The major weakness of global navigation satellite system receivers is their vulnerability to intentional and unintentional interference. Frequency domain interference suppression (FDIS) technology is one of the most useful countermeasures. The pseudo-range measurement is unbiased after FDIS filtering given an ideal analog channel. However, with the influence of the analog modules used in RF front-end, the amplitude response and phase response of the channel equivalent filter are non-ideal, which bias the pseudo-range measurement after FDIS filtering and the bias varies along with the frequency of the interference. This paper proposes an unbiased interference suppression method based on signal estimation and spectrum compensation. The core idea is to use the parameters calculated from the tracking loop to estimate and reconstruct the desired signal. The estimated signal is filtered by the equivalent filter of actual channel, then it is used for compensating the spectrum loss caused by the FDIS method in the frequency domain. Simulations show that the proposed algorithm can reduce the pseudo-range measurement bias significantly, even for channels with asymmetrical group delay and multiple interference sources at any location.

Outside wireless signals often obstruct GNSS receivers from acquiring satellite signals. Traditional anti-jamming algorithms are used to suppress interference using a convex optimization method based on minimizing output power. These algorithms can reduce interference. However, these models suppress satellite signals as well as jamming interference. Under the high-dynamic condition, the output signal-to-interference-and-noise ratio (SINR) deteriorates seriously and the success rate in acquiring satellite signals falls accordingly. This paper introduces a novel, broadened model with a no-main-lobe-and-multi-virtual-null-constraints (NMLCB) method based on maximizing output power and constraining interference sources. With the new method, GNSS receivers can receive satellite signals more easily than using the power inversion (PI) and power minimization with derivative constraints null (NB) methods under the high-dynamic condition.

Global navigation satellite system (GNSS) receivers equipped with the frequency domain interference suppression (FDIS) filter can operate in environments with harsh interference. The FDIS will not cause tracking error bias for an ideal analog receiver channel as its magnitude response and phase response are constant. However, the analog receiver channel distortion is induced by RF cables, amplifiers, and mixers. The distortion of the channel caused asymmetry correlation function. The correlation function is further deformed by the FDIS filter. More seriously, since the FDIS filter is adaptive, the bias will vary with the jamming pattern, especially when the frequency of interference is varying. For precision navigation applications, this bias must be mitigated. Fortunately, to prevent power loss, the analog receiver channel filter is a real function or the imaginary part is negligible. Therefore, the magnitude response and the phase response are even functions. Based on these channel features, a new FDIS filter based on mirror frequency amplitude compensation (MFAC) method is proposed in this paper. The amplitude of the symmetry position of the notch frequency is doubled in the MFAC method in order to mitigate the tracking bias. Simulation results show that the MFAC-based FDIS method is capable of reducing the bias error to less than 0.1ns, which is significant smaller than that achieved by the traditional FDIS method.