CN104916166A - Bridge anti-collision warning system and realization method - Google Patents
Bridge anti-collision warning system and realization method Download PDFInfo
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Abstract
The invention relates to a bridge anti-collision warning system which is mainly composed of an warning information processing center, upstream and downstream monitoring sites, and a piece of water level monitoring equipment. The warning information processing center comprises an AIS receiver, a data acquisition and processing server, an anti-collision warning information processing computer, a video monitoring computer, a data recording server, and a VHF radio station. The upstream and downstream monitoring sites are respectively arranged upstream and downstream of a bridge and in positions of the river bank which are 3-5km away from the bridge. Each monitoring site is provided with a monitoring camera and a cloud platform which can adjust the shooting angle. A target ship is identified by shooting ships with potential threat and dynamically tracking the geographical locations of the ships. The height of the ship is calculated after the background is removed. When the height of the ship reaches a warning height, secondary measurement is carried out manually. When the ship is determined as a threat ship, calling is carried out immediately through a VHF radio station or the maritime sector is notified.
Description
Technical field
The present invention relates to a kind of bridge-collision-avoidance early warning system, belong to vessel traffic service technical field.
Background technology
Along with developing rapidly of national economy and communications and transportation, on the one hand by building across river large bridge over strait, to alleviate traffic pressure, to promote land communications; Increase tonnage and the quantity of ships that transport on the other hand, to improve water transportation ability.For water transportation boats and ships, bridge becomes cultural obstacle.Bridge happens occasionally by ship collision accident, and the bridge span brought out therefrom event of collapsing is increasing.The Yangtze Bridge, bridge spanning the sea have become the sustainer of China's land transportation, and the problem of vessel bump bridge especially looms large.
The ship of bridge hits the light then bridge damnification of accident, heavy then cause bridge collapse, casualties, not only causes great direct economic loss and huge indirect economic loss, and produces severe social influence.Therefore, strengthen bridge-collision-avoidance technical research, set up bridge-collision-avoidance facility, occur with Accident prevention, alleviate causality loss, not only very necessary, and also very urgent.
The Anticollision Measures of bridge is generally divided into two kinds of modes: passive crashproof and initiatively crashproof.Passive crashproof be a kind of structural collision protection technology, utilize fender, check cable system, flexible energy device etc. to build bridge-collision-avoidance facility, object is the acting force produced after reducing ship collision bridge, alleviates the loss of colliding and causing.To so far, mainly concentrate on passive protection (structural collision protection) technology to the research of bridge-collision-avoidance both at home and abroad, achievement in research is horn of plenty comparatively.Initiatively crashproof near bridge district, set up the anti-ship of bridge hits early warning system to guide ship's navigation exactly, avoids or reduces the generation that ship hits accident.Visible active is crashproof is positive anti-pre-measure, have take precautions against in advance, feature that cost is low.
Find through retrieval, Chinese utility model patent CN 201788591 U proposes sea, a kind of river based on AIS Main Bridge automatic collsion avoidance system, it utilizes the state of motion of data processing unit to shippping traffic to analyze, with the distance of navigation main pier when prediction boats and ships are passed a bridge, automatic or manually accordingly shippping traffic is pointed out or warns, deck officer is made to see clearly the voyage conditions of boats and ships early, safe gap bridge of adopting an effective measure.The visible program designs mainly for pier anticollision, does not relate to the crashproof of bridge lower edge.
Chinese invention patent application CN 102915650 A then proposes a kind of bridge waters ship navigation safe early warning equipment based on intersection photography, utilize photogrammetry by intersection technology, image processing techniques, realize ship identification, containing height in identifying information, therefore can think that use equipment can realize the anti-collision early warning of bridge lower edge.Inventor studies discovery, and the identifying that the program exists boats and ships is complicated, the defects such as data processing amount is large.
Summary of the invention
The object of the invention is to: the defect overcoming above-mentioned prior art, propose a kind of bridge-collision-avoidance early warning system and implementation method.
In order to achieve the above object, the bridge-collision-avoidance early warning system that the present invention proposes, composition comprises:
AIS receives and analyzing device, for receiving watercraft AIS message constantly, watercraft AIS message to be resolved and stored in database, the packets of information parsed from watercraft AIS message contains boats and ships geographic coordinate information, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships steering angle over the ground;
CCTV camera, be arranged on the The Cloud Terrace near bridge upstream predeterminable range and riverbank, predeterminable range place, downstream respectively, for photographic subjects boats and ships, and data are passed to computer-processing equipment, the river course scope between bridge upstream predeterminable range and downstream predeterminable range is prewarning area;
Level sensor, for height of water level near Real-Time Monitoring bridge, the data of described level sensor export and send to computer-processing equipment, to calculate current headway;
Computer-processing equipment, for sending to the control module of The Cloud Terrace by entering the geographic coordinate information of boats and ships in prewarning area, maybe this geographic coordinate information is carried out processing the control module that rear formation instruction sends to The Cloud Terrace, make it control The Cloud Terrace and CCTV camera is taken with suitable level angle and the luffing angle boats and ships that aim at the mark; The pixels tall that computer-processing equipment surfaces in the picture according to the Distance geometry boats and ships of shooting angle, shooting point and boats and ships calculates height, carries out the risk judgment of ship from colliding bridge lower edge accordingly, and notifies managerial personnel;
VHF radio station, commands it for calling out the boats and ships clashing into risk.
Bridge-collision-avoidance early warning system of the present invention, also has following further feature:
1, described AIS reception and analyzing device comprise the AIS receiving instrument for receiving watercraft AIS message, the AIS packet parsing be connected with the data output end of this AIS receiving instrument and record server.
2, described computer-processing equipment comprises: video monitoring equipment and proximity warning information treatment facility, and described video monitoring equipment receives the video of CCTV camera shooting, adopts dynamic object recognition algorithm identify these boats and ships in video and remove background; Proximity warning information treatment facility calculates the height of potential threat boats and ships according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships, and carries out shock risk judgment.
3, the geographic coordinate information in described watercraft AIS message, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships over the ground steering angle resolved after stored in database, ship information in described computer-processing equipment reading database, as waiting, the boats and ships that may clash into bridge lower edge judge that boats and ships carry out elevation carrection and judge to clash into risk.
4, described CCTV camera is made up of visible light camera and thermal imaging system, and visible light camera and thermal imaging system are taken potential threat boats and ships simultaneously, and computer-processing equipment is chosen to carry out height identification as good video according to weather condition.
In addition, present invention also offers a kind of implementation method of bridge-collision-avoidance early warning, comprise the following steps:
The AIS message that the reception boats and ships that 1st step, AIS receiving instrument continue are sent, and send to AIS netscape messaging server Netscape;
2nd step, AIS netscape messaging server Netscape resolve AIS information, by the geographic coordinate information of boats and ships, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships over the ground steering angle be stored in database, the geographic coordinate information of every bar boats and ships is can be stored by the form of coherent reading;
3rd step, computer-processing equipment reading database, may clash into the boats and ships of bridge as potential threat boats and ships according to Ship Types, boat length and boats and ships width, and dynamically follow the tracks of the geographic position of potential threat boats and ships according to boats and ships geographic coordinate;
After 4th step, potential threat boats and ships enter prewarning area, computer-processing equipment forms to after the up-to-date geographic coordinate information process of potential threat boats and ships the control module that instruction sends to The Cloud Terrace;
After 5th step, cradle head control module receive instruction, control CCTV camera and take with suitable level angle and luffing angle aligning potential threat boats and ships, and the video of shooting is sent to computer-processing equipment;
6th step, computer-processing equipment adopt dynamic object recognition algorithm identify these boats and ships in video and remove background, the height of potential threat boats and ships is calculated according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships, height and current headway are compared, if be less than current headway M rice, then allow current, wherein the span of M is for manually to preset; Otherwise remind staff to carry out manual confirmation;
7th step is once confirm that potential threat boats and ships have the risk of clashing into bridge lower edge, and staff contacts this boats and ships by VHF radio station at once, or notice maritime sector.
Further, in described 6th step, current headway sends to computer-processing equipment after being gathered by the level sensor being installed on the water surface near bridge, is calculated obtain by computer-processing equipment.
Further, in order to improve the security of system, in described 6th step, measure after obtaining height, if height is higher than artificial predetermined threshold value, then staff estimates pixels tall that potential threat boats and ships surface in video image and to go forward side by side rower note, is recalculated the height of potential threat boats and ships, carry out shock risk judgment more subsequently by computer-processing equipment by computer-processing equipment.
The present invention changes video camera in conventional crash early warning system and is arranged at the scheme of bridge floor, and video camera is arranged at respectively on the riverbank of upstream and downstream (2-10KM) of bridge, be used for monitoring the boats and ships entering prewarning area, to obtain the longer anti-collision early warning time, thus realize advanced early warning, win the more time to ship dispatch, guarantee the safety of bridge and the safe passing of boats and ships.
The present invention realizes the accurate shooting to boats and ships by the geographic coordinate information of boats and ships, and identify boats and ships in the picture, according to the Distance geometry boats and ships pixels tall in the picture of shooting angle, shooting point and boats and ships after removal background, carry out the calculating of height, after height and headroom compare, crashproof risk judgment can be realized.This technique improves recognition efficiency and the recognition accuracy of risk boats and ships height, enable to prevent the early warning of ship from colliding bridge lower edge from being used in reality, the results showed and obtain good effect.
As further improvement, the information that the present invention utilizes watercraft AIS message to extract tentatively rejects the boats and ships not clashing into risk, make judgement target tightening on potential threat boats and ships, alleviate the burden of system cloud gray model, thus system and personnel have the sufficient time to judge the shock risk of every potential threat boats and ships, improve reliability and the accuracy of system cloud gray model.
In addition, CCTV camera contains can by light video camera and thermal imaging system, guarantees that system can safe operation under various state of weather, improves the adaptability of system.
Accompanying drawing explanation
Below in conjunction with accompanying drawing, the present invention is further illustrated.
Fig. 1 is bridge-collision-avoidance early warning system of the present invention composition schematic diagram.
Fig. 2 is the implementation method process flow diagram of bridge-collision-avoidance early warning system of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention will be further described.
As shown in Figure 1, be the present embodiment bridge-collision-avoidance early warning system, form primarily of early warning information processing enter, upstream monitoring station, downstream monitoring station and water level monitoring equipment.
Early warning information processing enter includes: AIS receiver, data acquisition and procession server; Proximity warning information process computer, video monitoring computing machine; Data logger server and VHF radio station.
Upstream and downstream monitoring station is arranged on the riverbank of bridge upstream and downstream 3-5 km respectively, each monitoring station has the The Cloud Terrace of CCTV camera and adjustable shooting angle, this CCTV camera is made up of visible light camera and thermal imaging system, can take by the carrying out in different weather situation.
Water level monitoring equipment includes the level sensor being installed on bridge Its Adjacent Waters.
In native system, the effect of each several part is as follows:
AIS receiver: for the reception watercraft AIS message continued, and send to data acquisition and procession server;
Data acquisition and procession server: stored in database after resolving AIS message, is read by network for other equipment;
Proximity warning information process computer: 1, the information of boats and ships in reading database, may clash into the boats and ships of bridge as potential threat boats and ships according to Ship Types, boat length and boats and ships width, and dynamically follow the tracks of the geographic position of potential threat boats and ships; 2, after potential threat boats and ships enter prewarning area, proximity warning information process computer has more its current geographic position and forms the The Cloud Terrace that instruction sends to monitoring station, and video camera is taken potential threat boats and ships with suitable level angle and luffing angle; 3, the waterlevel data that level sensor sends is received, to calculate the current headway of bridge; 4, the image of process that sends of receiver, video supervisory control comuter, calculate the height of potential threat boats and ships according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships, and carry out shock risk assessment accordingly; 5, providing VHF interface of calls, operating the threatens vessel that can directly utilize VHF calling-up to specify on computers, without the need to redialing.
Video monitoring computing machine: receive the vision signal that upstream and downstream monitoring station is sent, adopts dynamic object recognition algorithm identify target boats and ships in video and remove background, sends to proximity warning information process computer to judge in the picture after process.
Data logger server: the database being provided for storage vessel information and system cloud gray model information.
VHF radio station: be connected with the VHF interface of proximity warning information process computer, realize the calling to target boats and ships.
CCTV camera: for taking target boats and ships, and by wired or wireless network delivery to video monitoring computing machine;
The Cloud Terrace: for controlling the shooting angle of CCTV camera, makes boats and ships appear at clearly as far as possible near the position of picture central authorities.
Level sensor: monitoring water level information, and send to proximity warning information process computer by network, to calculate headway.
As shown in Figure 2, the implementation method of the present embodiment bridge-collision-avoidance early warning system, comprises the following steps:
The AIS message that the reception boats and ships that T1, AIS receiver continues are sent, and send to data acquisition and procession server (AIS netscape messaging server Netscape).
T2, data acquisition and procession server parses AIS information, by the geographic coordinate information of boats and ships, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships over the ground steering angle be stored in database, the geographic coordinate information of every bar boats and ships is can be stored by the form of coherent reading.
T3, proximity warning information process computer reading database, may clash into the boats and ships of bridge as potential threat boats and ships according to Ship Types, boat length and boats and ships width, and dynamically follow the tracks of the geographic position of potential threat boats and ships according to boats and ships geographic coordinate.
T4, level sensor send proximity warning information process computer after gathering water level information, calculated obtain current headway by proximity warning information process computer.
After T5, potential threat boats and ships enter prewarning area, proximity warning information process computer forms to after the up-to-date geographic coordinate information process of potential threat boats and ships the control module that instruction sends to The Cloud Terrace.
After T6, cradle head control module receive instruction, control CCTV camera and take with suitable level angle and luffing angle aligning potential threat boats and ships, and the video of shooting is sent to video monitoring computing machine.
T7, video monitoring computing machine adopt dynamic object recognition algorithm identify these boats and ships in video and remove background, send to proximity warning information process computer to judge the image after process.
T8, proximity warning information process computer calculate the height of potential threat boats and ships according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships.
T9, when height reaches artificial predetermined threshold value, staff estimates pixels tall that potential threat boats and ships surface in video image and to go forward side by side rower note, is recalculated the height of potential threat boats and ships by proximity warning information process computer; Otherwise judge that these potential threat boats and ships can safe passing.Artificial predetermined threshold value wherein can carry out artificial selection according to actual conditions, and such as when current headroom is 50 meters, this artificial predetermined threshold value can arrange 37 meters, or 38 meters.The suggested range that inventor provides for artificial predetermined threshold value is: headroom subtracts 10 to 20 meters, and concrete numerical value depends on the circumstances.
T10, the height after recalculating and current headway to be compared, if be less than current headway M rice, then allow current; Otherwise these potential threat boats and ships are threatens vessel.Wherein the value of M is for manually to preset, and in the present embodiment, M value is the headroom of 10%.The M span that inventor recommends is the headroom of 5-15%, and the setting of M value can set according to actual conditions.
T11 is once confirm that potential threat boats and ships have the risk of clashing into bridge lower edge, and staff contacts this boats and ships by VHF radio station at once, or notice maritime sector.
Step T8, calculate the height of potential threat boats and ships according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships, also interchangeable doing has been come by video monitoring computing machine; In same T9, also complete recalculating of height by video monitoring computing machine.Under such task matching pattern, the height that video monitoring computing machine second time calculates the potential threat boats and ships obtained sends to proximity warning information process computer, carries out shock risk judgment by proximity warning information process computer.
In this enforcement, the method for dynamically following the tracks of potential threat boats and ships geographic position is: the geographic coordinate of the target boats and ships of state-of-the-art record in database and velocity information are worth as initial monitoring; According to this initial monitoring value, coordinate position and velocity transformation are carried out to the AIS information of all target boats and ships that need follow the tracks of, obtains correlating transforms value, be i.e. the initial value of all target boats and ships.The relevant prediction and calculation to target ship tracking can be carried out according to this initial value, to determine navigation coordinate and the ship's speed of target boats and ships subsequent time, according to the coverage that predicted value and each monopod video camera are observed, carry out the inspection controlling thresholding, to determine the monopod video camera of the monitoring of subsequent time, thus automatic switchover monopod video camera, realize Continuous Tracking monitoring.Such as, and by the correction of predicted value to the controling parameters of this monopod video camera, cloud platform rotation angle is revised, guarantee clearly to photograph target boats and ships.
To the tracking of target boats and ships, the prediction and calculation of the position and speed of its subsequent time is very important, and when present invention employs, statistical error matrix assists Kalman filtering algorithm to realize the prediction and calculation to target boats and ships, and system can more accurately be followed the tracks of, and concrete steps are as follows.
First set up system state equation, according to the AIS information received, by Gauss-Ke Lvge coordinate conversion and rate conversion, the speed component (v of the earth planimetric rectangular coordinates (x, y) of boats and ships to be tracked and X, Y-axis can be obtained
x, v
y), and be set to state variable X=[x, y, the v of forecast model
x, v
y]
t, can obtain system continuous state equation is
Wherein
A
x, a
yfor the noise of state equation, affect the motion state of boats and ships, this noise is system noise, and its statistical property is similar to white noise.
As predicted time is spaced apart T, the time t of monitoring is continuously separated into some time discrete point by this time interval T, then the system state equation of Disgrete Time Domain is
X(k+1)＝Φ(k+1,k)X(k)+G(k)N(k) (2)
Wherein: k is time t is separated in a some time discrete point kth discrete point by time interval T, and is current time, k=1,2,3
Get the AIS information received, by coordinate conversion and rate conversion, the X of acquisition, the coordinate of Y-axis and speed component thereof are as observed quantity, then the observation equation corresponding to system state equation according to the discrete point moment is:
Z(k)＝HX(k)+V(k) (3)
Wherein
Then upgrade state value, upgrade to target boats and ships from time discrete point k to k+1 moment new navigation coordinate and ship's speed value etc., then according to the status predication equation of formula (2) k+1 current time:
Then carry out the calculating of predicting covariance battle array, before this calculating is carried out, carry out no receiving by the differentiation of the AIS message of the boats and ships of video tracking.
At the current time of k discrete point, if receive message, carry out the calculating of the predicting covariance battle array in next discrete point k+1 moment, the covariance matrix of its predicated error is:
P(k+1|k)＝Φ(k+1|k)P(k|k)Φ
T(k+1|k)+G(k+1|k)Q(k)G
T(k+1|k) (5)
Wherein: system noise Q (k)=E [N (k) N (k)], E for solving mathematical expectation, covariance matrix, Φ that Φ (k+1|k) is predicated error for continuous-time domain to the transformation matrix of Disgrete Time Domain, P (k|k)
t(k+1|k) for continuous-time domain to the transformation matrix transposition of Disgrete Time Domain, G (k+1|k) for continuous-time domain to the transformation matrix of Disgrete Time Domain, Q (k) be system noise, G
t(k+1|k) for continuous-time domain is to the transformation matrix transposition of Disgrete Time Domain.
Then by the calculating that the filter gain Matrix Formula of following formula is carried out
K (k+1|k)=P (k+1|k) H
t[HP (k+1|k) H
t+ R (k+1)]
-1(6) wherein R (k+1) is observation noise covariance matrix,
R(k+1)＝E[V(k+1)V(k+1)] (7)
Then according to calculate obtain the status predication value of current time, filter gain matrix, current time observed reading, then the state estimation in current k+1 discrete point moment is:
If do not receive the message information that target boats and ships send, the error covariance matrix adding up acquisition before utilizing is needed to be weighted on average, as shown in the formula (8):
P(k+1|k)＝τP(k|k)+(1-τ)P(k-1|k-1) (8)
Finally according to covariance matrix and the filter gain matrix of acquired predicated error, the error covariance matrix being updated to next discrete point k+1 moment is:
P(k+1|k+1)＝[I-K(k+1)H]P(k+1|k)，
The error covariance matrix upgraded is stored in order to adopting next time.
The prediction being relevant to the variable quantities such as target boats and ships coordinate position, speed the k+1 discrete point moment can be obtained from this error covariance matrix P (k+1|k+1), so that monopod video camera accurately can be selected by Surveillance center, and the prediction and calculation method of the above-mentioned position to target boats and ships subsequent time, speed etc. of the present invention can effectively prevent from postponing to cause the deficiency of video monitoring blind spot due to message information disappearance or information transmission, can predict more accurately and effectively.
In addition to the implementation, the present invention can also have other embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop on the protection domain of application claims.
Claims (9)
1. a bridge-collision-avoidance early warning system, composition comprises:
AIS receives and analyzing device, for receiving watercraft AIS message constantly, watercraft AIS message to be resolved and stored in database, the packets of information parsed from watercraft AIS message contains boats and ships geographic coordinate information, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships steering angle over the ground;
CCTV camera, be arranged on the The Cloud Terrace near bridge upstream predeterminable range and riverbank, predeterminable range place, downstream respectively, for photographic subjects boats and ships, and data are passed to computer-processing equipment, the river course scope between bridge upstream predeterminable range and downstream predeterminable range is prewarning area;
Level sensor, for height of water level near Real-Time Monitoring bridge, the data of described level sensor export and send to computer-processing equipment, to calculate current headway;
Computer-processing equipment, for sending to the control module of The Cloud Terrace by entering the geographic coordinate information of boats and ships in prewarning area, maybe this geographic coordinate information is carried out processing the control module that rear formation instruction sends to The Cloud Terrace, make it control The Cloud Terrace and CCTV camera is taken with suitable level angle and the luffing angle boats and ships that aim at the mark; The pixels tall that computer-processing equipment surfaces in the picture according to the Distance geometry boats and ships of shooting angle, shooting point and boats and ships calculates height, carries out the risk judgment of ship from colliding bridge lower edge accordingly, and notifies managerial personnel;
VHF radio station, commands it for calling out the boats and ships clashing into risk.
2. bridge-collision-avoidance early warning system according to claim 1, is characterized in that: described AIS receives and analyzing device comprises the AIS receiving instrument for receiving watercraft AIS message, the AIS packet parsing be connected with the data output end of this AIS receiving instrument and record server.
3. bridge-collision-avoidance early warning system according to claim 1, it is characterized in that: described computer-processing equipment comprises: video monitoring equipment and proximity warning information treatment facility, described video monitoring equipment receives the video of CCTV camera shooting, adopts dynamic object recognition algorithm identify these boats and ships in video and remove background; Proximity warning information treatment facility calculates the height of potential threat boats and ships according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships, and carries out shock risk judgment.
4. bridge-collision-avoidance early warning system according to claim 1, it is characterized in that: the geographic coordinate information in described watercraft AIS message, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships over the ground steering angle resolved after stored in database, ship information in described computer-processing equipment reading database, as waiting, the boats and ships that may clash into bridge lower edge judge that boats and ships carry out elevation carrection and judge to clash into risk.
5. bridge-collision-avoidance early warning system according to claim 1, it is characterized in that: described CCTV camera is made up of visible light camera and thermal imaging system, visible light camera and thermal imaging system are taken potential threat boats and ships simultaneously, and computer-processing equipment is chosen to carry out height identification as good video according to weather condition.
6. the implementation method of bridge-collision-avoidance early warning, is characterized in that comprising the following steps:
The AIS message that the reception boats and ships that 1st step, AIS receiving instrument continue are sent, and send to AIS netscape messaging server Netscape;
2nd step, AIS netscape messaging server Netscape resolve AIS information, by the geographic coordinate information of boats and ships, boats and ships MMSI code, boat length, boats and ships width, ship name, No. IMO, boats and ships, boats and ships speed on the ground and boats and ships over the ground steering angle be stored in database, the geographic coordinate information of every bar boats and ships is can be stored by the form of coherent reading;
3rd step, computer-processing equipment reading database, may clash into the boats and ships of bridge as potential threat boats and ships according to Ship Types, boat length and boats and ships width, and dynamically follow the tracks of the geographic position of potential threat boats and ships according to boats and ships geographic coordinate;
After 4th step, potential threat boats and ships enter prewarning area, computer-processing equipment forms to after the up-to-date geographic coordinate information process of potential threat boats and ships the control module that instruction sends to The Cloud Terrace;
After 5th step, cradle head control module receive instruction, control CCTV camera and take with suitable level angle and luffing angle aligning potential threat boats and ships, and the video of shooting is sent to computer-processing equipment;
6th step, computer-processing equipment adopt dynamic object recognition algorithm identify these boats and ships in video and remove background, the height of potential threat boats and ships is calculated according to the pixels tall of Distance geometry potential threat boats and ships in video image of shooting angle, shooting point and potential threat boats and ships, height and current headway are compared, if be less than current headway M rice, then allow current, wherein the span of M is for manually to preset; Otherwise remind staff to carry out manual confirmation;
7th step is once confirm that potential threat boats and ships have the risk of clashing into bridge lower edge, and staff contacts this boats and ships by VHF radio station at once, or notice maritime sector.
7. the implementation method of bridge-collision-avoidance early warning according to claim 6, it is characterized in that: in described 6th step, current headway sends to computer-processing equipment after being gathered by the level sensor being installed on the water surface near bridge, is calculated obtain by computer-processing equipment.
8. the implementation method of bridge-collision-avoidance early warning according to claim 6, it is characterized in that: in described 6th step, in described 6th step, measure after obtaining height, if height is higher than artificial predetermined threshold value, then staff estimates pixels tall that potential threat boats and ships surface in video image and to go forward side by side rower note, is recalculated the height of potential threat boats and ships, carry out shock risk judgment more subsequently by computer-processing equipment by computer-processing equipment.
9. the implementation method of bridge-collision-avoidance early warning according to claim 8, is characterized in that: the method for dynamically following the tracks of potential threat boats and ships geographic position is: the geographic coordinate of the target boats and ships of state-of-the-art record in database and velocity information are worth as initial monitoring; Be worth according to initial monitoring, to geodetic transformation and the velocity transformation of the target boats and ships of required tracking, obtain correlating transforms value; According to described transformed value, the navigation coordinate of prediction boats and ships subsequent time and ship's speed;
The described navigation coordinate of prediction boats and ships subsequent time and the method for ship's speed comprise:
The state equation of ship tracking system, observation equation and predicting covariance battle array equation is set up with Kalman filtering algorithm;
According to described initial monitoring value to state equation, observation equation and covariance matrix initialization;
Upgrade state value, calculate the status predication equation of current time;
The AIS message whether ship tracking system receives tracked boats and ships according to current time carries out the calculating of predicting covariance battle array respectively; If receive, calculate covariance matrix according to predicting covariance battle array equation and calculate corresponding filter gain matrix, then computing mode is estimated; If do not receive, then the error covariance matrix adding up acquisition before utilizing is weighted on average, the predicting covariance battle array of acquisition, and calculates corresponding filter gain matrix;
Upgrade current error covariance matrix, from the error covariance matrix of this renewal, obtain navigation coordinate and the ship's speed value of target boats and ships subsequent time;
The system continuous state equation of described ship tracking system in time t is:
Wherein: A is constant matrices,
N (t) is the system noise matrix in time t,
A
x, a
yfor the noise of state equation, affect the motion state of boats and ships;
Described system continuous state equation at the system state equation in discrete point moment is:
X(k+1)＝Φ(k+1,k)X(k)+G(k)N(k) (2)，
Wherein, k is time t is separated in a some time discrete point kth discrete point by time interval T, and is current time, k=1,2,3
According to the system state equation in discrete point moment, corresponding observation equation is:
Z(k)＝HX(k)+V(k) (3)，
Wherein: H is constant matrices,
V (k) is coordinate and rate matrices,
V
x, v
yfor the speed component of boats and ships to be tracked X, Y direction in the earth planimetric rectangular coordinates; X (k) is the system state equation in discrete point k moment;
Described renewal state value be target boats and ships by time discrete point k to the k+1 period, according to predicted value to navigation coordinate and the renewal of ship's speed value, described in the state of this period, predictive equation is:
Predicting covariance battle array equation is:
P(k+1|k)＝Φ(k+1|k)P(k|k)Φ
T(k+1|k)+G(k+1|k)Q(k)G
T(k+1|k)，
Wherein: system noise Q (k)=E [N (k) N (k)], E for solving mathematical expectation, covariance matrix, Φ that Φ (k+1|k) is predicated error for continuous-time domain to the transformation matrix of Disgrete Time Domain, P (k|k)
t(k+1|k) for continuous-time domain to the transformation matrix transposition of Disgrete Time Domain, G (k+1|k) for continuous-time domain to the transformation matrix of Disgrete Time Domain, Q (k) be system noise, G
t(k+1|k) for continuous-time domain is to the transformation matrix transposition of Disgrete Time Domain;
Described filter gain matrix computations is the calculating carried out according to following filter gain matrix equation, and this equation is:
K(k+1|k)＝P(k+1|k)H
T[HP(k+1|k)H
T+R(k+1)]
-1
Wherein, R (k+1) is observation noise covariance matrix, R (k+1)=E [V (k+1) V (k+1)];
Described state estimation be according to by status predication equation, filter gain matrix equation and observation equation obtain the calculating that state estimation equation carries out, this state estimation equation is:
The current error covariance matrix of described renewal is: P (k+1|k+1)=[I-K (k+1) H] P (k+1|k)
The error covariance matrix adding up acquisition before described utilization is weighted the average predicting covariance battle array obtained and is:
P(k+1k)＝τP(kk)+(1-τ)P(k-1k-1)。
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