CN116226633A

CN116226633A - Method, system, device and medium for real-time fusion identification of ship data

Info

Publication number: CN116226633A
Application number: CN202211599988.9A
Authority: CN
Inventors: 丁串串; 朱伟; 石乔木
Original assignee: Hangzhou Jingan Technology Co ltd
Current assignee: Hangzhou Jingan Technology Co ltd
Priority date: 2022-12-13
Filing date: 2022-12-13
Publication date: 2023-06-06

Abstract

The application relates to a method, a system, a device and a medium for real-time fusion identification of ship data, wherein the method comprises the following steps: acquiring and reporting ship data through AIS equipment and radar equipment respectively; AIS and radar data are read through the FlinkSql, and filtering and LAG function processing are carried out; performing association calculation on the processed AIS and radar data through the Flink flow table to obtain angle values of the AIS and the radar data, and screening the angle values through preset conditions to obtain a first association data table; and carrying out grouping processing on the first association data table according to the ID of the radar detection target and the MMSI ship number of the AIS detection ship to obtain a second association data table, screening the second association data table to obtain a corresponding relation between the ID of the radar detection target and the MMSI ship number detected by the AIS, and completing real-time fusion identification of the AIS data and the radar data of the ship. Through the method and the device, the fusion recognition speed is improved, and the ship can be accurately recognized.

Description

Method, system, device and medium for real-time fusion identification of ship data

Technical Field

The application relates to the technical field of satellite communication, in particular to a method, a system, a device and a medium for real-time fusion and identification of ship data.

Background

The AIS is automatic ship identification equipment, can realize communication among ships, and reports information such as ship name, calling sign, longitude and latitude of the ship. With the rapid development of ship monitoring technology, at present, when monitoring the trail of ship running on the sea, an AIS device and a radar device are generally used in combination, namely, target data detected by the AIS device and the radar device are subjected to fusion recognition, and the position of the ship and related information thereof which are recognized by the AIS device and the radar device in fusion are displayed on a chart, so that the information of the target ship is detected, and the safe sailing of the ship is ensured.

However, in the related art, fusion recognition of the detected ship data is realized through languages such as Java and Python, and the fused data is offline data, and is track correction combination performed under the condition that the actual running condition of a certain ship is clearly known. Therefore, the fusion recognition mode has high cost, low accuracy and low real-time performance.

At present, aiming at the problems of high data fusion cost, poor real-time performance and low accuracy of ship identification when monitoring ships in the related technology, no effective solution is proposed yet.

Disclosure of Invention

The embodiment of the application provides a method, a system, a device and a medium for real-time fusion and identification of ship data, which at least solve the problems of high data fusion cost, poor real-time performance and low accuracy of ship identification in the monitoring of ships in the related technology.

In a first aspect, an embodiment of the present application provides a method for real-time fusion identification of ship data, where the method includes:

acquiring ship data through AIS equipment and radar equipment respectively, and reporting the ship data to a message queue;

AIS data and radar data of the ship are read through the FlinkSql, and the read data are filtered and LAG function processed to obtain processed AIS data and radar data;

performing association calculation on the processed AIS data and radar data through a Flink flow table to obtain angle values of ship AIS data and radar data, and screening the calculated angle values through preset conditions to obtain a first association data table;

and grouping the first association data table according to the IDs of the radar detection targets and the MMSI ship numbers of the AIS detection ships to obtain the quantity and the fusion time of the MMSIs of the AIS detection ships fused with the IDs of each radar detection target, generating a second association data table, screening the second association data table to obtain the corresponding relation between the IDs of the radar detection targets and the MMSI ship numbers detected by the AIS, and completing real-time fusion identification of the AIS data and the radar data of the ships.

In some of these embodiments, filtering and LAG function processing the read data includes:

filtering AIS data with the MMSI ship number, longitude and latitude and empty time, and processing the AIS data through a LAG window function of the FlinkSql according to the MMSI ship number, the longitude and latitude of the point location and the water line time to obtain the longitude and latitude difference value between the current ship point location and the previous point location;

filtering out radar data with null longitude and latitude and time, and processing the radar data through a LAG window function of FlinkSql according to the ID of a radar detection target to obtain the longitude and latitude difference between the radar target point position and the previous point position.

In some embodiments, performing the association calculation on the processed AIS data and radar data through a link flow table includes:

correlating the processed AIS data with the radar data according to preset correlation conditions, and calculating absolute values of longitude and latitude distances and time differences of the AIS data and the radar data;

and calculating the angle values of the AIS data and the radar data through an ATAN2 function in the FlinkSql.

In some embodiments, the filtering the calculated angle value according to a preset condition to obtain the first association data includes:

screening the AIS data and the radar data according to the preset longitude and latitude distance and the calculated angle value to obtain the heading angle difference between the AIS detected ship and the radar detected ship;

and screening according to the radar data and the AIS data through a window function ROW_NUMBER of the FlinkSql to obtain AIS data with the lowest distance and the shortest time interval corresponding to the radar target data at each time point.

In some of these embodiments, screening the second association data table includes:

and windowing the second association data table through a ROW_NUMBER window function of the FlinkSql to obtain the corresponding relation between the ID of each radar detection target and the MMSI ship NUMBER detected by the AIS and the time of ship fusion.

In some of these embodiments, after completing the fusion identification of the AIS data and radar data of the ship, the method comprises:

and carrying out map dotting, alarming and real-time position and track monitoring on the ship according to the corresponding relation data.

In some of these embodiments, the message queue comprises a Kafka message queue.

In a second aspect, an embodiment of the present application provides a system for real-time fusion identification of ship data, the system comprising:

the database module is used for constructing a user information database according to the IP address database and longitude and latitude information;

the acquisition module is used for acquiring the ship data through the AIS equipment and the radar equipment respectively and reporting the ship data to the message queue;

the preprocessing module is used for reading AIS data and radar data of the ship through the FlinkSql, filtering the read data and performing LAG function processing on the read data to obtain processed AIS data and radar data;

the association fusion module is used for carrying out association calculation on the processed AIS data and radar data through the Flink flow table to obtain angle values of the ship AIS data and the radar data, screening the angle values obtained by calculation through preset conditions to obtain a first association data table,

In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method according to the first aspect described above when executing the computer program.

In a fourth aspect, embodiments of the present application provide a storage medium having stored thereon a computer program which, when executed by a processor, implements a method as described in the first aspect above.

Compared with the related art, the method for real-time fusion and identification of the ship data provided by the embodiment of the application obtains the ship data through the AIS equipment and the radar equipment respectively and reports the ship data to the message queue; AIS data and radar data of the ship are read through the FlinkSql, and the read data are filtered and LAG function processed to obtain processed AIS data and radar data; performing association calculation on the processed AIS data and radar data through the Flink flow table to obtain angle values of the ship AIS data and the radar data, and screening the calculated angle values through preset conditions to obtain a first association data table; the first association data table is grouped according to the IDs of radar detection targets and the MMSI ship numbers of AIS detection ships, the number and the fusion time of the MMSIs of the AIS detection ships fused by the IDs of each radar detection target are obtained, a second association data table is generated, the second association data table is screened, the corresponding relation between the IDs of the radar detection targets and the MMSI ship numbers detected by the AIS is obtained, and real-time fusion identification of AIS data and radar data of the ships is completed.

In the AIS and radar fusion mode in the prior art, offline data is used as carrier data, and Pyhton, various adjacent algorithms and the like are used for track correction under the condition that a ship is clearly known, or the offline data is used as fusion data for fusion dotting. The fusion instantaneity is poor, the accuracy is low, the adding, holding and maintaining of various algorithm models are not easy, and the fusion identification of the ship cannot be carried out accurately in real time. In comparison with the above

In the prior art, the Flink technology based on stream calculation carries out real-time fusion recognition of data from the time dimension, the space dimension and the direction dimension 5, so that the accuracy of fusion recognition of the ship can be rapidly improved, and meanwhile, the complexity of fusion recognition logic can be reduced. The method solves the problems of high data fusion cost, poor real-time performance and low accuracy of ship identification when monitoring ships in the related technology.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:

FIG. 1 is a flow chart of a method of real-time fusion identification of ship data according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a process for real-time fusion identification of ship data according to an embodiment of the present application;

FIG. 3 is a block diagram of a system for real-time fusion identification of ship data according to an embodiment of the present application; fig. 4 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described and illustrated below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of

To explain the present application and not to limit the present application. All other embodiments obtained by a person of ordinary skill in the art without inventive effort based on the embodiments provided herein are within the scope of this disclosure

Scope of the application. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.

Reference in the present application to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the embodiments described herein can be combined with other embodiments without conflict.

0 unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar terms herein do not denote a limitation of quantity, but rather denote the singular or plural. The terms "comprising," "including," "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "connected," "coupled," and the like in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as used herein means greater than or equal to two. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., "a and/or B" may mean: a exists alone, A and B exist together, and B exists alone. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.

The embodiment provides a method for real-time fusion and identification of ship data, fig. 1 is a flowchart of the method for real-time fusion and identification of ship data according to an embodiment of the application, and fig. 2 is a schematic flowchart of the flow of real-time fusion and identification of ship data according to an embodiment of the application, as shown in fig. 1 and 2, the flow includes the following steps:

step S101, acquiring ship data through AIS equipment and radar equipment respectively, and reporting the ship data to a message queue;

preferably, in this embodiment, real-time information of the ship is detected by the AIS device and the radar device, and information data related to the ship is obtained and reported to different topics of the message queue Kafka. It should be noted that other message queues may be used in this embodiment, which is not limited herein.

Step S102, AIS data and radar data of a ship are read through the FlinkSql, and the read data are filtered and LAG function processed to obtain processed AIS data and radar data;

in this embodiment, first, flink is used to subscribe to Topic of AIS data and Topic of radar data in the Kafka message queue respectively, and AIS data and radar data of the ship are read through FlinkSql. Wherein FlinkSql creates a table mapping Kafka-Topic and sets the water line.

Preprocessing read AIS data and radar data respectively, namely filtering out data with an MMSI ship number, longitude and latitude and empty time in the AIS data, using an LAG window function of the FlinkSql, sequencing according to a rising sequence of water line time by using the MMSI ship number as a partition key, and subtracting the longitude and latitude of the previous point position from the longitude and latitude of the current point position of the ship to obtain a longitude and latitude difference value between the current ship point position and the previous point position, wherein the longitude and latitude difference value forms a table A1; and the radar data is similar, firstly, radar data with empty longitude, latitude and time are filtered, the LAG function is used for windowing, the ID of a radar detection target is used as a partition key, and finally, longitude and latitude difference values of the radar target point position and the previous point position are respectively obtained, and the longitude and latitude difference values form a table A2.

Step S103, performing association calculation on the processed AIS data and radar data through a Flink flow table to obtain angle values of the ship AIS data and the radar data, and screening the calculated angle values through preset conditions to obtain a first association data table;

processed AIS data (i.e., table A1) and radar data (i.e., table A2) are obtained for a predetermined period of time and correlated through a link flow table according to predetermined correlation conditions. Specifically, if the time of the radar data is in the range of the time of the AIS data minus 10 seconds to the time of the AIS data plus 10 seconds, the association is successful. And then calculating absolute values of longitude and latitude distance and time difference values of the AIS data and the radar data, and then calculating an ATAN angle value of the AIS data and the radar data through an ATAN2 function in the FlinkSql. The angle values form a table A3, and the direction of travel can be determined from the calculated angle values. The parameters involved in the ATAN2 function include: the difference value between the current point latitude and the previous point latitude of the AIS/radar data, and the difference value between the current point longitude and the previous point longitude of the AIS/radar data.

Further, screening the data in the table A3 by a preset condition, and screening out data that the longitude and latitude distance of the AIS data and the radar data is smaller than a preset distance, such as fifty meters, and the ATAN angle value of the AIS is null, or the ATAN angle value of the radar is null, or the absolute value of the difference value between the ATAN angle value of the AIS and the ATAN angle value of the radar is smaller than 1.

The above-mentioned screened data represent the difference value of angle of course of AIS-detected ship and radar-detected ship, and it is necessary to judge whether the ship is in the same navigation direction by judging whether the angle difference is in the range of 0-pi or 0-pi.

After the association processing, the point location of one radar target ID may be associated with MMSI ship NUMBERs of a plurality of AIS data, so that window function row_number of FlinkSql needs to be used for windowing, wherein the radar target ID and time are used as partition keys, the ascending direction of the longitude and latitude distances of the AIS data and the radar data and the ascending direction of the time difference (i.e. the time difference between the AIS data and the radar data) are arranged, the AIS data with the lowest distance and the shortest time interval corresponding to each time point of the radar target data are screened out, and the corresponding data of the AIS data and the radar data form a first association data table A4.

Step S104, grouping the first association data table according to the IDs of the radar detection targets and the MMSI ship numbers of the AIS detection ships to obtain the quantity and the fusion time of the MMSIs of the AIS detection ships fused with the IDs of each radar detection target, generating a second association data table, screening the second association data table to obtain the corresponding relation between the IDs of the radar detection targets and the MMSI ship numbers detected by the AIS, and completing real-time fusion identification of AIS data and radar data of the ships.

After step S103 is completed, since the radar always has points, different points may be associated with different MMSI ship numbers, so that it is necessary to find the MMSI ship number of one AIS data most likely for each radar point. In this embodiment, the first association data table is first grouped according to the ID of the radar detection target and the MMSI ship number of the AIS detection ship, so that the COUNT number of the MMSI of the AIS detection ship fused with the ID of each radar detection target and the earliest and latest fused time can be obtained. And then screening the data with the COUNT data amount being greater than or equal to a preset value, wherein the screened data form a second associated data table A5. Preferably, the preset value in this embodiment is set to 10. It should be noted that if the amount of data is too small, this may be due to the sudden approach of the ship.

Further, the second association data table A5 is screened, specifically, in this embodiment, a window is opened on the table A5 by using a row_number window function of FlinkSql, wherein IDs of radar detection targets are used as partition keys, and the data are sorted in descending order of the counted COUNT NUMBER, so that a one-to-one correspondence between the IDs of each radar detection target and the MMSI ship NUMBER detected by the AIS, and the earliest and latest time of ship fusion are obtained.

Through the steps S101 to S104, the present embodiment performs real-time fusion recognition of data from the time dimension, the space dimension, and the direction dimension based on the Flink technique of stream computation, so that the accuracy of fusion recognition of the ship can be rapidly improved, and the complexity of fusion recognition logic can be reduced. The method solves the problems of high data fusion cost, poor real-time performance and low accuracy of ship identification when monitoring ships in the related technology.

In some embodiments, after the corresponding relation between the AIS data and the radar data is identified, fusion identification of the AIS data and the radar data of the ship is completed, map dotting, alarming and real-time position and track monitoring are performed on the ship according to the corresponding relation data.

It should be noted that the steps illustrated in the above-described flow or flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.

The embodiment also provides a system for real-time fusion and identification of ship data, which is used for implementing the above embodiment and the preferred implementation, and is not described in detail. As used below, the terms "module," "unit," "sub-unit," and the like may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Fig. 3 is a block diagram of a system for real-time fusion recognition of ship data according to an embodiment of the present application, and as shown in fig. 3, the system includes an acquisition module 31, a preprocessing module 32, and an association fusion module 33:

an acquiring module 31, configured to acquire ship data through the AIS device and the radar device, and report the ship data to the message queue; the preprocessing module 32 is configured to read AIS data and radar data of a ship through the FlinkSql, and perform filtering and LAG function processing on the read data to obtain processed AIS data and radar data; the association fusion module 33 is configured to perform association calculation on the processed AIS data and radar data through the link flow table to obtain angle values of the ship AIS data and radar data, screen the angle values obtained by calculation through preset conditions to obtain a first association data table, group the first association data table according to the ID of the radar detection target and the MMSI ship number of the AIS detection ship to obtain the number and fusion time of the MMSI of the AIS detection ship fused with the ID of each radar detection target, generate a second association data table, screen the second association data table to obtain a corresponding relation between the ID of the radar detection target and the MMSI ship number detected by the AIS, and complete real-time fusion identification of the AIS data and the radar data of the ship.

Through the system, the Flink technology based on stream calculation carries out real-time fusion recognition of data from time dimension, space dimension and direction dimension, so that the accuracy of fusion recognition of the ship can be improved rapidly, and meanwhile, the complexity of fusion recognition logic can be reduced. The method solves the problems of high data fusion cost, poor real-time performance and low accuracy of ship identification when monitoring ships in the related technology.

It should be noted that, specific examples in this embodiment may refer to examples described in the foregoing embodiments and alternative implementations, and this embodiment is not repeated herein.

The above-described respective modules may be functional modules or program modules, and may be implemented by software or hardware. For modules implemented in hardware, the various modules described above may be located in the same processor; or the above modules may be located in different processors in any combination.

The present embodiment also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.

Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.

In addition, in combination with the method for real-time fusion and identification of ship data in the above embodiment, the embodiment of the application can be realized by providing a storage medium. The storage medium has a computer program stored thereon; the computer program, when executed by a processor, implements the method of real-time fusion identification of ship data of any of the above embodiments.

In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements a method for real-time fusion identification of ship data. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

In one embodiment, fig. 4 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, as shown in fig. 4, and an electronic device, which may be a server, may be provided, and an internal structure diagram thereof may be shown in fig. 4. The electronic device includes a processor, a network interface, an internal memory, and a non-volatile memory connected by an internal bus, where the non-volatile memory stores an operating system, computer programs, and a database. The processor is used for providing computing and control capability, the network interface is used for communicating with an external terminal through network connection, the internal memory is used for providing environment for the operation of an operating system and a computer program, the computer program is executed by the processor to realize a method for fusing and identifying ship data in real time, and the database is used for storing the data.

It will be appreciated by those skilled in the art that the structure shown in fig. 4 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the electronic device to which the present application is applied, and that a particular electronic device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

It should be understood by those skilled in the art that the technical features of the above-described embodiments may be combined in any manner, and for brevity, all of the possible combinations of the technical features of the above-described embodiments are not described, however, they should be considered as being within the scope of the description provided herein, as long as there is no contradiction between the combinations of the technical features.

The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. A method for real-time fusion identification of ship data, the method comprising:

2. The method of claim 1, wherein filtering and LAG function processing the read data comprises:

3. The method of claim 1, wherein correlating the processed AIS data with radar data via a link flow table comprises:

4. The method of claim 1, wherein the filtering the calculated angle values by the preset condition to obtain the first association data table includes:

5. The method of claim 1, wherein screening the second association data table comprises:

6. The method of claim 1, wherein after completing the fusion identification of the AIS data and the radar data of the ship, the method comprises:

7. The method of claim 1, wherein the message queue comprises a Kafka message queue.

8. A system for real-time fusion identification of ship data, said system comprising:

9. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of claims 1 to 7.

10. A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of claims 1 to 7 when run.