The emerging Global Navigation Satellite Systems (GNSS) including the BeiDou Navigation Satellite System (BDS) offer more visible satellites for positioning users. To employ those new satellites in a real-time kinematic (RTK) algorithm to enhance positioning precision and availability, a data processing model for the dual constellation of GPS and BDS is proposed and analyzed. A Kalman filter-based algorithm is developed to estimate the float ambiguities for short baseline scenarios. The entire work process of the high-precision algorithm based on the proposed model is deeply investigated in detail. The model is validated with real GPS and BDS data recorded from one zero and two short baseline experiments. Results show that the proposed algorithm can generate fixed baseline output with the same precision level as that of either a single GPS or BDS RTK algorithm. The significantly improved fixed rate and time to first fix of the proposed method demonstrates a better availability and effectiveness on processing multi-GNSSs.

Jamming and spoofing are the two main types of intentional interference for global navigation satellite system (GNSS) receivers. Due to the entirely different signal characteristics they have, a few techniques can deal with them simultaneously. This paper proposes a two-stage interference suppression scheme based on antenna arrays, which can detect and mitigate jamming and spoofing before the despreading of GNSS receivers. First, a subspace projection was adopted to eliminate the high-power jamming signals. The output signal is still a multi-dimensional vector so that the spatial processing technique can be used in the next stage. Then, the cyclostationarity of GNSS signals were fully excavated to reduce or even remove the noise component in the spatial correlation matrix. Thus, the signal subspace, including information of the power and the directions-of-arrival (DOAs) of the GNSS signals, can be obtained. Next, a novel cyclic correlation eigenvalue test (CCET) algorithm was proposed to detect the presence of a spoofing attack, and the cyclic music signal classification (Cyclic MUSIC) algorithm was employed to estimate the DOAs of all the navigation signals. Finally, this study employed a subspace projection again to eliminate the spoofing signals and provide a higher gain for authentic satellite signals through beamforming. All the operations were performed on the raw digital baseband signal so that they did not introduce additional computational complexity to the GNSS receiver. The simulation results show that the proposed scheme not only suppresses jamming and spoofing effectively but also maximizes the power of the authentic signals. Nonetheless, the estimated DOA of spoofing signals may be helpful for the interference source positioning in some applications.

This paper presents a Lidar / ultra-wideband (UWB) fusion algorithm for simultaneous localization and mapping (SLAM) with anti-degeneration capability. In the proposed algorithm, the sensor states are estimated by minimizing the sum of the Mahalanobis norm of all measurement residuals associated with the Lidar sensor and the UWB sensors. Additionally, considering that a poor geometric distribution of the sensor measurements will introduce large estimation uncertainties in the fusion algorithm, a trade-off parameter with its self-adjustment strategy is introduced in the fusion algorithm to adjust the ratio of the contributions provided by the Lidar measurement residuals and the UWB measurement residuals in the state estimation according to their degeneration degrees. A method that can detect and determine the degeneration degree of the sensor measurements is also presented in the paper. In order to evaluate the performance of the proposed fusion algorithm, two experiments were carried out. Results of the experiments show that the proposed Lidar/UWB fusion algorithm can automatically adjust the trade-off parameter according to the degeneration degrees of the sensor measurements and mitigate the effects of the degeneration.

Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability for GNSS anti-spoofing since a spoofing attack that misleads the positioning and timing result will cause distortion to the MLE cost function. Based on the method, an estimation-cancellation approach is presented to detect spoofing attacks and recover the navigation solution. A statistic is derived for spoofing detection with the principle of the generalized likelihood ratio test (GLRT). Then, the MLE cost function is decomposed to further validate whether the navigation solution obtained by MLE-based positioning is formed by consistent signals. Both formulae and simulations are provided to evaluate the anti-spoofing performance. Experiments with recordings in real GNSS spoofing scenarios are also performed to validate the practicability of the approach. Results show that the method works even when the code phase differences between the spoofing and authentic signals are much less than one code chip, which can improve the availability of GNSS service greatly under spoofing attacks.

The spatiotemporal information plays crucial roles in a multi-agent system (MAS). However, for a highly dynamic and dense MAS in unknown environments, estimating its spatiotemporal states is a difficult problem. In this paper, we present BLAS: a wireless broadcast relative localization and clock synchronization system to address these challenges. Our BLAS system exploits a broadcast architecture, under which a MAS is categorized into parent agents that broadcast wireless packets and child agents that are passive receivers, to reduce the number of required packets among agents for relative localization and clock synchronization. We first propose an asynchronous broadcasting and passively receiving (ABPR) protocol. The protocol schedules the broadcast of parent agents using a distributed time division multiple access (D-TDMA) scheme and delivers interagent information used for joint relative localization and clock synchronization. We then present distributed state estimation approaches in parent and child agents that utilize the broadcast inter-agent information for joint estimation of spatiotemporal states. The simulations and real-world experiments based on ultra-wideband (UWB) illustrate that our proposed BLAS cannot only enable accurate, high-frequency and real-time estimation of relative position and clock parameters but also support theoretically an unlimited number of agents.