CN108872978A - A kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data - Google Patents
A kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data Download PDFInfo
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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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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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
- G01C21/203—Specially adapted for sailing ships
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention proposes a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data, being able to solve the ocean current field how to be detected using high-frequency ground wave radar is the topic that fuel driving path is most saved in marine water surface ship Dynamic Programming.A kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data of the invention, ship with fixed frequency report current location and final position to place sea area high-frequency ground wave radar central station after setting sail；After radar center station receives vessel position and final position, in conjunction with real-time ocean current data, path planning is carried out according to genetic algorithm, finds out optimal path, and optimal path is sent to ship.
Description
Technical field
The invention belongs to the data application fields of high-frequency ground wave radar detectable signal, and in particular to one kind is based on high-frequency ground wave
The waterborne vessel paths planning method of radar ocean current data.
Background technique
The advantages that high-frequency ground wave radar is a kind of emerging ocean remote sensing equipment, has large area, round-the-clock, inexpensive.
The detection of short time can be finally inversed by tens of thousands of square kilometres of ocean surface flow field, unrestrained field and wind field information.Maximum probe away from
From can achieve 400 kilometers or even farther.Currently, high-frequency ground wave radar at home and abroad has reached business operation level,
The detection of wind, wave, ocean current obtains important breakthrough, but how to carry out secondary use to the large-scale stormy waves stream information of detection, into
One step is scientific research, production and living, and military meteorology service still has huge excavations exploration space.
Ship's navigation across the sea, due to being influenced by ocean current, will receive ocean current resistance or motive force during advancing
Influence (special, when ship target is smaller, speed is smaller, and feeling the current is bigger, typical such as small-scale fishing vessel).For maximum limit
The resistance (adverse current) of the reduction ocean current of degree and the power (fair current) using ocean current of maximum possible, save fuel, can be according to boat
The ocean current characteristic in row section provides a reasonable optimal path.System for high-frequency earth wave radar can detect in real time and inverting
Ocean current data in radar signal coverage area out, under the conditions of normal meteorological, ship is during navigation mainly by ocean current and itself
Power overlaying influence.Using ocean current and ship self power as impact factor, using genetic algorithm, plan that energy consumption is the smallest
Globally optimal solution can be achieved on the active path planning of sea ship.Currently, utilizing system for high-frequency earth wave radar not yet
Inverting ocean current data carry out the technology of real-time active path planning to sea ship.
Summary of the invention
In view of the deficienciess of the prior art, the invention proposes a kind of based on the waterborne of high-frequency ground wave radar ocean current data
Ship paths planning method, how be able to solve is marine water surface ship dynamic using the ocean current field that high-frequency ground wave radar is detected
The problem of fuel driving path, is most saved in planning.
In order to solve the above technical problems, the present invention adopts the following technical scheme that：
A kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data, ship set sail after with fixed frequency
Rate reports current location and final position to place sea area high-frequency ground wave radar central station；Radar center station receive vessel position and
Behind final position, in conjunction with real-time ocean current data, path planning is carried out according to genetic algorithm, finds out optimal path, and will be optimal
Path is sent to ship.
Further, path planning is carried out according to genetic algorithm, finds out optimal path, specifically includes following steps：
Step 1: determining path code scheme：If each time when reporting position, the straight line of ship current location to terminal away from
From S, using distance d as unit equal part, d is the integer greater than zero, and S is divided into ROUNDUP (S/d) section, and section sum is defined as m,
It will be set as positive direction of the x-axis from the direction of origin-to-destination, will be perpendicular to the direction x, and y-axis is set as by the direction of starting point, y-axis is just
Direction is that x-axis is rotated by 90 ° signified direction counterclockwise, one from the path of origin-to-destination be by a series of key event structures
At from the off, it is a complete path that each key event straight line, which is connected,；
Step 2: initialization of population：According to the path code scheme of step 1, n paths are randomly generated, as at the beginning of algorithm
Beginning population；
Step 3: determining fitness function：For each paths, the energy of line disappears between calculating every two key node
Consumption value is defined as Ei, then 1≤i≤m adds up, and the energy consumption in as one whole path of ship traveling, is defined as
Wk,1≤k≤n；The fitness function of energy consumption is expressed as：
Wherein, CiSpeed, l are closed for the speed that ship externally shows between two key nodesiConnect for two key nodes
The length of line,Vcur_iFor the speed of ocean current on i-th of key event
Degree, β Vcur_iDirection with i-th section of key node line angle；Vi+1Indicate ship in i+1 key node still water speed,
K is a constant greater than zero, 0≤t≤(li/Ci)；
Step 4: population is arranged from small to large according to fitness function, the preceding n*R for selecting fitness bestcsPaths,
Remaining n* (1-Rcs) the poor path of fitness be eliminated, and by the best n* (1-R of fitnesscs) paths progress
Duplication is to replace by that superseded n* (1-Rcs) path, wherein RcsFor select probability；
Step 5: population is arranged from small to large according to fitness function, according to crossover probability RexBy preceding n*RexPaths
It is used as cross object two-by-two；
Step 6: population is arranged from small to large according to fitness function, according to mutation probability Rva, by n*RvaIt does in path
Mutation operation；
Step 7: repeating step 4 to six, after going to preset times X, stops circulation, selected from current population
The smallest path of fitness out, as optimal path.
Further, after central station calculates optimal path according to genetic algorithm, three continuous keys are sent to ship
Node, as planning path.
Further, the linear distance when ship current location apart from terminal arrives terminal less than or equal to ship current location
It when straight line etc. divides cell distance, is then no longer planned, directly sends final position to ship.
Further, after ship sends current location and final position to radar center station, radar center station path planning
Calculating needs certain time, cannot send guidance path to ship immediately.At this point, agreement ship is according to last planning path
Continue to travel, until receiving optimal path；If without planning path, or having arrived at the last one node in the path, then
Directly towards destination straight-line travelling.
Further, the key node is：Vertical line is done on each the unit Along ent for not including beginning and end,
It is randomly selected on vertical line a little as key node.
Further, the line of previous key node and the latter key node is less than with the angle of positive direction of the x-axis
α, wherein α>0, the line of penultimate key node to terminal is without meeting above-mentioned constraint.
Further, α value is 60 °.
Further, all Along ents in origin-to-destination rectilinear direction are attached, as a default path
It is put into algorithm initial population.
Further, the interpolation of ocean current speed on key node is completed using closest interpolation method.
Further, one ocean current data of radar center station inverting in every ten minutes, the nearest ocean current that will be finally inversed by
Data are as real-time ocean current data.
Further, when being arranged from small to large according to fitness function preferentially by fitness it is small and it is unduplicated be discharged to before
Face.
Compared with prior art, the present invention has the following advantages that：
1, system for high-frequency earth wave radar is applied into marine vessel active path planning for the first time, expands ground wave radar system
Application field.
2, it is put forward for the first time and genetic algorithm is applied into marine vessel active path planning, and provide detailed fitness letter for the first time
Number calculating method.
3, the path planning based on energy consumption is carried out to marine vessel with ocean current data, to marine Small Civil ship
Fuel spending is saved to be of great significance.
Detailed description of the invention
Attached drawing 1 is the flow chart of trajectory planning；
Attached drawing 2 is the geometrical relationship figure of ship speed under ocean currents；
Attached drawing 3, attached drawing 4, attached drawing 5, when attached drawing 6 is respectively that genetic algorithm calculates optimal path, the best road of different phase
Diameter schematic diagram.
Specific embodiment
With reference to the accompanying drawing, technical solution of the present invention is further elaborated with.
A kind of dynamic is carried out to water surface ship using high-frequency ground wave radar inverting flow field data as shown in Figure 1, of the invention
Paths planning method, (radar-marine communication involved in this embodiment and geo-location service are all made of domestic Beidou system
System), step includes：
Step 1：After ship sets sail, present bit is reported to place sea area high-frequency ground wave radar central station with fixed frequency
It sets and final position.
Step 2：After radar center station receives vessel position and final position, in conjunction with real-time ocean current data, road is carried out
Diameter planning.Radar center station can be finally inversed by an ocean current data for every ten minutes, it is contemplated that the continuity of ocean current in time, it is real
Using the time being finally inversed by a upper nearest ocean current data as real-time ocean current in the operation of border.The object of planning is from present bit
Set energy consumed by terminal (fuel oil) at least, planning principle is to seek globally optimal solution using genetic algorithm.
Step 3, genetic algorithm physical planning method：
1, path code scheme：Assuming that each time reporting position when, the linear distance S of ship current location to terminal, with
Distance d is equal sub-units (d is the integer greater than zero), S is divided into ROUNDUP (S/d) section, section sum is defined as m (agreement
ROUNDUP is to round up).It will be set as positive direction of the x-axis from the direction of origin-to-destination, will be perpendicular to the direction x, and pass through starting point
Direction be set as y-axis, positive direction of the y-axis is that x-axis is rotated by 90 ° signified direction counterclockwise.One is from the path of origin-to-destination
It is made of a series of key events, from the off, it is a complete path that each key event straight line, which is connected,.I
Projection of the regulation path in x-axis be strictly increasing, that is, not detour, this meets the daily reality of navigating of most of us
Border situation.
The selection rule of key event is：Vertical line is done on each the unit Along ent for not including beginning and end (to rise
Point and terminal are defaulted as key node), it is randomly selected on vertical line a little as key node.More to meet reality, Yi Jiwei
Guarantee genetic algorithm can obtain better convergence, provide the line of previous key node and the latter key node here
It is less than α (60 degree are taken α) with the angle of positive direction of the x-axis.Pay attention to α>0, and penultimate key event is to the company of terminal
Line is without meeting above-mentioned constraint.
2, initialization of population：The basic thought of genetic algorithm is to be intersected from the population of initialization by selection, and variation etc. is lost
Operator operation is passed, is to consider with fitness function, repeatedly survival of the fittest iteration is carried out, finally using the optimal solution in population as complete
Office's optimal solution.Initialization population is that n paths are randomly generated according to path code scheme.In view of starting point arrives in most cases
The straight line of terminal is exactly optimal solution, all Along ents in origin-to-destination rectilinear direction can be attached (such case
Lower Along ent is key node), it is put into population as a default path, algorithm can be allowed to restrain faster in this way.
3, the determination of fitness function：The target of this method path planning is that the energy sought from current location to terminal disappears
Minimum value is consumed, so needing to assess paths each in population, the smaller i.e. energy consumption of fitness function value is smaller.Needle
To each paths, the energy consumption values of line between every two key node are calculated, are defined as Ei, 1≤i≤m.Then into
Row is cumulative, and the energy consumption in as one whole path of ship traveling, is defined as Wk,1≤k≤n.It is expressed as：
Assuming that speed that ship between two key nodes, externally shows (closing speed) be all it is constant, be defined as Ci, two
The length of a key node line is li, then a length of l when ship is consumed between two key nodesi/Ci.It is quiet to define ship
Water speed is Vship, definition ocean current speed is Vcurrent, then on any two key node line any point conjunction speed Ci
By VshipAnd VcurrentIt is formed by stacking according to Vector triangle.(referring to attached drawing 2) considers the distance of any two key node simultaneously
It does not grow, function of the ship still water speed to the time can be defined as to a linear function, be expressed as：
Vship=(Vi+1-Vi)*Ci/li*t+Vi
(ViIndicate ship in i-th of key node still water speed, Vi+1Indicate ship in i+1 key node still water speed, 0
≤t≤(li/Ci)。)
It can be obtained according to physical knowledge, ENERGY EiFor the integral of power over time, it is expressed as：
P (t) is the function of power over time, is expressed as：
P (t)=K [(Vi+1-Vi)*Ci/li*t+Vi]2(K is a constant greater than zero)
Further, the fitness function of energy consumption can be expressed as：
Among these, according to the compositive relation of ocean current flow velocity and the still water speed of ship, ViCalculation method is：
Vcur_iFor the speed of ocean current on i-th of key event, β Vcur_iDirection with i-th section of key node line folder
Angle.According to the thinking of genetic algorithm, the distribution of key node is random.But the flow field data of high-frequency ground wave radar inverting are
According to certain rule distribution, ocean current velocity amplitude can just be directly read by not ensuring that on key node.So crucial
The speed V of node ocean currentcur_iInterpolation is also needed to obtain.This method directlys adopt closest interpolation method to complete on key node
The interpolation of ocean current speed.
4, genetic operator defines
Selection operation：Population is ranked up according to fitness function, is arranged from small to large according to fitness.Pay attention to here
Sequence preferentially by fitness it is small and it is unduplicated be discharged to front, its purpose is to prevent from falling into locally optimal solution faster.It is fixed
Adopted RcsFor select probability.The preceding n*R for selecting individual adaptation degree bestcsPaths, remaining n* (1-Rcs) fitness it is poor
Path is eliminated.And by the best n* (1-R of fitnesscs) paths are replicated to replace by that superseded n* (1-Rcs)
Path.
Crossover operation：First population is sorted, ordering rule is consistent with selection operation.According to certain crossover probability Rex, will
Preceding n*RexPaths are opposite as intersecting two-by-two.On two paths, [p is randomly choosedi, pj] section as transposition section, exchanges [pi,
pj] between key node latitude and longitude coordinates (1≤i≤m, i≤j≤m+1, i are with j key node serial number).
Mutation operation：First population is sorted, ordering rule is consistent with selection operation.According to certain mutation probability Rva, n*
RvaDo mutation operation in path.Specific practice is that a key node p is randomly selected on the path choseni(i≠1,i≠(m+
1)), by piCoordinate randomly select again, pay attention to selection rule still by path key node define constrain.
After the initialization of population of path, loop iteration is carried out according to selection-intersection-variation process, iteration is all each time
The smallest path optimal solution of a fitness can be generated, and this iteration is convergent.According to reality, set the number of iterations as
X.After X iteration, circulation is jumped out, final optimal solution is regarded as the consumption the smallest path of energy.
Step 4：After ship sends current location and terminal to radar center station, central station path planning, which calculates, to be needed
Certain time (related with the quantity of population and the number of loop iteration), therefore cannot guidance path be sent to ship immediately.At this point,
Agreement ship first continues to travel according to last planning path.If without planning path, or having arrived at the last of the path
One node, then directly towards destination straight-line travelling.Here it is continuous that planning path refers to that central station is issued to ship
The position of three key nodes.
Step 5：After central station calculates optimal path according to genetic algorithm, north can be passed through in conjunction with ship current location
It struggles against and sends three continuous key nodes to ship, as planning path.When linear distance of the ship current location apart from terminal
It when less than or equal to equal part cell distance d, is then no longer planned, directly sends final position to ship.So far, in ship
In the case where correctly exercising according to guidance path, entire path planning terminates.
Specific embodiment is named to be illustrated：
Ship sends current location to ground wave radar central station and target position, current position coordinates are：A(117.8452,
23.7270), target location coordinate is：B(117.3227,22.6688).After having sent location information to central station, ship
Current path planning information need to be inquired, is travelled towards next key event.The last one knot such as to reach current planning path
Point, or do not inquire planning path, then it is directly travelled towards destination B point.
After central station receives the position of A and B, current ocean current file LoDo_160730_0920_ in real time can read
7.865M_Current.xml is distributed then in conjunction with position and ocean current, starts to calculate.Ocean current file has central station real time inversion raw
At LODO indicates ground wave radar site zone, shown herein as the Taiwan Straits sea area near Dongshan, Fujian Longhai City, 160730_0920
Indicate 9 points 20 or so data on July 30th, 16, Current indicates that data type is ocean current.
The distance of A to B is 129.225km, is one with 4km and waits sub-units, the line of A to B can be divided into 33 sections,
Therefore the node sum in finally formed path is 34 nodes.Set 3000 for the population quantity of genetic algorithm, i.e., first with
Machine generates 3000 paths and (biggish population number is selected, primarily to faster convergence rate is able to achieve, due to ship's navigation
Route required precision is not high, it is possible to select less the number of iterations).All equal sub-units of A to B line are connected,
The straight line path defaulted as one, is denoted as S1, it is put into population.According to formula：
It finds out, straight line path S1Energy consumption be W1=349.427.
Here the W calculated is one and is used as the reference value that path fitness compares, and is not true energy consumption, can be with
Constant K is directly taken 1.
The number of iterations is set as 200 times, and select probability is set as 0.1, and crossover probability is set as 0.8, mutation probability setting
It is 0.5.
After iteration 1 time, as a result as shown in Fig. 3, straight line is still the smallest path of energy consumption between two o'clock at this time.
After iteration 20 times, as a result as shown in Fig. 4, the path calculated at this time is not straight line, energy consumption W=
335.103。
After iteration 100 times, as a result as shown in Fig. 5, path is more smooth at this time, energy consumption W=283.172.
After iteration 200 times, as a result as shown in Fig. 6, path occurs to change more by a small margin at this time, but energy consumption is still W=
283.172 not becoming smaller.
After iteration 200 times, circulation is jumped out, takes the smallest path of fitness as optimal solution, this Process Total time-consuming 227
Second.Path format is a series of set of key nodes, is expressed as：(117.8452,23.7270)(117.8308,23.6935)
(117.8216,23.6578)(117.8124,23.6222)(117.8103,23.5836)(117.8147,23.5423)
(117.8133,23.5034)(117.8171,23.4624)(117.7946,23.4322)(117.7860,23.3963)
(117.7762,23.3609)(117.7665,23.3254)(117.7515,23.2922)(117.7470,23.2546)
(117.7426,23.2170)(117.7378,23.1796)(117.7320,23.1424)(117.7253,23.1058)
(117.7179,23.0694)(117.7126,23.0323)(117.7011,22.9974)(117.6919,22.9618)
(117.6722,22.9303)(117.6486,22.9009)(117.6265,22.8706)(117.5969,22.8432)
(117.5686,22.8158)(117.5340,22.7908)(117.4990,22.7658)(117.4599,22.7428)
(117.4175,22.7207) (117.3752,22.6991) (117.3397,22.6742) (117.3227,22.6688) is total
34 nodes, first is ship current location：A (117.8452,23.7270), the last one point are target position：B
(117.3227,22.6688).At this point, central station is sent using three location points continuous after A point as routing information by Beidou
To ship.
After ship receives the routing information comprising continuous 3 coordinate points that central station is sent, path planning letter is updated
Breath.Course is adjusted, towards first coordinate points traveling of planning path.
So circulation above process, until next coordinate points of planning are terminal B, then entire trajectory planning process knot
Beam.
Claims (9)
1. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data, which is characterized in that ship sets sail
Sea area high-frequency ground wave radar central station reports current location where backward；After radar center station receives ship current location, in conjunction with
The final position of real-time ocean current data and ship carries out path planning according to genetic algorithm, finds out optimal path, and will most
Shortest path is sent to ship.
2. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as described in claim 1,
It is characterized in that, it is described that path planning is carried out according to genetic algorithm, path code scheme should be determined when finding out optimal path first, is had
Body is as follows：
If giving the correct time on current location each time, the linear distance of ship current location to terminal is S, using distance d as unit equal part,
S is divided into m sections, positive direction of the x-axis will be set as from the direction of origin-to-destination, will be perpendicular to the direction x, and the direction for passing through starting point
It is set as y-axis, positive direction of the y-axis is that x-axis is rotated by 90 ° signified direction counterclockwise, and a path from origin-to-destination is by a series of
Key node is constituted, and from the off, it is a complete path that each key node straight line, which is connected,.
3. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 2,
It is characterized in that, according to each paths, calculates the energy consumption values of line between every two key node, then add up, and
As the energy consumption in one whole path of ship traveling, the fitness function of the energy consumption are expressed as：
Wherein, CiSpeed, l are closed for the speed that ship externally shows between two key nodesiFor two key node lines
Length,Vcur_iFor the speed of ocean current on i-th of key event, β is
Vcur_iDirection with i-th section of key node line angle；Vi+1Indicate ship in i+1 key node still water speed, K mono-
It is a be greater than zero constant, 0≤t≤(li/Ci)。
4. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 3,
It is characterized in that, by the path in the initial population by selection, the operation of intersection, mutation genetic operator, with the adaptation
Degree function is to consider, and successive ignition is carried out, finally using optimal solution as globally optimal solution；By initial population when the selection operation
It is arranged from small to large according to fitness function, the preceding n*R for selecting fitness bestcsPaths, remaining n* (1-Rcs) adaptation
It spends poor path to be eliminated, and by the best n* (1-R of fitnesscs) paths are replicated to replace by superseded n*
(1-Rcs) path, wherein RcsFor select probability.
5. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 1 or 2,
It is characterized in that, sending three continuous key nodes after central station calculates optimal path according to genetic algorithm to ship, making
For planning path；When straight line etc. of linear distance of the ship current location apart from terminal less than or equal to ship current location to terminal
Sub-unit apart from when, then no longer planned, directly to ship send final position.
6. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 1 or 2,
It is characterized in that, path planning calculating in radar center station needs certain time after ship sends current location to radar center station,
Cannot guidance path be sent to ship immediately；At this point, agreement ship continues to travel according to last planning path, until receiving
To optimal path；If without planning path, or having arrived at the last one node in the path, then directly towards destination linear rows
It sails.
7. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 2,
It is characterized in that, the key node is：Vertical line is done on each the unit Along ent for not including beginning and end, on vertical line
It randomly selects a little as key node；Folder of the line of previous key node and the latter key node with positive direction of the x-axis
Angle is less than α, wherein α>0, the line of penultimate key node to terminal is without meeting above-mentioned constraint.
8. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 1 or 2,
It is characterized in that, all Along ents in origin-to-destination rectilinear direction are attached, calculation is put into as a default path
Method initial population.
9. a kind of waterborne vessel paths planning method based on high-frequency ground wave radar ocean current data as claimed in claim 1 or 2,
It is characterized in that, one ocean current data of radar center station inverting in every ten minutes, the nearest ocean current data being finally inversed by are made
For real-time ocean current data.
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