Global navigation satellite system (GNSS) plays a vital role in high-precision positioning whereas detecting and mitigating carrier phase multipath error is still a significant challenge. Multipath error is closely related to the users’ environment, so it is difficult to mitigate by traditional differencing techniques. In this paper, we discuss the possibility and potential performance of multipath detection and mitigation with low-cost antennas in real-time kinematic (RTK) positioning. We employ two low-cost antennas and assume that the baseline length is known. We employ the carrier phase, ephemeris, and baseline length to detect the observed and estimated baseline vectors’ consistency in real-time. A reasonable threshold is proposed to detect the satellite signals with the multipath effect, then we eliminate these signals and use the remaining satellite signals for RTK positioning to mitigate multipath. The experiments are carried out in the open environment without multipath and the environment with specular multipath. Experimental results show that the false alarm rate of this method is entirely consistent with the theoretical value. When the number of satellites is six and eight, this method can reduce the RMS (root mean square) of positioning error by approximately 64% and 49%, respectively. At the same time, this method can improve the ambiguity success rate to above 99%.

The vulnerability of civil receivers of the Global Satellite Navigation System (GNSS) to spoofing jamming has raised significant concerns in recent times. Traditional multi-antenna spoofing detection methods are limited in application scenarios and come with high hardware costs. To address this issue, this paper proposes a novel GNSS spoofing detection method utilizing three low-cost collinear antennas. By leveraging the collinearity information of the antennas, this method effectively constrains the observation equation, leading to improved estimation accuracy of the pointing vector. Furthermore, by employing a binary statistical detection model based on the sum of squares (SSE) between the observed value and the estimated value of the pointing vector, real-time spoofing signal detection is enabled. Simulation results confirm the efficacy of the proposed statistical model, with the error of the skewness coefficient not exceeding 0.026. Experimental results further demonstrate that the collinear antenna-based method reduces the standard deviation of the angle deviation of the pointing vector by over 55.62% in the presence of spoofing signals. Moreover, the experiments indicate that with a 1 m baseline, this method achieves 100% spoofing detection.

Navigation Signal based on Compound Carrier (NSCC), is proposed as the potential future global navigation satellite system (GNSS) signal modulation scheme. NSCC, a kind of multi-carrier (MC) signal, is generated by superposition and multi-parameter adjustment of sub-carriers. Therefore, a judious choice of parameter configation is needed. The main objective of this paper is to investigate the performance of the NSCC which is influenced by these parameters and to demonstrate its structure characteristics and superiority, employing a comprehensive evaluation system. The results show that the proposed NSCC signal processes full spectral efficiency and limited out of band (OOB) emissions, satisfying the demands of crowed frequency resources. It also presents better performance in terms of spectral separation coefficients (SSCs), tracking accuracy, multipath mitigation capability and anti-jamming reduction compared with the legacy navigation signals. NSCC modulation represents a serious candidate for navigation satellite augmentation systems, especially for signals applied in challenging environments.

Attitude determination technology based on the global navigation satellite system (GNSS) has been widely studied due to its low cost and no accumulation of errors. The essential task of attitude determination using GNSS is to estimate the pointing vector of the baseline. However, when the user is located in the complex urban canyon environment, the success rate of ambiguity will be significantly reduced, resulting in inaccurate attitude determination results. This paper presents improvements to existing methods for ambiguity resolution using collinear antennas. The collinear receiver system is built with low-cost commercial antennas to verify the method’s performance. Results indicate a success rate of over 68% with just four satellites, demonstrating significant improvement over traditional LAMBDA method. This method reduces operation time while maintaining a high success rate, with a potential reduction of up to three orders of magnitude compared to the baseline constrained LAMBDA method. The method also exhibits potential anti-multipath capability, reducing RMSE of the pointing vector coordinate component by 60.3%, 87.5%, and 94.2% in the urban canyon environment with significant multipath effects. These results demonstrate the practical effectiveness and potential of the method for ambiguity resolution in challenging environments.

Positioning based on Low Earth Orbit (LEO) satellite Signals of Opportunity (SOP) often relies on Doppler observations. Therefore, the accuracy of Doppler frequency measurements significantly impacts the positioning performance. Traditional frequency estimation methods for ORBCOMM satellite signals are typically implemented in the frequency domain and neglect the impact of the “frequency chirp” effect on measurement accuracy, which leads to low computational efficiency, poor noise resistance, and limited estimation accuracy. To address this issue, a high-precision frequency estimation method combining a “coarse and fine” process is proposed. In the coarse estimation process, ephemeris prior information is combined with matched filtering to effectively separate the Doppler rate, thereby mitigating the spectral broadening caused by the Doppler rate. In the fine estimation process, ORBCOMM signal characteristics are fully exploited. Single-sideband filtering is applied to improve noise resistance, followed by precise frequency discrimination of the delayed signal. Experimental results demonstrate that the proposed method outperforms the state-of-the-art “FFT + MLE” approach, achieving a frequency measurement accuracy on the order of 0.01 Hz while requiring fewer computational resources. Furthermore, this method improves estimation performance by approximately 12 dB without compromising frequency measurement accuracy.