CN106546953B - Object localization method under a kind of indoor water based on artificial bee colony algorithm - Google Patents

Object localization method under a kind of indoor water based on artificial bee colony algorithm Download PDF

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CN106546953B
CN106546953B CN201610951191.9A CN201610951191A CN106546953B CN 106546953 B CN106546953 B CN 106546953B CN 201610951191 A CN201610951191 A CN 201610951191A CN 106546953 B CN106546953 B CN 106546953B
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陈熙源
臧云歌
刘晓
方琳
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Southeast University
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    • 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
    • G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
    • 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]

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Abstract

The invention discloses object localization methods under a kind of indoor water based on artificial bee colony algorithm, the following steps are included: (1) disposes indoor submarine object-locating system, W hydrophone is installed in waters, ultrasonic transducer and hydraulic pressure depth gauge are installed in positioning target；(2) three-dimensional system of coordinate is established by origin of waters center, obtains hydrophone coordinate (xi,yi,zi), positioning the distance between target and W hydrophone si, positioning target depth h, wherein i ∈ (0,1,2 ..., W-1)；(3) constraint condition and objective function of artificial bee colony algorithm are established；(4) Underwater Navigation target is positioned using artificial bee colony algorithm.This method has very high convergence reliability and higher convergence rate, can obtain globally optimal solution quickly.

Description

Object localization method under a kind of indoor water based on artificial bee colony algorithm
Technical field
The invention belongs to target positioning and navigation fields, and in particular to a kind of submarine target localization method.
Background technique
Artificial bee colony algorithm (Artificial Bee Colony Algorithm, abbreviation ABC algorithm) is one by bee colony The algorithm that behavior inspires was proposed in 2005 by Karaboga group for optimization algebra problem.Artificial bee colony algorithm is to imitate Honeybee behavior propose a kind of optimization method, be a concrete application of swarm intelligence thought, it be mainly characterized by do not need The specific information of understanding problem, it is only necessary to the comparison that superiority and inferiority is carried out to problem, by the local optimal searching behavior of each one worker bee individual, It finally protrudes in group global optimum to come, there is faster convergence rate.
It is to employ bee (employed bee, EB), follow bee respectively there are three types of individual in artificial bee colony algorithm (ABC) (onlooker bee, OB) and three kinds of search bee (scouting bee, SB).Bee is employed to be responsible for search of food source；Follow bee negative It blames in dancing area according to the information selection food source for employing bee by transmitting of dancing；Search bee is responsible for finding New food source.It employs Number, that is, food source number of bee employs bee to become search bee if certain food source is employed bee and tracking bee to abandon.Honeybee The process of gathering honey, which is equivalent to, finds best foods source, the i.e. process of optimal solution.
Indoor submarine object-locating system is the range information and depth that target Yu known reference point are obtained using measuring system Information is spent, after data signal sampling and processing, positioning calculation is carried out by special algorithm, it is special at present for submarine target Not static object, what is mostly used is the method for least square, but its positioning accuracy is limited, application weighting least square method and its He resolves classical iterative methods, also little to the promotion effect of positioning accuracy.
Summary of the invention
Goal of the invention: aiming at the problems existing in the prior art, the invention discloses a kind of based on artificial bee colony algorithm Object localization method under indoor water, this method carry out optimizing using artificial bee colony algorithm come the coordinate value to Underwater Navigation target, Locating speed is fast, positioning accuracy is high.
A kind of technical solution: object localization method under the indoor water based on artificial bee colony algorithm, comprising the following steps:
(1) indoor submarine object-locating system is disposed, W hydrophone is installed in waters, installation is super in positioning target Acoustic wave transducer and hydraulic pressure depth gauge；
(2) three-dimensional system of coordinate is established by origin of waters center, obtains hydrophone coordinate (xi,yi,zi), positioning target and W The distance between a hydrophone si, positioning target depth h, wherein i ∈ (0,1,2 ..., W-1)；
(3) constraint condition and objective function of artificial bee colony algorithm are established；
(4) Underwater Navigation target is positioned using artificial bee colony algorithm.
Preferably, W hydrophone fitting depth is consistent as far as possible, does not contact water bottom.
Specifically, in step (3), constraint condition are as follows:
I.e. the waters range of horizontal direction is the rectangle of a × b, and rectangular centre is the origin of horizontal direction；
Objective function are as follows:
(x, y)=arg { min [(S-S0-cn)T(S-S0- cn)] }, (2)
Wherein (x, y) is positioning target coordinate value in the horizontal direction, S=[s0,s1,...,sW-1] it is the positioning measured The distance between target and W hydrophone, It is fixed Actual range between position target and i-th of hydrophone, c is acoustic wave propagation velocity, n=[n0,n1,...,nW-1], niIt is i-th The noise that hydrophone introduces when measuring, i ∈ (0,1,2 ..., W-1).
Step (4) specifically includes the following steps:
(41) algorithm parameter initializes；Generate N number of initial coordinate of positioning target at random within the scope of waters, i.e., it is N number of first Beginning food source, at the same generate it is N number of employ bee, N number of to follow bee, setting maximum cycle is M, and greatest iteration limited number of times is L, Current cycle time m=0, N number of that bee and N number of food source is employed to correspond, the corresponding iteration limit number of each food source It resets；
(42) each employs bee to generate new food source as the following formula to corresponding food source:
Wherein, Xj,YjRespectively indicate j-th of the food source position direction x, y coordinate value for employing bee exploiting, Vj,UjPoint Bee Biao Shi not be employed in (X j-thj,Yj) on the basis of the new food source position direction x, the y coordinate value exploited, k ∈ (0,1 ..., N-1), randomly select, and k ≠ j, RjRandom number between [- 1,1]；
(43) bee is employed to judge whether to update corresponding food source, if new food source fitness is greater than former food source and fits Response then updates corresponding food source；Otherwise, retain former food source；
(44) the select probability P of each food source is calculatedjValue:
(45) bee is followed to select PjIt is worth maximum food source, bee is each followed to generate new food as the following formula to this food source Source:
Wherein, subscript q indicates that selected food source is q-th in N number of food source, Xq,YqRespectively indicate selected food The position of material resource is in x, the direction y coordinate value, V 'j,U'jIt indicates to follow bee in (X j-thq,Yq) on the basis of the new food that generates The direction source position x, y coordinate value, k ∈ (0,1 ..., N-1), randomly selects, and k ≠ q, RjRandom number between [- 1,1]；
(46) bee is followed to judge whether to update corresponding food source, if new food source fitness is greater than former food source and fits Response then updates corresponding food source, and corresponding iteration limit number l is reset；Otherwise, retain former food source, it is corresponding to change Add one for limited number of times l；
(47) search bee scouts each food source corresponding iteration limit number l, such as l=L, that is, reaches greatest iteration limitation Number then abandons corresponding food source, and generates a new food source by following formula to replace:
Wherein,The New food source coordinate of search bee generation being used for instead of i-th of food source is respectively indicated,Respectively indicate the x of i-th of food source position, the desirable minimum value of y-coordinate,It respectively indicates i-th The x of food source position, the desirable maximum value of y-coordinate, minimum value and maximum value will meet according to depending on constraint equation (1) Condition:
(48) current cycle time m adds one, judges whether to reach maximum cycle M, such as reach, end loop；Otherwise, It jumps to step (42) and does next suboptimization；
(49) the maximum food source coordinate of fitness is the optimum coordinates for positioning target in N number of food source.
The fitness of above-mentioned j-th of food source is calculated as follows:
Wherein S=[s0,s1,...,sW-1] it is the distance between the positioning target measured and W hydrophone,For j-th of food source, that is, position the jth of target Actual range between a possible solution and i-th of hydrophone, i ∈ (0,1,2 ..., W-1).
The utility model has the advantages that compared with prior art, submarine target localization method disclosed by the invention is by using improved short Baseline principle combination artificial bee colony algorithm carries out Position-Solving to static object under indoor water, greatly improves target positioning accurate Degree, and it can obtain globally optimal solution with very high convergence reliability and higher convergence rate quickly.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is indoor submarine object-locating system deployment schematic diagram in embodiment；
Fig. 3 is the flow chart that the present invention positions indoor submarine target using artificial bee colony algorithm.
Specific embodiment
With reference to the accompanying drawings and detailed description, the present invention is furture elucidated.
Fig. 1 is the flow chart of object localization method under the indoor water disclosed by the invention based on artificial bee colony algorithm, including Following steps:
Step 1 disposes indoor submarine object-locating system；
As shown in Fig. 2, hardware includes a ultrasonic transducer, three hydrophones, one in the present embodiment Hydraulic pressure depth gauge；Three hydrophones are distributed in positioning waters using waters center as origin in a manner of certain structure the formation, and to the greatest extent may be used It is consistent to be able to maintain three hydrophone placement depth, does not contact water bottom；Ultrasonic transducer and hydraulic pressure depth gauge are mounted on fixed In the target of position, change position with target is mobile.In addition, further including data collecting card to acquire measurement data, an industry control PC machine To carry out calculating positioning to submarine target according to measurement data.
Step 2 establishes three-dimensional system of coordinate, obtains measured value；
If waters longitudinal length a, waters transverse width b, Larger water depths H, using waters center as origin in waters Three-dimensional system of coordinate is established, the coordinate of three hydrophones is respectively (x0,y0,z0)、(x1,y1,z1)、(x2,y2,z2)；Target is positioned, That is ultrasonic transducer, the distance between hydrophone s0,s1,s2It is obtained by subaqueous sound ranging principle, depth information h is by hydraulic pressure Depth gauge measures；Wherein, measured valueIn formula: c is acoustic wave propagation velocity, diIt is time delay estimation measurement Value, niThe noise that introduces when for measurement, it is believed that be independent identically distributed variance be σ2White Gaussian noise,To position target With the actual range between i-th of hydrophone, i ∈ (0,1,2).
Step 3, the constraint condition and objective function for establishing artificial bee colony algorithm；
Target is located in waters, and depth can be measured directly, therefore constraint condition are as follows:
Actual range according to geometry law, between target and hydrophone are as follows:
Note, S=[s0,s1,s2],N=[n0,n1,n2], it can obtain:
Coordinates of targets (x, y) is estimated using universal maximum likelihood method, asking makes the maximum coordinate value of likelihood function, i.e. target Function are as follows:
(x, y)=arg { min [(S-S0-cn)T(S-S0-cn)]}
Corresponding (x, y) coordinate when making Nonlinear function minimum is found out, this coordinate is the coordinate for positioning target.
Step 4 positions Underwater Navigation target using artificial bee colony algorithm, specifically comprises the following steps:
(41) algorithm parameter initializes；Generate N number of initial coordinate of positioning target at random within the scope of waters, i.e., it is N number of first Beginning food source, at the same generate it is N number of employ bee, N number of to follow bee, N number of search bee, setting maximum cycle is M, greatest iteration limit Number processed is L, current cycle time m=0, N number of that bee and N number of food source is employed to correspond, the corresponding iteration of each food source Limited number of times is all reset；
(42) each employs bee to generate new food source as the following formula to corresponding food source:
Vj=Xj+Rj(Xj-Xk)
Uj=Yj+Rj(Yj-Yk)
Wherein, Xj,YjRespectively indicate j-th of the food source position direction x, y coordinate value for employing bee exploiting, Vj,UjPoint Bee Biao Shi not be employed in (X j-thj,Yj) on the basis of the new food source position direction x, the y coordinate value exploited, k ∈ (0,1 ..., N-1), randomly select, and k ≠ j, RjRandom number between [- 1,1]；
(43) bee is employed to judge whether to update corresponding food source, if new food source fitness is greater than former food source and fits Response then updates corresponding food source；Otherwise, retain former food source；The fitness of j-th of food source is calculated as follows:
(44) the select probability P of each food source is calculatedjValue:
(45) bee is followed to select PjIt is worth maximum food source, bee is each followed to generate new food as the following formula to this food source Source:
V′j=Xq+Rj(Xq-Xk)
U'j=Yq+Rj(Yq-Yk)
Wherein, subscript q indicates that selected food source is q-th in N number of food source, Xq,YqRespectively indicate selected food The position of material resource is in x, the direction y coordinate value, V 'j,U'jIt indicates to follow bee in (X j-thq,Yq) on the basis of the new food that generates The direction source position x, y coordinate value, k ∈ (0,1 ..., N-1), randomly selects, and k ≠ q, RjRandom number between [- 1,1]；
(46) bee is followed to judge whether to update corresponding food source, if new food source fitness is greater than former food source and fits Response then updates corresponding food source, and corresponding iteration limit number l is reset；Otherwise, retain former food source, it is corresponding to change Add one for limited number of times l；
(47) search bee scouts each food source corresponding iteration limit number l, such as l=L, that is, reaches greatest iteration limitation Number then abandons corresponding food source, and generates a new food source by following formula to replace:
Wherein,The New food source coordinate of search bee generation being used for instead of i-th of food source is respectively indicated,Respectively indicate the x of i-th of food source position, the desirable minimum value of y-coordinate,Respectively indicate i-th of food The x of material resource position, the desirable maximum value of y-coordinate, minimum value and maximum value will meet item according to depending on constraint equation (1) Part:
(48) current cycle time m adds one, judges whether to reach maximum cycle M, such as reach, end loop；Otherwise, It jumps to step (42) and does next suboptimization；
(49) the maximum food source coordinate of fitness is the optimum coordinates for positioning target in N number of food source.

Claims (3)

1. object localization method under a kind of indoor water based on artificial bee colony algorithm, which comprises the following steps:
(1) indoor submarine object-locating system is disposed, W hydrophone is installed in waters, ultrasonic wave is installed in positioning target Energy converter and hydraulic pressure depth gauge；
(2) three-dimensional system of coordinate is established by origin of waters center, obtains hydrophone coordinate (xi,yi,zi), positioning target and W water Listen the distance between device si, positioning target depth h, wherein i ∈ (0,1,2 ..., W-1)；
(3) constraint condition and objective function of artificial bee colony algorithm are established；
(4) Underwater Navigation target is positioned using artificial bee colony algorithm；
The step (4) specifically includes the following steps:
(41) algorithm parameter initializes；Generate N number of initial coordinate of positioning target, i.e., N number of initial food at random within the scope of waters Material resource, at the same generate it is N number of employ bee, N number of to follow bee, setting maximum cycle is M, and greatest iteration limited number of times is L, currently Cycle-index m=0, N number of that bee and N number of food source is employed to correspond, the corresponding iteration limit number of each food source is reset；
(42) each employs bee to generate new food source as the following formula to corresponding food source:
Vj=Xj+Rj(Xj-Xk)
Uj=Yj+Rj(Yj-Yk)
Wherein, Xj,YjRespectively indicate j-th of the food source position direction x, y coordinate value for employing bee exploiting, Vj,UjTable respectively Showing j-th employs bee in (Xj,Yj) on the basis of the new food source position direction x, the y coordinate value exploited, k ∈ (0,1 ..., N- 1) it, randomly selects, and k ≠ j, RjRandom number between [- 1,1]；
(43) bee is employed to judge whether to update corresponding food source, if new food source fitness is greater than former food source and adapts to Degree, then update corresponding food source；Otherwise, retain former food source；
(44) the select probability P of each food source is calculatedjValue:
(45) bee is followed to select PjIt is worth maximum food source, bee is each followed to generate new food source as the following formula to this food source:
V′j=Xq+Rj(Xq-Xk)
U'j=Yq+Rj(Yq-Yk)
Wherein, subscript q indicates that selected food source is q-th in N number of food source, Xq,YqRespectively indicate selected food source Position in x, the direction y coordinate value, V 'j,U'jIt indicates to follow bee in (X j-thq,Yq) on the basis of the new food source position that generates X, the direction y coordinate value are set, k ∈ (0,1 ..., N-1) is randomly selected, and k ≠ q, RjRandom number between [- 1,1]；
(46) bee is followed to judge whether to update corresponding food source, if new food source fitness is greater than former food source and adapts to Degree then updates corresponding food source, and corresponding iteration limit number l is reset；Otherwise, retain former food source, corresponding iteration Limited number of times l adds one；
(47) search bee scouts each food source corresponding iteration limit number l, such as l=L, that is, reaches greatest iteration limitation time Number, then abandon corresponding food source, and generates a new food source by following formula to replace:
Wherein,The New food source coordinate of search bee generation being used for instead of i-th of food source is respectively indicated,Respectively indicate the x of i-th of food source position, the desirable minimum value of y-coordinate,It respectively indicates i-th The x of food source position, the desirable maximum value of y-coordinate, minimum value and maximum value are according to depending on following formula constraint condition:
Wherein a, b indicate the waters range of horizontal direction, i.e. waters range is the rectangle of a × b, and rectangular centre is horizontal direction Origin；
(48) current cycle time m adds one, judges whether to reach maximum cycle M, such as reach, end loop；Otherwise, it jumps Next suboptimization is done to step (42)；
(49) the maximum food source coordinate of fitness is the optimum coordinates for positioning target in N number of food source；
The fitness of j-th of food source is calculated as follows:
Wherein S=[s0,s1,...,sW-1] it is the distance between the positioning target measured and W hydrophone, For j-th of food source, that is, position j-th of target The actual range between i-th of hydrophone, i ∈ (0,1,2 ..., W-1) may be solved.
2. object localization method under the indoor water according to claim 1 based on artificial bee colony algorithm, which is characterized in that institute It states in step (1), W hydrophone fitting depth is consistent.
3. object localization method under the indoor water according to claim 1 based on artificial bee colony algorithm, which is characterized in that institute It states in step (3), constraint condition are as follows:That is rectangle of the waters range of horizontal direction for a × b, rectangular centre For the origin of horizontal direction；
The objective function are as follows:
(x, y)=arg { min [(S-S0-cn)T(S-S0- cn)] },
Wherein (x, y) is positioning target coordinate value in the horizontal direction, S=[s0,s1,...,sW-1] it is the positioning target measured The distance between W hydrophone, To position mesh Actual range between mark and i-th of hydrophone, c is acoustic wave propagation velocity, n=[n0,n1,...,nW-1], niIt is listened for i-th of water The noise that device introduces when measuring, i ∈ (0,1,2 ..., W-1).
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