## Evaluation Metric
The evaluation metric for this competition is [RMSE](https://en.wikipedia.org/wiki/Root-mean-square_deviation). The RMSE is commonly used to measure the differences between values. 


## Benchmark
The benchmark result is from a simple MLP model, model detail will be updated later. The input of the network is the pseudorange residual, CN0, and elevation angle, output is the pseudorange error prediction.

## Submission Format

**For every GPS Time and Every Satellite in the dataset**, submission files should contain two columns: `ID` and `Predict`. `ID` follows the same sequence with the testing dataset, and within each GPS Time, the satellite sequence should also be the same as that in the testing set. Every `Predict` is a float value, which means the pseudorange error prediction. 


The file should contain a header and have the following format:
```
ID,Predict
0,10.1
1,2
2,0
3,3.67
4,0.45
5,12
6,26.1
7,7
8,4.89
9,19.2
10,23.8
11,8
12,0
13,17.5
```