Research on filtering method of telemetry data based on whale optimization and wavelet transform

Abstract

Ground based telemetry stations are usually used to acquire real-time information of flight vehicles, and monitor the flying states in order to guarantee the safety of flight tests. However, when the telemetry ground station tracks the aerial vehicle, some wild values are inevitably included in the received telemetry data due to various interference factors, which can seriously affect the interpretation of the telemetry data and the evaluation of the vehicle performance. In order to make up for the shortage of existing telemetry data wild value elimination algorithms, this paper uses the wavelet transform threshold method to eliminate the wild values in telemetry data based on the principle of wavelet transform, and introduces the swarm intelligence optimization algorithm to obtain the optimal thresholds for different telemetry data adaptively. The optimal threshold and threshold function coefficients are obtained for different telemetry data to achieve better filtering effect. Corresponding results show that the proposed method can effectively eliminate the wild values in the telemetry data and realize the filtering of the telemetry data.