Satellite weak signal capturing method and system in high-dynamic low-signal-to-noise-ratio environment

Abstract

The invention discloses a satellite weak signal capturing method and a satellite weak signal capturing system in a high-dynamic low-signal-to-noise-ratio environment. The satellite weak signal capturing device comprises a primary capturing module and a secondary capturing module, which adopt an interpolation frequency calculation method for calculating signals; after successfully capturing the signal, the primary capturing module stops working and sends estimated coarse frequency offset and coarse timing information to the secondary capturing module; and if the primary capturing module successfully captures the signal, a starting signal for starting the secondary capturing module is given, and the secondary capturing module performs secondary frequency estimation and signal arrival verification according to the coarse timing position information given by the primary capturing module and the signal after coarse frequency offset compensation. According to the satellite weak signal capturing method and the satellite weak signal capturing system, the primary capturing module is used for rapidly capturing the frequency spectrum and the position of the signal, calculating the coarse frequency spectrum and the coarse position of the signal, and carrying out capture verification and frequency fine estimation on the signal according to the secondary capturing module; and the satellite weak signal capturing method and the satellite weak signal capturing system improve the estimation precision, can be applied to various receivers, and have high engineering value.

Description

technical field [0001] The invention belongs to the field of satellite communication systems, and in particular relates to a method and system for capturing weak satellite signals in a high-dynamic and low-SNR environment. Background technique [0002] In a low signal-to-noise ratio and high dynamic environment, the signal has a large Doppler frequency offset and Doppler frequency change rate, which brings considerable difficulties to the capture of weak signals. For the large frequency offset capture of weak signals, the combination of segmented matched filtering and fast Fourier transform is usually used, that is, PMF-FFT algorithm. However, there is a fence effect at the maximum value of the power spectrum of FFT, and the accurate Doppler frequency offset value cannot be estimated, resulting in a large scallop loss and estimated frequency error. On the other hand, the Doppler frequency offset has a certain attenuation effect on the frequency response result of the matche...

AI Technical Summary

Problems solved by technology

However, the improvement effects of the above methods are not obvious and the complexity is high, and the detection of low signal-to-noise ratio signals requires a long data storage to calculate the correlation peak

After the signal is successfully captured, the frequency estimated in the current frame is compensated in the next frame. Due to the Doppler change rate and the drift of the crystal oscillator, a new frequency offset will be introduced, especially for low-speed signals. The existing technology None of them take this into account, which will cause unstable signal reception and reduce the probability of capture

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