## 4 Experiments  
To verify the effectiveness of the proposed method, three known control points on campus were selected as the prior coordinates. Certain receivers were used to process the satellite signal. The processed observation data was acquired. The receivers at both ends of the baseline were required to acquire data at the same time during the data acquisition process. The data acquisition device was shown in Figure 2.  
In the experiment, the carrier phase observation data of two baselines of 522 m and 975 m were collected for differential positioning modeling, and the sampling interval is 5 s. For the baseline of 522 (baseline 1), the total sampling time was 1 h, and 305 consecutive sampling values which can observe 5 satellites were selected. Every 6 values formed an epoch for position solving, so we can obtain 300 epochs. Similarly, for the baseline of 975 m (baseline 2), the total sampling time is 30 min, and 165 consecutive sampling values are selected. We can obtain 160 epochs. Each epoch is solved independently. Whether the epoch is solved correctly is determined by the value of deviation. If the deviation is more than 10 cm, the solution of the epoch is considered incorrect. The ratio of the correctly solved epoch number to the total epoch number is used as the success rate of the solution. With the above two sets of data, LAMBDA was used to solve the integer ambiguity first. Then TEC test and prior coordinate accuracy test were used to analyze the correctness of the integer ambiguity solution. And GWO was used to correct the solution units that fail the test. The identification calculation results are shown in Figures 3-8. Figure 2: Data acquisition equipment. Figure 4: Coordinate identification error with LAMBDA (baseline 2). Figure 5: Total electron content delay residual of satellite 32 (baseline 1). Figure 3: Coordinate identification error with LAMBDA (baseline 1). Figure 8: Coordinate identification error with LAMBDA-GWO (baseline 2). Figure 6: Total electron content delay residual of satellite 32 (baseline 2). Figure 7: Coordinate identification error with LAMBDA-GWO (baseline 1). Figures 3 and 4 show the deviation between the coordinates obtained by the traditional LAMBDA and the actual coordinates for the two baselines. Since traditional LAMBDA cannot correct the erroneously solved epochs, we can see there are many cases in Figures 3 and 4 where the coordinates of the epoch have far deviated from the median for the solved integer ambiguity value is incorrect. Figures 5 and 6 show the Ionospheric delay residual of satellite 32 for the two baselines solved according to the traditional LAMBDA. The ionospheric delay residual value between adjacent epochs is similar due to the slow change of the ionosphere. When the integer ambiguity is incorrect, there will be a jump in the ionospheric delay residual between adjacent epochs, which is also the basis of ionospheric testing. The locations where the jump occurs in Figures 5 and 6 also correspond to the epochs in Figures 3 and 4 where the integer ambiguity is incorrect. Moreover, if the ionospheric delay residual is used alone for testing, the calculation of the ionospheric delay residual of the first epoch is very important, because the subsequent test is also based on the first epoch. It can be seen from Figure 4 that the integer ambiguity solution value of the first epoch is incorrect, so the ionospheric delay residual in the first epoch is incorrect as shown in Figure 6. Finally, the coordinate deviation of the two baselines is solved by the proposed test method and correction strategy, as shown in Figures 7 and 8, which can correct the incorrect solution in traditional LAMBDA method shown in Figures 3 and 4. To further verify the effectiveness of the method proposed in this paper, LAMBDA, IPSO-AR [16] and LAMBDA-GWO are used to solve the two sets of data collected, respectively.