Further Investigation of Ocean Remote Sensing Using High-frequency and Microwave Radars

高频微波雷达海洋遥感的进一步研究

• 批准号: RGPIN-2017-04508
• 负责人: Huang, Weimin
• 金额: $ 2.7万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752790
• 关键词: Further; Investigation; Ocean; Remote; Sensing

During the past four decades, both high frequency surface wave radar (HFSWR) and microwave nautical radar (MNR) have become important tools for ocean remote sensing. HFSWR is able to provide sea surface current, wind, wave and target information “over the horizon” due to the strong interactions between the HF (3-30 MHz) signal and the ocean gravity wave field. Increasingly frequent marine activities (e.g. transportation, offshore oil and gas exploration) result in the necessity for installing such radar systems on floating platforms (e.g., a ship or an offshore oil platform). However, a major challenge is that the platform motion will deteriorate the radar performance by distorting the radar Doppler spectra. Another challenge to the HF radar applications is contamination due to ionospheric clutter. To improve the utility of HF radar, both problems must be addressed.Although X-band MNR, which operates at around 10 GHz on land or ship, is a sort of “line-of-site” sensor, it can image the sea surface with relatively high spatial and temporal resolutions. Unfortunately, its performance in sea surface sensing will be negatively affected by rain. In order for this widely deployed system to provide real-time information under all weather conditions, countermeasures for rain-contamination need to be sought.The proposal aims to solve the above challenges by developing both theoretical models and application algorithms. The theoretical models are expected to provide an improved understanding of radio wave scattering from the ocean surface, while the application algorithms will bring significant assets to both HF and MNR radar communities and can be integrated into commercial radar products that may be exported internationally. A long-term goal of this research is to build a broad coastal ocean observation network that consists of HFSWR, MNR, Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) in Eastern Canada and Arctic regions. Such a network will improve marine safety through providing high quality sea surface data products to meet the ongoing needs of the Department of National Defence, Fisheries and Oceans Canada, the Canadian Coast Guard and other marine stakeholders such as the shipping and oil and gas industries. With financial support from NSERC, Memorial University will continue to train highly qualified personnel to augment the radar ocean remote sensing capacity of Canada and maintain its status as one of the leaders in this field.

在过去的四十年中，高频表面波雷达（HFSWR）和微波航海雷达（MNR）已成为海洋遥感的重要工具。由于HF（3-30 MHz）信号与海洋重力波场之间的强烈相互作用，HFSWR能够在“地平线上”提供海面电流，风，波和目标信息。越来越频繁的海洋活动（例如，运输，海上石油和天然气勘探）导致在浮动平台上安装此类雷达系统（例如，船舶或海上油平台）。但是，一个主要的挑战是平台运动将通过扭曲雷达多普勒光谱来确定雷达的性能。 HF雷达应用的另一个挑战是由于电离层混乱而污染。为了改善HF雷达的效用，必须解决这两个问题。尽管X频段MNR在陆地或船上的10 GHz约为10 GHz，这是一种“现场”传感器，但它可以用相对高空间和临时分辨率对海面进行成像。不幸的是，它在海面灵敏度中的表现将受到雨水的负面影响。为了使这个广泛部署的系统在所有天气条件下提供实时信息，需要害怕雨水污染的对策。该提案旨在通过开发理论模型和应用算法来解决上述挑战。预计理论模型将对海洋表面的无线电波散射有了深入的了解，而应用算法将为HF和MNR雷达社区带来重要资产，并可以集成到可能在国际上出口的商业雷达产品。这项研究的一个长期目标是建立一个由HFSWR，MNR，全球导航卫星系统（GNSS）和合成孔径雷达（SAR）组成的广泛的沿海海洋观察网络（SAR）和北极地区。这样的网络将通过提供高质量的海面数据产品来提高海洋安全，以满足加拿大国防部，渔业和海洋，加拿大海岸警卫队和其他海洋利益相关者（例如运输和石油和天然气行业）的持续需求。在NSERC的财政支持下，纪念大学将继续培训高素质的人，以增强加拿大的雷达海洋遥感能力，并保持其作为该领域领导者之一的地位。