Quality Control of Differential Phase of Dual Polarization Radar Based on Kalman Filter Algorithm

The maturity and wide application of dual linear polarization radar technology puts forward higher requirements for the calibration method, accuracy and stability of dual polarization.The differential phase data tends to increase monotonically due to the cumulative effect of the radar beam passing through the rain zone, but the quality of the differential phase data is disturbed due to system noise and other external noise effects, which does not fully comply with this trend. In this paper, kalman filter optimization is performed on the original differential phase data of the dualpolarization radar, and then the quality-controlled of differential phase using a polynomial fitting algorithm.The test was conducted using observation data at 11:35 during the rain process on June 5, 2016. The test shows that: In Table 1, it can be seen that the original differential phase data difference fluctuation range of the adjacent distance library is: $( 8.9212 \sim7.5863)$, after the kalman filter, the difference fluctuation range is reduced to: $(- 0.1555 \sim0.2480)$,after the final superposition polynomial fitting, the fluctuation range is reduced to: $( 0.007 \sim0.088)$. 1.It can be seen that the differential phase exhibits a more stable increasing trend after 2-step filtering optimization; 2.After filtering, the differential phase and the differential phase shift rate are improved compared with those before filtering. The contours of a and b in Fig.4 are more consistent than before filtering; 3.The differential phase and differential phase shift rate high value region after filtering are basically consistent with the high value region after filtering are basically consistent with the high value region of the reflectivity in Fig.3(a); 4. The strong echo A and B in Fig.3(a) are also reflected in Fig.4; 5.It can be seen from Fig.5(b) that the filtered differential phase shift rate has a tendency to increase with the increase of the reflectivity factor after filtering, which is consistent with the relationship between the differential phase shift rate and the reflectivity.It is shown that using kalman filter algorithm is a feasible solution for the differential phase shift rate and the differential phase quality control.