CN108168556A - Merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions - Google Patents
Merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions Download PDFInfo
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Abstract
The present invention discloses a kind of driving support frame ultra wide band location method for merging particle group optimizing and Taylor series expansions, according to the ultra wide band station layout of driving support frame, builds its location model；Ultra wide band positioning is converted into a kind of optimization problem, using particle swarm optimization algorithm, global optimizing obtains the positioning point coordinates with minimum position error；And then using the oplimal Location point that particle swarm optimization algorithm obtains as initial value, using Taylor series expansions, local positioning coordinate optimizing is realized by iteration, obtains the optimal value of positioning point coordinates.The positioning method accuracy is high, is easily achieved, and has preferable robustness to the ultra wide band positioning under driving this kind of noise circumstance of supporting, application prospect is notable.
Description
Technical field
The invention belongs to indoor positioning technologies fields under particular surroundings, and in particular to it is a kind of fusion particle group optimizing with
The driving support frame ultra wide band location method of Taylor series expansions.
Background technology
Study the important guarantee that nobody or few peopleization digging equipment are deep danger coal seam safety and high efficiencies.Tunneling process
As the important link of coal mining, the peace of progress of coal mining is directly affected to the stability of surrounding rock supporting and reliability thereafter
Full property and high efficiency.After the driving operation of each depth is completed, there is certain empty top in roadway surrounding rock of meeting head on.To avoid out
Existing surrounding rock separation layer needs to realize the gib to tunnel sky top using hydraulic pressure advance support rack.Meanwhile advance support rack
Absolute position in tunnel can have a direct impact the determining of anchor pole position in follow-up anchoring operation.Therefore, supporting is tunneled
The positioning of stent is most important.
There is high small, low in energy consumption, multi-path resolved rate, antinoise and strong antijamming capability, positioning in view of ultra wide band
The advantages that accuracy is high, therefore using the location position of ultra wide band realization advance support rack.However, ultra wide band location method
In, the calculation accuracy of positioning equation group is often relatively low.Therefore, this patent provides a kind of fusion particle swarm optimization algorithm and Taylor
The novel driving support frame ultra wide band location method of series expansion.
At present, the localization method for mining equipment in tunneling process is concentrated mainly on development machine location position, to advanced
The Position Research of support frame also lacks very much.(Tong Minming, Du Yuxin, Li Gaojun wait the development machine of multisensors to position to document
System research [J] coal mine machineries, 2013,34 (6):146-148) propose a kind of development machine alignment system based on multisensor.
Document (field original cantilever excavators automatic guide and location technology are explored [J] industrial and minerals and are automated, and 2010,8:26-29) analysis and
It compares based on the development machines automatic guides such as total powerstation, gyroscope, electronic compass, laser alignment telescope and vision-based detection and positioning skill
The principle and feature of art.Document (the heading machine pose inspection that the fragrant of Zhou Lingling, Dong Haibo, Du Yu is identified based on double excitation target image
Survey method [J] laser and optoelectronics are in progress, 2017,54 (4):It 180-186) is identified using double excitation target image, realizes pick
It is detected into seat in the plane appearance.Patent (positioning control system of rising sun coal mine boom-type roadheaders, 201320714937.6 [P] .2013)
Using laser range finder, laser alignment device etc., the positioning of development machine is realized.(field is former, Zhang Jianguang, Yang Wenjie, waits a kind of for patent
Four-point development machine is automatically positioned orientation method, 201611235639.3 [P] .2016) one kind is provided based on machine vision technique
Development machine automatic positioning orientation method.(Wang Kundong, Chen Bing, Sun Qiang wait drivings of the based on three laser labelling point images to patent
Machine alignment system and localization method, 201610614160.4 [P] .2016) utilize wireless camera instrument, wireless base station, computer, three
Angle laser marker etc. realizes the positioning of development machine.Patent (a kind of development machine alignment systems of the brave of stone, 201510592517.9
[P] .2015) spatial relation of the development machine relative to tunnel detected by high-frequency impulse device.Patent (Tong Minming, it is virgin
Purple former, Li Meng waits wireless navigation and positioning system and method for heading machine, 201310047061.9 [P] .2013) utilize radio node
Device realizes the navigator fix of tunneling process.(Tong Minming, Tong Ziyuan, Xu Nan wait development machine laser aiming positioning and directings to patent
Device and method, 201010278942.8 [P] .2010) positioning of development machine is realized using the method for laser aiming.But underground
Environment is complicated, dust concentration is big, is unfavorable for infrared ray, wireless sensor network signal, laser and transmission of visible light.Document (Wu
Vast, Jia Wenhao, Hua Wei wait boom-type roadheader pose self measuring method [J] the coals of based on space Convergent measurement technology
Journal, 2015,40 (11):2596-2602) propose a kind of autonomous pose of boom-type roadheader based on space Convergent measurement technology
Measuring method, but orientation distance is shorter.
Ultra-broadband signal is a kind of wide band non-sine impulse radio signal.By detecting ultra-broadband signal in ranging
Two-way flight time (Time of Fight, abbreviation TOA) between module and base station resolves distance, has very high ranging
Precision can effectively reduce the influence of fully mechanized workface complex environment and working condition to hydraulic support positioning accuracy.
Ultra wide band positioning equation group based on TOA is a kind of noise-containing Nonlinear System of Equations, can be utilized traditional
Analysis method solves.First, ultra wide band positioning is realized using Taylor correlation techniques.Mainly include：Directly-Taylor is compound fixed
A kind of position algorithm (UWB direct-Taylor compound localizations algorithm [J] Guilin electronics industries based on TOA of Jiang Wenmei, Wang Mei
Institute's journal, 2006,26 (1):1-5), (Liu Likun, Xu Yu shore are based on time of arrival (toa) to LSE-Taylor alignment by union algorithm
LSE-Taylor alignment by union algorithm research [C] China ITs with using academic marketplace, 2008,35 (4):261-
262), with reference to the co-located of APIT and Taylor (simulation and analysis [J] electronic sections of the quick ultra wide bands location algorithms of Jiang Min
Skill, 2008,21 (11):56-58), barycenter-Taylor mixed positionings algorithm (the firm of Zhang Ruifeng, Zhang Zhongjuan, Lv Chen be based on barycenter-
UWB indoor positioning algorithms research [J] the Chongqing Mail and Telephones Unvi journal of Taylor, 2011,23 (6):717-721), based on full matter
Mixed positioning algorithm (Wang Lei, Li Pengtao, UWB indoor positioning algorithms of ancestor's uncut jade based on full barycenter-Taylor of going into business of the heart-Taylor
[J] sensors and micro-system, 2017,36 (6):146-149), interior triangular centroid localization algorithm (Wei Pei, Jiang Ping, He Jingjing,
Wait UWB indoor positioning [J] the computer applications of based on interior triangular centroid algorithm, 2017,37 (1):289-293).Base
In positioning calculation method solving precision height, the fast convergence rate of Taylor, but it has initial value very strong dependence.Its
Two, ultra wide band positioning is realized using least square method.A kind of document (TOA underground spaces UWB based on weighting of Luan Fenggang, Wang Ping
Indoor positioning algorithms [J] industrial control computers, 2014,27 (1):It 73-75) proposes a kind of suitable for ring in underground space room
The ultra wide band location algorithm in border.Document (Shaowei Yang, Bo Wang.Residual Based Weighted Least
Square Algorithm for Bluetooth/UWB Indoor Localization System[C].Proceedings
of the 36th Chinese Control Conference,2017:5959-5963) using weighted least-squares method come real
Now position.Document (Feng G, Shen C, Long C, et al.GDOP index in UWB indoor location
system experiment[J].Sensors.2015:1-4.) the ultra wide band location method based on least square method, analyzes
Influence of the geometric dilution of precision to position error.Although such method is simple, inverse matrix is needed to calculate, positioning accuracy has
Limit.In addition to above-mentioned two major class localization method, document (Jie D, Cui X R, Zhang H, et al.A Ultra-Wideband
Location Algorithm Based on Neural Network[C].IEEE International Conference
on Wireless Communications Networking and Mobile Computing.2010:It 1-4) is utilized anti-
It is positioned to neural network algorithm.Document (calculate by a kind of UWB indoor positioning based on Kalman filtering of Yan Baofang, Mao Qingzhou
Method [J] sensors and micro-system, 2017,36 (10):137-143) propose that a kind of UWB indoor based on Kalman filtering is determined
Position algorithm, for there are the data of large error, locating effect is unsatisfactory.Has calculation method in view of positioning equation group
Deficiency, ultra wide band orientation problem is converted into a kind of optimization problem, utilizes the Parallel implementation of particle swarm optimization algorithm by this patent
Ability, global optimizing obtains the anchor point with minimum position error, as the initial value of Taylor series expansions, then by repeatedly
In generation, obtains oplimal Location coordinate.This method is missed by improving the initial value positioning accuracy of Taylor localization methods to reduce positioning
Difference.
Invention content
Goal of the invention：In coal mine roadway tunneling process, the positioning of advance support rack relies primarily on operating personnel at present, fixed
Position precision is low and unstable, and leading to subsequent Anchor Care operation, there are larger installation errors, influence the monolithic stability of roadway surrounding rock
Property and safety.Therefore, in order to overcome the deficiencies in the prior art, the present invention provide a kind of fusion particle group optimizing with
The driving support frame ultra wide band location method of Taylor series expansions, this is a kind of support frame autonomous positioning of efficiently and accurately
Method carries out location position to driving support frame using ultra wide band, merges particle swarm optimization algorithm and Taylor series expansions
The resolving of positioning equation group is realized, to obtain the location information with degree of precision.
Technical solution：To achieve the above object, the technical solution adopted by the present invention is：
This patent merges particle group optimizing and Taylor series expansions realize the ultra wide band positioning of driving support frame.According to
The operation principle of support frame is tunneled in digging laneway, builds ultra wide band location model；And then ultra wide band orientation problem is converted
For a kind of optimization problem, the anchor point of position error minimum is made using particle swarm optimization algorithm, as Taylor series exhibitions
By iterative solution, anchor point optimum coordinates are finally obtained in the initial value opened.
The specific implementation step of above-mentioned localization method is as follows：
1. establish ultra wide band location model
It is positioned using super-broadband tech to tunneling support frame in coal mine roadway, base station and range finder module layout are as schemed
Shown in 1.Ultra-broadband ranging module is mounted on driving support frame anchor point, and K base station is laid in tunnel rear, and each base
It stands and is demarcated before tunnelling accurately by ground survey personnel relative to the coordinate of roadway reference.K base station is successively to tunneling supporting branch
Frame anchor point carries out ultra-broadband ranging.According to ranging information, positioning equation group is established, and then calculates driving support frame positioning
Point coordinates resolves the position for obtaining driving support frame in tunnel.
Assuming that i-th, i=1,2 ..., the position coordinates of K base station are (xBi,yBi,zBi), driving support frame anchor point position
Coordinate is put as (xs,ys,zs), the measurement distance of i-th of base station and driving support frame anchor point is di, then all base stations and pick
It is into the TOA observational equation groups between support frame anchor point：
2. merge the driving support frame ultra wide band location method of Taylor and particle swarm optimization algorithm
Positioning calculation method based on Taylor has very strong dependency to initial value, therefore, using Particle Swarm Optimization
Initial value of the relatively figure of merit that method obtains as its interative computation, so as to improve its positioning accuracy.
2.1 particle swarm optimization algorithm
Assuming that positioning point coordinates meets xs∈[xsmin,xsmax], ys∈[ysmin,ysmax], zs∈[zsmin,zsmax].It is above-mentioned fixed
The extreme value in site depends on the bulk of coal mine digging laneway.Ultra wide band orientation problem is converted into following optimization problem：
In particle swarm optimization algorithm, using the error function of above-mentioned anchor point to each base station as ultra wide band positioning side
The object function that journey group resolves, anchor point (xs,ys,zs) as particle, realize that ultra wide band positioning is initial using above-mentioned WPSO algorithms
Value resolves.Idiographic flow is as follows：
Step1：Position and speed to particle carry out random initializtion, set algorithm key parameter；
Step2：The speed of more new particle and position；
Step3：Evaluate the adaptive value of each particle；
Step4：To each particle, according to current particle adaptive value, its history optimal value p is updatedi(t)；
Step5：To entire population, according to the current optimal value of population, update global optimum pg(t)；
Step6：If reaching maximum iteration, optimum results are exported；Otherwise, Step2 is gone to.
2.2 Taylor series expansions
There is the anchor point of minimum position error as Taylor series expansions using what above-mentioned particle swarm optimization algorithm obtained
Initial coordinate (xs0,ys0,zs0), Taylor series expansions are carried out, and ignore second order more than component to positioning equation group, are obtained
Position error (Δ x, Δ y, Δ z).According to position error, positioning point coordinates is corrected；Iteration, until meeting | Δ x |+| Δ y
|+| Δ z |≤ε, ε are preset error threshold.The oplimal Location point coordinates finally obtained is
Advantageous effect：This patent merges particle group optimizing and Taylor series expansions, proposes a kind of novel driving supporting branch
The ultra wide band location method of frame.First, the ultra wide band location model of driving support frame is established；Secondly, using particle group optimizing
Algorithm obtains the initial alignment coordinate of Taylor series expansions, by iteration, realizes the resolving of ultra wide band positioning equation group, obtains
Oplimal Location point coordinates；Finally, under noise ranging environment, five kinds of existing algorithms is compared and put forward the average positioning mistake of algorithm
Difference.From positioning result：The WPSO-Taylor algorithms that this patent proposes have significant advantage, and positioning accuracy highest can be more preferable
Requirement of the satisfaction driving support frame to positioning accuracy.
Description of the drawings
Fig. 1 coal mine roadways driving support frame alignment system composition；In figure, 1,2,3,4-locating base station；P-driving branch
Protect stent anchor point；
Fig. 2 merges the algorithm stream of particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions
Journey；
Average localization error of the different rangings apart from lower six kinds of localization methods in Fig. 3 noise circumstances；
Different rangings are schemed apart from lower six kinds of localization method position errors boxplot in Fig. 4 noise circumstances；In figure, each
Under ranging distance, six kinds of comparison algorithms from left to right, are followed successively by LS algorithms, direct method, WPSO algorithms, LS-Taylor algorithms, straight
Connect-Taylor algorithms, WPSO-Taylor algorithms.
Specific embodiment
The present invention discloses a kind of driving support frame ultra wide band positioning for merging particle group optimizing and Taylor series expansions
Method.According to the ultra wide band station layout of driving support frame, its location model is built；Ultra wide band positioning is converted into a kind of excellent
Change problem, using particle swarm optimization algorithm, global optimizing obtains the positioning point coordinates with minimum position error；It is excellent with population
Change the oplimal Location point of algorithm acquisition as initial value, using Taylor series expansions, pass through iteration and realize local positioning coordinate
Optimizing obtains anchor point optimum coordinates.The positioning method accuracy is high, is easily achieved, under driving this kind of noise circumstance of supporting
Ultra wide band positioning has preferable robustness, and application prospect is notable.
The present invention is further described with reference to the accompanying drawings and examples.
Embodiment
The present embodiment merges particle group optimizing and Taylor series expansions realize the ultra wide band positioning of driving support frame.Root
According to the ultra wide band base station and range finder module laid in coal mine digging laneway, the work according to driving support frame in digging laneway is former
Reason, establishes ultra wide band location model, and then obtain positioning equation group；Ultra wide band orientation problem is converted into optimization problem, is merged
Particle swarm optimization algorithm and Taylor series expansion methods resolve positioning equation group, seek the anchor point for making position error minimum,
Namely make the anchor point of position error minimum using particle swarm optimization algorithm, as the initial value of Taylor series expansions,
By iterative solution, anchor point optimum coordinates are finally obtained.
The specific implementation process is as follows：
1. establish ultra wide band location model
It is positioned using super-broadband tech to tunneling support frame in coal mine roadway, base station and range finder module layout are as schemed
Shown in 1.Ultra-broadband ranging module is mounted on driving support frame anchor point, and K base station is laid in tunnel rear, and each base
It stands and is demarcated before tunnelling accurately by ground survey personnel relative to the coordinate of roadway reference.K base station is successively to tunneling supporting branch
Frame anchor point carries out ultra-broadband ranging.According to ranging information, positioning equation group is established, and then calculates driving support frame positioning
Point coordinates resolves the position for obtaining driving support frame in tunnel.
Assuming that i-th, i=1,2 ..., the position coordinates of K base station are (xBi,yBi,zBi), driving support frame anchor point position
Coordinate is put as (xs,ys,zs), the measurement distance of i-th of base station and driving support frame anchor point is di, then all base stations and pick
It is into the TOA observational equation groups between support frame anchor point：
The purpose for resolving above-mentioned positioning equation is to obtain and most accurately tunnel support frame position, be denoted as
2. merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions
Very strong dependency is had to initial value based on the positioning calculation method of Taylor series expansions, therefore, using particle
Initial value of the relatively figure of merit that colony optimization algorithm obtains as its interative computation, so as to improve its positioning accuracy.
2.1 particle swarm optimization algorithm
Particle swarm optimization algorithm is a kind of swarm intelligence optimization side proposed by Eberhart and Kennedy in nineteen ninety-five
Method has many advantages, such as to realize simple, fast convergence rate, and it is all to be widely used in function optimization, artificial neural network training etc.
It is multi-field.Particle swarm optimization algorithm is applied to solve the problems, such as positioning calculation by this patent.
Particle swarm optimization algorithm is derived from the research to flock of birds predation, and basic thought is：One is formed by multiple particles
A group finds the optimal solution of problem by the cooperation between particle in group and information sharing.In algorithm, each particle pair
It should may be solved in one of optimization problem, heading and distance are described by speed and position.The performance of particle is good and bad
Object function depending on problem to be optimized.
Postulated particle group includes n particle.The position of i-th of particle in t generations and flying speed are denoted as x respectivelyi(t)
And vi(t), history optimal location is denoted as pi(t), the global optimum of particle is denoted as pg(t), then particle is flown according to following formula
Scanning frequency degree and the update of position：
xi(t+1)=vi(t+1)+xi(t) (2)
vi(t+1)=w (t) vi(t)+c1r1(pi(t)-xi(t))+c2r2(pg(t)-xi(t)) (3)
In formula, c1And c2For Studying factors, r1And r2Meet equally distributed random number between [0,1].W is weighed for inertia
Weight, for coordinating global search and local exploring ability.In adaptive weighting particle swarm optimization algorithm (Weight-particle
Swarm optimization, WPSO) in, w adaptive updates：
In formula, wmaxAnd wminThe respectively maximum and minimum value of inertia weight, t be current number, tmaxIt is greatest iteration time
Number.By particle position and the speed of iterating, until meeting algorithm end condition, optimizing result is exported.
Assuming that positioning point coordinates is (xs,ys,zs), meet xs∈[xsmin,xsmax], ys∈[ysmin,ysmax], zs∈[zsmin,
zsmax].The extreme value of above-mentioned anchor point depends on the bulk of coal mine digging laneway.Remember measurement of the ultra wide band base station to anchor point
Distance is di, then ultra wide band orientation problem be converted into following optimization problem：
In particle swarm optimization algorithm, positioned using the error function of above-mentioned anchor point to each base station as ultra wide band
Object function, anchor point (xs,ys,zs) as particle, using above-mentioned WPSO algorithms, solve ultra wide band anchor point.Idiographic flow is such as
Under：
Step1：Position and speed to particle carry out random initializtion, set algorithm key parameter；
Step2：The speed of more new particle and position；
Step3：Evaluate the adaptive value of each particle；
Step4：To each particle, according to current particle adaptive value, its history optimal value p is updatedi(t)；
Step5：To entire population, according to the current optimal value of population, update global optimum pg(t)；
Step6：If reaching maximum iteration, optimum results are exported；Otherwise, Step2 is gone to.
2.2 Taylor localization methods
Taylor localization methods are a kind of recursive algorithms, it is based on positioning initial value, by iterating, obtain positioning section
The true coordinate of point.Assuming that the true coordinate of anchor point is (xsa,ysa,zsa), initial value is (xs0,ys0,zs0), true anchor point
Coordinate meets following relationship with positioning point coordinates after resolving：
Based on initial coordinate (xs0,ys0,zs0), Taylor series expansions are carried out, and ignore more than second order to positioning equation group
Component, obtaining position error, (Δ x, Δ y, Δ z) are：
Wherein：
According to position error, correct and resolve positioning point coordinates, iteration, until meeting | Δ x |+| Δ y |+| Δ z |≤
ε, ε are preset error threshold.The oplimal Location point coordinates finally obtained is
Obviously, in above-mentioned Taylor localization methods, the final elements of a fix of acquisition are very sensitive to the setting of initial coordinate.
To effectively improve positioning accuracy, this patent provides a kind of fusion particle group optimizing and Taylor series expansions (WPSO-Taylor)
Novel localization method.First, ultra wide band positioning equation group resolving problem is converted into a kind of optimization problem, it is excellent using population
Change algorithm, an oplimal Location point coordinates is obtained by optimizing；Then, as the initial coordinate of Taylor localization methods,
Obtain final positioning point coordinates.As it can be seen that the overall situation that the novel localization method takes full advantage of particle swarm optimization algorithm is searched parallel
The fast local search ability of Suo Nengli and Taylor series expansions, so as to effectively increase positioning accuracy.Merge population
The algorithm flow of the driving support frame localization method of optimization and Taylor series expansions, as shown in Figure 2.
3. experimental analysis and result explanation
The reasonability and validity of the ultra wide band location method proposed fully to verify this patent, for digging laneway reality
Border running environment and there are verified under conditions of range error for positioning equation group.
3.1 test environments and parameter setting
Assuming that the wide 4.2m of rectangular shaped roadways, high 3.9m, long 100m, position advance support rack using 4 base stations, and
The coordinate of 4 base stations is respectively (0,0,0), (1.9,1.9,0), (- 1.9,1.9,0), (0,0,3.8).Every 10m, 4 base stations
Ultra-broadband ranging is carried out to driving support frame anchor point successively, and assumes that range error obedience mean value is 0, standard deviation is
The normal distribution of 2cm.Under above-mentioned localizing environment, 1000 rangings are carried out, its mean value is taken to be simulated as range estimation
It calculates.
Since driving support frame is located in long and narrow coal mine roadway, so the search range of particle depends on heading sizes,
That is xs∈ [- 2,2], ys∈ [10,100], zs∈[0,4].It is 40 to choose population scale, and maximum iteration was 300 generations, grain
Sub- maximum speed vmax=0.4, Studying factors c1=c2Error threshold in=2, Taylor series expansion is set as ε=0.5.
Assuming that the resolving positioning point coordinates obtained after kth time operation isTrue positioning point coordinates is (xsa,
ysa,zsa), L is number of run, then defines average localization error and be:
Known locations point is (xsa,ysa,zsa)=(0, m, 3.5), m=10,20 ..., 100.For each m, meet following
Positioning equation group：
The calculation result analysis of 3.2 different localization methods
In true digging laneway, using ultra-broadband ranging can there are certain noises.Under this kind of noise circumstance, respectively
It is calculated with direct method, LS algorithms, WPSO algorithms, directly LS-Taylor algorithms ,-Taylor algorithms and the WPSO-Taylor of proposition
Method realizes the resolving of driving support frame ultra wide band positioning equation group.Under different ranging distance conditions, 500 independent operatings
Position error afterwards, as shown in table 2；Corresponding average localization error and its boxplot figures, as shown in Figure 3 and Figure 4.
Average localization error (/m) result of the lower six kinds of calculation methods of 2 noise circumstance of table
The average localization error for comparing six kinds of algorithms is understood：With the increase of measurement distance, the average positioning of six kinds of algorithms
Error all linearly increases.In comparison, the whole positioning accuracy of LS algorithms and direct algorithm is relatively low.Although WPSO algorithms are better than
LS algorithms and direct method, but with the positioning accuracy poorer than LS-Taylor algorithm and direct-Taylor algorithms.Obviously, it is based on
Three kinds of localization methods of Taylor series expansions have relatively good performance.Wherein, the WPSO-Taylor that this patent is proposed
Algorithm has positioning accuracy more higher than LS-Taylor algorithm and direct-Taylor algorithms.
The above is only the preferred embodiment of the present invention, it should be pointed out that：For the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (8)
1. a kind of merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions, feature exists
In：Using the Parallel implementation ability of particle swarm optimization algorithm, global optimizing obtains the anchor point with minimum position error, as
The initial value of Taylor series expansions, then by iteration, obtain oplimal Location coordinate；
By improving the initial value positioning accuracy of Taylor localization methods, to reduce position error, specific algorithm step is as follows：
Step1：Build ultra wide band location model；
Step2：Position and speed to particle carry out random initializtion, set algorithm key parameter；
Step3：The speed of more new particle and position；
Step4：Evaluate the adaptive value of each particle；
Step5：To each particle, according to current particle adaptive value, its history optimal value p is updatedi(t)；
Step6：To entire population, according to the current optimal value of population, update global optimum pg(t)；
Step7：Judge whether to reach maximum iteration, the elements of a fix are then set as Taylor method initial values by satisfaction；It is no
Then, Step3 is gone to；
Step8：Taylor series expansions are carried out at initial value, and ignore second order more than component；
Step9：Calculation of position errors；
Step10：According to position error, positioning point coordinates is corrected；
Step11：Judge whether to meet error threshold values requirement, satisfaction then exports the final elements of a fix；Otherwise, Step9 is gone to.
2. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The specific method of the Step1 is：According to the ultra wide band layout type of driving support frame, structure is super
Broadband location model, it is assumed that i-th, i=1,2 ..., the position coordinates of K base station are (xBi,yBi,zBi), driving support frame is determined
Site location coordinate is (xs,ys,zs), the measurement distance of i-th of base station and driving support frame anchor point is di, then all bases
The TOA observational equation groups stood and tunnel between support frame anchor point are：
3. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The specific method of the Step3 is：I-th of particle in the position in t generations and flies in postulated particle group
Scanning frequency degree is xi(t), i=1,2 ..., n and vi(t), history optimal location is pi(t), population global optimum is pg
(t), then particle update flying speed and position are as follows：
xi(t+1)=vi(t+1)+xi(t) (2)
vi(t+1)=w (t) vi(t)+c1r1(pi(t)-xi(t))+c2r2(pg(t)-xi(t)) (3)
In formula, c1And c2For Studying factors, r1And r2Meet equally distributed random number between [0,1], w is used to for adaptive updates
Property weight, is denoted as：
In formula, wmaxAnd wminThe respectively maximum and minimum value of inertia weight, t be current number, tmaxIt is maximum iteration.
4. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The specific method of the Step4 is：Assuming that i-th, i=1,2 ..., the position coordinates of K base station are
(xBi,yBi,zBi), positioning point coordinates is (xs,ys,zs), i-th of base station is with the measurement distance for tunneling support frame anchor point
di, then ultra wide band orientation problem be converted into following optimization problem, for evaluating particle adaptive value：
5. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The specific method of the Step5 is：To each particle xi(t), by its current adaptive value f (xi(t)) with
Its history optimal value f (pi(t)) it is compared, if current particle adaptive value is better than its history adaptive optimal control value, particle is worked as
Preceding state retains as history optimal value；Conversely, retain original history optimal value：
6. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The specific method of the Step6 is：Compare each pi(t) with global optimum pg(t) adaptive value,
If pi(t) better than global optimum, then global optimum is updated to pi(t)；Conversely, then retain original global optimum.
7. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The Step8,9 specific method are：By what particle swarm optimization algorithm obtained there is minimum positioning to miss
Initial coordinate (x of the anchor point of difference as Taylor series expansionss0,ys0,zs0), based on initial coordinate (xs0,ys0,zs0), it is right
Positioning equation group carries out Taylor series expansions, and ignores second order more than component, and obtaining position error, (Δ x, Δ y, Δ z) are：
Wherein, i-th, i=1,2 ..., the position coordinates of K base station are (xBi,yBi,zBi), i-th of base station and driving support frame
The measurement distance of anchor point is di。
8. fusion particle group optimizing and the driving support frame ultra wide band of Taylor series expansions position as described in claim 1
Method, it is characterised in that：The specific method of the Step11 is：Judge whether position error meets
|Δx|+|Δy|+|Δz|≤ε
Wherein, ε is preset error threshold.Meet decision condition, then exporting oplimal Location point coordinates is
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| CN114245301A (en) * | 2021-12-20 | 2022-03-25 | 杭州电子科技大学 | UWB (ultra wide band) underground target positioning method based on redundant distance |
| CN114245301B (en) * | 2021-12-20 | 2024-02-09 | 杭州电子科技大学 | UWB underground target positioning method based on redundant distance |
| CN116801380A (en) * | 2023-03-23 | 2023-09-22 | 昆明理工大学 | UWB indoor positioning method based on improved full centroid-Taylor |
| CN116801380B (en) * | 2023-03-23 | 2024-05-28 | 昆明理工大学 | UWB indoor positioning method based on improved full centroid-Taylor |
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