CN109541606A - The underwater synchronous positioning of single acoustic beacon ranging auxiliary and patterning process - Google Patents
The underwater synchronous positioning of single acoustic beacon ranging auxiliary and patterning process Download PDFInfo
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Abstract
The invention discloses a kind of underwater synchronous positioning of single acoustic beacon ranging auxiliary and patterning process: step 1, determining the state equation of aircraft movement, obtains predictive equation according to state equation；Step 2, during real navigation, aircraft is observed environmental characteristic, obtains observed quantity, while carrying out ranging observation to the single acoustic beacon arranged in advance, obtains the observed quantity of augmentation；Step 3, the observed quantity of the augmentation obtained according to step 2 carries out data correlation to the road sign newly observed, is constantly updated to characteristics map and quantity of state, to obtain real-time location navigation result.The present invention constrains underwater synchronous positioning with patterning process using single acoustic beacon ranging information, reduces the influence of system noise, improves positioning accuracy.
Description
Technical field
The present invention relates to synchronous positioning and recompose-technique, in particular to a kind of single acoustic beacon ranging auxiliary is based on expansion card
The underwater synchronous positioning of Kalman Filtering and patterning process.
Background technique
In current underwater navigation localization method, mainly there is non-autonomous lead for the navigation mode that submarine navigation device uses
Boat and independent navigation two major classes.Non-autonomous navigation mode, such as rowland, omega, GPS, can only receive in receiver and lead
It could complete to navigate when boat signal.Rowland, omega want low relative to GPS navigation precision.But these leading based on radio
Boat mode, due to electromagnetic wave is decayed quickly in water, the use in aircraft is very limited under water.Relative to
For electromagnetic signal, acoustical signal can farther out, therefore sonic transducer can be used as beacon to guide carrier to propagation distance under water
Navigation.Currently used acoustic navigation system mainly has Long baselines navigation, the navigation of short baseline and ultra-short baseline three kinds of shapes of navigation
Formula.These three forms all need to lay energy converter or transducer array in navigation sea area in advance, as known to acoustic navigation needs position
Beacon, therefore this mode is more applicable for scientific research and other civil fields.Geophysical navigation method is main at present
There are the navigation based on earth magnetism, the navigation based on gravitational field and based on landform, three kinds of methods of navigation of landforms, but carries out this navigation
Shi Zaiti needs match the data measured with the schema mapping of priori or database, not only generate these priori schema mappings
Cost with it is difficult, and with the increase of space dimensionality, the computation complexity for finding match peak exponentially increases.
Just because of the deficiency of these air navigation aids, people's exploratory development is just promoted to be not necessarily to the Underwater Navigation Algorithm of priori figure, this is also just
It is that synchronous positioning is asked with what composition (Simultaneous Localization and Mapping, SLAM) algorithm made every effort to solve
Topic.
Robot perceives peripheral information and at the same time reality by self-contained sensor in totally unknown environment
The now positioning of itself and the creation of environmental map are critical issues that it really realizes independent navigation.SLAM technology it is initial
Target is to make mobile robot in unknown position and under conditions of without environment pre-known information, utilizes self-contained sensor
Map is constructed, while estimating the posture (position and direction) of itself using this map.
In recent years, it is numerous about solve indoor and outdoor or even aerial and underwater synchronous positioning and recompose-technique meet the tendency of and
It is raw, however in applying under water, sensor sensing capability weakens, and system noise increases and noise statistics are unpredictable, most
It is important that underwater identifiable feature is very poor, this makes underwater SLAM problem become most challenging one of problem.
Summary of the invention
The purpose of the present invention is overcoming deficiency in the prior art, a kind of the underwater same of single acoustic beacon ranging auxiliary is provided
Step positioning and patterning process constrain underwater synchronous positioning with patterning process using single acoustic beacon ranging information, reduce
The influence of system noise improves positioning accuracy.
The technical scheme adopted by the invention is that: a kind of underwater synchronous positioning of list acoustic beacon ranging auxiliary and composition side
Method, comprising the following steps:
Step 1, the state equation for determining aircraft movement obtains predictive equation according to state equation；
Step 2, during real navigation, aircraft is observed environmental characteristic, obtains observed quantity, while in advance
The single acoustic beacon arranged carries out ranging observation, obtains the observed quantity of augmentation；
Step 3, the observed quantity of the augmentation obtained according to step 2 carries out data correlation to the road sign newly observed, constantly right
Characteristics map and quantity of state are updated, to obtain real-time location navigation result.
Further, step 1 specifically includes the following steps:
Step 1-1, handles sidescan-sonar image, carries out feature extraction, and the feature extracted in step 1-1 is special for point
Sign；
Step 1-2 is predicted using the model of EKF-SLAM system, obtains predicted state amount and predicted state association side
Difference:
Remember that the state of submarine navigation device at various moments is x1,x2,...,xk, wherein k is discrete time index；?
In SLAM system, the state of system is the position and direction of submarine navigation device, describes state estimation problem with formula (1):
Wherein, f () indicates that the equation of motion, u indicate control input, and w indicates that motion artifacts, z indicate observation data, g
() indicates that observational equation, n indicate observation noise；
According to initial information, the prediction result of state is obtained, it may be assumed that
Formula (2) indicates the state vector prediction result of system, i.e., obtains the shape at k moment by the state quantity prediction at k-1 moment
State amount, quantity of state are made of the position and direction of submarine navigation device, and wherein x_x () indicates submarine navigation device in two-dimensional surface
Abscissa, x_y () indicates that ordinate of the submarine navigation device in two-dimensional surface, φ () indicate course；
Obtain the prediction result of state covariance, it may be assumed that
P indicates state covariance in formula (3),Indicate the Jacobian matrix of state transition function, QkIndicate noise variance.
Further, step 2 specifically includes the following steps:
Step 2-1 during the motion once observes characteristic point at interval of same time, obtains observed result:
The coordinate for remembering each characteristic point isThen aircraft under each motion state with characteristic point
The distance between are as follows:
Remember dx (i)=lm_x (i)-x_x (i), dy (i)=lm_y (i)-x_y (i), the then course observed are as follows:
It is as follows that observing matrix is obtained at this time:
Step 2-2 carries out single acoustic beacon ranging, obtains distance measurement result, and distance measurement result is added to observational equation and is worked as
In:
While observation each time, aircraft and single acoustic beacon carry out ranging work, obtain aircraft and believe with single
The distance between mark and deflection, and the distance between aircraft and single beacon and deflection are added in observational equation and carried out
Constraint；
The plan-position coordinate of the underwater fixed single beacon of note is (a, b), carries out single beacon ranging to underwater fixed single beacon
It obtains:
Remember that dx1 (i)=a-x_x (i), dy1 (i)=b-x_y (i) then obtain course are as follows:
It obtains at this time as follows to single beacon observation matrix:
Meanwhile single beacon observation matrix (9) will be added in former observing matrix (6), obtain final observing matrix:
Z=(z r) (10).
Further, step 3 specifically includes the following steps:
Step 3-1, carries out data correlation to the road sign newly observed: carrying out data pass using closest data association algorithm
Connection, i.e., judged by the distance value in observing matrix and the most relevance distance of setting, see whether with the road that newly observes
Mark is associated, and the road sign newly observed is added in observation map；
Step 3-2 carries out state update by the result of step 3-1 data correlation, and the quantity of state and state to system are assisted
Variance is updated, to obtain new motion state:
Calculate the difference between actual observation and prediction observation:
In formula (11), z () indicates actual observation amount,Indicate prediction observed quantity；
State vector after update are as follows:
X (k | k)=x (k | k-1)+K* ε (k) (12)
In formula (12), K indicates kalman gain, i.e. observation and predicted value a weight.
The beneficial effects of the present invention are: a kind of underwater synchronous positioning of list acoustic beacon ranging auxiliary and patterning process, this
The mobile aircraft of the small underwater being directed in deep-marine-environment is invented, a kind of good navigation effect, accurate positioning are provided and do not needed
Priori schema mapping synchronizes positioning and recompose-technique based on the underwater of single beacon ranging auxiliary, especially can recognize characteristic body under water
Positioning result can be corrected under very poor situation.Compared to tradition based on EKF compared to the synchronous positioning that ranging assists
With patterning process, this method improves in positioning accuracy, reduces influence of the ambient noise to SLAM system, make its
Do not have to realize the location navigation of degree of precision under the case where priori schema mapping.Moreover, based on the underwater of single beacon ranging auxiliary
Location algorithm only needs a fixed underwater single beacon, by the ranging in the continuous observation time between subsea beacon and aircraft
As a result with direction be added observational equation, observational equation is carried out to be augmented processing, using relatively accurate single beacon ranging information as
Constraint condition, so that it may position positioning be carried out to aircraft, there is apparent advantage during the long-distance navigation of aircraft, more
Add and is suitable for the less situation of underwater observation number of features.It will be further appreciated that fixed based on synchronizing for single beacon ranging auxiliary
Position, which does not need priori schema mapping with patterning process, to be positioned, and be an innovation on conventional mapping methods.
Detailed description of the invention
Fig. 1 is SLAM course of work schematic diagram；
Fig. 2 is underwater synchronous positioning and the patterning process flow chart of single acoustic beacon ranging auxiliary；
Fig. 3 is synchronous positioning and patterning process analogous diagram based on EKF；
Fig. 4 is the underwater synchronous positioning and patterning process analogous diagram of single acoustic beacon ranging auxiliary.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows:
Positioning of the present invention for the underwater mobile aircraft in deep-marine-environment in long-distance navigation, main purpose are
It solves in current underwater position fixing technique, the priori map of navigation is not easy to obtain or priori map is inaccurate and underwater environment is made an uproar
Sound is very big, can recognize the very poor deficiency of feature, and the deficiency that traditional acoustic positioning system basic matrix arrangement is complicated.Carry this
The aircraft of the studied navigation positioning system of method carries out continuous by inside and outside sensor information and with underwater fixed subsurface buoy
Distance measuring, Extended Kalman filter (Extend Kalman Filter, EKF) is applied in SLAM system, realize
The real-time positioning of submarine navigation device.
A kind of the underwater of list acoustic beacon ranging auxiliary synchronous positions and patterning process: a two-dimensional surface at deep-sea
It is interior, it is known that the submarine navigation device of motion model has the environment of several environmental characteristics at one from a unknown initial point
Middle movement, aircraft determine the two-dimensional coordinate of environment by the data of sensor, while determining the three-dimensional coordinate of itself.(1) really
The state equation for determining aircraft movement obtains predictive equation according to state equation；(2) during real navigation, aircraft pair
Environmental characteristic is observed, and is obtained observed quantity, while carrying out ranging observation to the single acoustic beacon arranged in advance, is obtained augmentation
Observed quantity；(3) data correlation is carried out to the road sign that newly observes according to the observed quantity of above-mentioned augmentation, constantly to characteristics map and
Quantity of state is updated, to obtain real-time location navigation result.
Fig. 1,2 be respectively the course of work schematic diagram of SLAM and the underwater synchronous positioning of single acoustic beacon ranging auxiliary and
Patterning process flow chart is described further below with reference to process and principle of the Fig. 1 and Fig. 2 to the method for the present invention.
(1) sidescan-sonar image is handled, carries out feature extraction, the feature extracted herein is point feature.
(2) it is predicted using the model of EKF-SLAM system, obtains predicted state amount and predicted state covariance.
Remember that the state of submarine navigation device at various moments is x1,x2,...,xk, wherein k is discrete time index.?
In SLAM system, we will usually estimate the position of submarine navigation device, then the state of system just refers to submarine navigation device
Pose (position and direction).State estimation problem is described with two equations:
Wherein, f () indicates that the equation of motion, u indicate control input, and w indicates that motion artifacts, z indicate observation data, g
() indicates that observational equation, n indicate observation noise.
According to initial information, the prediction result of our available states, it may be assumed that
Formula (2) indicates the state vector prediction result of system, i.e., obtains the shape at k moment by the state quantity prediction at k-1 moment
State amount, quantity of state are made of the position and direction of submarine navigation device, and wherein x_x () indicates submarine navigation device in two-dimensional surface
Interior abscissa, x_y () indicate that ordinate of the submarine navigation device in two-dimensional surface, φ () indicate course.
Equally, in forecast period, we can also obtain the prediction result of state covariance, it may be assumed that
P indicates state covariance in formula (3),Indicate the Jacobian matrix of state transition function, QkIndicate noise variance.
(3) characteristic point is once observed at interval of same time during the motion, obtains observed result.
The coordinate for remembering each characteristic point isThen aircraft under each motion state with characteristic point
The distance between are as follows:
Remember dx (i)=lm_x (i)-x_x (i), dy (i)=lm_y (i)-x_y (i), the then course observed are as follows:
So when available observing matrix it is as follows:
(4) single acoustic beacon ranging is carried out, obtains distance measurement result, and distance measurement result is added in observational equation.
While observation each time, aircraft and single acoustic beacon carry out ranging work, obtain aircraft and believe with single
The distance between mark and deflection, and the distance between aircraft and single beacon and deflection are added in observational equation and carried out
Constraint.
The plan-position coordinate of the underwater fixed single beacon of note is (a, b) herein, carries out single beacon to underwater fixed single beacon
Ranging is available:
Remember dx1 (i)=a-x_x (i), dy1 (i)=b-x_y (i), then available course are as follows:
So when it is available as follows to single beacon observation matrix:
Meanwhile the observing matrix of single beacon will be added in former observing matrix, obtain the observing matrix of this method:
Z=(z r) (10)
(5) data correlation is carried out to the road sign newly observed.Data pass is carried out using closest data association algorithm herein
Connection, i.e., judged by the distance value in observing matrix and the most relevance distance of setting, see whether with the road that newly observes
Mark is associated, and the road sign newly observed is added in observation map.
(6) state update is carried out by the result of above-mentioned data correlation, the quantity of state and state covariance to system carry out
It updates, to obtain new motion state.
We need to calculate new breath, i.e. difference between actual observation and prediction observation in the process:
In formula (11), z () indicates actual observation amount,Indicate prediction observed quantity.
State vector after then updating are as follows:
X (k | k)=x (k | k-1)+K* ε (k) (12)
In formula (12), K indicates kalman gain, i.e. observation and predicted value a weight.
As shown in Figure 1, X0Indicate the physical location of initial time submarine navigation device, X1Indicate submarine navigation device in lower a period of time
The actual motion position at quarter, and X1',X1" table is then divided to indicate that the method for submarine navigation device according to the present invention is estimated in subsequent time
The position arrived, Z0,Z1Respectively indicate submarine navigation device carve at the beginning and the actual motion of subsequent time during can observe
Characteristic body, and m then indicate in the process under water but another characteristic object, in synchronous positioning with patterning process, we use u
Indicating the process of its more new estimation, that is, pass through prediction --- what is obtained after observation is new as a result, being represented by dashed line in Fig. 1.
As shown in Figure 3,4, " * " indicates the position of fact characteristic point, and "+" indicates the characteristic point position of estimation, ellipse representation
Error ellipse, error is bigger, and elliptical area is bigger, and " --- " indicates the physical location of submarine navigation device,It indicates
Estimated location on submarine navigation device, and " △ " indicates the position of underwater single beacon in Fig. 4.It is by 3,4 as can be seen that traditional
Synchronous positioning and patterning process based on EKF are larger by the interference of ambient noise, and when observation point is more sparse, underwater to navigate
Row device is just moved according to pushing algorithm, and positioning accuracy is poor.And the method for using the invention can subtract to a certain extent
The influence of weak ambient noise, while when for the less actual conditions of underwater observation characteristic point, it can according to single beacon ranging information
To carry out position correction, positioning accuracy is improved to a certain extent.So the present invention can be advantageously applied to submarine navigation device
High accuracy positioning work.
Present invention is mainly applied to positioning and navigation of the aircraft in the deep-sea of no priori map when operation, when underwater
When recognizable characteristic body is very poor, positioning in real time and navigation are carried out according to synchronous positioning and patterning process, while utilizing single water
Acoustic marker distance measurement result is constrained, to improve the positioning accuracy of synchronous positioning and patterning process.
Although the preferred embodiment of the present invention is described above in conjunction with attached drawing, the invention is not limited to upper
The specific embodiment stated, the above mentioned embodiment is only schematical, be not it is restrictive, this field it is common
Technical staff under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, may be used also
By make it is many in the form of, within these are all belonged to the scope of protection of the present invention.
Claims (4)
1. a kind of underwater synchronous positioning of list acoustic beacon ranging auxiliary and patterning process, which comprises the following steps:
Step 1, the state equation for determining aircraft movement obtains predictive equation according to state equation；
Step 2, during real navigation, aircraft is observed environmental characteristic, obtains observed quantity, while to arranging in advance
Good single acoustic beacon carries out ranging observation, obtains the observed quantity of augmentation；
Step 3, the observed quantity of the augmentation obtained according to step 2 carries out data correlation to the road sign newly observed, constantly to feature
Map and quantity of state are updated, to obtain real-time location navigation result.
2. the underwater synchronous positioning of list acoustic beacon ranging auxiliary according to claim 1 and patterning process, feature exist
In, step 1 specifically includes the following steps:
Step 1-1, handles sidescan-sonar image, carries out feature extraction, and the feature extracted in step 1-1 is point feature；
Step 1-2 is predicted using the model of EKF-SLAM system, obtains predicted state amount and predicted state covariance:
Remember that the state of submarine navigation device at various moments is x1,x2,...,xk, wherein k is discrete time index；In SLAM system
In system, the state of system is the position and direction of submarine navigation device, describes state estimation problem with formula (1):
Wherein, f () indicates that the equation of motion, u indicate control input, and w indicates that motion artifacts, z indicate observation data, g () table
Show that observational equation, n indicate observation noise；
According to initial information, the prediction result of state is obtained, it may be assumed that
Formula (2) indicates the state vector prediction result of system, i.e., obtains the quantity of state at k moment by the state quantity prediction at k-1 moment,
Quantity of state is made of the position and direction of submarine navigation device, and wherein x_x () indicates cross of the submarine navigation device in two-dimensional surface
Coordinate, x_y () indicate that ordinate of the submarine navigation device in two-dimensional surface, φ () indicate course；
Obtain the prediction result of state covariance, it may be assumed that
Pxx,k|k-1=▽ fPxx,k-1|k-1▽fT+Qk (3)
P indicates that state covariance, ▽ f indicate the Jacobian matrix of state transition function, Q in formula (3)kIndicate noise variance.
3. the underwater synchronous positioning of list acoustic beacon ranging auxiliary according to claim 1 and patterning process, feature exist
In, step 2 specifically includes the following steps:
Step 2-1 during the motion once observes characteristic point at interval of same time, obtains observed result:
The coordinate for remembering each characteristic point isThen aircraft is under each motion state between characteristic point
Distance are as follows:
Remember dx (i)=lm_x (i)-x_x (i), dy (i)=lm_y (i)-x_y (i), the then course observed are as follows:
It is as follows that observing matrix is obtained at this time:
Step 2-2 carries out single acoustic beacon ranging, obtains distance measurement result, and distance measurement result is added in observational equation:
While observation each time, aircraft and single acoustic beacon carry out ranging work, obtain aircraft and single beacon it
Between distance and deflection, and the distance between aircraft and single beacon and deflection are added observational equation and carried out about in the middle
Beam；
The plan-position coordinate of the underwater fixed single beacon of note is (a, b), carries out single beacon ranging to underwater fixed single beacon and obtains:
Remember that dx1 (i)=a-x_x (i), dy1 (i)=b-x_y (i) then obtain course are as follows:
It obtains at this time as follows to single beacon observation matrix:
Meanwhile single beacon observation matrix (9) will be added in former observing matrix (6), obtain final observing matrix:
Z=(z r) (10).
4. the underwater synchronous positioning of list acoustic beacon ranging auxiliary according to claim 1 and patterning process, feature exist
In, step 3 specifically includes the following steps:
Step 3-1, carries out data correlation to the road sign newly observed: data correlation is carried out using closest data association algorithm,
Judged by the distance value in observing matrix and the most relevance distance of setting, see whether with the road sign that newly observes into
Row association, and the road sign newly observed is added in observation map；
Step 3-2 carries out state update by the result of step 3-1 data correlation, to the quantity of state and state covariance of system
It is updated, to obtain new motion state:
Calculate the difference between actual observation and prediction observation:
In formula (11), z () indicates actual observation amount,Indicate prediction observed quantity；
State vector after update are as follows:
X (k | k)=x (k | k-1)+K* ε (k) (12)
In formula (12), K indicates kalman gain, i.e. observation and predicted value a weight.
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| CN110082706A (en) * | 2019-04-23 | 2019-08-02 | 哈尔滨工程大学 | It is a kind of based on delay inequality and phase difference and to be suitable for the asynchronous underwater single beacon method of clock |
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| CN113124881A (en) * | 2021-06-17 | 2021-07-16 | 天津大学 | Fault recovery method of synchronous positioning and composition system based on magnetic beacon |
| CN114228959A (en) * | 2021-12-29 | 2022-03-25 | 中国科学院沈阳自动化研究所 | Underwater robot polar region under-ice recovery method based on acoustic road sign and optical road sign combined auxiliary navigation |
| CN114370879A (en) * | 2022-01-14 | 2022-04-19 | 东南大学 | AUV robust VBHIAKF-SLAM navigation method based on underwater environment characteristics |
| WO2022174545A1 (en) * | 2021-02-19 | 2022-08-25 | 鹏城实验室 | Path optimization method, underwater vehicle and computer-readable storage medium |
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| CN110082706A (en) * | 2019-04-23 | 2019-08-02 | 哈尔滨工程大学 | It is a kind of based on delay inequality and phase difference and to be suitable for the asynchronous underwater single beacon method of clock |
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| CN110554359A (en) * | 2019-09-11 | 2019-12-10 | 哈尔滨工程大学 | seabed flight node positioning method integrating long baseline positioning and single beacon positioning |
| CN110554359B (en) * | 2019-09-11 | 2021-07-09 | 哈尔滨工程大学 | Seabed flight node positioning method integrating long baseline positioning and single beacon positioning |
| WO2022174545A1 (en) * | 2021-02-19 | 2022-08-25 | 鹏城实验室 | Path optimization method, underwater vehicle and computer-readable storage medium |
| CN113124881A (en) * | 2021-06-17 | 2021-07-16 | 天津大学 | Fault recovery method of synchronous positioning and composition system based on magnetic beacon |
| CN113124881B (en) * | 2021-06-17 | 2021-10-08 | 天津大学 | Fault recovery method of synchronous positioning and composition system based on magnetic beacon |
| CN114228959A (en) * | 2021-12-29 | 2022-03-25 | 中国科学院沈阳自动化研究所 | Underwater robot polar region under-ice recovery method based on acoustic road sign and optical road sign combined auxiliary navigation |
| CN114370879A (en) * | 2022-01-14 | 2022-04-19 | 东南大学 | AUV robust VBHIAKF-SLAM navigation method based on underwater environment characteristics |
| CN114370879B (en) * | 2022-01-14 | 2023-03-10 | 东南大学 | AUV robust VBHIAKF-SLAM navigation method based on underwater environment characteristics |
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