The artificial object detection and current velocity measurement using SAR ocean surface images

2017 ◽  
Author(s):  
Valery V. Strotov ◽  
Boris A. Alpatov ◽  
Maxim D. Ershov ◽  
Vadim S. Muraviev ◽  
Alexander B. Feldman ◽  
...  
Keyword(s):  
Object Detection ◽  
Current Velocity ◽  
Velocity Measurement ◽  
Ocean Surface ◽  
Surface Images

scholarly journals Improved Method to Suppress Azimuth Ambiguity for Current Velocity Measurement in Coastal Waters Based on ATI-SAR Systems

2020 ◽  
Vol 12 (20) ◽  
pp. 3288
Author(s):  
Na Yi ◽  
Yijun He ◽  
Baochang Liu
Keyword(s):  
Coastal Waters ◽  
Velocity Measurement ◽  
Phase Fluctuation ◽  
Ocean Surface ◽  
Pollution Monitoring ◽  
Speed Ratio ◽  
Improved Method ◽  
Eigenvalue Spectrum ◽  
Practical Applications ◽  
Along Track

Measurements of ocean surface currents in coastal waters are crucial for improving our understanding of tidal atlases, as well as for ecosystem and water pollution monitoring. This paper proposes an improved method for estimating the baseline-to-platform speed ratio (BPSR) for improving the current line-of-sight (LOS) velocity measurement accuracy in coastal waters with along-track interferometric synthetic aperture radar (ATI-SAR) based on eigenvalue spectrum entropy (EVSE) analysis. The estimation of BPSR utilizes the spaceborne along-track interferometry and considers the effects of a satellite orbit and an inaccurate baseline responsible for azimuth ambiguity in coastal waters. Unlike the existing methods, which often assume idealized rather than actual operating environments, the proposed approach considers the accuracy of BPSR, which is its key advantage applicable to many, even poorly designed, ATI-SAR systems. This is achieved through an alternate algorithm for the suppression of azimuth ambiguity and BPSR estimation based on an improved analysis of the eigenvalue spectrum entropy, which is an important parameter representing the mixability of unambiguous and ambiguous signals. The improvements include the consideration of a measurement of the heterogeneity of the scene, the corrections of coherence-inferred phase fluctuation (CPF), and the interferogram-derived phase variability (IPV); the last two variables are closely related to the determination of the EVSE threshold. Besides, the BPSR estimation also represents an improvement that has not been achieved in previous work of EVSE analysis. When the improved method is used on the simulated ocean-surface current LOS velocity data obtained from a coastal area, the root-mean-square error is less than 0.05 m/s. The other strengths of the proposed algorithm are adaptability, robustness, and a limited user input requirement. Most importantly, the method can be adopted for practical applications.

Mean current velocity measurement from a movable base

1994 ◽  
Vol 5 (5) ◽  
pp. 395-399
Author(s):  
N. P. Bulgakov ◽  
V. I. Remchukov ◽  
A. G. Evgushchenko
Keyword(s):  
Current Velocity ◽  
Velocity Measurement ◽  
Mean Current

scholarly journals Velocity Estimation of Ocean Surface Currents in along-Track InSAR System Based on Conditional Generative Adversarial Networks

2021 ◽  
Vol 13 (20) ◽  
pp. 4088
Author(s):  
He Yan ◽  
Qianru Hou ◽  
Guodong Jin ◽  
Xing Xu ◽  
Gong Zhang ◽  
...  
Keyword(s):  
Current Velocity ◽  
Surface Current ◽  
Ocean Surface ◽  
Velocity Estimation ◽  
Training Dataset ◽  
Generative Adversarial Networks ◽  
Surface Currents ◽  
Ocean Surface Currents ◽  
Ocean Surface Current ◽  
Along Track

Velocity estimation of ocean surface currents is of great significance in the fields of the fishery, shipping, sewage discharge, and military affairs. Over the last decade, along-track interferometric synthetic aperture radar (along-track InSAR) has been demonstrated to be one of the important instruments for large-area and high-resolution ocean surface current velocity estimation. The calculation method of the traditional ocean surface current velocity, as influenced by the large-scale wave orbital velocity and the Bragg wave phase velocity, cannot easily separate the current velocity, characterized by large error and low efficiency. In this paper, a novel velocity estimation method of ocean surface currents is proposed based on Conditional Generative Adversarial Networks (CGANs). The main processing steps are as follows: firstly, the known ocean surface current field diagrams and their corresponding interferometric phase diagrams are constructed as the training dataset; secondly, the estimation model of the ocean surface current field is constructed based on the pix2pix algorithm and trained by the training dataset; finally, the interferometric phase diagrams in the test dataset are input into the trained model. In the simulation experiment, processing results of the proposed method are compared with those of traditional ocean surface current velocity estimation methods, which demonstrate the efficiency and effectiveness of the novel method.

Sign in / Sign up

Export Citation Format

Share Document