Enhanced Wave Buoy Analogy Through Heading Adjustment Strategy Based on Restricted Isometry Property
Wave Buoy Analogy (WBA) is a cost-effective method for real-time sea state estimation using ship motion responses, but its accuracy is limited by the ship’s inherent hydrodynamic properties (RAOs). When a ship is on specific courses (like head, following, or beam seas), “power leakage” can occur in the motion response spectra due to inadequate response excitation. Concurrently, the unevenly distributed RAOs can cause numerical instability when solving the inverse problem, degrading estimation performance.
To address this, a research team from Tsinghua University, Shenzhen International Graduate School, has proposed an adaptive heading adjustment strategy based on the “Restricted Isometry Property” (RIP). This study uses RIP theory to pre-evaluate the WBA performance under the current sea state using only RAOs as input.
The strategy first identifies the peak wave frequency and mean direction of the current sea state. The algorithm then checks if the ship is in a predefined “inferior” sea state (e.g., head or following seas). If so, a heading adjustment is imperative. If not, the algorithm further checks if the RIP assessment value exceeds a preset threshold. If the value is too high (implying poor performance), a heading adjustment is also deemed necessary.
This strategy is applicable for vessels equipped with Dynamic Positioning (DP) systems. The algorithm searches for an optimal heading with the lowest RIP value within a preset adjustment range (e.g., ±40°) and controls the vessel to rotate to that angle. Through this active adjustment, the ship can avoid inaccurate measurements and significantly improve the accuracy and robustness of the WBA estimation.
The related research, titled “Enhanced Wave Buoy Analogy Through Heading Adjustment Strategy Based on Restricted Isometry Property,” was published in the ASME Journal of Offshore Mechanics and Arctic Engineering. The authors include Taiyu Zhang, Can Ma, Shangyuan Chen, and Zhengru Ren. This work was supported by the Natural Science Foundation of Guangdong Province, China, and the Shenzhen Science and Technology Program, China.