Abstract
LFM interference is a typical non-stationary interference, which is common in the application of satellite navigation receiver. The normal SFAP does not distinguish the characteristics of received signals, and uniformly carries out covariance matrix estimation, weight calculation and adaptive filtering in each frequency bin, which may attenuate the performance of LFM interference suppression. To solve this problem, a SFAP algorithm based on short-time Fourier transform (STFT) was proposed. Firstly, the time-frequency characteristics of the received data were analyzed by short-time Fourier transform. Then the sampled data were grouped in two-dimensional time and frequency domain according to their time-frequency characteristics, and the sampled data with consistent time-frequency characteristics were divided into the same group. Finally, the covariance matrix estimation, weight calculation and adaptive filtering were carried out by using the grouped data to improve the interference to noise ratio, the null depth and the anti-interference ability. Both theoretical analysis and simulation results verify the effectiveness of the algorithm.
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Liu, P., Wang, D., Ren, Q., Tang, D., Peng, B. (2022). Space-Frequency Adaptive Processing Algorithm Based on STFT for LFM Interference Suppression. In: Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC 2022) Proceedings. CSNC 2022. Lecture Notes in Electrical Engineering, vol 909. Springer, Singapore. https://doi.org/10.1007/978-981-19-2580-1_40
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DOI: https://doi.org/10.1007/978-981-19-2580-1_40
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