Sea Wave Profile Reconstruction With Segmented Radar Sampling
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Solution Overview
Problem
Existing methods for deterministic sea wave prediction (DSWP) using mixed space-time sampling data are computationally complex, requiring O(R) operations, where R is the number of radar beams, making real-time sea wave profiling challenging due to the need for complex processing units.
Innovation Solution
The method involves separating the sampling data into sub-sets, determining sub-set sea models using a subsampled set of wavenumbers, up-sampling these models, and combining them to form a complete sea model, reducing the number of operations to O(max{RL, log2L}), where R is the number of radar beams and L is a user-selectable integer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing mixed space-time approaches are used to determine spectral coefficients, then sea wave prediction can be achieved, but computational complexity increases to O(R) operations requiring complex processing units
Solution Approach 1:
The patent divides the radar scan data into multiple segments (first portion and second portion) corresponding to different angular ranges. Each segment is processed independently to determine spectral coefficients, reducing the computational burden on any single processing unit while maintaining overall prediction accuracy through combination of segment results.
Solution Approach 2:
The patent transforms the computational problem from a full O(R) operation space to a reduced dimension by utilizing the angular segmentation and selecting representative beam indices from each segment. This dimensional reduction enables simpler processing units to achieve the same prediction reliability.
2Productivity
If real-time sea wave profiling is implemented, then operational responsiveness improves, but computational operations required increase to O(R) per scan
Solution Approach 1:
By segmenting the radar data angularly and processing each segment independently with reduced computational operations, the patent enables real-time processing. The total processing time is reduced from O(R) to a lower complexity operation count, allowing the system to keep up with real-time radar scans without significant delays.
Solution Approach 2:
The patent processes only the necessary portion of data from each radar scan by selecting representative beam indices from each angular segment rather than processing all R beams fully. This partial action approach maintains sufficient prediction accuracy while dramatically reducing processing time to enable real-time operation.
Data Source
AI summary
A method and system for deterministic sea wave profiling and/or prediction. Mixed space-time sampling data of the sea is obtained, where the sampling data is helical in time and space and comprises a plurality of beam waveforms. The sampling data is separated into a plurality of sub-sets of the sampling data, where each sub-set of the sampling data corresponds to a region of the sea. For each sub-set of the sampling data, a sub-set sea model is determined using a subsampled set of wavenumbers. Determining the sub-set sea model is based on the beam waveforms in the corresponding sub-set of the sampling data. The sub-set sea models are up-sampled and then combined to form a complete sea model.