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

处理高频雷达数据以提取海面参数以及相关应用，如在雷达系统部署在运动平台或船只上时补偿平台运动，通常的做法是首先从数据形成多普勒频谱，这涉及将获取的数据转换到频域。虽然这有一些优点，例如将一阶和高阶多普勒能量分离到频率空间的不同区域，但它也导致处理成本增加，并且由于数据到频域的变换而可能导致不准确的结果。 在我以前在这方面工作的基础上，这项研究的目的是放弃通常的高频雷达数据处理的第一步，将其转换到频域，而直接在时间域处理数据，在时间域中获取数据。我以前工作的结果表明，这导致了概念上更简单的算法，通常比它们的频域对应的算法更准确，而且在实现上也更快。 最近，从运动平台获取的高频雷达数据的运动补偿问题与从X波段雷达数据中对无人机(UAV)的微多普勒检测之间的联系被发现。这两个看似完全不同的问题之间的联系将被利用，以得出每个问题的新结果和解决方案，这可能对国防和安全行业有利，对这些行业来说，对非合作无人机的自动检测正成为一个日益重要和紧迫的问题。 高频雷达已被用作监测海洋表面参数的低成本替代方案，例如在距离其沿海部署长达数百公里的大片海洋上监测有效波高和主波向。基于时域高频雷达算法的研究将有助于加拿大降低高频雷达部署的成本和复杂性，这些高频雷达用于许多应用，如环境监测和国防。它还将允许在移动平台和船舶上更有效地部署这种系统，因为已经开发的对从这些平台和船舶获取的数据进行运动补偿的时域算法已经被证明比它们的频域同行更准确和有效。

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.