay sending time, the sending time and the receiving time of signals sent by any two adjacent wireless sensors, and determining the signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time, wherein the delay sending time is the time between the time when the wireless sensors receive data packets and the time when the wireless sensors send the signals;
and determining the distance between the two wireless sensors according to the signal transmission time length.
Optionally, the obtaining a delay sending time, a sending time and a receiving time for sending signals to any two adjacent wireless sensors, and determining a signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time includes:
aiming at a first sensor and a second sensor in any two adjacent wireless sensors, acquiring a first time T of a signal sent by the first sensor 1A A second time T for receiving the data packet 2A A first delayed transmission time length T reply1 First time T of signal sent by second sensor 1B A second time T for receiving the data packet 2B And a second delayed transmission time period T reply2 ；
By a first formula:
calculating the signal transmission time length T between the two wireless sensors prop (ii) a Wherein, T round1 ＝T 2A -T 1A ；T round2 ＝T 2B -T 1B 。
Optionally, performing dual centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after the centralization to obtain the eigenvalue and the eigenvector of the matrix after the centralization, including:
carrying out square calculation on each element in the dissimilarity matrix of the wireless sensor network to obtain a dissimilarity matrix after square calculation;
using a second formula:
b＝-σ*J*a (2) J
performing double centralization on the dissimilarity matrix to obtain a centralized matrix b, wherein sigma is a first coefficient, J is a central matrix,
e is a unit matrix with a preset order, and I is a full 1 square matrix with a preset order; a is (2) The calculated dissimilarity matrix is squared,
is a second coefficient;
performing singular value decomposition on the centered matrix b to obtain a maximum second preset number of eigenvalues lambda of the centered matrix 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Wherein n is a second preset number of values, and the order of the feature vector is the same as the preset order;
according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates between a first preset number of wireless sensors in a wireless sensor network, comprising:
the feature vector xi 1 ，ξ 2 ，…，ξ n And a characteristic value lambda 1 ，λ 2 ，…，λ n And multiplying to obtain the relative position coordinates among the wireless sensors of the first preset number in the wireless sensor network.
Optionally, after determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network, the method further includes:
when a wireless sensor with a known absolute position exists in the wireless sensor network, the absolute position coordinates of all the wireless sensors in the wireless sensor network are determined based on the position coordinates of the wireless sensor with the known absolute position, the relative position coordinates of the reference wireless sensor and the relative position coordinates of other wireless sensors.
In a second aspect, an embodiment of the present invention further provides a distributed cooperative positioning apparatus, which is applied in a wireless sensor network, and the apparatus may include:
the distance acquisition module is used for acquiring the distance between any two adjacent wireless sensors in the wireless sensor network when no wireless sensor with a known position exists in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
the singular value decomposition module is used for performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after the centralization to obtain a characteristic value and a characteristic vector of the matrix after the centralization;
the first relative position coordinate determination module is used for determining the characteristic value and the characteristic vector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; taking the relative position coordinates of the wireless sensors with the first preset number as the relative position coordinates of the reference wireless sensors;
and the second relative position coordinate determination module is used for determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network based on the relative position coordinates of the reference wireless sensor.
Optionally, the distance obtaining module is specifically configured to:
acquiring the delay sending time, the sending time and the receiving time of signals sent by any two adjacent wireless sensors, and determining the signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time, wherein the delay sending time is the time between the time when the wireless sensors receive data packets and the time when the wireless sensors send the signals;
and determining the distance between the two wireless sensors according to the signal transmission time length.
Optionally, the distance obtaining module is specifically configured to:
aiming at a first sensor and a second sensor in any two adjacent wireless sensors, acquiring a first time T of a signal sent by the first sensor 1A A second time T for receiving the data packet 2A A first delayed transmission time length T reply1 First time T of signal sent by second sensor 1B A second time T for receiving the data packet 2B And a second delayed transmission time period T reply2 ；
By a first formula:
calculating the signal transmission time length T between the two wireless sensors prop (ii) a Wherein, T round1 ＝T 2A -T 1A ；T round2 ＝T 2B -T 1B 。
Optionally, the singular value decomposition module is specifically configured to:
carrying out square calculation on each element in the dissimilarity matrix of the wireless sensor network to obtain a dissimilarity matrix after square calculation;
using a second formula:
b＝-σ*J*a (2) J
performing double centralization on the dissimilarity matrix to obtain a centralized matrix b, wherein sigma is a first coefficient, J is a central matrix,
e is a predetermined orderA unit matrix of numbers, I is a full 1 square matrix of a preset order; a is (2) The calculated dissimilarity matrix is squared,
is a second coefficient;
performing singular value decomposition on the centered matrix b to obtain a maximum second preset number of eigenvalues lambda of the centered matrix 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Wherein n is a second preset number of values, and the order of the feature vector is the same as the preset order;
a first relative position coordinate determination module, specifically configured to:
the feature vector xi 1 ，ξ 2 ，…，ξ n And a characteristic value lambda 1 ，λ 2 ，…，λ n And multiplying to obtain the relative position coordinates among the wireless sensors of the first preset number in the wireless sensor network.
Optionally, the apparatus further comprises:
and the absolute position coordinate determination module is used for determining the absolute position coordinates of all the wireless sensors in the wireless sensor network based on the position coordinates of the wireless sensors with known absolute positions, the relative position coordinates of the reference wireless sensors and the relative position coordinates of other wireless sensors when the wireless sensors with known absolute positions exist in the wireless sensor network after determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for implementing the steps of the distributed co-location method shown in any one of the above embodiments when executing the program stored in the memory.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the distributed co-location method shown in any of the foregoing embodiments are implemented.
In a fifth aspect, an embodiment of the present invention further provides a computer program product containing instructions, which when run on a computer, causes the computer to perform the steps of the distributed co-location method shown in any of the above embodiments.
The embodiment of the invention has the following beneficial effects:
according to the distributed cooperative positioning method, the distributed cooperative positioning device, the electronic equipment and the storage medium, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired firstly; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network may then be accomplished. Of course, not all of the above advantages need be achieved in the practice of any one product or method of the present invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other embodiments can be obtained by using the drawings without creative efforts.
Fig. 1 is a flowchart of a first implementation manner of a distributed co-location method according to an embodiment of the present invention;
fig. 2 is a flowchart of a second implementation manner of a distributed co-location method according to an embodiment of the present invention;
fig. 3 is a flowchart of a distributed co-location method according to a third implementation manner of the embodiment of the present invention;
fig. 4 is a schematic structural diagram of a distributed cooperative positioning apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived from the embodiments given herein by one of ordinary skill in the art, are within the scope of the invention.
In order to solve the problems in the prior art, embodiments of the present invention provide a distributed cooperative positioning method and apparatus, an electronic device, and a storage medium, so as to implement positioning of a wireless sensor in a wireless sensor network.
Next, first, a distributed cooperative positioning method in an embodiment of the present invention is described, as shown in fig. 1, which is a flowchart of a first implementation manner of the distributed cooperative positioning method in the embodiment of the present invention, where the method may include:
s110, when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
s120, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
s130, according to the eigenvalue and the eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
s140, taking the relative position coordinates of the first preset number of wireless sensors as the relative position coordinates of the reference wireless sensors;
and S150, determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network based on the relative position coordinates of the reference wireless sensor.
In some examples, when positioning each wireless sensor in the wireless sensor network according to the embodiment of the present invention, it may be determined whether there is a wireless sensor with a known location in the wireless sensor network.
In still other examples, the wireless sensors in the wireless sensor network may generally carry their own location coordinates when transmitting signals, and when no data packet transmitted by any wireless sensor in the wireless sensor network carries their own location coordinates, it may be determined that there is no wireless sensor in the wireless sensor network with a known location.
When a data packet sent by any wireless sensor in the wireless sensor network carries the position coordinates of the wireless sensor, it can be determined that a wireless sensor with a known position exists in the wireless sensor network.
In still other examples, when a data packet sent by any wireless sensor in the wireless sensor network carries its own absolute position coordinates, it may be determined that a wireless sensor with a known position exists in the wireless sensor network.
Wherein the position comprises an absolute position or a relative position. The relative position is a relative position between the wireless sensors in the wireless sensor network.
In some examples, when there is no wireless sensor with a known location in the wireless sensor network, in order to determine the location coordinates of each wireless sensor in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network may be obtained first.
Then constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; wherein the dissimilarity matrix may be used to characterize relative distances between respective neighboring wireless sensors in the wireless sensor network.
After the dissimilarity matrix of the wireless sensor network is obtained, the dissimilarity matrix of the wireless sensor network can be subjected to double centralization, so that a centralized dissimilarity matrix can be obtained, and then singular value decomposition can be performed on the centralized dissimilarity matrix, so that the eigenvalue and the eigenvector of the centralized dissimilarity matrix can be obtained.
Finally, the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network can be determined through the feature values and the feature vectors of the centralized dissimilarity matrix;
in some examples, the dissimilarity matrix of the wireless sensor network is doubly centered and subjected to singular value decomposition, in effect reducing the dimension of the dissimilarity matrix of the wireless sensor network. By reducing the dimension of the dissimilarity matrix of the wireless sensor network, the relative position coordinate of the wireless sensor with higher relative position coordinate accuracy can be obtained.
After the relative position coordinates of the first preset number of wireless sensors in the wireless sensor network are obtained, the relative position coordinates of the first preset number of wireless sensors can be used as the relative position coordinates of the reference wireless sensors; further, the relative position coordinates of the wireless sensors other than the reference wireless sensor in the wireless sensor network may be determined based on the relative position coordinates of the reference wireless sensor.
In this way, relative position coordinates between each adjacent wireless sensor in the wireless sensor network can be determined.
In some examples, when there is a wireless sensor with a known absolute position in the wireless sensor network, the absolute position coordinates of all wireless sensors in the wireless sensor network may be determined based on the position coordinates of the wireless sensor with the known absolute position and the distance between any two adjacent wireless sensors.
Specifically, a matrix p of position coordinates of the wireless sensor with known absolute positions may be constructed first a ＝[p 1 p 2 ...p m ] T And a matrix p of position coordinates of the wireless sensor with unknown absolute position s ＝[p 1 p 2 ...p n ] T Where m is the total number of wireless sensors whose absolute positions are known, n is the total number of wireless sensors whose absolute positions are unknown, and m + n is the total number of all wireless sensors in the wireless sensor network.
And then constructing a centroid coordinate matrix L between the wireless sensor with known absolute position and the neighbor wireless sensor as And a centroid coordinate matrix L between the wireless sensor with unknown absolute position and the neighbor wireless sensor thereof ss 。
Then, by the following formula:
p s (k+1)＝(E-ε(E-L ss ) T (E-L ss ))p s (k)+ε(E-L ss ) T L as p a
and performing iterative computation. Here, according to the markov chain, the centroid coordinate matrix L between the wireless sensor whose absolute position is unknown and its neighbor wireless sensor ss Is less than 1, so that after a plurality of iterative calculations, a converged iterative calculation result can be obtained, which can be madeThe position coordinates of the wireless sensors are unknown in absolute position, and therefore the absolute position coordinates of each wireless sensor in the wireless sensor network can be obtained.
Wherein at the start of an iteration, the matrix p s The value of each element in (b) may be 0 or may be an arbitrarily set value. E is a matrix with a diagonal of 1, epsilon is a convergence factor, and epsilon is 2/(lambda) max ((E-L ss ) T (E-L ss ))+λ min ((E-L ss ) T (E-L ss )))，λ max ((E-L ss ) T (E-L ss ) λ) and λ min ((E-L ss ) T (E-L ss ) Are respectively a matrix (E-L) ss ) T (E-L ss ) Maximum eigenvalue and minimum eigenvalue of (d).
In some examples, when performing the (k + 1) th iteration, the wireless sensor with unknown i-th absolute position coordinate may first obtain the estimated value p of the position coordinate before the current iteration i (k) Sending the position information to the neighbor nodes and acquiring the position coordinates p of the self-estimation of the neighbor wireless sensors j∈J (k) (ii) a J is a set of names of all neighbor wireless sensors of the wireless sensor with unknown absolute position coordinates, and J is the name of any neighbor wireless sensor in the set;
then, the wireless sensor with unknown i-th absolute position coordinate can obtain an estimated value p of the position coordinate before the iteration according to the wireless sensor i (k) Position coordinate p estimated by its neighbor wireless sensor to itself j∈J (k) And position coordinates p estimated for itself with the neighbor wireless sensor j∈J (k) Corresponding centroid coordinate a ij By the following formula:
when the (k + 1) th iteration is calculated, the estimated value of the position coordinate of the wireless sensor with unknown ith absolute position coordinate and the position coordinate estimated by the wireless sensor adjacent to the wireless sensorp j∈J (k) Residual xi of i (k)。
The wireless sensor with unknown i-th absolute position coordinate obtains an estimated value p of the position coordinate before the iteration i (k) After being sent to its neighboring node, its neighboring node may be based on the estimated value of the position coordinate of the wireless sensor whose i absolute position coordinates are unknown and the estimated value p of the position coordinate sent by the wireless sensor whose i absolute position coordinates are unknown i (k) To calculate the residual xi jQJ (k) Then the calculated residual xi j∈J (k) And sending the position information to the wireless sensor of which the i-th absolute position coordinate is unknown.
Thus, the i-th wireless sensor whose absolute position coordinate is unknown may be based on the estimated value p of the position coordinate obtained before the current iteration i (k) And residual xi i (k) Sum residual ξ j∈J (k) By the following formula:
and calculating to obtain the estimated value of the position coordinate of the wireless sensor with unknown i-th absolute position coordinate when the (k + 1) th iteration is carried out.
After a plurality of iterations, a third preset number of iteration results are selected, that is, the estimated value of the position coordinate of the wireless sensor with unknown absolute position coordinates for a continuous preset number of times is selected.
And then calculating the variance of the third preset number of iteration results, and if the variance is smaller than a preset variance threshold, indicating that the iteration results have converged, then taking any one of the third preset number of iteration results as the position coordinate of the wireless sensor whose absolute position coordinate is unknown, or taking the average value of the third preset number of iteration results as the position coordinate of the wireless sensor whose absolute position coordinate is unknown.
The third preset number is a preset number, for example, the preset number may be 10 or 15. The preset varianceThe threshold is a preset threshold, for example, the preset variance threshold may be set to 10 -3 。
By the distributed cooperative positioning method, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired firstly; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network may then be accomplished.
On the basis of the distributed cooperative positioning method shown in fig. 1, an embodiment of the present invention further provides a possible implementation manner, as shown in fig. 2, which is a flowchart of a second implementation manner of the distributed cooperative positioning method according to the embodiment of the present invention, where the method may include:
s210, when no wireless sensor with a known position exists in a wireless sensor network, obtaining the delay sending time, the sending time and the receiving time of signals sent by any two adjacent wireless sensors, and determining the signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time, wherein the delay sending time is the time between the time when the wireless sensors receive data packets and the time when the wireless sensors send the signals;
in some examples, when the distance between any two adjacent wireless sensors in the wireless sensor network is acquired, the distance may be calculated based on a signal transmission time length and a signal transmission speed between the two adjacent wireless sensors. The signal transmission duration may be a time interval between a time at which one of the two adjacent wireless sensors transmits a signal and a time at which the other wireless sensor receives a signal.
In still other examples, when two adjacent wireless sensors a and B transmit signals to each other, after the wireless sensor a transmits a signal to the wireless sensor B, the wireless sensor B may transmit a signal to the wireless sensor a after a certain delay time. At this time, if the delay time length is not excluded, the signal transmission time length calculated by the wireless sensor a may be too long, thereby causing a too large error in the distance calculated subsequently.
In this regard, the delay transmission time, the transmission time and the reception time for the two adjacent wireless sensors to transmit signals to each other may be obtained, and the signal transmission time between the two wireless sensors may be determined based on the delay transmission time, the transmission time and the reception time.
In still other examples, the signal transmission time period between the two wireless sensors may be calculated as follows:
aiming at a first sensor and a second sensor in any two adjacent wireless sensors, acquiring a first time T of a signal sent by the first sensor 1A A second time T for receiving the data packet 2A A first delayed transmission time length T reply1 First time T of signal sent by second sensor 1B A second time T for receiving the data packet 2B And a second delayed transmission time period T reply2 ；
By a first formula:
computing the two radiosSignal transmission time length T between sensors prop (ii) a Wherein, T round1 ＝T 2A -T 1A ；T round2 ＝T 2B -T 1B 。
Through the step, the two-way bilateral distance measurement of the two adjacent wireless sensors can be realized, so that the accuracy of determining the distance between the two adjacent wireless sensors can be improved, and the accuracy of determining the relative position coordinates can be further improved.
S220, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
s230, according to the eigenvalue and the eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
s240, taking the relative position coordinates of the first preset number of wireless sensors as the relative position coordinates of the reference wireless sensors;
and S250, determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network based on the relative position coordinates of the reference wireless sensor.
In some examples, when dual centering is performed on the dissimilarity matrix of the wireless sensor network, each element in the dissimilarity matrix of the wireless sensor network may be squared to obtain a squared dissimilarity matrix;
and then adopting a second formula:
b＝-σ*J*a (2) J
and performing double centralization on the dissimilarity matrix to obtain a centralized matrix b.
Where σ is the first coefficient, J is the central matrix,
e is a unit matrix with a preset order, and I is a full 1 square matrix with a preset order; a is (2) The calculated dissimilarity matrix is squared,
is a second coefficient; the preset order is a preset value, and may be set to a value of 4, 5, 6, etc., for example. The first coefficient and the second coefficient may also be coefficient values set in advance, for example, the first coefficient σ may be set to 5, and the second coefficient σ may be set to a value of 5
May be set to 4.
After b, singular value decomposition may be performed on the centered matrix to obtain a second preset number of maximum eigenvalues λ of the centered matrix 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Wherein n is a second preset number of values, and the order of the feature vector is the same as the preset order; n is less than the number of wireless sensors in the wireless sensor network.
Obtaining the characteristic value lambda 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Then, the feature vector xi can be set 1 ，ξ 2 ，…，ξ n And a characteristic value lambda 1 ，λ 2 ，…，λ n And multiplying to obtain the relative position coordinates among the wireless sensors of the first preset number in the wireless sensor network.
For example, if the second preset number is 3 and the preset order is 4, the number of the eigenvectors is 3, and each eigenvector is a 4 × 1 column matrix; then, a 4 x 3 matrix consisting of three eigenvectors can be obtained;
then, constructing a diagonal matrix corresponding to the three eigenvalues based on the 3 eigenvalues, wherein the diagonal matrix is as follows:
then, a 4 × 3 matrix formed by the three eigenvectors and a diagonal matrix corresponding to the three eigenvalues are subjected to dot multiplication, so that relative position coordinates of four wireless sensors in the wireless sensor network can be obtained.
It is understood that steps S220 to S250 in the second implementation manner of the embodiment of the present invention are the same as or similar to steps S120 to S150 in the first implementation manner of the embodiment of the present invention, and are not described again here.
On the basis of the distributed cooperative positioning method shown in fig. 1, an embodiment of the present invention further provides a possible implementation manner, and as shown in fig. 3, the method is a flowchart of a third implementation manner of the distributed cooperative positioning method according to the embodiment of the present invention, and the method may include:
s310, when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
s320, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after the centralization to obtain a characteristic value and a characteristic vector of the centralized matrix;
s330, according to the eigenvalue and the eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
s340, taking the relative position coordinates of the first preset number of wireless sensors as the relative position coordinates of the reference wireless sensors;
and S350, determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network based on the relative position coordinates of the reference wireless sensor.
And S360, when the wireless sensor with the known absolute position exists in the wireless sensor network, determining the absolute position coordinates of all the wireless sensors in the wireless sensor network based on the position coordinates of the wireless sensors with the known absolute positions, the relative position coordinates of the reference wireless sensor and the relative position coordinates of other wireless sensors. The absolute position coordinates may be, for example, the position coordinates of the wireless sensor in a geodetic or geographic coordinate system.
In some examples, after obtaining the relative position coordinates of each wireless sensor in the wireless sensor network through steps S310 to S350, the embodiment of the present invention may further obtain the absolute position coordinates of each wireless sensor in the wireless sensor network.
Specifically, when there is a wireless sensor with a known absolute position in the wireless sensor network, the absolute position coordinates of all the wireless sensors in the wireless sensor network may be determined based on the position coordinates of the wireless sensor with a known absolute position, the relative position coordinates of the reference wireless sensor, and the relative position coordinates of the other wireless sensors.
For example, the absolute position coordinates of all the wireless sensors in the wireless sensor network may be obtained by adding or subtracting the absolute position coordinates of the reference wireless sensor based on the relative position coordinates of the wireless sensors whose absolute positions are known and the relative position coordinates of the other wireless sensors.
By the embodiment of the invention, when the wireless sensor with known absolute position exists in the wireless sensor network, the absolute position coordinates of all the wireless sensors in the wireless sensor network can be obtained through calculation. Therefore, the absolute position coordinate is obtained on the basis of obtaining the relative position coordinate of the wireless sensor, and the application range of the position coordinate of the wireless sensor is enlarged.
It is understood that steps S310 to S250 in the third implementation manner of the embodiment of the present invention are the same as or similar to steps S110 to S150 in the first implementation manner of the embodiment of the present invention, and are not described again here.
Corresponding to the foregoing method embodiment, an embodiment of the present invention further provides a distributed cooperative positioning apparatus, as shown in fig. 4, which is a schematic structural diagram of the distributed cooperative positioning apparatus according to the embodiment of the present invention, and the apparatus may include:
a distance obtaining module 410, configured to obtain a distance between any two adjacent wireless sensors in the wireless sensor network when there is no wireless sensor with a known location in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
the singular value decomposition module 420 is configured to perform dual centering on the dissimilarity matrix of the wireless sensor network, and perform singular value decomposition on the dissimilarity matrix obtained after the centering to obtain a eigenvalue and a eigenvector of the matrix after the centering;
a first relative position coordinate determination module 430, configured to determine a feature value and a feature vector according to the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; taking the relative position coordinates of the wireless sensors with the first preset number as the relative position coordinates of the reference wireless sensors;
and a second relative position coordinate determination module 440, configured to determine relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor based on the relative position coordinates of the reference wireless sensor.
By the distributed cooperative positioning device, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired firstly; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network can be achieved.
In some examples, the distance obtaining module 410 is specifically configured to:
acquiring the delay sending time, the sending time and the receiving time of signals sent by any two adjacent wireless sensors, and determining the signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time, wherein the delay sending time is the time between the time when the wireless sensors receive data packets and the time when the wireless sensors send the signals;
and determining the distance between the two wireless sensors according to the signal transmission time length.
In some examples, the distance obtaining module 410 is specifically configured to:
aiming at a first sensor and a second sensor in any two adjacent wireless sensors, acquiring a first time T of a signal sent by the first sensor 1A A second time T for receiving the data packet 2A A first delayed transmission time length T reply1 First time T of signal sent by second sensor 11 A second time T for receiving the data packet 2B And a second delayed transmission time period T reply2 ；
By a first formula:
calculating the signal transmission time length T between the two wireless sensors prop (ii) a Wherein, T round1 ＝T 2A -T 1A ；T round2 ＝T 2B -T 1B 。
In some examples, the singular value decomposition module 420 is specifically configured to:
carrying out square calculation on each element in the dissimilarity matrix of the wireless sensor network to obtain a dissimilarity matrix after square calculation;
using a second formula:
b＝-σ*J*a (2) J
performing double-centering on the dissimilarity matrix to obtain a centered matrix b, wherein sigma is a first coefficient, J is a center matrix,
e is a unit matrix with a preset order, and I is a full 1 square matrix with a preset order; a is (2) The calculated dissimilarity matrix is squared,
is a second coefficient;
performing singular value decomposition on the centered matrix b to obtain a maximum second preset number of eigenvalues lambda of the centered matrix 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Wherein n is a second preset number of values, and the order of the feature vector is the same as the preset order;
the first relative position coordinate determination module 430 is specifically configured to:
the feature vector xi 1 ，ξ 2 ，…，ξ n And a characteristic value lambda 1 ，λ 2 ，…，λ n And multiplying to obtain the relative position coordinates among the wireless sensors of the first preset number in the wireless sensor network.
In some examples, the apparatus further comprises:
and the absolute position coordinate determination module is used for determining the absolute position coordinates of all the wireless sensors in the wireless sensor network based on the position coordinates of the wireless sensors with known absolute positions, the relative position coordinates of the reference wireless sensors and the relative position coordinates of other wireless sensors when the wireless sensors with known absolute positions exist in the wireless sensor network after determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network.
An embodiment of the present invention further provides an electronic device, as shown in fig. 5, which includes a processor 501, a communication interface 502, a memory 503 and a communication bus 504, where the processor 501, the communication interface 502 and the memory 503 complete mutual communication through the communication bus 504,
a memory 503 for storing a computer program;
the processor 501 is configured to implement the steps of the distributed co-location method according to any of the embodiments described above when executing the program stored in the memory 503, for example, the following steps may be implemented:
when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
taking the relative position coordinates of the wireless sensors with the first preset number as the relative position coordinates of the reference wireless sensors;
based on the relative position coordinates of the reference wireless sensor, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor are determined.
By the electronic equipment provided by the embodiment of the invention, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired firstly; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network may then be accomplished.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
In another embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, and when executed by a processor, the computer program implements the steps of a distributed co-location method shown in any of the above embodiments, for example, the following steps may be implemented:
when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
taking the relative position coordinates of the wireless sensors with the first preset number as the relative position coordinates of the reference wireless sensors;
based on the relative position coordinates of the reference wireless sensor, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor are determined.
By the computer-readable storage medium of the embodiment of the invention, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired firstly; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network may then be accomplished.
In a further embodiment of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the steps of a distributed co-location method as shown in any of the above embodiments, for example, the following steps may be performed:
when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
taking the relative position coordinates of the wireless sensors with the first preset number as the relative position coordinates of the reference wireless sensors;
based on the relative position coordinates of the reference wireless sensor, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor are determined.
By the computer program product containing the instructions, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired first; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network may then be accomplished.
An embodiment of the present invention further provides a computer program, which when running on a computer, causes the computer to execute the steps of the distributed cooperative positioning method shown in any of the foregoing embodiments, for example, the following steps may be executed:
when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
according to the eigenvalue and eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network;
taking the relative position coordinates of the wireless sensors of the first preset number as the relative position coordinates of the reference wireless sensors;
based on the relative position coordinates of the reference wireless sensor, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor are determined.
By the computer program of the embodiment of the invention, when no wireless sensor with a known position exists in the wireless sensor network, the distance between any two adjacent wireless sensors in the wireless sensor network can be acquired firstly; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network; then, performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization; then according to the eigenvalue and eigenvector of the matrix after centralization; determining relative position coordinates of a first preset number of wireless sensors in a wireless sensor network; after the relative position coordinates of the wireless sensors of the first preset number in the wireless sensor network are obtained, the relative position coordinates of the wireless sensors of the first preset number can be used as the relative position coordinates of the reference wireless sensors; thus, the relative position coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor can be determined based on the relative position coordinates of the reference wireless sensor. Determining the relative position coordinates of the wireless sensors in the wireless sensor network may then be accomplished.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the invention may be carried out in whole or in part when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for embodiments of devices, electronic devices, and the like, since they are substantially similar to the method embodiments, the description is relatively simple, and reference may be made to some descriptions of the method embodiments for relevant points.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (9)
1. A distributed cooperative positioning method is applied to a wireless sensor network, and the method comprises the following steps:
when no wireless sensor with a known position exists in the wireless sensor network, acquiring the distance between any two adjacent wireless sensors in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after centralization to obtain a characteristic value and a characteristic vector of the matrix after centralization;
according to the eigenvalue and the eigenvector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in the wireless sensor network;
taking the relative position coordinates of the first preset number of wireless sensors as the relative position coordinates of the reference wireless sensors;
determining relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network based on the relative position coordinates of the reference wireless sensor;
the dual centralization of the dissimilarity matrix of the wireless sensor network and singular value decomposition of the dissimilarity matrix obtained after the centralization to obtain the eigenvalue and the eigenvector of the matrix after the centralization include:
carrying out square calculation on each element in the dissimilarity matrix of the wireless sensor network to obtain a dissimilarity matrix after square calculation;
using a second formula:
b＝-σ*J*a (2) J
performing double centralization on the dissimilarity matrix to obtain a centralized matrix b, wherein sigma is a first coefficient, J is a central matrix,
e is a unit matrix with a preset order, and I is a full 1 square matrix with a preset order; a is (2) The calculated dissimilarity matrix is squared,
is a second coefficient;
performing singular value decomposition on the centralized matrix b to obtain a maximum second preset number of eigenvalues lambda of the centralized matrix 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Wherein n is the value of the second preset number, and the order of the feature vector is the same as the preset order;
the eigenvalue and eigenvector of the matrix after the centralization; determining relative position coordinates between a first preset number of wireless sensors in the wireless sensor network, comprising:
the feature vector xi 1 ，ξ 2 ，…，ξ n And the characteristic value lambda 1 ，λ 2 ，…，λ n And multiplying to obtain the relative position coordinates among the wireless sensors of the first preset number in the wireless sensor network.
2. The method of claim 1, wherein the obtaining the distance between any two adjacent wireless sensors in the wireless sensor network comprises:
acquiring the delay sending time, the sending time and the receiving time of the mutual sending signals of any two adjacent wireless sensors, and determining the signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time, wherein the delay sending time is the time between the time when the wireless sensors receive the data packets and the time when the wireless sensors send the signals;
and determining the distance between the two wireless sensors according to the signal transmission time length.
3. The method of claim 2, wherein the obtaining of the delayed transmission time, the transmission time and the receiving time of the signals mutually transmitted by any two adjacent wireless sensors, and the determining of the signal transmission time between the two wireless sensors based on the delayed transmission time, the transmission time and the receiving time comprise:
aiming at a first sensor and a second sensor in any two adjacent wireless sensors, acquiring a first time T of a signal sent by the first sensor 1A A second time T for receiving the data packet 2A A first delayed transmission time length T reply1 A first time T at which the second sensor sends a signal 1B A second time T for receiving the data packet 2B And a second delayed transmission time period T reply2 ；
By a first formula:
calculating the signal transmission time length T between the two wireless sensors prop (ii) a Wherein, T round1 ＝T 2A -T 1A ；T round2 ＝T 2B -T 1B 。
4. The method of claim 1, wherein after said determining relative location coordinates of other wireless sensors in the wireless sensor network except the reference wireless sensor, the method further comprises:
when a wireless sensor with a known absolute position exists in the wireless sensor network, the absolute position coordinates of all the wireless sensors in the wireless sensor network are determined based on the position coordinates of the wireless sensor with the known absolute position, the relative position coordinates of the reference wireless sensor and the relative position coordinates of the other wireless sensors.
5. A distributed co-location apparatus, for use in a wireless sensor network, the apparatus comprising:
the distance acquisition module is used for acquiring the distance between any two adjacent wireless sensors in the wireless sensor network when no wireless sensor with a known position exists in the wireless sensor network; constructing a dissimilarity matrix of the wireless sensor network according to the distance between any two adjacent wireless sensors in the wireless sensor network;
the singular value decomposition module is used for performing double centralization on the dissimilarity matrix of the wireless sensor network, and performing singular value decomposition on the dissimilarity matrix obtained after the centralization to obtain a characteristic value and a characteristic vector of the matrix after the centralization;
the first relative position coordinate determination module is used for determining the characteristic value and the characteristic vector of the centralized matrix; determining relative position coordinates of a first preset number of wireless sensors in the wireless sensor network; taking the relative position coordinates of the first preset number of wireless sensors as the relative position coordinates of the reference wireless sensors;
the second relative position coordinate determination module is used for determining the relative position coordinates of other wireless sensors except the reference wireless sensor in the wireless sensor network based on the relative position coordinates of the reference wireless sensor;
the singular value decomposition module is specifically configured to:
carrying out square calculation on each element in the dissimilarity matrix of the wireless sensor network to obtain a dissimilarity matrix after square calculation;
using a second formula:
b＝-σ*J*a (2) J
performing double centralization on the dissimilarity matrix to obtain a centralized matrix b, wherein sigma is a first coefficient, J is a central matrix,
e is a unit matrix with a preset order, and I is a full 1 square matrix with a preset order; a is (2) The calculated dissimilarity matrix is squared,
is a second coefficient;
performing singular value decomposition on the centered matrix b to obtain a maximum second preset number of eigenvalues lambda of the centered matrix 1 ，λ 2 ，…，λ n And feature vector xi 1 ，ξ 2 ，…，ξ n Wherein n is a second preset number of values, and the order of the feature vector is the same as the preset order;
a first relative position coordinate determination module, specifically configured to:
the feature vector xi 1 ，ξ 2 ，…，ξ n And a characteristic value lambda 1 ，λ 2 ，…，λ n And multiplying to obtain the relative position coordinates among the wireless sensors of the first preset number in the wireless sensor network.
6. The apparatus of claim 5, wherein the distance acquisition module is specifically configured to:
acquiring the delay sending time, the sending time and the receiving time of the mutual sending signals of any two adjacent wireless sensors, and determining the signal transmission time between the two wireless sensors based on the delay sending time, the sending time and the receiving time, wherein the delay sending time is the time between the time when the wireless sensors receive the data packets and the time when the wireless sensors send the signals;
and determining the distance between the two wireless sensors according to the signal transmission time length.
7. The apparatus of claim 5, further comprising:
an absolute position coordinate determination module, configured to, after determining the relative position coordinates of the other wireless sensors in the wireless sensor network except the reference wireless sensor, determine the absolute position coordinates of all the wireless sensors in the wireless sensor network based on the position coordinates of the wireless sensor with a known absolute position, the relative position coordinates of the reference wireless sensor, and the relative position coordinates of the other wireless sensors when there is a wireless sensor with a known absolute position in the wireless sensor network.
8. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1 to 4 when executing a program stored in the memory.
9. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of claims 1 to 4.
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