Aimed at radio-frequency (RF) interference suppression, this article presents an RF interference adaptive cancellation system (RFIACS) with the down-conversion correlator and proposes the time domain model of the RFIACS with integrated delay mismatch about mixers, RF circuit, and intermediate frequency (IF) circuit. Then, the influence of the integrated delay mismatch and loop gain on the system stability, convergence time, and interference cancellation ratio is analyzed based on the time model. Studies show that the RF and IF delay mismatch each must be matched on their respective frequency bands and the proper arrangement of circuits and loop gain can effectively improve the cancellation performance of the system. Results of simulations and experiments with different parameters show that the theoretical model is valid and accurate. The research result is of much value to the circuit design and delay-matching debugging of the RFIACS.

The analog control circuit of existing RF interference cancellation system is too complex, and the convergence speed cannot be flexibly tuned. This article proposes a digital-to-analog hybrid RF interference cancellation system based on multitap structure (MDARFICS), where the analog control circuit is digitized, so it can be highly integrated and easily tuned. The analytical theory model of the MDARFICS is established for the first time, which can suppress interference with a large power dynamic range and bandwidth. The factors that affect the cancellation performance, i.e., stability, wideband interference cancellation ratio (WICR), and convergence speed, are studied. The stability criterion is obtained, that is, loop gain, sample rate, and tap delay affect the stability cooperatively, and it is found that the sample rate must be selected according to tap delay. Studies show the MDARFICS can effectively suppress wideband interference. The larger the number of taps and control step size, the smaller the bandwidth and delay difference between the tap and interference channel, and the larger the WICR. The convergence speed accelerates as the control step size and filter coefficient increase. Simulations and experiments verify the theoretical analysis. The research results are of much value to the implementation of the MDARFICS.

The interference cancellation ratio (ICR) is a key performance indicator of digital-to-analog hybrid radio frequency (RF) interference cancellation systems. Aiming at the low convergence speed of a digital-to-analog hybrid RF interference cancellation system based on a multi-tap structure (MDARFICS), a novel, fast, and robust variable-step-size least-mean-square (LMS) algorithm based on an improved hyperbolic tangent function (IHVSS-LMS) is proposed. The IHVSS-LMS algorithm adopts an improved hyperbolic tangent function and uses adjustable parameters and the iteration number to jointly adjust the step size, which improves the convergence speed and reduces the computational complexity. Moreover, by using the prior information of the input signal, the non-linear relationship between the step size and the input signal power is established, which enhances the robustness and the ability to suppress interference with mutable power. The IHVSS-LMS algorithm is applied to the MDARFICS. Through theoretical derivation, the convergence speed and the steady-state expressions of the interference cancellation ratio of the MDARFICS are obtained. The simulation results show that under the conditions of high and low signal-to-noise ratio (SNR), the robustness, convergence speed, and steady-state error performance of the IHVSS-LMS algorithm are better than the existing variable-step-size algorithm. The experimental results show that using the IHVSS-LMS algorithm, the MDARFICS can not only effectively accelerate the convergence speed by at least three times but can also improve the ICR by more than 3 dB.

Sidelobe cancellation (SLC) is a well‐established beamforming technique for mitigating interference, particularly in the context of satellite communication (SATCOM). However, traditional SLC suffers from the issue of partially canceling the desired signal at high signal‐to‐noise ratio (SNR), primarily due to unconstrained beamforming processing. Extensive research has been conducted to address this problem; however, existing algorithms have limitations such as dependence on knowledge of signal array vectors or number of interferers and involve high computational complexity. In this paper, we propose a robust SLC algorithm based on beamforming vector norm constraint. Our proposal offers a practical solution by only requiring knowledge of the earth station antenna gain and maximum auxiliary array gain to the desired signal, both of which are fully known. Furthermore, compared to traditional SLC, our proposed method introduces additional computational complexity that only scales linearly with the size of the auxiliary array. Simulation results demonstrate comparable performance between our proposed method and existing techniques such as diagonal loading and spatial degrees‐of‐freedom control‐based algorithms.