Token Reward Metrics

What is GNSS Signal SNR?

GEODNET adopts the GNSS signal SNR (Signal-to-Noise Ratio) on L1 as an indicator for each tracked GNSS signal quality. Please refer to the article: Measuring GNSS Signal Strength for details about GNSS signal SNR. Typical GNSS L1 SNR for each satellite should range from 37-45 for an acceptable installation. The GNSS signals with SNR below 32 will not be used in GEODNET backend algorithm. The following screenshot is the GNSS SNR signal from one online miner.

Token Calculation based on Satellite No. and Satellite SNR

Each satellites’ SNR (signal noise ratio) will be recorded. Effective satellite number means, only SNR >= 32 satellites will be counted.

Previous Reward Ratio (RRR):

Reward ratio = 100%, if effective satellite number ≥ 30;

Reward ratio = 0%, if effective satellite number ≤ 20;

Reward ratio = (30-x)/10, if effective satellite number is between 20 to 30.

New Reward Ratio Since Approval of GIP6:

Based on discussions within the GEODNET community regarding GIP6, North America has significantly fewer satellite views compared to the rest of the world. As a result, it is unfair to use a single or high satellite count as a factor in the RRR (Rolling Reward Rate) calculation for GEODNET stations. After considering all relevant factors, the reward ratio has been be adjusted globally for all stations upon the approval of GIP6 as follows: Reward ratio = 100%, if effective satellite number ≥ 29;

Reward ratio = 0%, if effective satellite number ≤26 (<80% RRR as proposed in GIP6).

Steps

1. Count all satellites which has SNR ≥ 32

2. Display effective satellite no. (SNR>32)

3. Calculate reward based on the new number

4. Display the reward ratio in the graph

More Reward Metrics to Be Implemented

Data quality is essential to the usability of GEODNET. The GEODNET team is working hard to employ more metrics over time to improve data quality and determine the token rewards for miners. In addition to the existing metrics, we are planning to add metrics such as multi-path, network delay, etc.

The following table provides an overview of our reward metrics since 2022.

* These metrics may change when being implemented.

GNSS Multipath (MP) Quality Control Metrics

1. What is GNSS multipath effect

GNSS signals (see Figure 11) can be easily affected by multipath issues, where the radio signals reflect off surrounding terrain; buildings, canyon walls, hard ground, etc. GNSS multipath1,2 effect is one of the major GNSS positioning error sources (see Table 12). Unlike other GNSS error sources, which can be compensated by error modelling and/or greatly reduced (or fully cancelled) by GNSS RTK technology, the multipath effect of the RTK base stations will be directly shifted to the RTK rover devices and directly impact the RTK rover positioning performance. Therefore, it is very important to install the RTK base station in an open-sky view and multipath free environments.

Table 1. GNSS Positioning Error Sources (SPP=Single Point Positioning, which stands the standard GPS/GNSS positioning technology with meter-level positioning accuracy; RTK=Real-Time Kinematic represents the cm-level high precision GNSS Technology, the positioning accuracy of RTK depends on how close the RTK base station is located, normally referred to as RTK baseline length).

1. How to evaluate GNSS multipath effect of an RTK base station

The multipath effects on the GNSS code measurements are normally in decimeters to meters, depending on the GNSS receiver environment, while the multipath effects on the GNSS carrier phase measurements are in the range of millimeters to centimeters. This provides a method to evaluate the multipath effects on GNSS code measurements. Below are simplified equations to evaluate the GNSS multipath effects of an RTK base station (the same principle applies to other GNSS receivers):

Here P1, P2 are the code measurements, and Φ1, Φ2 the carrier phase measurements on L1 and L2 in meters; R is the geometric distance between the satellite and receiver; I is the ionosphere delay from the satellite to the receivers, M1 and M2 are the multipath effects on L1 and L2; N1 and N2 are the phase ambiguity terms on L1 and L2; λ1 and λ2 are the carrier phase wavelengths; β is a constant terms relating to L1 and L2 frequencies. The carrier phase multipath effects (mm to cm level) on L1 and L2 are ignored here.

Based on (3) and (4), the ionospheric term can be represented as a combination of carrier phase measurements, as shown in Equation (5). The multipath effect M1 can be represented as code measurement P1 and carrier phase measurements Φ1 and Φ2, as shown in Equation (6). Similarly, the multipath effect M2 can be represented as code measurement P2 and carrier phase measurements Φ1 and Φ2, as shown in Equation (7). Due to the constant ambiguity terms N1 and N2 in Equations (6) and (7), it is not possible to evaluate the absolute multipath effects M1 and M2. However, the variations in multipath effects M1 and M2 over time play a more significant role in reflecting the GNSS multipath environment. The multipath effect variations of all satellites on GNSS L1 and L2 frequencies are referred to as Multipath metrics MP12 and MP21, often abbreviated as MP1 and MP2.

TEQC³, developed by UNAVCO, is a well-known GNSS data QC (Quality Control) software. It provides Multipath QC metrics MP1 and MP2 (as well as MP5 for GPS L5/GALILEO E5a frequency, MP6 for GALILEO E6 frequency, MP7 for GALILEO E5b frequency, and MP8 for GALILEO AltBoc (E5a+E5b) frequency). GEODNET uses TEQC to calculate GNSS QC metrics, including Multipath metrics MP1 and MP2, hourly for all GEODNET stations. These GNSS QC metrics are available to GEODNET RTK data customers under NDA.

1. What is the expected Multipath QC metrics for a RTK base station

RTK data customers set requirements for the multipath QC metrics MP1 and MP2 of RTK base stations, typically requiring MP1 and MP2 < 0.5m for an hourly window. Below are examples of MP1 and MP2 from 3600 GEODNET RTK base stations (shown in Figure 2).

Figure 2. MP1 and MP2 from GEODNET RTK base stations

Reference:

1) https://gssc.esa.int/navipedia/index.php/Multipath

2) https://en.wikipedia.org/wiki/Error_analysis_for_the_Global_Positioning_System

3) https://www.unavco.org/software/data-processing/teqc/teqc.html