# GNSS Signal Quality in Forest Stands for Off-Road Vehicle Navigation
## 1 Introduction
(19) measured GPS performance by two aspects--position accuracy and data update frequency--using image processing for measuring canopy densities. [PERSON] and G  
Figure 1: Forest cover in Europe. GPS survey components under different vegetation density covers. [PERSON] et al. [21] described the accuracy of measurement using differential GPS and GLONASS receivers under mountainous Pinus sylvestris canopy. [PERSON] et al. [22] analyzed the influence of forest stand variables on the accuracy of measurements performed by global positioning systems (GPS) receivers, using genetic algorithms. [PERSON] and [PERSON] [23] observed interactions between signal interruption probability (SIP), canopy opening index, observation period, number of available satellites, and positional dilution of precision (PDOP). [PERSON] et al. [24] studied the seasonal impact of oak-hickory forest on the positioning level using recreation-grade GPS receivers. [PERSON] and [PERSON] [25] raised the antenna of a GNSS receiver during measurements, in order to reduce the multipath effect in the highest part of various forest conditions. [PERSON] et al. [26] presented the rapid static and real-time kinematic (RTK) technology for GPS/GLONASS surveying under forest environments. [PERSON] et al. [27] presented the first-ever dual-frequency multi-constellation Global Navigation Satellite Systems Reflectometry (GNSS-R) polarimetric measurements over boreal forests and lakes from the stratosphere. According to the study by [PERSON] and [PERSON] [28], positioning accuracy in a coniferous forest stand ranged from 0.27 to 3.48 m for observation periods ranging from 120 min to 15 min, respectively, depending on the time of measurement and number of tries. [PERSON] et al. [29] presented an analysis of the vegetation impact on GPS L1 C/A (coarse acquisition code) signals in terms of attenuation and depolarization. [PERSON] et al. [30] developed a post-processing strategy to improve the positional accuracy of GNSS-measured sample plot centers and to develop a method to automatically match trees within a terrestrial sample plot to aerially detected trees. [PERSON] et al. [31] examined contemporaneous ALOS2 PALSAR-2 L-band imaging radar, CYGNSS GNSS reflections, and ground measurements to assess associated advantages and challenges to mapping inundation dynamics, particularly in regions under dense tropical forest canopies. [PERSON] et al. in [32] presented GPS (Global Positioning System)-based methods to measure L-band GPS signal-to-noise ratios (SNRs) through different forest canopy conditions using hemispherical sky-oriented photos (HSOPs) along with GPS receivers. Terrestrial mobile laser scanning (MLS) with GNSS navigation support has been developing dynamically in recent years. [PERSON] et al. [33] proposed a two-phase on-board process, where tree stem registration produces a sparse point cloud (PC) which is then used for simultaneous location and mapping (SLAM). A field test was carried out using a harvester with a laser scanner and a global navigation satellite system (GNSS) performing forest thinning over a 520 m strip route. [PERSON] et al. [34] proposed an approach to the processing of MLS data of forest scanned from different views with two mobile laser scanners under heavy canopy. [PERSON] et al. in [35] analyzed how the highly precise attitude and velocity information from GNSS/INS could be integrated with SLAM to improve its robustness and accuracy for high-precision positioning in forests. [PERSON] et al. [36] tested the accuracy of various instruments utilizing GNSS in motion under forest canopies of varying densities using several different combinations of GNSS and inertial measurement unit (IMU). GNSS devices are mainly used for the navigation of off-road vehicles in forest cover. The accuracy of navigation depends on the quality of GNSS receivers, on the number and location of satellites, and also on the type of vegetation, the properties of which can change due to meteorological conditions.