Positioning compensation method and system based on shipborne laser wireless charging

Abstract

The invention relates to a positioning compensation method and system based on shipborne laser wireless charging, and belongs to the technical field of ships, an extended Kalman filtering algorithm is called, ship position information and target unmanned aerial vehicle position information are fused, and the relative position between a ship and a target unmanned aerial vehicle is obtained; and calling a model prediction control algorithm according to the energy receiving state of the target unmanned aerial vehicle and the relative position, and adjusting the beam direction of the laser beam during laser wireless charging, so as to carry out laser wireless charging on the target unmanned aerial vehicle according to the laser with the adjusted beam direction. The problems of aiming and energy transmission caused by relative movement between a mobile platform (ship) and a dynamic target (unmanned aerial vehicle) are solved, so that the charging efficiency and the system robustness are improved. According to the method, the relative positioning precision is improved through cooperative data acquisition, data fusion and prediction, target compensation control, closed-loop feedback optimization and other methods, the system robustness is enhanced, and the charging efficiency is improved.

Description

Technical Field

[0001] This invention relates to a positioning compensation method and system based on shipborne laser wireless charging, belonging to the field of marine technology. Background Technology

[0002] With the widespread application of drones in fields such as marine monitoring, search and rescue, and military reconnaissance, their endurance has become a critical bottleneck. Traditional battery power supply methods limit the mission duration of drones, while wireless power transfer technologies (such as laser charging) are considered an effective means to extend endurance. However, in the maritime environment, not only do ships experience periodic rolling due to waves, but the flight trajectory of drones also changes dynamically, making it difficult for the laser beam to accurately target the drone's laser battery. Existing laser charging solutions mostly rely on unilateral positioning (such as radar or visual tracking), lacking a collaborative mechanism between the ship and the drone, making it difficult to adapt to complex and dynamic environments, and resulting in insufficient energy transfer efficiency and stability.

[0003] In existing technologies, laser charging uses a laser tracking system installed on a ship platform to locate aerial drones. Since the drone is the target being searched, the laser transmitter cannot directly obtain its position; instead, radar or a tracking camera, combined with a ranging device, is used to calculate the drone's location. Clearly, existing solutions rely heavily on unilateral positioning (such as radar or visual tracking), lacking a collaborative mechanism between the ship and the drone. This makes them ill-suited for complex and dynamic environments, resulting in insufficient energy transfer efficiency and stability. Furthermore, single positioning methods lack accuracy in complex marine environments and are susceptible to signal blockage and electromagnetic interference. Therefore, a target compensation technology based on cooperative positioning is urgently needed. Summary of the Invention

[0004] The purpose of this invention is to provide a positioning compensation method and system based on shipborne laser wireless charging to solve the dynamic alignment problem and improve the practicality of marine laser charging.

[0005] To achieve the above objectives, this invention proposes a positioning compensation method based on shipborne laser wireless charging, comprising the following steps: 1) Use the extended Kalman filter algorithm to fuse the ship's position information and the target UAV's position information to obtain the relative position between the ship and the target UAV; 2) Based on the target UAV's energy receiving status and relative position, invoke the model predictive control algorithm to adjust the laser beam direction during laser wireless charging, so as to perform laser wireless charging on the target UAV according to the laser beam direction after adjustment.

[0006] Furthermore, when invoking the extended Kalman filter algorithm, the relative positions are adjusted by residual matching using noise covariance.

[0007] Furthermore, the energy reception status of the target UAV includes the deviation and power of the received energy; wherein, the deviation and power data of the received energy are obtained through the light intensity sensor and power detector on the target UAV.

[0008] Furthermore, when wirelessly charging the target drone with laser according to the laser beam direction adjustment, diffractive optical elements are used to shape the laser beam direction adjustment into a flat-top distribution.

[0009] Furthermore, the ship and the target robot are matched via radio frequency communication; based on the matched ship and the target robot, the ship's position information and the target UAV's position information are obtained.

[0010] On the other hand, the present invention proposes a positioning compensation system based on shipborne laser wireless charging, including a controller, the controller being used to perform the following method: 1) Use the extended Kalman filter algorithm to fuse the ship's position information and the target UAV's position information to obtain the relative position between the ship and the target UAV; 2) Based on the target UAV's energy receiving status and relative position, invoke the model predictive control algorithm to adjust the laser beam direction during laser wireless charging, so as to perform laser wireless charging on the target UAV according to the laser beam direction after adjustment.

[0011] Furthermore, when invoking the extended Kalman filter algorithm, the relative positions are adjusted by residual matching using noise covariance.

[0012] Furthermore, the energy reception status of the target UAV includes the deviation and power of the received energy; wherein, the deviation and power data of the received energy are obtained through the light intensity sensor and power detector on the target UAV.

[0013] Furthermore, when wirelessly charging the target drone with laser according to the laser beam direction adjustment, diffractive optical elements are used to shape the laser beam direction adjustment into a flat-top distribution.

[0014] Furthermore, the ship and the target robot are matched via radio frequency communication; based on the matched ship and the target robot, the ship's position information and the target UAV's position information are obtained.

[0015] The beneficial effects of this invention are as follows: It utilizes an extended Kalman filter algorithm to fuse the ship's position information and the target UAV's position information to obtain the relative position between the two. Based on the target UAV's energy reception status and the relative position, it invokes a model predictive control algorithm to adjust the laser beam direction during wireless laser charging. This allows for wireless laser charging of the target UAV according to the adjusted beam direction, solving the aiming and energy transfer challenges caused by the relative motion between the mobile platform (ship) and the dynamic target (UAV), thereby improving charging efficiency and system robustness. This invention improves relative positioning accuracy, enhances system robustness, and increases charging efficiency through cooperative data acquisition, data fusion and prediction, target compensation control, and closed-loop feedback optimization. Attached Figure Description

[0016] Figure 1 This is a flowchart of a positioning compensation method based on shipborne laser wireless charging proposed in this invention; Figure 2 This is a flowchart of a positioning compensation method based on shipborne laser wireless charging proposed in this invention in a practical application scenario; Figure 3 This is a system structure diagram of a positioning compensation system based on shipborne laser wireless charging proposed in this invention in a practical application scenario. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0018] The inventive concept of this invention is as follows: In order to enable shipborne laser to charge aerial drones, the invention utilizes real-time information interaction between the ship and the drone, employs extended Kalman filtering (EKF) to fuse multi-source data to predict their relative positions (i.e., the relative positions between the ship and the drone), combines model predictive control (MPC) to dynamically adjust the laser beam direction, and achieves closed-loop optimization through the drone feedback mechanism.

[0019] Furthermore, the wireless charging described in this invention refers to a novel energy transmission method that uses energy carriers other than electrical energy to achieve precise energy transmission and intelligent network interconnection in a three-dimensional environment without direct electrical contact.

[0020] Detailed implementation method 1: like Figure 1 The diagram shows a flowchart of a positioning compensation method based on shipborne laser wireless charging proposed in this invention, which includes steps S11 and S12, specifically: Step S11: The Extended Kalman Filter (EKF) algorithm is invoked to fuse the ship's position information and the target UAV's position information to obtain the relative position between the ship and the target UAV. Here, the Extended Kalman Filter algorithm refers to the Extended Kalman Filter (EKF), a recursive filter based on Kalman filtering theory, mainly used for state estimation of nonlinear dynamic systems. Before fusing the ship's position information and the target UAV's position information, the ship and the target robot are matched via radio frequency (RF) communication. Based on the matched ship and the target robot, the ship's position information and the target UAV's position information are obtained. Here, RF communication refers to Radio Frequency, which is an abbreviation for high-frequency alternating electromagnetic waves.

[0021] Step S12: Based on the target UAV's energy reception status and relative position, the model predictive control algorithm is invoked to adjust the laser beam direction during laser wireless charging, so that the target UAV is wirelessly charged according to the adjusted beam direction. Here, the model predictive control algorithm refers to model predictive control (MPC), whose core function is to achieve precise control of complex dynamic systems by predicting the future behavior of the system and optimizing the control strategy online. The target UAV's energy reception status is used to reflect the target UAV's energy reception situation. By combining the target UAV's energy reception status with the beam direction adjustment, it is ensured that the target UAV receives energy in the best reception state during the energy transmission process. In this invention, the target UAV's energy reception status preferably includes the energy reception deviation and power. The energy reception deviation and power data are obtained through the light intensity sensor and power detector on the target UAV.

[0022] Through the above steps S11-S12, the ship and the drone share position data; the relative position is predicted by fusing the data using extended Kalman filter; and the laser beam direction is adjusted based on model prediction control to accurately "track" the drone during the laser wireless charging process.

[0023] Method Detailed Implementation 2: The following explanation, in conjunction with a practical application scenario, details the positioning compensation method based on shipborne laser wireless charging proposed in this invention, which includes steps 1-5, specifically: Step 1: Collaborative data acquisition, in which the ship acquires its own position and attitude information through GPS and inertial measurement unit (IMU, a key sensor component used to measure and track the motion state of an object); the UAV acquires its own position, speed and attitude information through GPS and IMU, and shares ship-related data and UAV-related data in real time through wireless communication.

[0024] Step 2: Data fusion and prediction. In this step, extended Kalman filtering is used to fuse multi-source data (i.e., ship-related data and UAV-related data collected in Step 1) and to predict the relative positions between ships and UAVs. The process noise covariance is adaptively adjusted through residual matching.

[0025] Step 3: Target compensation control, which is based on model prediction control, dynamically adjusting the pointing angle of the laser beam according to the predicted relative position and the reception status fed back by the UAV.

[0026] Step 4: Closed-loop feedback optimization. In this step, the UAV measures the energy received from the laser beam using a light intensity sensor and a power detector. During the reception process, it generates deviation and power data, which are then fed back to the ship. This allows the UAV to adjust the pointing angle of the laser beam based on the feedback deviation and power data, forming a closed-loop control that optimizes alignment accuracy and energy efficiency.

[0027] Step 5: Beam shaping. In this step, diffractive optical elements (DOEs, which are optical elements that control the diffraction characteristics of light waves through micro-nano structures to achieve beam shaping, beam splitting, and other functions) are used to shape the laser beam into a flat-top distribution (that is, the light intensity of the laser beam is uniformly and flatly distributed in the cross-section, its energy is basically consistent in the effective area, and the light intensity drops sharply to zero at the edge, forming a "flat-top" shape), to ensure that the energy uniformly covers the UAV receiver.

[0028] In addition, in order to achieve "mutual constraint" between relative position, receiving state and pointing angle, steps 3 and 4 are executed cyclically during laser wireless charging until charging is completed.

[0029] Method Detailed Implementation 3: Following the specific embodiments described above, firstly, the ship and the UAV share position and attitude data via wireless communication; then, the extended Kalman filter is used to fuse the data to predict the relative position between the ship and the UAV; next, the laser beam direction is adjusted based on model predictive control to perform laser charging; during the laser charging process, the UAV provides feedback on its receiving status, forming a closed-loop optimization, and finally the laser charging process is completed.

[0030] It is particularly important to emphasize that: 1. Using Extended Kalman Filter (EKF) to fuse data for relative position prediction: EKF is a method that combines the position and velocity data of ships and UAVs to predict relative positions, aiding in laser targeting and predicting the relative position of UAVs. EKF is a nonlinear extension of the Kalman Filter, used to estimate state variables (such as position and velocity) in dynamic systems. The core steps of EKF include prediction and updating. Prediction involves predicting the current state based on the previous state and the system model; updating involves combining sensor observation data to correct the prediction result and output a more accurate state estimate.

[0031] 2. During the laser beam pointing adjustment process based on Model Predictive Control (MPC), the laser beam direction is dynamically adjusted according to the EKF output to ensure alignment with the UAV. The core of MPC in adjusting the laser beam direction is to optimize the control sequence, predict the UAV's position over a future period, and adjust the laser beam direction in advance, reducing alignment errors caused by system delays. Through data fusion and feedback, it can adapt to complex maritime environments (such as periodic wave interference), enabling the shipborne laser system to dynamically adjust the laser beam direction and accurately align with moving UAVs. It also copes with ship swaying and changes in UAV flight trajectory, exhibiting predictive, robust, and efficient characteristics.

[0032] Method Detailed Implementation 4: like Figure 2 The diagram shows a flowchart of a positioning compensation method based on shipborne laser wireless charging proposed in this invention, applied in a practical scenario. First, the position and attitude information of the ship, as well as the position, speed, and attitude information of the drone, are collected in real time, and the obtained ship and drone information are shared in real time. Next, the EKF algorithm is invoked to fuse the collected ship and drone information and predict their relative positions. Based on the obtained relative positions, a model predictive control algorithm is invoked to predict the future positions of the ship and drone, thereby adjusting the laser beam direction in advance to achieve laser beam direction compensation control, thus realizing angle compensation during laser beam charging.

[0033] Considering that the drone is in motion and the ship is also in a dynamic maritime environment, in order to ensure that the laser beam can be received by the drone efficiently and completely, during the charging process, the energy received by the drone is measured in real time through the light intensity sensor and power detector, generating deviation and power data; the deviation and power data are fed back to the ship to control and optimize the laser beam emitted by the ship, thereby optimizing the accuracy of the laser beam speed and energy efficiency.

[0034] In addition, considering that in order to ensure that the laser beam can uniformly cover the drone, optical elements can be used to reshape the laser beam.

[0035] As can be seen, the positioning compensation method based on shipborne laser wireless charging proposed in this invention employs cooperative positioning technology and a target compensation mechanism to solve the aiming and energy transfer challenges caused by the relative motion between the mobile platform (ship) and the dynamic target (UAV), thereby improving charging efficiency and system robustness. The relative positioning accuracy is improved through cooperative data acquisition, data fusion and prediction, target compensation control, and closed-loop feedback optimization, enhancing system robustness and increasing charging efficiency.

[0036] System Specific Implementation Method 1: On the other hand, this invention also proposes a positioning compensation system based on shipborne laser wireless charging, which includes a controller for executing the positioning compensation method based on shipborne laser wireless charging as described above. In practical applications, the preferred positioning compensation system includes a laser emitting module, a positioning and feedback module, a control unit, a communication module, an energy receiving module, etc., combined with adaptive noise adjustment and beam shaping technology to ensure efficient and stable energy transmission in dynamic maritime environments. Cooperative positioning technology solves the aiming and energy transmission challenges caused by the relative motion between the mobile platform (ship) and the dynamic target (UAV), significantly improving charging efficiency and system robustness. Once the UAV reaches the target, it can continue its mission, forming continuous support operations and avoiding mission interruptions due to prolonged charging. The positioning compensation system proposed in this invention will be explained below in conjunction with practical applications.

[0037] like Figure 3 The diagram shown illustrates the system structure of a positioning compensation system based on shipborne laser wireless charging proposed in this invention, applied in a practical scenario. Preferably, it is divided into a ship-side (transmitter) and a drone-side (receiver). The ship-side (transmitter) includes a laser emission module, a positioning and tracking module, a communication module, and a control unit. The drone-side (receiver) includes an energy receiving module, a status detection and feedback module, and a communication module. Through cooperative positioning and adaptive adjustment, closed-loop optimization and efficient transmission are achieved. The ship-side (transmitter end) includes a laser emission module, a positioning and tracking module, a communication module, and a control unit. The laser emission module consists of a laser, a beam shaping mechanism, and a dynamic pointing adjustment mechanism, enabling laser emission, beam shaping, and dynamic pointing adjustment. The positioning and tracking module comprises GPS and an inertial measurement unit (IMU), but radar or cameras can also be used. The communication module uses an RF (radio frequency) communication module to receive feedback from the UAV and transmit ship status, enabling information sharing and two-way communication. The control unit installed on the ship-side runs predictive algorithms, calculates target tracking information, and issues commands to the servo drive system of the dynamic pointing adjustment mechanism to control the laser beam emission angle.

[0038] The UAV receiver includes an energy receiving module, a status detection and feedback module, and a communication module. The energy receiving module, composed of a laser battery and an energy management system, efficiently converts light energy into electrical energy. The communication module uses an RF (radio frequency) communication module, matched with the ship's receiver, to transmit the UAV's position (latitude, longitude, and altitude) and velocity vector in real time, sharing position and attitude data. It employs low-latency, high-bandwidth wireless communication (such as 5G NR or millimeter wave) to ensure real-time transmission of UAV position data.

[0039] In addition, the specific implementation of the system can also refer to the specific implementation methods 1-4 above, which will not be repeated here.

[0040] This invention proposes a positioning compensation method and system based on shipborne laser wireless charging, used to charge aerial drones in dynamic maritime environments via shipborne lasers. Through cooperative positioning, closed-loop feedback, and beam shaping techniques, the alignment challenge of laser charging in dynamic maritime environments is solved, demonstrating significant technical advantages and application prospects. It is suitable for maritime drone missions requiring long-duration flight, such as marine monitoring, search and rescue, and patrol. Traditional battery life limitations can be overcome by shipborne laser charging, especially when drones cannot frequently return for resupply.

Claims

1. A positioning compensation method based on shipborne laser wireless charging, characterized in that, Includes the following steps: 1) Use the extended Kalman filter algorithm to fuse the ship's position information and the target UAV's position information to obtain the relative position between the ship and the target UAV; 2) Based on the target UAV's energy receiving status and relative position, invoke the model predictive control algorithm to adjust the laser beam direction during laser wireless charging, so as to perform laser wireless charging on the target UAV according to the laser beam direction after adjustment.

2. The positioning compensation method based on shipborne laser wireless charging according to claim 1, characterized in that, When invoking the extended Kalman filter algorithm, the relative positions are adjusted by residual matching using noise covariance.

3. The positioning compensation method based on shipborne laser wireless charging according to claim 1, characterized in that, The energy reception status of the target UAV includes the deviation and power of the received energy; wherein, the deviation and power data of the received energy are obtained through the light intensity sensor and power detector on the target UAV.

4. The positioning compensation method based on shipborne laser wireless charging according to claim 1, characterized in that, When wirelessly charging a target drone with a laser beam after the beam direction has been adjusted, diffractive optical elements are used to shape the laser beam after the beam direction has been adjusted into a flat-top distribution.

5. The positioning compensation method based on shipborne laser wireless charging according to claim 1, characterized in that, The ship is matched with the target robot via radio frequency communication; based on the matched ship and target robot, the ship's position information and the target UAV's position information are obtained.

6. A positioning compensation system based on shipborne laser wireless charging, characterized in that, Includes a controller, which is configured to perform the following methods: 1) Use the extended Kalman filter algorithm to fuse the ship's position information and the target UAV's position information to obtain the relative position between the ship and the target UAV; 2) Based on the target UAV's energy receiving status and relative position, invoke the model predictive control algorithm to adjust the laser beam direction during laser wireless charging, so as to perform laser wireless charging on the target UAV according to the laser beam direction after adjustment.

7. The positioning compensation system based on shipborne laser wireless charging according to claim 6, characterized in that, When invoking the extended Kalman filter algorithm, the relative positions are adjusted by residual matching using noise covariance.

8. The positioning compensation system based on shipborne laser wireless charging according to claim 6, characterized in that, The energy reception status of the target UAV includes the deviation and power of the received energy; wherein, the deviation and power data of the received energy are obtained through the light intensity sensor and power detector on the target UAV.

9. The positioning compensation system based on shipborne laser wireless charging according to claim 6, characterized in that, When wirelessly charging a target drone with a laser beam after the beam direction has been adjusted, diffractive optical elements are used to shape the laser beam after the beam direction has been adjusted into a flat-top distribution.

10. The positioning compensation system based on shipborne laser wireless charging according to claim 6, characterized in that, The ship is matched with the target robot via radio frequency communication; based on the matched ship and target robot, the ship's position information and the target UAV's position information are obtained.

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