Bidirectional photoelectric measurement cooperative positioning method

Abstract

The invention provides a bidirectional photoelectric measurement cooperative positioning method, which is used for realizing high-precision and low-delay cooperative positioning through bidirectional photoelectric distance measurement and direction finding and data link synchronization between an unmanned ship and a patrolling flight device when the navigation equipment of the patrolling flight device has short-time faults (such as electromagnetic interference, shielding and high maneuvering states). The unmanned surface vehicle and the patrolling flying devices measure the other one by using self photoelectric equipment respectively, and position estimation values of the two patrolling flying devices are independently calculated respectively based on the high-precision position of the unmanned surface vehicle; the collaborative weight coefficient is calculated according to the measurement error of the photoelectric equipment of the two parties, weighted average fusion is carried out at the patrolling device end, the optimized positioning result is directly output, and the delay error caused by back-and-forth transmission of a data chain is effectively avoided. And reliable positioning information can be obtained by the patrolling device in a complex electromagnetic environment and a maneuvering condition. The method is suitable for a cooperative scene of the unmanned surface vehicle and the patrol aircraft, and has the advantages of good real-time performance, strong anti-interference performance, low cost and the like.

Description

Technical Field

[0001] This invention relates to a two-way photoelectric measurement cooperative positioning method, and more particularly to a two-way photoelectric measurement cooperative positioning method applicable to unmanned surface vessels and loitering aircraft in GNSS denied environments, belonging to the field of unmanned system platform cooperative navigation technology. Background Technology

[0002] Loitering drones, with their low cost and high mobility, have become an important component of modern unmanned systems. To control cost and size, loitering drones typically employ MEMS (Micro-Electro-Mechanical Systems) integrated navigation systems. However, MEMS inertial sensors themselves suffer from rapid error accumulation and low accuracy. Furthermore, their GNSS receiver modules are highly susceptible to signal interruption when faced with electromagnetic interference, physical obstructions, or poor antenna attitude due to high-speed maneuvers. This can cause the loitering drone to lose reliable positioning information, severely impacting its performance.

[0003] Unmanned surface vessels (USVs), as mobile platforms that persist at sea, are typically equipped with high-precision fiber optic inertial navigation systems (FINS). FINS features high short-term accuracy and strong autonomy, maintaining high-precision positioning capabilities even during short-term GNSS outages, providing stable and accurate self-position information far exceeding that of MEMS systems.

[0004] Existing collaborative positioning approaches largely rely on one-way assistance, where a high-precision platform (unmanned surface vessel) provides position reference or correction to a low-precision platform (loitering drone). This approach has significant limitations: First, it fails to fully utilize the sensing information of the low-precision platform itself, resulting in insufficient exploitation of the system's potential. Second, the common processing mode involves transmitting all raw data or intermediate results back to the unmanned surface vessel for centralized processing before sending the final result back to the loitering drone. In scenarios involving high-speed maneuvering loitering drones, the back-and-forth data transmission introduces a significant time delay, causing the sent positioning results to be severely outdated and unable to accurately reflect the instantaneous position of the loitering drone—a problem of "positioning not following maneuvering." This is fatal for loitering drones that require real-time, precise control. Summary of the Invention

[0005] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a two-way photoelectric measurement cooperative positioning method, which aims to solve the problems of inaccurate positioning and positioning delay of loitering rovers when GNSS fails.

[0006] The technical solution of this invention is: This invention discloses a bidirectional photoelectric measurement cooperative positioning method, comprising: The distance, azimuth, and elevation information of the unmanned surface vessel relative to the loitering drone are obtained from the optoelectronic equipment carried by the unmanned surface vessel. The distance, azimuth, and elevation information of the loitering drone relative to the unmanned surface vessel are obtained from the optoelectronic equipment carried by the loitering drone. Based on the position information of the fiber optic inertial navigation system on the unmanned surface vessel (USV), and combined with the distance, azimuth, and elevation angle information of the USV relative to the loitering vehicle obtained by the optoelectronic equipment on the USV, the estimated value of the current first position of the loitering vehicle is calculated. Based on the position information of the fiber optic inertial navigation system on the unmanned surface vessel (USV), and combined with the distance, azimuth, and elevation angle information of the loitering vehicle relative to the USV obtained by the optoelectronic equipment on the loitering vehicle, the estimated value of the current second position of the loitering vehicle is calculated. Based on the measurement errors of the optoelectronic devices mounted on unmanned surface vessels and loitering drones, calculate the collaborative weighting coefficient; Through the data link between the unmanned surface vessel (USV) and the loitering drone, the position information of the fiber optic inertial navigation system on the USV and the cooperative weight coefficients are synchronized to the loitering drone. Using the aforementioned collaborative weighting coefficients, the first position estimate and the second position estimate are weighted and averaged to obtain the optimized position estimate of the loitering drone, which serves as the real-time position of the loitering drone. The optimized position estimate of the loitering drone is synchronized to the unmanned surface vessel (USV) via a data link, enabling both the USV and the loitering drone to share and collaboratively perceive the loitering drone's position.

[0007] Furthermore, in the above method, the estimation of the current first position of the loitering pod is specifically as follows:

[0008]

[0009]

[0010] in, This is the estimated current first position of the loitering drone; The coordinates of the fiber optic inertial navigation system of the unmanned surface vessel; The equivalent elevation angle of the unmanned surface vessel's optoelectronic equipment is the angle between the target direction line MM1 and the horizontal plane. The equivalent azimuth of the unmanned surface vessel's optoelectronic equipment is the angle between the projection lines of the orientation line OY and the target direction line MM1 onto the horizontal plane of the imaging equipment. The spatial distance between the unmanned surface vessel (USV) and the loitering drone is measured by the optoelectronic equipment of the USV.

[0011] Furthermore, in the above method, the estimated second position of the loitering rovers is specifically as follows: =( )

[0012]

[0013] in, This is the estimated second position of the loitering rovers. The position coordinates of the unmanned surface vessel's fiber optic inertial navigation system obtained by the loitering glider via data link; It is the spatial distance between the unmanned surface vessel and the loitering drone; The equivalent elevation angle for the optoelectronic equipment of the loitering drone; The equivalent azimuth angle of the loitering drone's optoelectronic equipment; It is the spatial distance between the unmanned surface vessel and the loitering drone, measured by the loitering drone's optoelectronic equipment.

[0014] Furthermore, in the above method, the collaborative weight coefficient is specifically formulated as follows:

[0015] in, , For collaborative weighting coefficients; It concerns the covariance of the unmanned surface vessel's position error and the measurement error of its optoelectronic equipment. It relates to the covariance of the measurement errors of the loitering drone's optoelectronic equipment and the positional errors of the unmanned surface vessel.

[0016] Furthermore, in the above method, the optimized position estimation of the loitering drone is specifically as follows: When there is only one unmanned surface vessel:

[0017] in, The optimized position estimate for the loitering drone. , For collaborative weighting coefficients; This is the estimated second position of the loitering rovers. This is the estimated current first position of the loitering drone.

[0018] Furthermore, in the above method, the optimized position estimation of the loitering drone is specifically as follows: When there is more than one unmanned surface vessel:

[0019]

[0020] in, It is the first The location of the loitering drone is calculated by combining the positions of the unmanned surface vessels (USVs) and the loitering drones, where n is the total number of USVs. It relates to the covariance of the position error of the unmanned surface vessel i and the measurement error of its optoelectronic equipment. This concerns the measurement errors of the optoelectronic equipment of the loitering rovers and the referenced [reference number]. The composite covariance of the positional errors of the unmanned surface vessel; For the first Coordination weighting coefficient for unmanned surface vessels.

[0021] Furthermore, in the above method, the loitering pod uses a MEMS integrated navigation device, and the unmanned surface vessel uses a fiber optic inertial navigation system.

[0022] Furthermore, in the above method, the optoelectronic device includes an infrared, laser, or visible light sensor, which supports ranging and direction finding in an electromagnetic interference environment.

[0023] The advantages of this invention over the prior art are as follows: (1) This invention achieves high-precision, low-latency positioning of the patrol vehicle when the navigation equipment fails by using two-way ranging and direction finding of the unmanned surface vessel and the patrol vehicle, adaptive weighting of errors and data fusion at the patrol vehicle end.

[0024] (2) This invention proposes a two-way photoelectric measurement cooperative positioning method. Compared with the prior art, this invention adopts a two-way independent position calculation path and effectively improves the accuracy and robustness of the positioning results through information complementarity. It proposes a cooperative weight coefficient, which dynamically calculates the weight based on the real-time measurement error covariance, so that the fusion result automatically tends to the more reliable observation data source, realizing adaptive optimization of fusion position calculation. It proposes a computing architecture for fusion at the roving vehicle end, ensuring that the final positioning result is generated and applied in real time on the roving vehicle, solving the core problem of data link delay in cooperative positioning under high maneuverability of the roving vehicle. Photoelectric measurement means itself has strong anti-electromagnetic interference capability. Combined with this method, the roving vehicle can still maintain accurate navigation and positioning in high-confrontation environments such as strong electromagnetic interference and complete GNSS denial.

[0025] (3) The technical solution of the present invention can be extended to the scenario of multiple unmanned surface vessels cooperating with a single loitering vehicle. By increasing the observation source, the positioning accuracy and reliability can be further improved, providing technical support for future unmanned swarm collaborative systems.

[0026] (4) The bidirectional collaborative positioning method of this invention is based on the stable ranging and direction-finding capabilities of the optoelectronic devices carried by the unmanned surface vessel (USV) and the loitering drone, and the high positioning accuracy of the USV. By calculating the position of the loitering drone through bidirectional measurement and combining the measurement errors of the optoelectronic devices carried by the USV and the loitering drone, a collaborative weighting coefficient calculation method is proposed. The weighting coefficient is used to fuse the bidirectionally calculated positions to obtain the optimized estimated position of the loitering drone. If there are multiple USVs, a multi-USV single-device collaborative weighted average positioning method is extended. In terms of system architecture, the position fusion calculation is completed at the loitering drone end. The bidirectional measurement data is transmitted and synchronized in real time through a data link to ensure that the USV and the loitering drone perform positioning calculations under the same time reference. The data link adopts an anti-interference communication protocol to ensure high-precision and low-latency synchronization of position information under the high maneuverability of the loitering drone, and to ensure that the loitering drone has continuous and accurate positioning capabilities in complex adversarial environments.

[0027] (5) In this invention, the unmanned surface vessel (USV) and the loitering drone each use their own optoelectronic devices to measure the other, and based on the high-precision position of the USV, independently calculate the position estimates of the two loitering drones. Then, based on the measurement errors of the optoelectronic devices of both parties, a collaborative weighting coefficient is calculated, and a weighted average fusion is performed at the loitering drone end to directly output the optimized positioning result, effectively avoiding the delay error caused by the back-and-forth transmission of data links. The bidirectional optoelectronic measurement collaborative positioning method proposed in this invention overcomes the problems of poor navigation accuracy and susceptibility to interference of loitering drones, ensuring that the loitering drone can obtain reliable positioning information under complex electromagnetic environments and maneuvering conditions. This invention is applicable to collaborative scenarios between USVs and loitering drones, and has the advantages of good real-time performance, strong anti-interference ability, and low cost. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the overall architecture and data flow of the bidirectional cooperative positioning system described in this invention; Figure 2 This is a geometric schematic diagram of the unmanned surface vessel (USV) performing photoelectric measurements on the loitering vehicle according to the present invention. Figure 3 This is a geometric schematic diagram of the loitering drone of the present invention performing photoelectric measurements on an unmanned surface vessel; Figure 4 This is an extended schematic diagram illustrating the collaborative positioning of multiple unmanned surface vessels and a single loitering drone according to the present invention; Figure 5 This is a simulation result comparing the multi-ship single-device bidirectional photoelectric measurement fusion positioning of the present invention with the traditional multi-ship measurement fusion positioning. Detailed Implementation

[0029] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] like Figure 1 As shown, the present invention provides a bidirectional photoelectric measurement cooperative positioning method, comprising the following steps: S1. Two-way photoelectric measurement. The unmanned surface vessel and the loitering drone use their respective onboard photoelectric devices (such as laser rangefinders, infrared imaging systems, etc.) to measure distance and direction to each other under a unified time reference, and synchronously acquire two-way measurement data, including relative distance, azimuth angle and elevation angle.

[0031] S2. Unmanned surface vessel (USV) position calculation. The USV calculates its position coordinates based on high-precision coordinates provided by its own fiber optic inertial navigation system. (Using the Northeast Celestial Coordinate System as the navigation system), combined with the equivalent azimuth angle of the loitering pod relative to the vessel measured by the vessel's optoelectronic equipment. The angle between the orientation line OY and the target direction line MM1 projected onto the horizontal plane of the imaging device, with clockwise being positive; equivalent elevation angle. The angle between the target direction line MM1 and the horizontal plane, with upward being positive; and the spatial distance. ;like Figure 2 As shown, the first position estimate of the loitering drone is calculated. The calculation formula is:

[0032] S3. Loitering Vehicle Position Calculation. The loitering vehicle calculates its position based on the unmanned surface vessel's coordinates received via data link. The equivalent azimuth angle of the unmanned surface vessel relative to the loitering aircraft was measured by the optoelectronic equipment of this loitering aircraft. The angle between the orientation line OY and the target direction line MM1 projected onto the horizontal plane of the imaging device, with clockwise being positive; equivalent elevation angle. The angle between the target direction line MM1 and the horizontal plane, with upward being positive; and the spatial distance. The second position estimate of the loitering drone was calculated. The calculation formula is:

[0033] S4. Weighting Coefficient Calculation. The position error of the loitering drone depends on factors such as the measurement error of the UAV's optoelectronic equipment and the position error of the UAV itself. Based on the covariance of the measurement errors of the UAV and the loitering drone's optoelectronic equipment, the collaborative weighting coefficient is calculated. and The weighting coefficients reflect the reliability of the measurements taken by each party, and the specific formula is as follows:

[0034] in, It is the composite covariance of the unmanned surface vessel's position error and its optoelectronic equipment measurement error. It is the composite covariance of the measurement error of the loitering drone's optoelectronic equipment and the position error of the unmanned surface vessel used.

[0035] S5, weighted fusion positioning of the unmanned surface vessel (USV). The USV transmits its own position coordinates via data link. The first position estimate obtained by calculation and collaborative weighting coefficient The data is sent to the loitering drone. The loitering drone's computer uses the received unmanned surface vessel coordinates to estimate its own second position. and collaborative weighting coefficient Combined with the first position estimate received and collaborative weighting coefficient A weighted average fusion is performed to obtain the final optimized location estimate. :

[0036] The fusion result The data is generated directly at the loitering vehicle and immediately output to its flight control and navigation system for real-time positioning and trajectory planning, fundamentally avoiding the delay error introduced by transmitting the data back to the submarine for processing and then retransmitting it.

[0037] S6. Multi-vessel single-device collaborative weighted average positioning. When there are n (n>1) unmanned surface vessels (USVs), the multi-vessel single-device collaborative weighted average positioning method is adopted. First, based on S1-S5, n optimized position estimates of the loitering drone relative to the n USVs are calculated. Since the position error of the loitering drone depends on factors such as the measurement error of the loitering drone's own optoelectronic equipment, the measurement error of the unmanned surface vessel's optoelectronic equipment, and the position error of the unmanned surface vessel, the collaborative weighting coefficient is extended to a collaborative weighted average coefficient for the case of multiple unmanned surface vessels and a single drone. The calculation formula is as follows:

[0038] in, It is the first The composite covariance of the position error of an unmanned surface vessel and the measurement error of its optoelectronic equipment. The measurement error of the optoelectronic equipment of the loitering rovers and the referenced first... The composite covariance of the positional errors of an unmanned surface vessel.

[0039]

[0040] in It is the first The unmanned surface vessel and the loitering drone are fused and calculated according to the method described in steps 1-5 to obtain the optimized position estimate of the loitering drone.

[0041] S7. Synchronize collaborative information. The loitering drone will synchronize its optimized location information. By sending data back to the unmanned surface vessel (USV) via a data link, the USV can accurately and in real time grasp the location of the loitering drone, enabling situational awareness collaboration between the USV and the loitering drone.

[0042] Example The system for implementing this invention mainly includes: Unmanned surface vessel platform: equipped with a high-precision fiber optic inertial navigation system, high-performance optoelectronic measurement equipment (with ranging and angle measurement functions), data link terminal and computer.

[0043] Loitering platform: Equipped with a MEMS integrated navigation system, high-performance optoelectronic measurement equipment (with ranging and angle measurement functions), data link terminal and computer.

[0044] Anti-jamming data link: used to achieve low-latency, highly reliable two-way data communication between unmanned surface vessels and loitering drones.

[0045] Workflow diagram (see) Figure 1 .

[0046] This invention proposes a bidirectional photoelectric measurement-based cooperative positioning method, such as... Figure 1 As shown, it includes the following steps: S1. Initialization and Cooperative Triggering: The system powers on, establishes a communication link, and completes time synchronization. When the loitering rovers detect that the GNSS signal quality is below the threshold or that the navigation calculation is abnormal, they automatically send a cooperative positioning request command to the unmanned surface vessel.

[0047] S2. Synchronous Two-Way Measurement: The unmanned surface vessel's optoelectronic equipment, based on pre-programmed information or radar guidance, captures and stably tracks the loitering pod, performing real-time measurements. The loitering drone's optoelectronic equipment searches for, captures, and tracks the unmanned surface vessel (USV) based on its approximate location, and measures it in real time. .

[0048] S3. Weight Calculation and Parallel Position Calculation: The navigation system and photoelectric system provide error covariance based on a preset error model or real-time filtering results. and And calculate the weights according to the following formula. .

[0049]

[0050] Unmanned surface vessel (USV) end: The first position estimate is calculated using the following formula. .

[0051]

[0052] Loitering drone end: Based on the received unmanned surface vessel position and its own measurement value The second position estimate is calculated using the following formula. .

[0053]

[0054] S4. Data transmission and loitering vehicle integration: The unmanned surface vessel will integrate data packets... The data is sent to the loitering rovers via data link. Upon receiving the data, the loitering rovers' computer immediately executes the fusion algorithm. The optimized position is obtained. . The navigation filter, directly injected into the loitering drone, serves as an absolute position observation, rapidly correcting the accumulated errors of the MEMS inertial navigation and achieving precise positioning.

[0055] S5. Information Feedback and Closed Loop: The Loitering Wing will... The unmanned surface vessel (USV) sends the information back. The USV uses this information to update its tracking status of the loitering pod and can then perform cooperative positioning for the next cycle, forming a closed loop.

[0056] S6. Multi-vessel single-vessel cooperative localization: When there are n (n>1) unmanned surface vessels, first calculate n optimized position estimates of the loitering drone relative to the n unmanned surface vessels based on S1-S5. And calculate the collaborative weighted average coefficient of individual units in multiple boats. Finally, the optimized position estimate of the loitering aircraft for multiple vessels was obtained through fusion calculation. .

[0057]

[0058]

[0059] Specific examples of the technical solution of the present invention are as follows: Suppose that during a single-vessel, single-device mission, interference causes an anomaly in the GNSS status of the loitering drone. This anomaly signal triggers the loitering drone's two-way collaborative positioning preparation and is transmitted to the unmanned surface vessel (USV) via a communication link. Upon receiving the anomaly signal, the USV will perform the following tasks in parallel: it will send its own position back to the loitering drone to assist in position calculation; based on the ranging and lateral positioning results from its onboard optoelectronic equipment, it will calculate the loitering drone's current actual position; it will calculate the USV's current weighting coefficients and transmit the calculation results and weighting coefficients to the loitering drone's computer via the communication link. The loitering drone, combining its onboard optoelectronic equipment and the USV's position information, will calculate its own current position and weighting coefficients. Then, it will perform a weighted fusion calculation with its own weighting coefficients and the received USV position calculation results and weighting coefficients to obtain an optimized estimate of the loitering drone's current position. This optimized estimate is then transmitted back to the USV via the communication link, completing a GNSS anomaly-level collaborative positioning operation. The overall architecture and data flow diagram of the two-way collaborative positioning system are shown below. Figure 1 As shown.

[0060] The specific solution method for unmanned surface vessels is as follows: Figure 2 As shown, assuming the current position information of the unmanned surface vessel's fiber optic inertial navigation system is... Let the location of the unmanned surface vessel (USV) be M1, and the location of the loitering drone be M. Then, when the USV's onboard optoelectronic equipment measures the loitering drone, what is the azimuth angle of the optoelectronic equipment? The elevation angle is the angle between the projection lines of the orientation line OY and the target direction line MM1 onto the horizontal plane of the imaging device, with clockwise being positive; The angle between the target direction line MM1 and the horizontal plane is positive; the spatial distance from the unmanned surface vessel to the loitering pod is the spatial distance between points M and M1. The measurements were obtained in real time by optoelectronic equipment carried by the unmanned surface vessel. The results of the optoelectronic equipment measurements... , , and the position of the hull itself Based on the spatial geometric relationship between the unmanned surface vessel and the loitering drone, the current position of the loitering drone can be calculated. The formula is as follows:

[0061] Similarly, the specific solution method at the loitering rovers is as follows: Figure 3 As shown, the current position information of the unmanned surface vessel's fiber optic inertial navigation system is known to be... Similarly, if the location of the unmanned surface vessel (USV) is M1 and the location of the loitering drone is M, then when the loitering drone uses its electro-optical equipment to measure the USV, it can obtain the azimuth angle of the USV's electro-optical equipment. Elevation angle And the spatial distance between the unmanned surface vessel and the loitering drone measured by the onboard optoelectronic equipment of the loitering drone. Based on the spatial geometric relationship between the unmanned surface vessel (USV) and the loitering drone, the current position of the loitering drone can be calculated. The formula is as follows:

[0062] The weighting coefficients of the photoelectric measurement equipment for the unmanned surface vessel (USV) and the loitering drone were calculated at the USV end and the loitering drone end, respectively:

[0063] The unmanned surface vessel (USV) navigation system and the optoelectronic systems at both ends provide the covariance of the USV's position error and the measurement error of its optoelectronic devices based on a preset error model or real-time filtering results. Covariance of measurement errors of the loitering drone's optoelectronic equipment and position errors of the unmanned surface vessel. .

[0064] After completing the bidirectional photoelectric measurement position calculation and the cooperative weighting coefficient calculation, a weighted fusion positioning calculation is performed on the loitering drone to obtain the current optimized position estimate of the loitering drone:

[0065] During fusion, the measurement result with higher accuracy takes precedence, while the one with lower accuracy serves as a secondary verification tool. This weighting strategy ensures that the fused result... It surpasses any single positioning result in terms of accuracy and reliability, effectively avoiding the problem of cooperative positioning failure caused by the malfunction of a single-sided optoelectronic device. The fusion strategy at the loitering vehicle end enables this method to accurately locate the current position of the loitering vehicle even under highly maneuverable conditions.

[0066] Assuming there are n unmanned surface vessels and a single loitering drone, the diagram is as follows: Figure 4 As shown, an extended algorithm can be adopted: the multi-boat single-device collaborative weighted average positioning method.

[0067] Assume the position information of the fiber optic inertial navigation systems of n unmanned surface vessels are as follows: , … First, following the single-vessel, single-device method, a weighted fusion calculation is performed to determine the bidirectional photoelectric measurement collaborative optimization position estimation between each unmanned surface vessel and the loitering drone. , … Next, the collaborative weighted average coefficient of individual components across multiple vessels is calculated. as follows:

[0068] Finally, the optimized position estimation results of the multi-ship single-vessel loitering aircraft obtained by fusion calculation are as follows:

[0069] This invention has been verified through simulation and can reduce the positioning error of the loitering drone in a GNSS denied environment.

[0070] Simulation results are as follows Figure 5 As shown. To address short-term navigational anomalies in the loitering drone under normal circumstances, two unmanned surface vessels (USVs) can be used for collaborative positioning. Through simulation experiments, the coordinates of USV 1 were set to [100 -400 10], USV 2 to [100 200 10], and the loitering drone to [23.40 -267.32 138.56]. The azimuth error of the onboard photoelectric measuring equipment was set to <0.1 degrees, the pitch error to <0.05 degrees, and the ranging error to <1.5%. 500 simulated positioning calculations were performed, and the results are as follows. Figure 5 As shown in the figure, it can be seen that the proposed method (multi-vessel single-device two-way ranging fusion positioning) is superior to the traditional one-way measurement and positioning method based on unmanned surface vessel optoelectronic equipment. The root mean square value of the statistical error is 1.7708m for the proposed method and 2.4395m for the traditional method.

[0071] The loitering drone uses a MEMS integrated navigation device, while the unmanned surface vessel uses a fiber optic inertial navigation system. When the MEMS integrated navigation device of the loitering drone malfunctions, its positioning function is maintained through the aforementioned cooperative positioning method.

[0072] The location fusion calculation is completed at the loitering vehicle end, and the data link adopts an anti-interference communication protocol to ensure low-latency synchronization of location information under the high maneuverability conditions of the loitering vehicle.

[0073] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

[0074] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A bidirectional photoelectric measurement and cooperative positioning method, characterized in that, include: The distance, azimuth, and elevation information of the unmanned surface vessel relative to the loitering drone are obtained from the optoelectronic equipment carried by the unmanned surface vessel. The distance, azimuth, and elevation information of the loitering drone relative to the unmanned surface vessel are obtained from the optoelectronic equipment carried by the loitering drone. Based on the position information of the fiber optic inertial navigation system on the unmanned surface vessel (USV), and combined with the distance, azimuth, and elevation angle information of the USV relative to the loitering vehicle obtained by the optoelectronic equipment on the USV, the estimated value of the current first position of the loitering vehicle is calculated. Based on the position information of the fiber optic inertial navigation system on the unmanned surface vessel (USV), and combined with the distance, azimuth, and elevation angle information of the loitering vehicle relative to the USV obtained by the optoelectronic equipment on the loitering vehicle, the estimated value of the current second position of the loitering vehicle is calculated. Based on the measurement errors of the optoelectronic devices mounted on unmanned surface vessels and loitering drones, calculate the collaborative weighting coefficient; Through the data link between the unmanned surface vessel (USV) and the loitering drone, the position information of the fiber optic inertial navigation system on the USV and the cooperative weight coefficients are synchronized to the loitering drone. Using the aforementioned collaborative weighting coefficients, the first position estimate and the second position estimate are weighted and averaged to obtain the optimized position estimate of the loitering drone, which serves as the real-time position of the loitering drone. The optimized position estimate of the loitering drone is synchronized to the unmanned surface vessel (USV) via a data link, enabling both the USV and the loitering drone to share and collaboratively perceive the loitering drone's position.

2. The method according to claim 1, characterized in that, The estimated first position of the loitering rovers is as follows: in, This is the estimated current first position of the loitering drone; The coordinates of the fiber optic inertial navigation system of the unmanned surface vessel; The equivalent elevation angle of the unmanned surface vessel's optoelectronic equipment is the angle between the target direction line MM1 and the horizontal plane. The equivalent azimuth of the unmanned surface vessel's optoelectronic equipment is the angle between the projection lines of the orientation line OY and the target direction line MM1 onto the horizontal plane of the imaging equipment. The spatial distance between the unmanned surface vessel (USV) and the loitering drone is measured by the optoelectronic equipment of the USV.

3. The method according to claim 1, characterized in that, The current estimated second position of the loitering rovers is as follows: =( ) in, This is the estimated second position of the loitering rovers. The position coordinates of the unmanned surface vessel's fiber optic inertial navigation system obtained by the loitering glider via data link; The spatial distance between the unmanned surface vessel and the loitering drone; The equivalent elevation angle for the optoelectronic equipment of the loitering drone; The equivalent azimuth angle of the loitering drone's optoelectronic equipment.

4. The method according to claim 1, characterized in that, The collaborative weighting coefficient is calculated using the following formula: in, , For collaborative weighting coefficients; It concerns the covariance of the unmanned surface vessel's position error and the measurement error of its optoelectronic equipment. It relates to the covariance of the measurement errors of the loitering drone's optoelectronic equipment and the positional errors of the unmanned surface vessel.

5. The method according to claim 1, characterized in that, The optimized location estimation for the loitering drone is as follows: When there is only one unmanned surface vessel: in, For the optimized position estimate of the loitering drone, , For collaborative weighting coefficients; This is the estimated second position of the loitering rovers. This is the estimated current first position of the loitering drone.

6. The method according to claim 1, characterized in that, The optimized location estimation for the loitering drone is as follows: When there is more than one unmanned surface vessel: in, It is the first The location of the loitering drone is calculated by combining the positions of the unmanned surface vessels (USVs) and the loitering drones, where n is the total number of USVs. It relates to the covariance of the position error of the unmanned surface vessel i and the measurement error of its optoelectronic equipment. This concerns the measurement errors of the optoelectronic equipment of the loitering rovers and the referenced [reference number]. The composite covariance of the positional errors of the unmanned surface vessel; For the first Coordination weighting coefficient for unmanned surface vessels.

7. The method according to claim 1, characterized in that, The loitering drone uses MEMS integrated navigation equipment, while the unmanned surface vessel uses a fiber optic inertial navigation system.

8. The method according to claim 1, characterized in that, The optoelectronic device includes infrared, laser, or visible light sensors, and supports ranging and direction finding in electromagnetic interference environments.

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