Snow Layer Detection by Pattern Matching in a Multipath Radar Interference Scenario

Abstract

Snowpack in sloped mountain terrain may present stratification in which layers of snow accumulate over a certain period. The loosely adhering layers in snowpack may exhibit a severe avalanche risk, and detecting such stratification phenomena is key to avalanche detection. The danger of manual, in-situ sampling calls for investigation of alternative approaches, including the use of in-situ radars. Considering a buried radar sensor, this manuscript analyses the impact of multipath phenomena on the results of the sensing operation. Multiple bounces in snow layers may degrade the received signal and corrupt the estimation results. Multipath phenomena are well known and analysed in communication systems, but snow layering measurement is a different problem, with little previous research done on related multipath phenomena. This paper analyses the problem with a multi-receiver radar architecture, investigating the impact of multi-path effects from layered snow on measurements carried out by a multi-static radar of Frequency-Modulated Continuous Wave (FMCW) type. A few simplifying assumptions are formulated, in order to make the problem manageable, and a possible approach for solving the related issues is proposed, using a robust algorithm based on pattern matching to detect snow layering in such a challenging environment. Results obtained from various simulations carried out with realistic environmental and geometrical parameters appear to support the effectiveness of the proposed method. Results show that with 3 metres of snow thickness, the probability of successfully detecting the correct numbers of layers exceeds 80%.

Measurement, data analysis and modeling of electromagnetic wave propagation gain in a typical vegetation environment

“…The final expression of the electromagnetic field of the Tamir model in region 1 is shown in Eq [ 27 ]. In the above model, the path of side waves is T-A-B-R, where the length of each segment is: TA = ( H T − h 0 ) secθ C , , and BR = ( H T − h 1 ) secθ C .…”

“…By analyzing the characteristics of wireless broadband channel in the above chapter, this paper designs a set of channel test scheme suitable for scenario requirements according to the characteristics of complex channel environment, including continuous wave measurement method [ 27 ] and broadband signal measurement method [ 31 ].…”