Time-domain processing for ocean surface parameter extraction from HF-radar data and related applications

从高频雷达数据提取海洋表面参数的时域处理及相关应用

• 批准号: RGPIN-2020-07155
• 负责人: Shahidi, Reza
• 金额: $ 2.04万
• 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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741628
• 关键词: Time; domain; processing; ocean; surface

The usual approach to the processing of high-frequency radar data for ocean surface parameter extraction, as well as related applications, such as compensation for platform motion when the radar system is deployed on a moving platform or ship, has been to first form the Doppler spectrum from the data, which involves transforming the acquired data to the frequency domain.  Although this has some advantages, such as separating out the first and higher-order Doppler energies into different regions in frequency space, it also leads to increased processing cost and potentially less accurate results due to transformation of the data to the frequency domain. Building on my previous work in the area, the research in this proposal aims to forego the usual first step of HF radar data processing of transforming it to the frequency domain, and instead process the data directly in the time domain, where it is acquired.  Results from my previous work shows that this leads to conceptually-simpler algorithms which are often more accurate than their frequency-domain counterparts, and also faster in their implementations. Recently, links have been discovered between the problems of motion compensation of HF radar data acquired from moving platforms and Micro-Doppler detection of e.g., Unmanned Aerial Vehicles (UAVs) from X-band radar data.  Links between these two seemingly-disparate problems will be exploited to derive new results and solutions to each of them, which could potentially be of benefit to the defense and security industries, for which automatic detection of non-cooperative UAVs is becoming an increasingly important and pressing problem. High-frequency radar is already used as a lower-cost alternative to monitoring ocean surface parameters such as significant wave height and principal wave direction over large swaths of the ocean, up to several hundreds of kilometres away from their coastal deployments.  Research based on time-domain high-frequency radar algorithms will help Canada by reducing the cost and complexity of high-frequency radar deployments used for many applications, such as environmental monitoring and national defence.  It will also allow for more effective deployments of such systems on moving platforms and ships, as already-developed time-domain algorithms for motion compensation of data acquired from these platforms and ships have already been shown to be more accurate and efficient than their frequency-domain counterparts.

处理用于海洋表面参数提取的高频雷达数据以及相关应用（例如当雷达系统部署在移动平台或船上时补偿平台运动）的通常方法是首先从数据形成多普勒频谱，这涉及将所获取的数据变换到频域。例如将一阶和更高阶多普勒能量分离到频率空间中的不同区域中，由于将数据变换到频域，这还导致处理成本增加和可能不太精确的结果。基于我以前在该领域的工作，本提案中的研究旨在放弃通常的高频雷达数据处理的第一步，将其转换到频域，而是直接在时域中处理数据，在时域中获取数据。我以前的工作结果表明，这导致概念上更简单的算法，通常比频域算法更准确，并且在实现中也更快。最近，已经发现了从移动平台获取的HF雷达数据的运动补偿问题与例如，这两个完全不同的问题之间的联系将被利用，以获得新的结果和解决方案，这可能有利于国防和安全行业，对这些行业来说，非合作无人机的自动检测正在成为一个越来越重要和紧迫的问题。高频雷达已被用作监测海洋表面参数的低成本替代方案，如在距其沿海部署数百公里的大片海洋上监测有效波高和主波方向，基于时域高频雷达算法的研究将有助于加拿大降低用于许多应用的高频雷达部署的成本和复杂性，它还将使这些系统能够更有效地部署在移动平台和船舶上，因为已经开发的用于对从这些平台和船舶获得的数据进行运动补偿的时域算法已被证明比频域算法更准确和有效。