An HF channel parameter estimation method based on HR-IPFrFT

Abstract

The long-distance high-frequency (HF) ionospheric channel is characterized by high noise levels and severe signal fading, which seriously affects signal capture and channel parameter extraction. Chirp continuous wave is often applied as a transmitted waveform due to its anti-noise and anti-Doppler advantages. The periodic fractional Fourier transform (PFrFT) algorithm possesses the optimal detection capability for chirp continuous waves. It can achieve periodic energy accumulation at the specific order. This paper proposes a new HF channel parameter estimation method combining their advantages. Firstly, an high-resolution improved periodic fractional Fourier transform (HR-IPFrFT) algorithm is introduced. This algorithm adapts the kernel function to fit the periodic chirp signal and then gives the periodic non-coherent accumulation expression for the discrete HR-IPFrFT. In this expression, two adjustable factors introduced can flexibly adjust the fractional domain range. Further, it is demonstrated that the HR-IPFrFT shows time-shifted and frequency-shifted properties. The parameter estimation method uses a dual-chirp continuous wave as the transmitted signal. By analyzing the variation of the peak position of the received signal in the HR-IPFrFT domain, the channel parameters are accurately extracted. Simulation and experiments show that this method exhibits superior parameter identification and estimation accuracy under low signal-to-noise ratio and severe fading conditions