Introduction
"Different materials affect GNSS signals in different ways."
The environment surrounding a GNSS antenna is not a passive backdrop - it actively interacts with signals arriving from satellites. The materials present in and around the deployment site determine the severity, character, and predictability of multipath interference. While the general concept of multipath is well understood, the specific behaviours associated with water, glass, and metal deserve individual attention. Each material type produces distinct reflection characteristics that influence how multipath manifests and how it should be mitigated in a given deployment context.
Metal Structures
Metal is the strongest common reflector of GNSS signals. Aluminium, steel, and other conductive metals produce high-amplitude, specular reflections across the L-band frequency range. Controlled experiments comparing the multipath effects of different building materials have consistently ranked aluminium as producing the highest levels of multipath-induced error, ahead of glass and other common construction materials.
Metal structures commonly encountered in GNSS deployments include:
- Steel-framed buildings and industrial structures
- Shipping containers and port infrastructure
- Large vehicles and heavy machinery
- Antenna masts and communication towers
- Overhead crane structures in warehouses and dockyards
In industrial environments where GNSS is used for machine guidance or asset tracking, the proximity of metal structures can make the signal environment as challenging as a dense urban canyon, even in an otherwise open location. The reflections are strong, specular, and consistent, producing systematic pseudorange biases that do not average out over time if the geometry of the reflector relative to the satellite does not change.
Glass Facades
Modern commercial and residential architecture makes extensive use of large glass curtain walls. These surfaces are highly reflective to GNSS signals and present a particularly problematic environment for urban navigation. Glass facades produce strong specular reflections at mid and high satellite elevation angles - precisely the geometry where signals would otherwise be valuable for maintaining a good vertical component in the position solution.
Glass reflections in urban environments contribute significantly to NLOS (non-line-of-sight) reception. A receiver standing in the shadow of a tall building may not receive a direct signal from a satellite on the other side, but may receive a reflection of that satellite's signal from a glass-faced building on the opposite side of the street. The receiver cannot distinguish this from a direct signal, and the additional path length introduces a range error of several to tens of metres, directly corrupting the position solution.
Water Reflections
Water surfaces are excellent specular reflectors of GNSS signals, particularly when calm. The smoothness of still or slow-moving water produces coherent reflections comparable in strength to those from glass or metal. Key deployment contexts where water-surface multipath is significant include:
- Marine and harbour environments: Vessels manoeuvring at low speed during docking face persistent water-surface multipath. At low speeds, the geometry changes slowly, meaning multipath errors persist for extended periods rather than averaging out.
- River and lake shorelines: Survey receivers or infrastructure monitoring equipment installed near water bodies are exposed to strong, specular low-angle reflections that are difficult to reject without aggressive elevation masking.
- Coastal GNSS reference stations: Permanent reference station performance can be significantly degraded if the site has a clear view of nearby open water. Tide-dependent changes in water level also cause the reflection geometry to vary over time, producing cyclic multipath patterns.
- Intertidal and wetland areas: Irregular water coverage in tidal zones creates spatially variable and time-dependent multipath that is particularly difficult to model or mitigate.
It is worth noting that water-surface reflections have also been turned into a useful signal source in the field of GNSS Interferometric Reflectometry (GNSS-IR), where the multipath interference pattern in the Signal-to-Noise Ratio (SNR) data is used to measure water levels and wave heights. This application exploits the very phenomenon that degrades navigation performance, turning a liability into a measurement tool.
Coastal Environments
Coastal environments combine several of the most challenging GNSS conditions simultaneously. Water reflections, salt spray on antenna surfaces, proximity to port infrastructure (metal cranes, quays, vessels), and the dynamic character of a moving vessel all interact. Signal quality in a busy port can exhibit rapid, unpredictable fluctuations as ships, cranes, and containers move relative to the antenna, creating a time-varying obstruction and reflection environment that is extremely difficult to characterise in advance.
Environment-Specific Design Responses
| Environment | Primary Material Challenge | Recommended Response |
|---|---|---|
| Urban streets with glass buildings | Glass facades - strong NLOS reflections | 3D mapping, shadow matching, multi-constellation, SNR weighting |
| Industrial sites (ports, factories) | Metal structures - high-amplitude specular multipath | Choke ring antenna, elevation masking, site survey before deployment |
| Marine / harbour | Water surface - persistent specular reflections | Antenna placement above deck, high-quality ground plane, IMU integration |
| Coastal reference stations | Mixed water and land coverage | Site selection away from water line-of-sight, antenna phase centre stability monitoring |
| Near tall metallic structures | Metal - systematic bias in fixed directions | Sidereal filtering for static surveys, robust GNSS/INS for dynamic applications |
The key insight for all material-related multipath is that the environment must be understood before the system is deployed. A site survey - whether physical inspection, simulation using a 3D building model, or signal quality data collection - is not an optional step. It is a necessary precondition for defining realistic accuracy expectations and selecting appropriate mitigation measures for any deployment where reflective surfaces are present.