Differential code biases (DCBs) are important parameters that must be estimated accurately for precise positioning and Satellite Based Augmentation Systems (SBAS) ionospheric related parameter generation. In this paper, in order to solve the performance degradation problem of the traditional minimum STD searching algorithm in disturbed ionosphere status and in geomagnetic low latitudes, we propose a linear planar based minimum STD searching algorithm. Firstly, we demonstrate the linear planar trend of the local vertical TEC and introduce the linear planar model based minimum standard variance searching method. Secondly, we validate the correctness of our proposed method through theoretical analysis and propose bias detection to avoid large estimation bias. At last, we show the performance of our proposed method under different geomagnetic latitudes, different seasons and different ionosphere status. The experimental results show that for the traditional minimum STD searching algorithm based on constant model, latitude difference is the key factor affecting the performance of DCB estimation. The DCB estimation performance in geomagnetic mid latitudes is the best, followed by the high latitudes and the worst is for the low latitudes. While the algorithm proposed in this paper can effectively solve the performance degradation problem of DCB estimation in geomagnetic low latitudes by using the linear planar model which is with a higher degree of freedom to model the local ionosphere characteristics and design dJ to screen the epochs. Through the analysis of the DCB estimation results of a large number of stations, it can be found that the probability of large estimation deviation of the traditional method will increase obviously under the disturb ionosphere conditions, but the algorithm we proposed can effectively control the amplitude of the maximum deviation and alleviate the probability of large estimation deviation in disturb ionosphere status.

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.

This paper proposes a technique for efficient standing multipath mitigation of geostationary earth orbit (GEO) satellites. The performance of traditional filtering methods for GEO multipath errors can be effectively improved by using carrier frequency variation approach. Conventional multipath mitigation methods do not pay much attention to the GEO satellite multipath effects, and they are less effective due to the non-zero average characteristics of GEO multipath errors for short epochs. By varying carrier frequency, the multipath error average becomes approaching zero in short epochs due to the faster multipath carrier phase variation. Therefore, it could enhance the traditional filtering method performance on the multipath signals. By varying the carrier frequency or the carrier phase offset, the average multipath error will approach zero as a result of the frequent multipath carrier phase variations. This method aims to explore the potential for signal pattern design while improving the performance of current satellite navigation systems. The results show that the root mean square error (RMSE) for pseudo-range multipath errors of the proposed approach improves about 0.3m with a frequency variation range of 15MHz.

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.

A novel multipath mitigation algorithm for binary offset carrier (BOC) signals in the global navigation satellite system (GNSS) is presented. Based on the W2 code correlation reference waveform (CCRW) structure, a series of bipolar reference waveforms (BRWs) is introduced to shape the unambiguous s-curve. The resulted s-curve has a single stable zero-crossing point such that the tracking unambiguity in BOC (1,1) can be solved. At the same time, multipath mitigation capability is improved as well. As verified by simulations, the proposed method matches the multipath mitigation performance of W2 CCRW, and is superior to conventional receiver correlation techniques. This method can be applied in GPS L1 and Galileo E1.