Power Signal Parameter Estimation Based on Central Difference Strong Tracking Kalman Filter Algorithm

Aiming at the problem that the strong tracking Kalman filter algorithm needs to calculate the Jacobian matrix, the convergence speed is slow and the algorithm estimation accuracy is low in power signal parameter estimation. This paper proposes a central difference strong tracking Kalman filter algorithm. The algorithm uses the first derivative term of the nonlinear differential center polynomial to estimate the pre-test and post-test error covariance matrix and the fading factor in the filtering process in real time. The proposed algorithm simplifies the calculation process more traditionally, avoids the need to solve the Jacobian matrix in the filtering process, and improves the convergence speed and estimation accuracy of the algorithm after the system parameters are abrupt. The simulation results show that the proposed algorithm improves the parameter estimation accuracy and calculation speed, and verifies the effectiveness of the algorithm in power signal parameter estimation.