SAR wave pattern directional ocean wave spectrum product optimization algorithm

Abstract

The invention discloses an SAR wave pattern directional ocean wave spectrum product optimization algorithm, which comprises the following steps: (1) a wind wave spectrum and a swell spectrum of the WVW directional ocean wave spectrum are separated; (2) a wind wave spectrum model is introduced; (3) spectrum segmentation and cross adjustment on the wind wave spectrum are carried out; and (4) the swell spectrum separated from the WVW directional ocean wave spectrum is effectively fused with a wind wave spectrum through Wen's spectrum adjustment to acquire a new directional ocean wave spectrum. The algorithm does not use a quasi-real time first guess spectrum which is hard to acquire but adopts an already-verified cross spectrum inversion result WVW product with a high inversion precision in the swell part, with the widely-applied wind wave spectrum (Wen's spectrum) model, the two are effectively fused, and a directional ocean wave spectrum with the swell information and the wind wave information is obtained.

Description

technical field [0001] The invention relates to an algorithm, in particular to an optimization algorithm of a SAR wave mode ocean wave direction spectrum product. Background technique [0002] The wave direction spectrum simultaneously describes the distribution of wave energy relative to the frequency and direction of the wave, and all wave parameters (such as effective wave height, average wave direction, average wave period, and average wavelength, etc.) can be obtained from it. Determination of wave direction spectrum is one of the core issues in ocean wave research. Spaceborne SAR is an active microwave imaging radar, which can obtain radar images with a spatial resolution as high as 1-10m, and has the advantage of working around the clock. Spaceborne SAR does not directly image ocean waves, but only interacts with short gravity waves or capillary waves on the ocean surface to form images. Based on the modulation effect of ocean waves on the short gravity waves on the...

AI Technical Summary

Problems solved by technology

[0007] 1. MPI inversion method: depends on the first guess spectrum, but it is difficult to obtain the quasi-real-time first guess spectrum

[0008] 2. Cross-spectrum inversion method: It is impossible to restore the high-frequency information of waves lost due to velocity bunching (that is, wind and wave information), and only the wave direction spectrum within the cut-off wave number can be obtained, not the complete wave direction spectrum

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