LAUSR

The amplitude–frequency characteristics play an essential role in analyzing transmission power grids, such as harmonic amplification using the amplitude–frequency characteristics as the harmonic amplification factor, harmonic resonance, etc. However, when the cable line with distributed parameters is connected to powers, the model would be troublesome to be calculated for the amplitude–frequency characteristics by the existing methods. To fill this gap, we proposed a method of variable covariance probabilistic data association (PDA) Kalman filtering deconvolution. First, a typical high-voltage cable transmission system (HVCTS) and its dynamic model are established. Next, a square wave impulse excitation (SWIR) is injected into the system, and the square wave impulse response is extracted at the measurement ports. Then the variable covariance PDA Kalman filter (VCPDAKF) algorithm is proposed to denoise the noisy square wave impulse response. Meanwhile, the deconvolution method is used to obtain the amplitude–frequency characteristics based on the convolution model. Finally, it is verified through simulation and experiment that the VCPDAKF algorithm could effectively denoise the noisy square wave impulse response. The effectiveness of the proposed method for the amplitude–frequency characteristics is verified.