Information processing and underwater situation fusion method based on double unmanned ship towed array

Abstract

The invention discloses an information processing and underwater situation fusion method based on a double-unmanned-ship towed array, and belongs to the technical field of ad hoc network communication, information fusion and target tracking, and the method comprises the steps: obtaining the platform information and detection information of two unmanned ships, the platform information comprises the GPS coordinate data of the unmanned ships, and the detection information comprises the GPS coordinate data of the unmanned ships; the detection information comprises a relative orientation between the unmanned ship and a target; converting the GPS coordinate data into coordinates in a north-east coordinate system; performing cross positioning according to the positions of the two unmanned ships and the relative orientation between the two unmanned ships and the target so as to realize initial positioning of the target; and after the initial positioning of the target is realized, the position of the target is corrected in real time by using a Kalman filtering technology. According to the invention, pure orientation positioning and tracking of the underwater target are realized, and observability of the detection system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of ad hoc network communication, information fusion and target tracking, and more specifically, relates to an information processing and underwater situation fusion method based on a dual unmanned boat towed array. Background Art

[0002] Cross-location technology is a method of determining the location of a target through multiple measurement points (or sensors). This technology is widely used in many fields, such as military, navigation, aviation, geological exploration, and intelligent transportation systems. Its core principle is based on measuring the same target from different locations, and then calculating the precise location of the target through these measurements. The most common cross-location technology is to determine the location of the target by measuring the angles from multiple fixed points (such as radar stations, sensors, or satellites) to the target. When the measurement lines of two or more fixed points intersect, the intersection is the location of the target. Since the towed array is often towed behind the boat for a distance and does not completely coincide with the GPS position of the platform, using the boat-side GPS information to locate the target will produce obvious deviations, and the GPS information is compensated for position according to the length of the towed array.

[0003] Ad Hoc Network Communication Technology is a network technology that does not require the establishment of a fixed infrastructure in advance, in which each node in the network can be used as both a terminal device and a relay station for data transmission. The key features of this technology are the flexibility and dynamism of the network, which can be quickly established as needed and can adapt to the dynamic changes of network nodes. Ad Hoc network technology has a wide range of applications in military, emergency rescue, disaster recovery, intelligent transportation systems and other fields. The network topology of an ad hoc network is not fixed and can change dynamically according to the addition, movement or departure of nodes. The network does not rely on a centralized control structure or infrastructure, and each node collaborates to maintain network connectivity and data transmission. The stability and efficiency of the network cannot be guaranteed without centralized management. Due to the influence of the stability of the relay nodes, the ad hoc network system will experience communication interruptions. It is necessary to consider the processing of information interruptions and use Kalman filters for prediction.

[0004] The Kalman filter algorithm (KF) proposed by Kalman in 1960 is one of the earliest filter algorithms used in target tracking and is the optimal algorithm for solving the linear Gaussian problem. After the target is located by cross positioning, the Kalman filter is used to achieve the position correction of target tracking. The Kalman filter process is shown in Figure 7 .

[0005] However, the current single-boat towed linear array sonar only has angle information and the position information of the platform itself, and the calculated target information has the problem of poor observability, which is a defect of single-boat detection. Summary of the invention

[0006] In view of the above defects or improvement needs of the prior art, the present invention proposes an information processing and underwater situation fusion method based on a dual unmanned boat towed array, which combines wireless ad hoc network communication with target detection technology, performs situation fusion according to the platform information and detection information of the two unmanned boats, and obtains observable state information of the target.

[0007] To achieve the above object, the present invention provides an information processing and underwater situation fusion method based on a dual unmanned boat towed array, comprising:

[0008] Acquire platform information and detection information of two unmanned boats, wherein the platform information includes GPS coordinate data of the unmanned boats, and the detection information includes the relative position between the unmanned boats and the target;

[0009] Convert GPS coordinate data into coordinates in the North-East coordinate system;

[0010] Cross-positioning is performed based on the positions of the two unmanned boats and their relative orientation to the target to achieve the initial positioning of the target;

[0011] After achieving the initial positioning of the target, the Kalman filter technology is used to correct the target position in real time.

[0012] In some optional implementation schemes, the platform information and detection information of the two unmanned boats are obtained through the UDP communication network using a wireless ad hoc network.

[0013] In some optional implementations, converting the GPS coordinate data into coordinates in a north-east coordinate system includes:

[0014] Select a local reference point as the origin of the North East coordinate system NED;

[0015] Convert the GPS coordinates of the unmanned boat into the Cartesian coordinate system under the Earth-centered Earth-fixed coordinate system ECEF;

[0016] Transform the difference of ECEF coordinates relative to the local reference point to the NED coordinate system.

[0017] In some optional implementation schemes, the cross positioning is performed according to the positions of the two unmanned boats and the relative positions between the two unmanned boats and the target to achieve the initial positioning of the target, including:

[0018] Convert the relative positions between the two unmanned boats and the target into the absolute positions between the two unmanned boats and the target;

[0019] The distance between the two unmanned boats and the target is calculated by the cross relationship based on the absolute orientation between the two unmanned boats and the target;

[0020] Taking one of the unmanned boats as the base point, the target position is calculated according to the distance between the two unmanned boats and the target.

[0021] In some optional implementation schemes, the relative bearing of the two unmanned boats is converted into an absolute bearing by True Bearing = Heading of Course + Relative Bearing, wherein Heading of Course is the heading angle, which refers to the direction in which the bow is pointing, measured clockwise from the north to the bow, Relative Bearing is the relative bearing, which refers to the angle from the bow to the target, and True Bearin is the absolute bearing, which refers to the direction measured clockwise from the north to the target.

[0022] In some optional embodiments, Calculate the distance between the two unmanned boats and the target, where L is the real-time distance between the two unmanned boats, θ1 is the observed absolute position of one unmanned boat, θ2 is the observed absolute position of the leading unmanned boat, θ0 is the clockwise angle between the line L connecting the two unmanned boats and the true north direction, R1 is the distance between one unmanned boat and the target, and R2 is the distance between the other unmanned boat and the target.

[0023] In some optional embodiments, Calculate the target position (x, y), with (x1, y1) as the coordinates of the base point.

[0024] In some optional embodiments, the method further comprises:

[0025] In the case of communication interruption in the ad hoc network, cross positioning is not performed, and the Kalman filter is used directly to predict the next position of the target.

[0026] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0027] The information processing and underwater situation fusion method based on the dual unmanned boat towed array of the present invention combines ad hoc network communication, coordinate conversion algorithm, cross positioning and Kalman filtering technology to provide an effective solution for underwater target detection and tracking. It can not only achieve stable target tracking in complex marine environments, but also maintain high operational flexibility and data processing capabilities when facing challenges such as communication interruption. It realizes pure azimuth positioning and tracking of underwater targets, and improves the observability of the detection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1It is a framework diagram of an information processing and underwater situation fusion method based on a dual unmanned boat towed array provided by an embodiment of the present invention;

[0029] Figure 2 is a schematic diagram of platform information and target information provided by an embodiment of the present invention;

[0030] Figure 3 It is a visualization schematic diagram of target location positioning provided by an embodiment of the present invention;

[0031] Figure 4 It is a display of target longitude and latitude information provided by an embodiment of the present invention;

[0032] Figure 5 It is a communication structure diagram provided by an embodiment of the present invention;

[0033] Figure 6 is a schematic diagram of cross positioning provided by an embodiment of the present invention;

[0034] Figure 7 This is a Kalman filtering principle provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0036] Figure 1 : is a framework diagram of an information processing and underwater situation fusion method based on a dual unmanned boat towed array provided by an embodiment of the present invention, including:

[0037] ① Network communication establishment and data reporting

[0038] In order to stably report the platform information and detection information of the two unmanned boats to the software, a UDP communication network was designed. The lower computer software on the boat side was connected to the upper computer processing software on the shore side using a wireless ad hoc network, and two multicast segments were set up to report the platform information and target information respectively. Figure 5 .

[0039] Establishment of ad hoc network communication: The shore control center and the two unmanned boats established a flexible communication network through three wireless ad hoc network radio equipment. This ad hoc network structure can maintain stable communication in complex marine environments.

[0040] Platform information reporting: Using a multicast IP address (e.g. 226.101.100.101), the unmanned boat reports its real-time platform information, including latitude and longitude, heading angle, and speed, to the shore control center. This information is crucial for real-time monitoring of the location and status of the unmanned boat.

[0041] Detection information reporting: Using another multicast IP address (for example: 226.101.100.102), the unmanned boat reports the target's detection information, including relative position, strength, etc. This information is the key data for effective target positioning and tracking.

[0042] ②Target search and detection

[0043] Start of target search: The unmanned boat starts the towed array sonar detection function and begins searching for underwater targets. At the same time, the shore control center starts the information processing software to receive and process data from the unmanned boat.

[0044] Deployment of towed array: The unmanned boat lowers the towed array cable and detects underwater targets through the sonar system.

[0045] ③Target positioning

[0046] Coordinate conversion: The received GPS coordinate data is converted into coordinates in the North-East coordinate system. This step is crucial to achieve accurate target positioning.

[0047] Since most sonar detections use the north-east coordinate system, and the platform's location information is generally the longitude and latitude information reported by GPS, a coordinate system conversion is required. The algorithm flow is as follows:

[0048] i. Define local reference points

[0049] First, choose a local reference point as the origin of the North-East coordinate system. This point is usually the starting point for measurement or navigation. The GPS coordinates (i.e. longitude, latitude and altitude) of this reference point are the basis of the conversion process.

[0050] ii. Convert GPS coordinates to Cartesian coordinates

[0051] Convert GPS coordinates (longitude, latitude and altitude) to a Cartesian coordinate system in the Earth-centered Earth-fixed coordinate system.

[0052] iii. Convert from ECEF to NED coordinates

[0053] Convert ECEF coordinates to NED coordinates. This requires converting the difference of ECEF coordinates relative to the local reference point to the NED coordinate system.

[0054] Cross positioning: After obtaining the positions of the two unmanned boats and the target detection information, the system performs cross positioning to achieve the initial positioning of the target. The user interface will display the intersection and relative position of the target, providing the operator with intuitive target position information.

[0055] Furthermore, in order to stably obtain the target position, a cross positioning algorithm is used to locate the target based on the received platform information and target information, such as Figure 6 As shown, the process is as follows.

[0056] i. Convert the relative position of the target into an absolute position

[0057] True Bearing=Heading of Course+Relative Bearing

[0058] Absolute bearing = heading angle + relative bearing, where the heading angle (Heading of Course) refers to the direction the bow is pointing, usually expressed in degrees, measured clockwise from the north to the bow. For example, north is 0° or 360°, east is 90°, south is 180°, and west is 270°. Relative bearing (Relative Bearing) refers to the angle from the bow to the target, also expressed in degrees, measured clockwise from the front of the bow (0°) to the target. For example, the target is 0° when it is directly in front of the bow, 90° to the right, 180° to the back, and 270° to the left. True bearing (True Bearing) refers to the direction measured clockwise from the north to the target. Absolute bearing indicates the position of the target relative to the North Pole of the Earth, and does not depend on the current orientation of the observer.

[0059] ii. Calculate distance based on intersection relationship

[0060]

[0061] Among them, L is the real-time distance between the two platforms, θ1 is the observed absolute orientation of 5003, θ2 is the observed absolute orientation of 5005, and θ0 is the clockwise angle between the line L connecting the two platforms and the true north direction. R1 is the distance between 5003 and the target, and R2 is the distance between 5005 and the target.

[0062] iii. Calculate the target position based on point 5003 (or 5005)

[0063]

[0064] The obtained (x, y) is the current coordinate position of the target in the north-east coordinate system.

[0065] ④Target tracking

[0066] Kalman filter application: After successfully locating the target, the system uses Kalman filter technology to make real-time corrections to the target position to improve tracking accuracy.

[0067] Communication interruption response: In the event of a communication interruption in the ad hoc network, the system will skip the cross-positioning step and directly use the Kalman filter to predict the next position of the target, ensuring the continuity and stability of target tracking.

[0068] Furthermore, the Kalman filter corrects the target position, such as Figure 7 When the platform information is interrupted, the state of the previous moment of the Kalman filter is used to predict the next moment to compensate for the information loss caused by the interruption.

[0069] 5003 and 5005 are the codes of two unmanned boats. Each platform corresponds to two visualization boxes on the left and right, which respectively display platform information and detection information. The detection information is the relative position of the detected target and the calculated absolute position. Figure 2 .

[0070] The north-east coordinate system with (ref_lat, ref_lon) as the center point has a scale of 1000m per grid. The platform position and the detected target position will be displayed in real time on the north-east coordinate system. As time goes by, a historical track of a period of time (30s) can be left. Figure 3 .

[0071] Convert the target's real-time position from the north-east coordinate system to the longitude and latitude coordinate system, and display the target's longitude and latitude information on this page, such as Figure 4 shown.

[0072] It should be pointed out that, according to the needs of implementation, the various steps / components described in this application can be split into more steps / components, and two or more steps / components or partial operations of steps / components can be combined into new steps / components to achieve the purpose of the present invention.

[0073] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for information processing and underwater situation fusion based on a dual unmanned boat towed array, characterized in that: include: Acquire platform information and detection information of two unmanned boats, wherein the platform information includes GPS coordinate data of the unmanned boats, and the detection information includes the relative position between the unmanned boats and the target; Convert GPS coordinate data into coordinates in the North-East coordinate system; Cross-positioning is performed based on the positions of the two unmanned boats and their relative orientation to the target to achieve the initial positioning of the target; After achieving the initial positioning of the target, the Kalman filter technology is used to correct the target position in real time.

2. The method according to claim 1, characterized in that Through the UDP communication network, the platform information and detection information of the two unmanned boats are obtained using the wireless ad hoc network.

3. The method according to claim 2, characterized in that The step of converting the GPS coordinate data into coordinates in a north-east coordinate system includes: Select a local reference point as the origin of the North East coordinate system NED; Convert the GPS coordinates of the unmanned boat into the Cartesian coordinate system under the Earth-centered Earth-fixed coordinate system ECEF; Transform the difference of ECEF coordinates relative to the local reference point to the NED coordinate system.

4. The method according to claim 3, characterized in that The cross positioning is performed according to the positions of the two unmanned boats and their relative positions to the target to achieve the initial positioning of the target, including: Convert the relative positions between the two unmanned boats and the target into the absolute positions between the two unmanned boats and the target; The distance between the two unmanned boats and the target is calculated by the cross relationship based on the absolute orientation between the two unmanned boats and the target; Taking one of the unmanned boats as the base point, the target position is calculated according to the distance between the two unmanned boats and the target.

5. The method according to claim 4, characterized in that The relative orientation of the two unmanned boats is converted into an absolute orientation by True Bearing = Heading of Course + Relative Bearing, where Heading of Course is the heading angle, which refers to the direction the bow is pointing in, measured clockwise from the north to the bow; Relative Bearing is the relative orientation, which refers to the angle from the bow to the target; True Bearin is the absolute orientation, which refers to the direction measured clockwise from the north to the target.

6. The method according to claim 5, characterized in that Depend on Calculate the distance between the two unmanned boats and the target, where L is the real-time distance between the two unmanned boats, θ1 is the observed absolute position of one unmanned boat, θ2 is the observed absolute position of the leading unmanned boat, θ0 is the clockwise angle between the line L connecting the two unmanned boats and the true north direction, R1 is the distance between one unmanned boat and the target, and R2 is the distance between the other unmanned boat and the target.

7. The method according to claim 6, characterized in that Depend on Calculate the target position (x, y), with (x1, y1) as the coordinates of the base point.

8. The method according to claim 7, characterized in that The method further comprises: In the case of communication interruption in the ad hoc network, cross positioning is not performed, and the Kalman filter is used directly to predict the next position of the target.

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