CN114440893A - Cooperative positioning method, system and storage medium for resolving TDOA (time difference of arrival) signals - Google Patents

Cooperative positioning method, system and storage medium for resolving TDOA (time difference of arrival) signals Download PDF

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CN114440893A
CN114440893A CN202210141861.6A CN202210141861A CN114440893A CN 114440893 A CN114440893 A CN 114440893A CN 202210141861 A CN202210141861 A CN 202210141861A CN 114440893 A CN114440893 A CN 114440893A
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sparrow
mobile terminal
base station
location
population
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邓中亮
雷鸣
郑心雨
许�鹏
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Beijing University of Posts and Telecommunications
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Beijing University of Posts and Telecommunications
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/0009—Transmission of position information to remote stations
    • G01S5/0018—Transmission from mobile station to base station
    • G01S5/0027—Transmission from mobile station to base station of actual mobile position, i.e. position determined on mobile
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/04—Position of source determined by a plurality of spaced direction-finders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]

Abstract

The invention provides a co-location method, a system and a storage medium for resolving TDOA signals, wherein the method comprises the following steps: calculating time differences between the mobile terminal and each receiving base station through a TDOA positioning algorithm, and calculating distance differences between the mobile terminal and each receiving base station based on the calculated time differences; resolving an initial position coordinate of the mobile terminal through a CHAN algorithm; establishing an initial sparrow population; calculating the fitness of each sparrow in the initial sparrow population; updating the positions of sparrows in the initial sparrow population respectively based on the updating formulas of the finder, the follower and the early-warning person, calculating the fitness of each sparrow after the positions are updated, and determining an optimal fitness value; and under the condition that the optimal fitness value is smaller than a preset threshold value or the current iteration number is equal to the maximum iteration number, determining the final position coordinate of the mobile terminal based on the sparrow population generated in the current iteration process. The method can accelerate the convergence speed of the sparrow search algorithm, and the accuracy of the determined final position coordinate is high.

Description

Cooperative positioning method, system and storage medium for resolving TDOA (time difference of arrival) signals
Technical Field
The invention relates to the technical field of wireless positioning, in particular to a co-positioning method, a system and a storage medium for resolving TDOA signals.
Background
In recent years, with the rapid development of wireless positioning technology, Location Based Services (LBS) include, for example: indoor mall navigation positioning, vehicle-mounted navigation systems, etc. have become the hot directions of research. These services can perform navigation tracking through navigation satellites in outdoor environments, but the positioning results of satellite navigation systems in indoor or complex building sheltered areas are not satisfactory. Moreover, studies have shown that people perform activities indoors, such as work, life, shopping, entertainment, etc., on average 20 hours a day. With the continuous advance of modern city construction, research on location services has slowly shifted from outdoor space to indoor space.
The currently basic wireless positioning methods include time of arrival (TOA), angle of arrival (AOA), and time of arrival (TDOA), etc.; compared with TOA, the TDOA method simplifies strict clock synchronization requirements and reduces hardware cost; compared with AOA, the TDOA method is less influenced by environmental factors and is more suitable for indoor complex environments. Based on the advantages of better practicability, easy implementation and the like, the TDOA method is concerned, but in an NLOS (non line of sight) environment, the TDOA positioning method still has larger errors; how to judge the NLOS signal and reduce the NLOS error in the NLOS environment to improve the positioning accuracy becomes one of the problems that need to be solved at present. Generally, when wireless positioning information is acquired, a positioning result can be solved by using a Least Square method (LS), a CHAN algorithm, a Fang algorithm, a Taylor algorithm and the like; in the NLOS environment, the algorithm has the defect of large error, namely the positioning accuracy is obviously reduced; in addition, some of the prior art adopt a Particle Swarm Optimization (PSO) and Partial Least Squares (PLS) combined positioning method to perform preliminary position estimation on TDOA parameters, which increases the convergence rate of the particle swarm, but has a high requirement on the parameters, that is, has low positioning accuracy under the condition of high noise. Therefore, how to provide a positioning method with fast convergence rate and high positioning accuracy is an urgent technical problem to be solved.
Disclosure of Invention
In view of the above, the present invention provides a co-location method, system and storage medium for TDOA signal solution to solve one or more problems in the prior art.
According to one aspect of the invention, the invention discloses a co-location method for TDOA signal resolving, the method comprising:
calculating time differences between the mobile terminal and each receiving base station through a TDOA positioning algorithm, and calculating distance differences between the mobile terminal and each receiving base station based on the calculated time differences;
calculating initial position coordinates of the mobile terminal through a CHAN algorithm based on the calculated distance difference between the mobile terminal and each receiving base station;
establishing an initial sparrow population, determining the proportion of foragers, followers and early-warning persons in the initial sparrow population, and acquiring the maximum iteration times of a sparrow search algorithm; wherein the initial sparrow population obeys normal distribution with the mean value being the initial coordinate position;
calculating the fitness of each sparrow in the initial sparrow population based on a preset fitness function, and determining a finder, a follower and an early warning person based on the fitness corresponding to the initial sparrow population;
updating the position of each sparrow in the initial sparrow population respectively based on the updating formulas of the finder, the follower and the early-warning person, calculating the fitness of each sparrow after the position is updated, and determining an optimal fitness value based on the calculated fitness of each sparrow after the position is updated;
and determining the final position coordinate of the mobile terminal based on the sparrow population generated in the current iteration process under the condition that the optimal fitness value is smaller than a preset threshold value or the current iteration number is equal to the maximum iteration number.
In some embodiments of the invention, the fitness function is:
Figure BDA0003506673570000021
wherein f is1＝l2-l1-r2,1，f2＝l3-l1-r3,1，f3＝l4-l1-r4,1；lkDistance from a sparrow to a receiving base station k, k being 1,2,3, 4; r isk,1Is the distance difference between the mobile terminal and the receiving base station k and the receiving base station 1.
In some embodiments of the invention, the location update formula of the seeker is:
Figure BDA0003506673570000022
wherein the content of the first and second substances,
Figure BDA0003506673570000023
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; beta is a random number, and beta is an element of (0,1)](ii) a T is the maximum iteration number; r0Is a sparrow's early warning value, and R0∈[0,1](ii) a ST is the safety threshold of the population, and ST belongs to [0.5,1 ]](ii) a Q is a random number which follows normal distribution; l represents a 1 × d matrix, and each element in the matrix is 1; k is 1 or-1; i represents the ith sparrow.
In some embodiments of the invention, when
Figure BDA0003506673570000024
Then, the location update formula of the follower is:
Figure BDA0003506673570000031
wherein the content of the first and second substances,
Figure BDA0003506673570000032
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; xcIs a fixed value and is an analytic value of the CHAN algorithm; q is a random number which follows normal distribution;
Figure BDA0003506673570000033
for the t-th iterationGlobal worst positions of the sparrow populations; i represents the ith sparrow; n is the total number of sparrows in the population.
In some embodiments of the present invention, when
Figure BDA0003506673570000034
Then, the location update formula of the follower is:
Figure BDA0003506673570000035
wherein the content of the first and second substances,
Figure BDA0003506673570000036
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; i represents the ith sparrow; n is the total number of sparrows in the population; gamma is belonged to 0,1](ii) a D represents a dimension;
Figure BDA0003506673570000037
and searching the optimal position for the finder at the t +1 th iteration.
In some embodiments of the present invention, the location update formula of the pre-warner is:
Figure BDA0003506673570000038
wherein the content of the first and second substances,
Figure BDA0003506673570000039
the j-th dimension position of a sparrow i at the T-th iteration is represented by T, 1,2,3, …, T, j is represented by 1,2,3, …, D; k is a random number, and K ∈ [ -1,1](ii) a Epsilon is a constant, and epsilon is not equal to 0; f. ofiThe fitness of sparrow i; f. ofgThe global optimal fitness is obtained; f. ofwIs the global worst fitness;
Figure BDA00035066735700000310
representing a global optimal position;
Figure BDA00035066735700000311
representing a global worst location; beta is a random number following a normal distribution, a factor used to control sparrow flight.
In some embodiments of the present invention, the distance difference between the mobile terminal and each receiving base station is calculated according to the following formula:
Figure BDA00035066735700000312
wherein, Δ di,1Is the distance difference between the mobile terminal to the receiving base station i and the receiving base station 1; c is the speed of light; tau isi,1Is the time difference between the mobile terminal and the receiving base station i and the receiving base station 1; x and y are position coordinates of the mobile terminal; x is the number ofi、yiTo receive the location coordinates of base station i.
In some embodiments of the present invention, calculating the initial position coordinates of the mobile terminal by a CHAN algorithm based on the calculated distance difference between the mobile terminal and each receiving base station includes:
calculating initial position coordinates of the mobile terminal by combining a CHAN algorithm and a least square method based on the calculated distance difference between the mobile terminal and each receiving base station
According to another aspect of the present invention, there is also disclosed a co-location system for TDOA signal resolution, the system comprising a processor and a memory, the memory having stored therein computer instructions for executing the computer instructions stored in the memory, the system implementing the steps of the method according to any one of the embodiments described above when the computer instructions are executed by the processor.
According to yet another aspect of the invention, a computer-readable storage medium is also disclosed, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any of the embodiments above.
The invention discloses a co-location method, a system and a storage medium for resolving TDOA signals, wherein a TDOA location model is established under the condition that random errors exist in terminal location information, an initial location solution of a terminal is estimated through a CHAN algorithm, the initial solution is introduced into an ISSA (improved sparrow search algorithm) to relocate a mobile terminal, and the ISSA is distributed near the initial solution, so that the iteration times of the algorithm are reduced, the algorithm is prevented from falling into local optimization, the location errors are minimized, and the location precision is improved.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
It will be appreciated by those skilled in the art that the objects and advantages that can be achieved with the present invention are not limited to the specific details set forth above, and that these and other objects that can be achieved with the present invention will be more clearly understood from the detailed description that follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. For purposes of illustrating and describing some portions of the present invention, corresponding parts of the drawings may be exaggerated, i.e., may be larger, relative to other components in an exemplary apparatus actually manufactured according to the present invention. In the drawings:
fig. 1 is a flowchart illustrating a co-location method for resolving TDOA signals according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating a co-location method for TDOA signal solution according to another embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
It should be noted that, in order to avoid obscuring the present invention with unnecessary details, only the structures and/or processing steps closely related to the scheme according to the present invention are shown in the drawings, and other details not closely related to the present invention are omitted.
It should be emphasized that the term "comprises/comprising/comprises/having" when used herein, is taken to specify the presence of stated features, elements, steps or components, but does not preclude the presence or addition of one or more other features, elements, steps or components.
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the drawings, the same reference numerals denote the same or similar parts, or the same or similar steps.
FIG. 1 is a flowchart illustrating a co-location method for resolving TDOA signals according to an embodiment of the present invention, where the co-location method for resolving TDOA signals includes steps S10-S60, as shown in FIG. 1.
Step S10: the time difference between the arrival of the mobile terminal at each receiving base station is calculated by the TDOA location algorithm, and the distance difference between the mobile terminal and each receiving base station is calculated based on the calculated time differences.
TDOA location is a method of location using time difference; by measuring the time of arrival of the signal at the receiving base station, the distance of the signal source can be determined; the location of the mobile terminal can be determined by the distance from the signal source to each receiving base station (taking the receiving base station as the center and the distance as the radius to make a circle). In this step, assuming that the mobile terminal coordinate position is (x, y), the actual position of the i-th receiving base station is (x)i，yi) (i ═ 1, …, N), N being the total number of receiving base stations; the distance from the mobile terminal to the ith receiving base station is recorded as di(i ═ 1,2, …, N); the time difference of arrival of the measuring signal from the mobile terminal to other base station and the base station No. 1 is recorded as taui,1(i ═ 1,2, …, N); knowing the speed of light c, the distance difference between the mobile terminal and the ith base station and the 1 st base station can be obtained: Δ d ofi,1＝cτi,1Wherein, isdi,1Is the difference in distance between the mobile terminal to the receiving base station i and the receiving base station 1. In addition, Δ di,1Or indirectly from the difference in distance between the mobile terminal and different receiving base stations, i.e.
Figure BDA0003506673570000051
The following are exemplary:
Figure BDA0003506673570000052
in this embodiment, if the receiving base station 1 is taken as the reference base station, Δ d2,1For the distance difference, Δ d, between the mobile terminal to the receiving base station 2 and the receiving base station 13,1Is the difference in distance between the mobile terminal to the receiving base station 3 and the receiving base station 1; and (x)2，y2)、(x3，y3) Position coordinates of the receiving base station 2 and the receiving base station 3, respectively.
In addition,. DELTA.di,1＝di-d1Therefore, based on the above two distance difference calculation formulas, the estimated position of the mobile terminal can be further obtained, and c τ is usedi,1Is time information with errors, and thus may cause a deviation in the estimated position of the mobile terminal.
Step S20: and calculating the initial position coordinates of the mobile terminal through a CHAN algorithm based on the calculated distance difference between the mobile terminal and each receiving base station.
In this step, the initial position coordinates of the mobile terminal are solved by the CHAN algorithm. Due to diFor the distance of the mobile terminal to the i-th receiving base station, i.e. di 2＝(xi-x)2+(yi-y)2And due to di,1＝di-d1Thus, based on the above formula, can be obtained
Figure BDA0003506673570000053
Wherein, Ui＝xi 2+yi 2，xi,1＝xi-x1，yi,1＝yi-y1In addition, x, y, diAs an argument, let Zα＝(x,y,d1)TThen
Figure BDA0003506673570000061
Figure BDA0003506673570000062
It can be expressed as a linear system of equations: gαZα＝h。
At GαZαIn the range of h, the number of the catalyst,
Figure BDA0003506673570000063
n is the total number of receiving base stations, and N is the maximum value of i.
Further, let Zα 0Is a standard value, then GαZαThe error h can be written as: e-h-GαZα. Assuming that the error approximation follows a normal distribution and has a covariance matrix ψ, then there is ψ -E (ee)T)＝c2BQB; wherein, B ═ diag { d ═ d2，d3，…，dNAnd Q is a noise covariance matrix obeying a gaussian distribution.
In an embodiment, calculating the initial position coordinates of the mobile terminal based on the calculated distance difference between the mobile terminal and each receiving base station through a CHAN algorithm specifically includes: and calculating the initial position coordinates of the mobile terminal by combining a CHAN algorithm and a least square method based on the calculated distance difference between the mobile terminal and each receiving base station.
In this embodiment, the equation is further solved using a least squares method: gα TGαZα＝Cα Th, assume x, y, d1Independently of each other, haveαTψGα)Zα＝Gα TψhThen Z isαWls (weighted least squares) of Zα＝(Gα Tψ-1Gα)-1GαTψ-1h. When the mobile terminal is connected withWhen the receiving base station is far away, replacing psi with Q to obtain:
Figure BDA0003506673570000064
using ZαThe B matrix can be derived to obtain the value of psi, finally Z is taken inα＝(Gα Tψ-1Gα)-1GαTψ-1h can give ZαA first time estimate of; and then on the basis of obtaining the first estimated value, carrying out weighted least square method calculation again to obtain the final initial position coordinate of the mobile terminal calculated by the CHAN method.
Step S30: establishing an initial sparrow population, determining the proportion of foragers, followers and early-warning persons in the initial sparrow population, and acquiring the maximum iteration times of a sparrow search algorithm; wherein the initial sparrow population follows a normal distribution with a mean value of the initial coordinate position.
In the existing Sparrow Search Algorithm (SSA), the entire sparrow population is divided into: seekers, followers and forewarners; the finder is used for searching food, providing foraging direction and foraging place for the follower, and the finder accounts for 10-20% of the population; the follower will observe the action of the finder and compete with the finder for food to become a new finder; in addition, some early-warning persons who can be aware of danger, alert predators and give warnings exist in the population, and fly to other safer areas when encountering danger, and the proportion of the early-warning persons in the population is 10% -20%. In a D-dimensional target search space, the SSA generates M sparrows, and the coordinate positions of the ith sparrow satisfy Xi＝[xi1，xi2，xi2，…，xiD](i ═ 1,2,3, …, M), where xiDIndicating the coordinate position of the ith sparrow in the D-dimension.
In general, the location update formula of the finder of the existing sparrow search algorithm can be expressed as:
Figure BDA0003506673570000065
Figure BDA0003506673570000071
wherein:
Figure BDA0003506673570000072
position of sparrow i in jth dimension at tth iteration (T is 1,2,3, …, T, j is 1,2,3, …, D); beta e (0,1)]Is a random number; t is the maximum number of iterations; r0Between 0 and 1, the early warning value of sparrow population is shown, ST is between 0.5 and 1, and R is generally taken00.8, representing the safety threshold of the population; r0<ST indicates that no predators are found in sparrow population and the finder can perform extensive search, R0>ST indicates that the predator is found by the early-warning person, the warning signal is released, and the population is about to move to a safe area. Q is a random number following a Gaussian distribution, and L is a full 1 matrix of 1 row and d columns.
While the location update formula for the followers of the Sparrow Search Algorithm (SSA) can be expressed as:
Figure BDA0003506673570000073
wherein, XworstIs the global worst position, X, of the sparrow populationpIs the best position searched by the finder, A is a matrix of 1 row and d columns, the elements are randomly assigned to-1 or 1, A+＝AT(AAT)-1Indicating the direction the sparrow is flying. When i is>N/2, indicating that the ith follower is starved and not enough food, in order to obtain more food, the follower will fly to other places to feed, and the next position to be searched conforms to the standard normal distribution. When i is<N/2, indicating that the ith follower will be at the current global optimum position XpAnd searching a position around the foraging. The location update formula of the forewarner of the existing Sparrow Search Algorithm (SSA) is expressed as:
Figure BDA0003506673570000074
wherein, beta is a random number which follows normal distribution and can control the flying factor of sparrows;
Figure BDA0003506673570000075
representing a global optimal position; k is a random number between-1 and 1; ε is a constant other than 0 to avoid the case where the denominator is zero; f. ofiIs the fitness of the ith sparrow, fgFor global optimal fitness, fwIs the global worst fitness. When f isi>fgWhen the sparrows are in the periphery of the population, the sparrows can gather to the Zhongxing to avoid being attacked; when f isi＝fgBy time, it is meant that the sparrow experiences a danger and may be approaching another sparrow to avoid being attacked by predators.
Step S40: calculating the fitness of each sparrow in the initial sparrow population based on a preset fitness function, and determining a finder, a follower and an early warning person based on the fitness corresponding to the initial sparrow population.
In SSA, foragers typically have high energy reserves and are responsible for searching for areas with abundant food throughout the population, providing areas and directions for foraging for all enrollees. The energy reserve in the model building depends on the Fitness Value (Fitness Value) corresponding to the sparrow individual. Specifically, the fitness function adopted when the fitness of each sparrow in the initial sparrow population is calculated in the invention is as follows:
Figure BDA0003506673570000076
wherein f is1＝l2-l1-r2,1，f2＝l3-l1-r3,1，f3＝l4-l1-r4,1；lkDistance from a sparrow to a receiving base station k, k being 1,2,3, 4; r isk,1Is the distance difference between the mobile terminal and the receiving base station k and the receiving base station 1. In this embodiment, the number of receiving base stations is set to four, and it is understood that the number of receiving base stations may be more in other examples.
Step S50: updating the position of each sparrow in the initial sparrow population respectively based on the updating formulas of the finder, the follower and the early-warning person, calculating the fitness of each sparrow after the position is updated, and determining the optimal fitness value based on the calculated fitness of each sparrow after the position is updated.
In this step, after the positions of the sparrows in the sparrow population are updated once, the fitness values of the sparrows in the corresponding population change accordingly, and therefore after the positions of the sparrows in the sparrow population are updated, the fitness values of the sparrows after the positions are updated are calculated based on the fitness function.
According to the existing Sparrow Search Algorithm (SSA), when the early warning value of the finder is smaller than the safety threshold value, the position update of the finder is determined by a normal distribution function and an exponential function. f (x) e-xWhen x is>At 0, the range is between (0,1), with increasing argument x, f (x) converges to 0; and according to the 2 sigma principle, the standard normal distribution function Q has the probability distribution of 95.44 percent in [ -2,2]In the meantime. Therefore, the sparrow search algorithm can converge quickly when the optimal solution is near the origin, but the practical problem is random, and the performance of the SSA is not so superior when the optimal solution is not near the origin. Secondly, the follower is at i>And N/2, position updating is carried out once in the global scope, and similarly to the problem, the updating position of the position updating device is still spread near the origin, so that the requirements of other scenes cannot be met. Therefore, in order to improve the performance of the SSA and meet the scenario requirement of the present invention, an Improved Sparrow Search Algorithm (ISSA) is adopted in this step, and the location update formula of the finder in the ISSA is:
Figure BDA0003506673570000081
wherein the content of the first and second substances,
Figure BDA0003506673570000082
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; beta is a random number, and beta is an element of (0,1)](ii) a T is the maximum iteration number; r0Is a sparrow's early warning value, and R0∈[0,1](ii) a ST is the safety threshold of the population, and ST belongs to [0.5,1 ]](ii) a Q is a random number which follows normal distribution; l represents 1A xd matrix, and each element in the matrix is 1; k is 1 or-1 and satisfies
Figure BDA0003506673570000083
The second distribution of (a); i represents the ith sparrow.
In addition, when
Figure BDA0003506673570000084
Then, the location update formula of the follower is:
Figure BDA0003506673570000085
wherein the content of the first and second substances,
Figure BDA0003506673570000086
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; xcIs a fixed value and is an analytic value of the CHAN algorithm; q is a random number which follows normal distribution;
Figure BDA0003506673570000087
the global worst position of the sparrow population at the t iteration; i represents the ith sparrow; n is the total number of sparrows in the population.
When in use
Figure BDA0003506673570000088
Then, the location update formula of the follower is:
Figure BDA0003506673570000091
wherein the content of the first and second substances,
Figure BDA0003506673570000092
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; i represents the ith sparrow; n is the total number of sparrows in the population; gamma is belonged to 0,1](ii) a D represents a dimension;
Figure BDA0003506673570000093
and searching the optimal position for the finder at the t +1 th iteration. Gamma is uniformly distributed in [0,1 ]]The searching capability of the ISSA can be refined.
In addition, the location updating formula of the ISSA forewarner in the invention is the same as the location updating formula of the SSA forewarner in the prior art, and is all as follows:
Figure BDA0003506673570000094
wherein the content of the first and second substances,
Figure BDA0003506673570000095
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; k is a random number, and K ∈ [ -1,1](ii) a Epsilon is a constant, and epsilon is not equal to 0; f. ofiThe fitness of sparrow i; f. ofgThe global optimal fitness is obtained; f. ofwIs the global worst fitness;
Figure BDA0003506673570000096
representing a global optimal position;
Figure BDA0003506673570000097
representing a global worst location; beta is a random number following a normal distribution, a factor used to control sparrow flight.
Step S60: and under the condition that the optimal fitness value is smaller than a preset threshold value or the current iteration number is equal to the maximum iteration number, determining the final position coordinate of the mobile terminal based on the sparrow population generated in the current iteration process.
After the fitness values of the sparrows are calculated, selecting the minimum value among the fitness values as an optimal fitness value, and further comparing whether the optimal fitness value of the iteration is smaller than a preset threshold value or not; if the optimal fitness value is smaller than the preset threshold value, the iteration updating process is ended, and at the moment, the current iteration times are generally smaller than the maximum iteration times, namely, the program is ended in advance. And if the current iteration times are equal to the maximum iteration times and the optimal fitness value in the current sparrow population is greater than or equal to the preset threshold value, ending the iteration updating process and ending the program. The final location coordinates of the mobile terminal are determined based on the sparrow population at the end of the procedure.
Compared with the original Sparrow Search Algorithm (SSA), the Improved Sparrow Search Algorithm (ISSA) adopted by the co-location method for resolving the TDOA signal not only increases the global search capability, but also can accelerate the convergence rate of the sparrow search algorithm and is more suitable for solving the problem of a wide-area locating point and the like. The method utilizes a CHAN algorithm to process TDOA data in advance to obtain an initial solution, then uses ISSA to optimize the initial solution again, finally obtains the coordinates of the positioning point, and combines the CHAN algorithm and the ISSA, thereby effectively improving the positioning precision and obviously reducing the calculation time.
The above method is described below with reference to a specific example, however, it should be noted that the specific example is only for better describing the present application and is not to be construed as limiting the present application.
Fig. 2 is a flowchart illustrating a co-location method for resolving TDOA signals according to an embodiment of the present invention, and as shown in fig. 2, the location method includes the following steps:
(1) acquiring a group of latest TDOA values, and calculating an initial value of the mobile terminal coordinate through settlement by a CHAN algorithm;
(2) and transmitting the calculated initial coordinate value to the ISSA, and taking the initial coordinate value as a mean value, wherein the sparrow population obeys normal distribution taking the mean value as the initial coordinate value.
(3) Initializing a sparrow population, and specifying the total number of sparrows, the proportion of foragers and followers, variable dimensionality, choice of an early-warning person and maximum iteration times.
(4) A fitness function is established, the adaptive value selected in the embodiment is a positioning variance, and the specific function formula is as follows:
Figure BDA0003506673570000101
wherein f is1＝l2-l1-r2,1，f2＝l3-l1-r3,1，f3＝l4-l1-r4,1。lkIndicates the distance from the current position of the sparrow to the base station (k is 1,2,3,4), rk,1Is the distance difference between the mobile terminal and the receiving base station k and the receiving base station 1.
(5) And respectively updating the positions of the finder, the follower and the early-warning person based on the position updating formulas of the finder, the follower and the early-warning person.
(6) In each iteration, for each sparrow, the adaptive value f of the sparrow is compared with the recorded global optimal adaptive value, if the current fitness is better, the current fitness f replaces the global optimal adaptive value, the current position is changed into a global optimal position, and the optimal position and the worst position of each iteration are saved.
(7) And if the global optimal adaptive value f is smaller than the specified threshold value, the program can be ended in advance, otherwise, the program is ended and the position of the terminal is output until the iteration reaches the maximum iteration times.
The cooperative positioning method solves the problems of low positioning accuracy and high calculation complexity of the positioning calculation algorithm in the prior art under the indoor complex condition, improves the accuracy and stability of the positioning algorithm, and reduces the calculation complexity.
Correspondingly, the invention also discloses a co-location system for resolving TDOA signals, which comprises a processor and a memory, wherein the memory stores computer instructions, the processor is used for executing the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system realizes the steps of the method according to any one of the above embodiments.
In addition, the invention also discloses a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the method according to any of the above embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative components, systems, and methods described in connection with the embodiments disclosed herein may be implemented as hardware, software, or combinations of both. Whether this is done in hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments noted in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and/or in combination with or instead of the features of the other embodiments in the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A co-location method for TDOA signal resolution, the method comprising:
calculating time differences between the mobile terminal and each receiving base station through a TDOA positioning algorithm, and calculating distance differences between the mobile terminal and each receiving base station based on the calculated time differences;
calculating initial position coordinates of the mobile terminal through a CHAN algorithm based on the calculated distance difference between the mobile terminal and each receiving base station;
establishing an initial sparrow population, determining the proportion of foragers, followers and early-warning persons in the initial sparrow population, and acquiring the maximum iteration times of a sparrow search algorithm; wherein the initial sparrow population obeys normal distribution with the mean value being the initial coordinate position;
calculating the fitness of each sparrow in the initial sparrow population based on a preset fitness function, and determining a finder, a follower and an early warning device based on the fitness corresponding to the initial sparrow population;
updating the position of each sparrow in the initial sparrow population respectively based on the updating formulas of the finder, the follower and the early-warning person, calculating the fitness of each sparrow after the position is updated, and determining an optimal fitness value based on the calculated fitness of each sparrow after the position is updated;
and under the condition that the optimal fitness value is smaller than a preset threshold value or the current iteration number is equal to the maximum iteration number, determining the final position coordinate of the mobile terminal based on the sparrow population generated in the current iteration process.
2. The co-location method for TDOA signal resolution as recited in claim 1, wherein said fitness function is:
Figure FDA0003506673560000011
wherein f is1＝l2-l1-r2,1，y2＝l3-l1-r3,1，f3＝l4-l1-r4,1；lkDistance from a sparrow to a receiving base station k, k being 1,2,3, 4; r isk,1Is the distance difference between the mobile terminal and the receiving base station k and the receiving base station 1.
3. The co-location method for TDOA signal resolution of claim 1, wherein the location update formula of the seeker is:
Figure FDA0003506673560000012
wherein the content of the first and second substances,
Figure FDA0003506673560000013
the j-th dimension position of a sparrow i at the T-th iteration is represented by T, 1,2,3, …, T, j is represented by 1,2,3, …, D; beta is a random number, and beta is an element of (0,1)](ii) a T is the maximum iteration number; r0Is a sparrow's early warning value, and R0∈[0，1](ii) a ST is the safety threshold of the population, and ST belongs to [0.5,1 ]](ii) a Q is a random number which follows normal distribution; l represents a 1 × d matrix, and each element in the matrix is 1; k is 1 or-1; i represents the ith sparrow.
4. The co-location method for resolving TDOA signals of claim 1, wherein said method further comprises determining a location of said location based on said signal
Figure FDA0003506673560000021
Then, the location update formula of the follower is:
Figure FDA0003506673560000022
wherein the content of the first and second substances,
Figure FDA0003506673560000023
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; xcIs a fixed value and is an analytic value of the CHAN algorithm; q is a random number which follows normal distribution;
Figure FDA00035066735600000213
the global worst position of the sparrow population during the t iteration; i represents the ith sparrow; n is the total number of sparrows in the population.
5. The co-location method for resolving TDOA signals of claim 4, wherein said method further comprises determining a location of said location based on said signal
Figure FDA0003506673560000024
Then, the location update formula of the follower is:
Figure FDA0003506673560000025
wherein the content of the first and second substances,
Figure FDA0003506673560000026
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; i represents the ith sparrow; n is the total number of sparrows in the population; gamma is belonged to 0,1](ii) a D represents a dimension;
Figure FDA0003506673560000027
and searching the optimal position for the finder at the t +1 iteration.
6. The co-location method for TDOA signal resolution as recited in claim 1, wherein the location update formula of the pre-warner is:
Figure FDA0003506673560000028
wherein the content of the first and second substances,
Figure FDA0003506673560000029
the position of the j-th dimension of the sparrow i at the T-th iteration is T, 1,2,3, …, and T, j, 1,2,3, …, D; k is a random number, and K ∈ [ -1,1](ii) a Epsilon is a constant, and epsilon is not equal to 0; f. ofiThe fitness of sparrow i; f. ofgGlobal optimal fitness; f. ofwIs the global worst fitness;
Figure FDA00035066735600000210
representing a global optimal position;
Figure FDA00035066735600000211
representing a global worst location; beta is a random number following a normal distribution, a factor used to control sparrow flight.
7. The co-location method for resolving TDOA signals of claim 1, wherein the distance difference between said mobile terminal and each receiving bs is calculated by the formula:
Figure FDA00035066735600000212
wherein, Δ di,1Is the distance difference between the mobile terminal to the receiving base station i and the receiving base station 1; c is the speed of light; tau isi,1Is the time difference between the mobile terminal and the receiving base station i and the receiving base station 1; x and y are position coordinates of the mobile terminal; x is the number ofi、yiTo receive the location coordinates of base station i.
8. The co-location method for resolving TDOA signals of claim 1, wherein the resolving of initial location coordinates of said mobile terminal based on calculated distance differences between said mobile terminal and each receiving base station by CHAN algorithm comprises:
and calculating the initial position coordinates of the mobile terminal by combining a CHAN algorithm and a least square method based on the calculated distance difference between the mobile terminal and each receiving base station.
9. A co-location system for TDOA signal resolution, the system comprising a processor and a memory, wherein the memory has stored therein computer instructions for executing the computer instructions stored in the memory, the system implementing the steps of the method as claimed in any one of claims 1 to 8 when the computer instructions are executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
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