A system for simultaneous acquisition of apparent water spectra and inversion of water quality parameters based on unmanned surface vessels

By constructing a deep reinforcement learning model and a modality separation module on an unmanned surface vessel (USV), a vortex beam carrying orbital angular momentum is generated, solving the problem of optical field stability of USVs in marine environments. This enables high-precision inversion and source tracing of water quality parameters, and is applicable to nearshore environmental law enforcement and red tide disaster early warning.

CN121231390BActive Publication Date: 2026-06-30SECOND INST OF OCEANOGRAPHY MNR
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Patent Information

Application Number
CN202511324051.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-09-17
Publication Date
2026-06-30
Estimated Expiration
2045-09-17

AI Technical Summary

Technical Problem

In the marine environment, the roll and pitch motion caused by wave disturbances on unmanned surface vessels leads to dynamic changes in the angle between the incident light field and the water interface. Traditional IMU combined with Kalman filtering stabilization platforms are unable to compensate for severe disturbances, and the dynamic environment adaptability of smart sensors is insufficient.

Method used

A deep reinforcement learning model is constructed using a phase control module to generate a vortex beam carrying orbital angular momentum. Noise-free spectral data is extracted through a mode separation module, and a water quality parameter inversion model is constructed. Combined with an update weight module and a parameter distribution module, real-time inversion and distribution display of water quality parameters are achieved.

Benefits of technology

It improves the stability of the beam incident angle, enhances the robustness of the optical system in dynamic water bodies, and improves the accuracy of the spectral signal-to-noise ratio and pollution source tracing path, making it suitable for nearshore environmental law enforcement and red tide disaster early warning.

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Abstract

This invention discloses a system for simultaneous acquisition of apparent spectra and inversion of water quality parameters based on an unmanned surface vessel (USV), belonging to the field of intelligent sensing technology. The system includes: acquiring environmental parameters from the USV; constructing a deep reinforcement learning (PLSR) model and inputting the environmental parameters, outputting phase control commands; constructing a water quality parameter inversion model and inputting noise-free spectral data, outputting water quality parameters; when the turbidity in the water quality parameters exceeds a dynamic turbidity mutation threshold, triggering the acquisition of laboratory water quality verification data and comparing it with the water quality parameters to output turbidity error; when the turbidity error exceeds an inversion verification error threshold, updating the weights of the water quality parameter inversion model; performing spatial interpolation calculations based on the updated water quality parameter inversion model, outputting the water quality parameter distribution, and displaying a water quality parameter heatmap and tracing pollution source paths via an electronic map. This invention uses an incremental learning algorithm to update the PLSR weights online, improving the model's adaptation speed.
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Citation Information

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