UAV-BORNE UWB RADAR FOR SNOWPACK SURVEYS

Source at https://hdl.handle.net/11250/2649630In this report we summarize the capabilities and technical characteristics of our UAV-borne UWB radar system, designed for conducting snow surveys. We developed an ultrawideband snow sounder that is capable of imaging snow stratigraphy with a 5 cm range resolution. The radar can be carried by an octocopter UAV in order to carry out airborne snowpack surveys. During a demonstration on Andøya, we showed that the radar was capable of resolving snow stratigraphy in wet snow conditions, as well as detecting a buried person under 1.5 m of wet snow. In this report, we present the results of the demonstration in detail. We furthermore discuss capabilities and incapabilities of our radar system and offer a list of future steps to bring it to an operational status

Snow Stratigraphy Measurements With UWB Radar

The focus of this thesis is to find and verify a non-invasive method to determine the layer distribution (stratigraphy) in snowpacks, which might aid avalanche risk assessment. Slab avalanches release due to failure and collapse in a weak snow layer. Determining the spatial distribution and depth of weak layers in avalanche starting zones is a high-risk task. Moreover, by manually digging snow pits, the occurrence of a weak layer can only be identified on a pit scale. We, therefore, propose a technical solution to this problem by mounting an ultra wideband radar system onto an unmanned aerial vehicle to obtain information about weak layers over a larger area and improve safety for avalanche professionals. During 2016, we have operated the radar system via a stationary platform 1 m above the snow, along 4.2 m long transects. For verification, we dug a full snowpit and used snow measurement probes (Avatech SP2 and Toikka SnowFork) to measure snow depth, liquid water content and density, as well as snow stratigraphy. Results show an average correlation between radar and in situ measurements of 0.97 and RMS error of 2.48 cm when extracting the most prominent transitions in the snow. The method developed in this thesis is tested on different types of snow. Additionally, the radar system is tested as payload on an unmanned aerial vehicle. Future work includes further development of the radar system and airborne measurements on snowpacks

Radar System Development for Drone Borne Applications with Focus on Snowpack Parameters

A complete representation of the Arctic cryosphere has historically been restricted by its remoteness, large extent, and restrictions in measurement methods and equipment. Here, remote sensing of snow-cover is a central method to improve the current knowledge of the Earth's ecosystem, and hence a critical component in cryospheric models. The use of drone-borne radar systems has seen considerable advances over recent years, allowing for the application of drone-mounted remote sensing of snow properties. This thesis describes the development of an ultra-wideband radar system for drone-mounted snow measurements. From the initial testing and technical implementation to field trials and method development for more advanced radar data analysis. This involves the development of lightweight and high-bandwidth radar systems intending to understand the limitations of design parameters for drone-borne radar systems and how these parameters influence the ability to measure snow conditions. Such understanding includes antenna theory and ultra wide-band radar theory, where most choices involve compromises. Snow as an electromagnetic propagation medium is presented with a focus on the previous design solutions. In that respect, various methods to measure snow parameters are discussed. Furthermore, this thesis aims to describe the iterative process of a drone-borne radar system development and how experiences from field trials are central to further improvements

Drone-Mounted UWB Snow Radar: Technical Improvements and Field Results

Drone borne radar systems have seen considerable advances over recent years, and the application of drone-mounted continuous wave (CW) radars for remote sensing of snow properties has great potential. Regardless, major challenges remain in antenna design for which both low weight and small size combined with high gain and bandwidth are important design parameters. Additional limiting factors for CW radars include range ambiguities and antenna isolation. To solve these problems, we have developed an ultra-wideband snow sounder (UWiBaSS), specifically designed for drone-mounted measurements of snow properties. In this paper, we present the next iteration of this prototype radar system, including a novel antenna configuration and useful processing techniques for drone borne radar. Finally, we present results from a field campaign on Svalbard aimed to measure snow depth distribution. This radar system is capable of measuring snow depth with a correlation coefficient of 0.97 compared to in situ depth probin

Drone-Mounted Ultrawideband Radar for Retrieval of Snowpack Properties

Extracting snowpack parameters from snow cover on sea ice or land is a time-consuming and potentially high-risk task. Moreover, deriving such parameters by manually digging a snow pit evidently yields low area coverage. We, therefore, propose a practical solution to this problem by mounting an ultrawideband radar system onto an unmanned aerial vehicle (UAV) to obtain information such as snowpack depth, density, and stratigraphy in order to increase personnel safety and extend coverage area. In this paper, we describe the development of radar system hardware and its mounting onto a UAV, as well as initial tests with this radar as a snow measuring device. Preliminary results from both ground and airborne testing show that the radar system is capable of obtaining snow depth information that corresponds well to in situ validation data with a correlation of 0.87. The radar system also works well while mounted on a UAV platform with little additional signal noise from vibrational and translatory movements

UAV-BORNE UWB RADAR FOR SNOWPACK SURVEYS

In this report we summarize the capabilities and technical characteristics of our UAV-borne UWB radar system, designed for conducting snow surveys. We developed an ultrawideband snow sounder that is capable of imaging snow stratigraphy with a 5 cm range resolution. The radar can be carried by an octocopter UAV in order to carry out airborne snowpack surveys. During a demonstration on Andøya, we showed that the radar was capable of resolving snow stratigraphy in wet snow conditions, as well as detecting a buried person under 1.5 m of wet snow. In this report, we present the results of the demonstration in detail. We furthermore discuss capabilities and incapabilities of our radar system and offer a list of future steps to bring it to an operational status

UAV-BORNE UWB RADAR FOR SNOWPACK SURVEYS. (8/2018)

In this report we summarize the capabilities and technical characteristics of our UAV-borne UWB radar system, designed for conducting snow surveys. We developed an ultrawideband snow sounder that is capable of imaging snow stratigraphy with a 5 cm range resolution. The radar can be carried by an octocopter UAV in order to carry out airborne snowpack surveys. During a demonstration on Andøya, we showed that the radar was capable of resolving snow stratigraphy in wet snow conditions, as well as detecting a buried person under 1.5 m of wet snow. In this report, we present the results of the demonstration in detail. We furthermore discuss capabilities and incapabilities of our radar system and offer a list of future steps to bring it to an operational status.publishedVersio

Mosideo/cirfa tank experiments on behavior and detection of oil in ice

In the Arctic, presence of sea ice presents a challenge to safe and sustainable operations. To optimize planning and minimize impact of inadvertent oil spills, oil-in-ice experiments were performed at the HSVA Arctic Environmental Test Basin (AETB) from 14 March to 4 April 2017. Following an under-ice spill and simulated springtime warming, the microscopic movement and distribution of oil in the sea ice pore space as well as the detectability of oil as it approaches the surface were investigated. Two ice types were studied simultaneously, i.e., columnar ice with and without a granular ice surface layer. Among the detection techniques were electromagnetic (radar, tomographic SAR) and optical (fluorescent, hyperspectral, thermal) sensors, and microscopic distribution of oil in sea ice were determined through X-ray computed tomography (CT). This paper presents the setup of the experiment and general ice properties. It was found that the movement of oil differed considerably between the investigated ice types. Predicting the behavior of oil in ice based on environmental conditions will help optimize the approaches used in spill detection and response.publishedVersio

Mosideo/cirfa tank experiments on behavior and detection of oil in ice

In the Arctic, presence of sea ice presents a challenge to safe and sustainable operations. To optimize planning and minimize impact of inadvertent oil spills, oil-in-ice experiments were performed at the HSVA Arctic Environmental Test Basin (AETB) from 14 March to 4 April 2017. Following an under-ice spill and simulated springtime warming, the microscopic movement and distribution of oil in the sea ice pore space as well as the detectability of oil as it approaches the surface were investigated. Two ice types were studied simultaneously, i.e., columnar ice with and without a granular ice surface layer. Among the detection techniques were electromagnetic (radar, tomographic SAR) and optical (fluorescent, hyperspectral, thermal) sensors, and microscopic distribution of oil in sea ice were determined through X-ray computed tomography (CT). This paper presents the setup of the experiment and general ice properties. It was found that the movement of oil differed considerably between the investigated ice types. Predicting the behavior of oil in ice based on environmental conditions will help optimize the approaches used in spill detection and response

Mosideo/cirfa tank experiments on behavior and detection of oil in ice

In the Arctic, presence of sea ice presents a challenge to safe and sustainable operations. To optimize planning and minimize impact of inadvertent oil spills, oil-in-ice experiments were performed at the HSVA Arctic Environmental Test Basin (AETB) from 14 March to 4 April 2017. Following an under-ice spill and simulated springtime warming, the microscopic movement and distribution of oil in the sea ice pore space as well as the detectability of oil as it approaches the surface were investigated. Two ice types were studied simultaneously, i.e., columnar ice with and without a granular ice surface layer. Among the detection techniques were electromagnetic (radar, tomographic SAR) and optical (fluorescent, hyperspectral, thermal) sensors, and microscopic distribution of oil in sea ice were determined through X-ray computed tomography (CT). This paper presents the setup of the experiment and general ice properties. It was found that the movement of oil differed considerably between the investigated ice types. Predicting the behavior of oil in ice based on environmental conditions will help optimize the approaches used in spill detection and response