CN112637952A - Method for distributing power of wireless cooperative positioning network - Google Patents

Method for distributing power of wireless cooperative positioning network Download PDF

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Publication number
CN112637952A
CN112637952A CN202110233057.6A CN202110233057A CN112637952A CN 112637952 A CN112637952 A CN 112637952A CN 202110233057 A CN202110233057 A CN 202110233057A CN 112637952 A CN112637952 A CN 112637952A
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node
target node
power
wireless
interference
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CN112637952B (en
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张睿
刘爽
闵济海
叶增军
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Nanjing Tetra Electronic Technology Co ltd
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Nanjing Tetra Electronic Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/243—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account interferences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/245—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account received signal strength
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/28—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non transmission
    • H04W52/283—Power depending on the position of the mobile

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a method for distributing power of a wireless cooperative positioning network, which extracts key information of a received signal through K-L transformation and Schulb complement, calculates a mathematical form of a positioning error by utilizing a Bai and Golub theorem according to the information, models a power distribution problem into a nonlinear optimization problem, and deduces a specific iteration step by utilizing a Lagrange multiplier method and a particle swarm algorithm to obtain power distribution under the highest positioning precision. The invention carries out joint power distribution on the anchor node, the target node and the interference node in the wireless cooperative positioning network, and can effectively improve the utilization rate of the positioning system resources; in addition, the interference of other wireless communication networks in a complex environment is considered, and the robustness of wireless positioning is enhanced.

Description

Method for distributing power of wireless cooperative positioning network
Technical Field
The invention belongs to the network communication technology, and particularly relates to a power distribution method of a wireless cooperative positioning network.
Background
Wireless positioning systems often reduce system cost and improve positioning accuracy by optimizing positioning algorithms and improving network topology. However, optimizing the resource allocation of the system may also improve the positioning accuracy of resource-constrained positioning systems. 1) Generally, people simply and averagely allocate system resources to each node, and do not consider that nodes at different positions contribute different to a positioning system, so that the optimal allocation of the system resources is not realized; 2) the current research focuses on a non-cooperative positioning network, but the non-cooperative positioning network ignores the topological structure among target nodes, the waste is unacceptable for a wireless positioning network with limited resources, and the cooperative positioning network can effectively utilize the topological structure among the nodes; 3) most studies now ignore the fact that in practical environments, other wireless networks may exist in the vicinity of the positioning network, which cause interference to the wireless positioning network. The existing distribution method has the following problems:
due to the fact that the uncooperative positioning network is simple in structure, the solving algorithm is generally simple, the algorithm universality is poor, and the uncooperative positioning network cannot be applied to a large-scale cooperative positioning network with a complex topological structure. Interference of other networks in the actual environment is not considered, the robustness of positioning is poor, and the method can be applied to actual deployment in doubt. And a non-cooperative positioning network is mostly adopted, so that the topological structure among target nodes is wasted, and the positioning effect is poor.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to solve the defects in the prior art and provides a power distribution method of a wireless cooperative positioning network.
The technical scheme is as follows: the invention discloses a method for distributing power of a wireless cooperative positioning network, which comprises the following steps:
step S1, deploying an interfered cooperative wireless positioning network, wherein the interfered cooperative wireless positioning network comprises
Figure 713130DEST_PATH_IMAGE001
A target node
Figure 503231DEST_PATH_IMAGE002
，
Figure 398506DEST_PATH_IMAGE003
An anchor node
Figure 666676DEST_PATH_IMAGE004
And
Figure 455641DEST_PATH_IMAGE005
an interference node
Figure 541277DEST_PATH_IMAGE006
；
Step S2, extracting Fisher information matrix of the information received by all target nodes to be positioned in the step S1 through K-L transformation and Schulvin complement
Figure 782903DEST_PATH_IMAGE007
；
Step S3, obtaining the Fisher information matrix according to the obtained Fisher information matrix
Figure 730130DEST_PATH_IMAGE007
Calculating the square positioning error by utilizing the Bai and Golub theorem
Figure 904760DEST_PATH_IMAGE008
；
Figure 505505DEST_PATH_IMAGE009
；
Wherein the content of the first and second substances,
Figure 890219DEST_PATH_IMAGE010
；
Figure 234613DEST_PATH_IMAGE011
；
Figure 139115DEST_PATH_IMAGE012
；
Figure 910762DEST_PATH_IMAGE013
representing Fisher information matrices
Figure 658138DEST_PATH_IMAGE007
Of order of (i) i.e
Figure 930856DEST_PATH_IMAGE014
；
Figure 814499DEST_PATH_IMAGE015
Representing and taking matrix
Figure 22626DEST_PATH_IMAGE007
The trace of (a) is determined,
Figure 867085DEST_PATH_IMAGE016
representing a matrix
Figure 553282DEST_PATH_IMAGE007
The square of the norm is determined by the square of the norm,
Figure 687503DEST_PATH_IMAGE017
representing and taking matrix
Figure 66532DEST_PATH_IMAGE007
The minimum eigenvalue of (d);
step S4 to minimize
Figure 257341DEST_PATH_IMAGE008
Anchor node total power as objective function
Figure 622595DEST_PATH_IMAGE018
Total power of target node
Figure 480829DEST_PATH_IMAGE019
And total power of interference node
Figure 420972DEST_PATH_IMAGE020
Establishing an optimization problem for constraint;
step S5,According to the first
Figure 99078DEST_PATH_IMAGE021
Result of the sub-iteration
Figure 392657DEST_PATH_IMAGE022
Substituting the Fisher information matrix
Figure 980764DEST_PATH_IMAGE023
To obtain a local approximate objective function
Figure 701595DEST_PATH_IMAGE024
；
Figure 257210DEST_PATH_IMAGE022
Representing a current optimal power allocation in the interfered cooperative wireless location network;
step S6, converting the original problem into an optimization problem containing simple constraints through a Lagrange multiplier method;
step S7, setting iteration times
Figure 88900DEST_PATH_IMAGE025
；
Step S8, solving the optimization problem by adopting a particle swarm algorithm to obtain the current optimal power distribution
Figure 656148DEST_PATH_IMAGE022
；
Step S9, setting threshold judgment conditions
Figure 423247DEST_PATH_IMAGE026
Performing iterative operation;
when iterating to be less than the threshold value
Figure 607103DEST_PATH_IMAGE027
When, i.e. when
Figure 101538DEST_PATH_IMAGE028
Stopping iteration and outputting the optimumPower distribution
Figure 788872DEST_PATH_IMAGE022
；
Otherwise, return to step S5.
In the above step S9
Figure 851506DEST_PATH_IMAGE029
Take a value of
Figure 866866DEST_PATH_IMAGE030
。
Wherein, in the step S2, all target nodes to be positioned
Figure 305938DEST_PATH_IMAGE031
Fisher information matrix of positions
Figure 972411DEST_PATH_IMAGE023
Expressed as:
Figure 205947DEST_PATH_IMAGE032
wherein the content of the first and second substances,
Figure 833237DEST_PATH_IMAGE033
representing a target node
Figure 420207DEST_PATH_IMAGE031
The position of (a);
Figure 82133DEST_PATH_IMAGE034
representing a target node
Figure 486569DEST_PATH_IMAGE031
To all anchor nodes
Figure 725790DEST_PATH_IMAGE004
A Fisher information matrix obtained by communication, represented as
Figure 241085DEST_PATH_IMAGE035
；
Figure 632883DEST_PATH_IMAGE036
Representing a target node
Figure 473800DEST_PATH_IMAGE031
And a target node
Figure 810103DEST_PATH_IMAGE037
Fisher information matrix obtained by inter-communication and
Figure 519302DEST_PATH_IMAGE038
and is
Figure 624661DEST_PATH_IMAGE039
；
Figure 511846DEST_PATH_IMAGE040
Is formed by anchor nodes
Figure 69866DEST_PATH_IMAGE004
The intensity of distance information determined by the waveform and power of the transmitted signal;
Figure 458122DEST_PATH_IMAGE041
the representation is made by the target node
Figure 542622DEST_PATH_IMAGE037
The intensity of distance information determined by the waveform and power of the transmitted signal;
Figure 725341DEST_PATH_IMAGE042
representing a target node
Figure 36237DEST_PATH_IMAGE031
Intensity of interference, total power of all interference nodes and interference nodes
Figure 837971DEST_PATH_IMAGE043
Position correlation;
Figure 652343DEST_PATH_IMAGE044
representing a target node
Figure 390318DEST_PATH_IMAGE037
The intensity of the disturbance;
Figure 188510DEST_PATH_IMAGE045
by the target node
Figure 387410DEST_PATH_IMAGE031
And anchor node
Figure 197234DEST_PATH_IMAGE004
Relative angle determination between them;
Figure 987335DEST_PATH_IMAGE046
by the target node
Figure 741665DEST_PATH_IMAGE031
And a target node
Figure 400048DEST_PATH_IMAGE047
The relative angle therebetween.
Further, the specific process of establishing the optimization problem in step S4 is as follows:
to minimize
Figure 189012DEST_PATH_IMAGE048
For an objective function, the total power of the anchor nodes, the total power of the target nodes and the total power of the interference nodes are constraints, and the established optimization problem is as follows:
Figure 759802DEST_PATH_IMAGE049
Figure 532586DEST_PATH_IMAGE050
Figure 338868DEST_PATH_IMAGE051
Figure 372552DEST_PATH_IMAGE052
Figure 238877DEST_PATH_IMAGE053
Figure 108744DEST_PATH_IMAGE054
Figure 718717DEST_PATH_IMAGE055
wherein the target node
Figure 747853DEST_PATH_IMAGE002
Transmit power of
Figure 644133DEST_PATH_IMAGE056
In the range of
Figure 391510DEST_PATH_IMAGE057
To reduce power consumption, the total power of all target nodes is less than
Figure 680540DEST_PATH_IMAGE019
；
Anchor node
Figure 298603DEST_PATH_IMAGE004
Transmit power of
Figure 506730DEST_PATH_IMAGE058
In the range of
Figure 600457DEST_PATH_IMAGE059
To reduce power consumption, the total power of all anchor nodes is less than
Figure 552233DEST_PATH_IMAGE018
；
Interference node
Figure 165748DEST_PATH_IMAGE043
Transmit power of
Figure 544776DEST_PATH_IMAGE060
In the range of
Figure 1165DEST_PATH_IMAGE061
In order to ensure the normal operation of the interference network, the total power of all the interference nodes is greater than
Figure 615686DEST_PATH_IMAGE062
。
Further, in the step S5
Figure 473921DEST_PATH_IMAGE022
Expressed as:
(Vector)
Figure 23851DEST_PATH_IMAGE063
；
wherein the content of the first and second substances,
Figure 577323DEST_PATH_IMAGE064
is shown as
Figure 870901DEST_PATH_IMAGE021
Performing secondary iteration;
when the number of iterations
Figure 708276DEST_PATH_IMAGE065
The transmission power of the target node, the anchor node and the interference node are uniformly distributed, namely
Figure 429108DEST_PATH_IMAGE066
、
Figure 860089DEST_PATH_IMAGE067
And
Figure 567145DEST_PATH_IMAGE068
thus obtaining
Figure 134392DEST_PATH_IMAGE069
；
When the number of iterations
Figure 416338DEST_PATH_IMAGE070
When the temperature of the water is higher than the set temperature,
Figure 803457DEST_PATH_IMAGE022
the value is the result obtained by the last iterative operation;
according to the first
Figure 704417DEST_PATH_IMAGE021
Result of the sub-iteration
Figure 1537DEST_PATH_IMAGE022
Then locally approximate the objective function
Figure 329750DEST_PATH_IMAGE024
The estimation process of (2) is:
will be provided with
Figure 204166DEST_PATH_IMAGE022
Substituted into Fisher information matrix
Figure 773730DEST_PATH_IMAGE023
In that it obtains
Figure 49991DEST_PATH_IMAGE021
At the time of the second iteration,
Figure 424471DEST_PATH_IMAGE071
、
Figure 51762DEST_PATH_IMAGE072
and
Figure 28945DEST_PATH_IMAGE073
are each as follows
Figure 815504DEST_PATH_IMAGE074
、
Figure 485520DEST_PATH_IMAGE075
And
Figure 944315DEST_PATH_IMAGE076
(ii) a Then the
Figure 990768DEST_PATH_IMAGE024
Expressed as:
Figure 241621DEST_PATH_IMAGE077
。
further, the detailed process of step S6 is:
first, an objective function is defined
Figure 207172DEST_PATH_IMAGE048
Replaced by its locally approximated objective function
Figure 277896DEST_PATH_IMAGE024
；
Then, extracting constraint terms related to the total power of the target node, the anchor node and the interference node into an objective function through an external penalty function method, and obtaining an optimization problem containing simple constraints as follows:
Figure 737827DEST_PATH_IMAGE078
Figure 108766DEST_PATH_IMAGE050
Figure 855005DEST_PATH_IMAGE052
Figure 68817DEST_PATH_IMAGE054
wherein the content of the first and second substances,
Figure 925915DEST_PATH_IMAGE079
，
Figure 292305DEST_PATH_IMAGE080
，
Figure 209446DEST_PATH_IMAGE081
the value range of (1) is 10-100.
Here, the constrained optimization problem can be simplified into the unconstrained optimization problem through the external penalty function method, the complexity of the original problem is reduced, more algorithms can be adopted for solving, and the solving efficiency is improved.
Further, in step 8, when the number of iterations is:
Figure 520341DEST_PATH_IMAGE025
then, the particle swarm algorithm is used for solving the optimization problem obtained in the step S6, and the specific method is as follows:
respectively setting three constraint terms in the optimization problem containing simple constraints as the boundaries of corresponding particles, and then solving by using a particle swarm algorithm to obtain
Figure 305763DEST_PATH_IMAGE082
Obtaining the current optimal power distribution in the interfered cooperative wireless positioning network
Figure 651294DEST_PATH_IMAGE082
。
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) compared with the existing non-cooperative positioning method, the cooperative positioning method has good positioning effect.
(2) The method considers the interference of other networks in the actual environment, has better positioning robustness and has more reference value for actual deployment.
(3) The invention realizes overall distribution of the power of the target node, the anchor node and the interference node in the interfered cooperative wireless positioning network, and improves the utilization rate of resources of a resource-limited system on the premise of ensuring the normal operation of a plurality of networks.
Drawings
FIG. 1 is a schematic diagram of an interfered cooperative wireless location network deployed according to an embodiment of the present invention;
FIG. 2 is a schematic overall flow chart of the present invention;
FIG. 3 is a diagram illustrating the squared positioning error of each target node in an embodiment of the present invention and comparison with other prior art.
Detailed Description
The technical solution of the present invention is described in detail below, but the scope of the present invention is not limited to the embodiments.
As shown in figure 1, the method extracts key information of a received signal through K-L transformation and Schulvin complement, then calculates the mathematical form of a positioning error by utilizing the Bai and Golub theorem according to the information, models a power distribution problem into a nonlinear optimization problem, and deduces a specific iteration step by utilizing a Lagrange multiplier method and a particle swarm algorithm to obtain the optimal power distribution under the highest positioning precision.
As shown in fig. 2, a method for power allocation of a wireless cooperative positioning network of this embodiment includes the following steps:
step S1, deploying an interfered cooperative wireless positioning network, wherein the interfered cooperative wireless positioning network comprises
Figure 880281DEST_PATH_IMAGE001
A target node
Figure 412894DEST_PATH_IMAGE002
，
Figure 142952DEST_PATH_IMAGE003
An anchor node
Figure 202044DEST_PATH_IMAGE004
And an interference node
Figure 726566DEST_PATH_IMAGE006
；
Step S2, calculating Fisher information matrix of information received by all target nodes to be positioned in step S1
Figure 746475DEST_PATH_IMAGE007
；
Step S3, obtaining the Fisher information matrix according to the obtained Fisher information matrix
Figure 155591DEST_PATH_IMAGE007
Calculating the square positioning error by utilizing the Bai and Golub theorem
Figure 944555DEST_PATH_IMAGE008
；
Step S4 to minimize
Figure 764613DEST_PATH_IMAGE008
Anchor node total power as objective function
Figure 271817DEST_PATH_IMAGE018
Total power of target node
Figure 343678DEST_PATH_IMAGE019
And total power of interference node
Figure 862516DEST_PATH_IMAGE020
Establishing an optimization problem for constraint;
step S5 according to
Figure 994420DEST_PATH_IMAGE021
Result of the sub-iteration
Figure 113554DEST_PATH_IMAGE022
Substituting the Fisher information matrix
Figure 723527DEST_PATH_IMAGE023
To obtain a local approximate objective function
Figure 487084DEST_PATH_IMAGE024
；
Figure 399676DEST_PATH_IMAGE022
Representing a current optimal power allocation in the interfered cooperative wireless location network;
step S6, converting the original problem into an optimization problem containing simple constraints through a Lagrange multiplier method;
step S7, setting iteration times
Figure 881473DEST_PATH_IMAGE025
；
Step S8, solving the optimization problem by adopting a particle swarm algorithm to obtain the current optimal power distribution
Figure 29558DEST_PATH_IMAGE022
；
Step S9, setting threshold judgment conditions
Figure 55412DEST_PATH_IMAGE026
Performing iterative operation;
when iterating to be less than the threshold value
Figure 529119DEST_PATH_IMAGE027
When, i.e. when
Figure 107999DEST_PATH_IMAGE028
Stopping iteration and outputting optimal power distribution
Figure 59774DEST_PATH_IMAGE022
；
Otherwise, return to step S5.
Example 1:
in this example, one was deployed
Figure 797923DEST_PATH_IMAGE083
And the square interfered cooperative wireless positioning network of m comprises 3 anchor nodes, 3 interference nodes and 8 target nodes. The coordinates of 3 anchor nodes are respectively (0,0), (5,10) and (10,0), the positions of 3 interference nodes are respectively (0,10), (5,0) and (10,10), and 8 target nodes are sequentially distributed in (3, 3), (3, 5), (3, 7), (5, 3), (5, 5), (5, 7), (7, 3) and (7, 5). Transmit power of a single node
Figure 301586DEST_PATH_IMAGE084
、
Figure 757975DEST_PATH_IMAGE058
And
Figure 388807DEST_PATH_IMAGE060
limited to 0-0.5, target node total power
Figure 981463DEST_PATH_IMAGE085
Total power of anchor node
Figure 531393DEST_PATH_IMAGE086
Total power of interference node
Figure 334132DEST_PATH_IMAGE062
Set to 1, threshold judgment condition
Figure 893290DEST_PATH_IMAGE029
Is arranged as
Figure 340452DEST_PATH_IMAGE030
。
The square positioning error of the positions of 8 target nodes is used as an objective function, and the total power of each type of node is used as constraint to establish an optimization problem. When the iteration times are 7 times, the optimal solution can be converged, and the total square positioning error of uniform distribution is 0.0106
Figure 202228DEST_PATH_IMAGE087
The total positioning error of the present embodiment is finally obtained as 0.00883
Figure 102051DEST_PATH_IMAGE087
。
As shown in fig. 3, which is the square positioning error of each node in this embodiment, it can be seen from fig. 3 that the resource allocation scheme of the present invention is superior to the conventional allocation algorithm in both single positioning accuracy and total positioning accuracy; particularly, the final result is that the power of 3 anchor nodes is 0.299, 0.499 and 0.202 respectively; the power of the 3 interfering nodes is 0.300, 0.201, 0.499, respectively; the power of 8 target nodes is 0.071,0.071,0.071,0.071,0.071,0.071,0.071,0.499, respectively.
The embodiment further verifies that the overall operation efficiency of the method is improved, and the actual positioning effect obtained by resource allocation is better under the influence of adding the interference node.

Claims (8)

1. A method for wireless cooperative positioning network power allocation is characterized in that: the method comprises the following steps:
step S1, deploying an interfered cooperative wireless positioning network, wherein the interfered cooperative wireless positioning network comprises
Figure 253808DEST_PATH_IMAGE001
A target node
Figure 391528DEST_PATH_IMAGE002
，
Figure 650471DEST_PATH_IMAGE003
An anchor node
Figure 404800DEST_PATH_IMAGE004
And
Figure 610654DEST_PATH_IMAGE005
an interference node
Figure 399618DEST_PATH_IMAGE006
；
Step S2, calculating and obtaining Fisher information matrixes of the positions of all target nodes to be positioned in the step S1
Figure 767146DEST_PATH_IMAGE007
；
Step S3, obtaining the Fisher information matrix according to the obtained Fisher information matrix
Figure 274350DEST_PATH_IMAGE007
Calculating the square positioning error of the target node position by utilizing the Bai and Golub theorem
Figure 18315DEST_PATH_IMAGE008
；
Step S4 to minimize
Figure 661786DEST_PATH_IMAGE008
Anchor node total power as objective function
Figure 967259DEST_PATH_IMAGE009
Total power of target node
Figure 696181DEST_PATH_IMAGE010
And total power of interference node
Figure 243837DEST_PATH_IMAGE011
For constraint, establish about target node, anchorOptimization problem of power distribution of node and interference node
Figure 741814DEST_PATH_IMAGE012
；
Step S5 according to
Figure 716723DEST_PATH_IMAGE013
Result of the sub-iteration
Figure 667362DEST_PATH_IMAGE014
Substituting the Fisher information matrix
Figure 815446DEST_PATH_IMAGE015
To obtain a local approximate objective function
Figure 371193DEST_PATH_IMAGE016
；
Figure 579320DEST_PATH_IMAGE014
Representing a current optimal power allocation in the interfered cooperative wireless location network;
step S6, optimizing the problem by Lagrange multiplier method
Figure 220517DEST_PATH_IMAGE017
Conversion to optimization problems with simple constraints
Figure 172292DEST_PATH_IMAGE018
；
Step S7, setting iteration times
Figure 582545DEST_PATH_IMAGE019
；
Step S8, solving step S6 by particle swarm optimization
Figure 961574DEST_PATH_IMAGE018
To obtain the current optimal power distribution
Figure 90067DEST_PATH_IMAGE020
；
Step S9, setting threshold judgment conditions
Figure 579954DEST_PATH_IMAGE021
Performing iterative operation;
when iterating to be less than the threshold value
Figure 907030DEST_PATH_IMAGE022
When, i.e. when
Figure 129064DEST_PATH_IMAGE023
Stopping iteration and outputting optimal power distribution
Figure 807170DEST_PATH_IMAGE014
(ii) a Otherwise, return to step S5.
2. The method of wireless cooperative positioning network power allocation according to claim 1, wherein: step S2 is executed for all target nodes to be positioned
Figure 536967DEST_PATH_IMAGE024
Fisher information matrix of positions
Figure 984128DEST_PATH_IMAGE015
Expressed as:
Figure 642643DEST_PATH_IMAGE025
wherein the content of the first and second substances,
Figure 542466DEST_PATH_IMAGE026
representing a target node
Figure 311839DEST_PATH_IMAGE024
The position of (a);
Figure 613507DEST_PATH_IMAGE027
representing a target node
Figure 708502DEST_PATH_IMAGE024
To all anchor nodes
Figure 830042DEST_PATH_IMAGE004
A Fisher information matrix obtained by communication, represented as
Figure 465422DEST_PATH_IMAGE028
；
Figure 824860DEST_PATH_IMAGE029
Representing a target node
Figure 887493DEST_PATH_IMAGE024
And a target node
Figure 699592DEST_PATH_IMAGE030
Fisher information matrix obtained by inter-communication and
Figure 873084DEST_PATH_IMAGE031
(ii) a And is
Figure 87028DEST_PATH_IMAGE032
；
Figure 320563DEST_PATH_IMAGE033
Is formed by anchor nodes
Figure 416695DEST_PATH_IMAGE004
Transmitting signal waveform and power blockThe strength of the determined distance information;
Figure 331561DEST_PATH_IMAGE034
the representation is made by the target node
Figure 462328DEST_PATH_IMAGE030
The intensity of distance information determined by the waveform and power of the transmitted signal;
Figure 305913DEST_PATH_IMAGE035
representing a target node
Figure 154920DEST_PATH_IMAGE024
Intensity of interference, total power of all interference nodes and interference nodes
Figure 873477DEST_PATH_IMAGE036
Position correlation;
Figure 858751DEST_PATH_IMAGE037
representing a target node
Figure 371772DEST_PATH_IMAGE030
The intensity of the disturbance;
Figure 708075DEST_PATH_IMAGE038
by the target node
Figure 964744DEST_PATH_IMAGE024
And anchor node
Figure 804524DEST_PATH_IMAGE004
Relative angle determination between them;
Figure 754026DEST_PATH_IMAGE039
by the target node
Figure 577625DEST_PATH_IMAGE024
And a target node
Figure 169144DEST_PATH_IMAGE040
The relative angle therebetween.
3. The method of wireless cooperative positioning network power allocation according to claim 1, wherein: with respect to the target node in the step S3
Figure 66693DEST_PATH_IMAGE024
The squared positioning error of a position is expressed as:
Figure 249412DEST_PATH_IMAGE041
wherein the content of the first and second substances,
Figure 232412DEST_PATH_IMAGE042
represents the trace of the sampling matrix, because
Figure 893200DEST_PATH_IMAGE043
Without specific mathematical analysis, it is approximated using the Bai and Golub theorem as:
Figure 910835DEST_PATH_IMAGE044
wherein the content of the first and second substances,
Figure 998876DEST_PATH_IMAGE045
；
Figure 967707DEST_PATH_IMAGE046
；
Figure 432187DEST_PATH_IMAGE047
；
Figure 304328DEST_PATH_IMAGE048
representing Fisher information matrices
Figure 297691DEST_PATH_IMAGE015
Of order of (i) i.e
Figure 317600DEST_PATH_IMAGE049
；
Figure 257874DEST_PATH_IMAGE050
Representing a matrix
Figure 46839DEST_PATH_IMAGE015
The square of the norm is determined by the square of the norm,
Figure 679945DEST_PATH_IMAGE051
representing and taking matrix
Figure 187150DEST_PATH_IMAGE015
The minimum eigenvalue of (c).
4. The method of wireless cooperative positioning network power allocation according to claim 1, wherein: the specific process of establishing the optimization problem in step S4 is as follows:
to minimize
Figure 665536DEST_PATH_IMAGE052
An optimization problem is established by taking the total power of the anchor nodes, the total power of the target nodes and the total power of the interference nodes as constraints for an objective function
Figure 574586DEST_PATH_IMAGE017
Comprises the following steps:
Figure 113015DEST_PATH_IMAGE053
Figure 841936DEST_PATH_IMAGE054
Figure 186330DEST_PATH_IMAGE055
Figure 887570DEST_PATH_IMAGE056
Figure 924796DEST_PATH_IMAGE057
Figure 78697DEST_PATH_IMAGE058
Figure 226781DEST_PATH_IMAGE059
wherein the target node
Figure 295711DEST_PATH_IMAGE002
Transmit power of
Figure 503839DEST_PATH_IMAGE060
In the range of
Figure 145036DEST_PATH_IMAGE061
Total power of all target nodes is less than
Figure 831232DEST_PATH_IMAGE010
；
Anchor node
Figure 303801DEST_PATH_IMAGE004
Transmit power of
Figure 620513DEST_PATH_IMAGE062
In the range of
Figure 811323DEST_PATH_IMAGE063
Total power of all anchor nodes is less than
Figure 238894DEST_PATH_IMAGE009
；
Interference node
Figure 565970DEST_PATH_IMAGE036
Transmit power of
Figure 53583DEST_PATH_IMAGE064
In the range of
Figure 731689DEST_PATH_IMAGE065
Total power of all interfering nodes is greater than
Figure 759688DEST_PATH_IMAGE066
。
5. The method of wireless cooperative positioning network power allocation according to claim 1, wherein: in said step S5
Figure 144533DEST_PATH_IMAGE014
Representing a vector
Figure 599785DEST_PATH_IMAGE067
；
Wherein the content of the first and second substances,
Figure 702870DEST_PATH_IMAGE068
is shown as
Figure 534560DEST_PATH_IMAGE013
Performing secondary iteration;
when the number of iterations
Figure 39490DEST_PATH_IMAGE069
The transmission power of the target node, the anchor node and the interference node are uniformly distributed, namely
Figure 665644DEST_PATH_IMAGE070
、
Figure 754560DEST_PATH_IMAGE071
And
Figure 389941DEST_PATH_IMAGE072
thus obtaining
Figure 280537DEST_PATH_IMAGE073
；
When the number of iterations
Figure 280854DEST_PATH_IMAGE074
When the temperature of the water is higher than the set temperature,
Figure 155269DEST_PATH_IMAGE014
the value is the result obtained by the last iterative operation;
according to the first
Figure 532023DEST_PATH_IMAGE013
Result of the sub-iteration
Figure 808284DEST_PATH_IMAGE014
Then locally approximate the objective function
Figure 979502DEST_PATH_IMAGE016
The estimation process of (2) is:
will be provided with
Figure 341214DEST_PATH_IMAGE014
Substituted into Fisher information matrix
Figure 256080DEST_PATH_IMAGE015
In that it obtains
Figure 121268DEST_PATH_IMAGE013
At the time of the second iteration,
Figure 525704DEST_PATH_IMAGE075
and are/is
Figure 312395DEST_PATH_IMAGE076
Are each as follows
Figure 827690DEST_PATH_IMAGE077
、
Figure 16226DEST_PATH_IMAGE078
And
Figure 591563DEST_PATH_IMAGE079
(ii) a Then the
Figure 865550DEST_PATH_IMAGE016
Expressed as:
Figure 184536DEST_PATH_IMAGE080
。
6. the method of wireless cooperative positioning network power allocation according to claim 1, wherein:
the detailed problem of step S6 is:
first, an objective function is defined
Figure 24316DEST_PATH_IMAGE052
Replaced by its locally approximated objective function
Figure 475282DEST_PATH_IMAGE016
；
Then, extracting constraint terms related to the total power of the target node, the anchor node and the interference node into an objective function through an external penalty function method to obtain an optimization problem containing simple constraints
Figure 767723DEST_PATH_IMAGE018
Comprises the following steps:
Figure 828083DEST_PATH_IMAGE081
Figure 787949DEST_PATH_IMAGE054
Figure 642772DEST_PATH_IMAGE056
Figure 953668DEST_PATH_IMAGE058
wherein the content of the first and second substances,
Figure 552140DEST_PATH_IMAGE082
，
Figure 366512DEST_PATH_IMAGE083
and
Figure 454553DEST_PATH_IMAGE084
the value range of (1) is 10-100.
7. The method of wireless cooperative positioning network power allocation according to claim 1, wherein: in step 8, when the number of iterations is:
Figure 924849DEST_PATH_IMAGE019
then, the particle swarm algorithm is used for solving the optimization problem obtained in the step S6, and the specific method is as follows:
respectively setting three constraint terms in the optimization problem containing simple constraints as the boundaries of corresponding particles, and then solving by using a particle swarm algorithm to obtain
Figure 389328DEST_PATH_IMAGE014
Obtaining the current optimal power distribution in the interfered cooperative wireless positioning network
Figure 995890DEST_PATH_IMAGE014
。
8. The method of wireless cooperative positioning network power allocation according to claim 1, wherein: in the step S9
Figure 520413DEST_PATH_IMAGE085
Take a value of
Figure 478004DEST_PATH_IMAGE086
。
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