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.

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 probing.

The use of uav-mounted radar for obtaining snowpack parameters has seen considerable advances over recent years. However, a robust method of snow density estimation still needs further development. The objective of this work is to develop a method to reliably and remotely estimate swe using uav-mounted radar and to perform initial field experiments. In this paper, we present an improved scheme for measuring swe using uwb (0.7GHz–4.5GHz) pseudo-noise radar on a moving uav, which is based on airborne snow depth and density measurements from the same platform. The scheme involves autofocusing procedures with the f-k migration algorithm combined with the Dix equation for layered media in addition to altitude correction of the flying platform. Initial results from field experiments show high repeatability (R>0.92) for depth measurements up to 5.5 m, and good agreement with Monte Carlo simulations for the statistical spread of snow density estimates with standard deviation of 0.108 g/cm3. This paper also outlines needed system improvements to increase the accuracy of a snow density estimator based on an f-k migration technique.