# On Mitigating the Effects of Multipath on GNSS Using Environmental Context Detection
## 1 Introduction
In almost all of the previous work on context detection, signal strength or its variants were used as fundamental environment recognition parameters; however, this may not result in accurate context detection in the case of multi-constellation GNSS because: (1) the strength of the received signal is highly affected by NLOS and/or multipath; however, the severity of effects varies by frequency [43]; (2) the signal strength is majorly influenced by the elevation angle and can also be affected by the receiver efficiency or antenna design; and (3) a combination of multiple navigation systems in multi-constellation GNSS mode results in increased satellite density, and therefore monitoring the strength of each satellite can lead to a huge processing load. This paper presents a detailed study on environmental context detection using multi-frequency and multi-constellation GNSS signals. A new context-aware navigation (CAN) method is proposed with context detection and characterization capabilities to mitigate the multipath effects in constrained environments by using adaptive GNSS receiver design in the multi-constellation mode. The ultimate aim of work is to improve the navigation accuracy by detecting the operating environments and then adjusting the mitigation strategy accordingly. The CAN method utilizes a handful of GNSS parameters to categorize the environment into standard, degraded and highly degraded classes and then updates the receiver tracking loop based on the inferred environment to suppress the degradation effects. The main difference between the proposed CAN and other methods is that it does not use the signal strength or its variants as key parameters for environment detection, instead it utilizes the globally and equally distributed property of GNSS, i.e., satellite availability and a new feature named the change factor (CF) for environment categorization. Additionally, the efficient design of proposed CAN, which includes selection of the optimal GNSS parameters along with context definitions for environment characterization makes it more practically realizable as compared to complex methods that would become practically impossible to implement in receivers. Finally, to validate the performance of the proposed CAN algorithm, a detailed study on a multi-constellation GNSS receiver in the quad-constellation mode, i.e., GPS, BeiDou, Galileo and GLONASS, is conducted by driving an instrumented vehicle in and around the city center, and the results are then compared with a standard receiver. The rest of the manuscript is organized as follows: Section 2 discusses the methodology used for GNSS performance evaluation in a multi-constellation mode with field experiments, route dynamics, observation periods and signal-reception characteristics. Section 3 highlights the results of GNSS performance evaluation along with the statistical characteristics of the received signal quality. Section 4 presents the context-aware navigation (CAN) algorithm and its implementation on a real-time GNSS receiver. Finally, Section 5 gives our concluding remarks and recommendations for future extensions.