Intelligent navigation is a fundamental technology that enables unmanned systems to achieve autonomy in the intelligent era. However, existing navigation schemes suffer from high computational complexity and power consumption, as well as low robustness in complex or unknown environments. To address these challenges, this article proposes a novel 3-D brain-inspired simultaneous localization and mapping (SLAM) method, called oriented FAST and rotated BRIEF (ORB)-NeuroSLAM, based on the ORB features. The proposed method takes inspiration from the robust and low-power navigation capabilities of humans and animals. The ORB-NeuroSLAM leverages the ORB features of camera images to compute robot self-motion and visual cues. Then, continuous attractor neural networks (CANNs) model multilayered head-direction cells and 3-D grid cells that exist in animal brains. These cells are utilized jointly to represent the robot poses. Efficient and robust methods for loop closure detection and experience map construction were also developed. The proposed method was verified on ten KITTI data sets, and experimental results demonstrate that it outperforms state-of-the-art brain-inspired SLAM methods in terms of accuracy and efficiency. Additionally, it is comparable to the state-of-the-art visual SLAM method ORB-SLAM3.

Real-time Precise Point Positioning (PPP) is an innovative and useful atmosphere remote sensing tool to estimate Zenith Tropospheric Delays (ZTD) to support various emerging meteorological applications such as weather and climate research. However, additional costs on Internet accesses or service subscription licenses are required to obtain real-time precise satellite orbit and clock products from external PPP augmentation service operators. We present the real-time precise estimation of ZTD with freely- and openly- accessible GNSS satellite-based PPP augmentation services, i.e., BeiDou Navigation Satellite System (BDS) PPP-B2b service, Galileo High Accuracy Service (HAS), and Quasi-Zenith Satellite System (QZSS) Multi-GNSS ADvanced Orbit and Clock Augmentation-Precise Point Positioning (MADOCA-PPP) service. GNSS observations of 49 days from 15 stations in the Asia-Pacific region are used for performance assessment and comparison. It shows that the real-time PPP estimated ZTDs agree well with International GNSS Service (IGS) final ZTDs, with mean Standard Deviation values (STDs) of 20.0, 17.5 and 9.5 mm for BDS PPP-B2b, Galileo HAS, and QZSS MADOCA-PPP, respectively. The derived real-time Zenith Wet Delays (ZWDs) are further compared with those derived from Integrated Global Radiosonde Archive (IGRA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) datasets, which confirms that the real-time PPP estimated ZWDs are accurate with mean STDs of smaller than 30 mm. It concludes that real-time PPP with GNSS satellite-based real-time PPP augmentation correction services will be a flexible and cost-effective tool to derive real-time precise ZTDs/ZWDs with high spatiotemporal resolution in all-weather conditions.

The China BeiDou Navigation Satellite System (BDS-3) is recognized for its advantages compared to BDS-2. However, the enhancement of performance through the simultaneous utilization of BDS-2 and BDS-3 in real-time kinematic (RTK) applications remains insufficiently investigated. Herein, we developed an overlapping triple-frequency (TF) BDS-3/BDS-2/inertial navigation system (INS) tightly coupled (TC) integration model that takes advantage of the BDS-3/BDS-2 overlapping frequencies of B1I/B2b(B2I)/B3I for intersystem combination and INS-assisted positioning. An analytical formula for ambiguity dilution of precision (ADOP) was derived, serving as the foundation for an exploration into how multi-frequency measurements and INS assistance affect ambiguity resolution (AR). A vehicle experiment was conducted in a city to evaluate the performance of the measurement models for various frequencies, available satellites, and INS assistance. Analysis of the double differencing errors of the pseudorange and carrier phases revealed that a robust model in kinematic situations is preferred over static situations. AR ability was assessed regarding ADOP, ratio test, and success rates, and the positioning and attitude determination results were examined. Overall, the characteristics of the ADOP analytic formula and processing results produce a similar conclusion regarding the contribution of multi-frequency, available measurements, and INS assistance on AR; further, they provide reference values for moving measuring system users to implement the optimal model in kinematic situations.

Carrier phase integer ambiguities must be determined for BDS-3/inertial navigation system (INS) tightly coupled (TC) integration to achieve centimetre-level positioning accuracy. However, cycle slip breaks the consistency of the integer ambiguities. Conventional multi-frequency cycle slip methods use the pseudorange; thus, requiring improvement when applied to kinematic situations. Furthermore, a concise and nonprior information-dependent model is crucial for real-time processing. In this study, an inertial-aided BDS-3 cycle slip detection and repair (I-CDR) method was developed. First, a BDS-3/INS TC model with I-CDR was created. The ionospheric delays were modelled as part of the TC states; therefore, they could be estimated and eliminated. Investigations were conducted on the effects of carrier phase noise, residual ionosphere delay, and INS-predicted position error on combined cycle slip detection (CCD) accuracy. The optimal CCDs under various frequency available configurations were determined. The effectiveness of I-CDR was demonstrated using land vehicle test data. The false alarm ratio was less than 1.0%, and the missed detection ratio was almost zero even in situations with challenging abundant 1-cycle slips in random epochs. Furthermore, the right determination ratio reached 100%. In addition, BDS-3 signal loss-recovery cases were simulated, and all cycle slips for all satellites could be repaired within 40s. I-CDR exhibits outstanding cycle slip detection and repair performance for dense 1-cycle slip and signal loss-recovery cases, demonstrating its suitability for BDS-3/INS TC integration.

Under harsh propagation conditions, Global Navigation Satellite Systems (GNSS) receivers are susceptible to signal degradation, which can lead to loss of signal lock. Unlocked receivers, when subjected to spoofing attacks, are highly susceptible to false re-acquisition, and their tracking-stage anti-spoofing algorithms may become ineffective, thereby simplifying the execution of spoofing interference. Compared to the traditional scalar tracking loop (STL), the vector tracking loop (VTL) demonstrates superior performance in maintaining Positioning, Navigation, and Timing (PNT) service continuity in complex environments. Therefore, this study designs an enhanced VTL by developing an adaptive loop controller and constructs a composite interference scenario using the Oak Ridge Spoofing and Interference Test Battery (OAKBAT) database to compare the anti-spoofing performance of STL and VTL under various application challenges. In the os2 scenario, the STL’s root mean square (RMS) value of the receiver clock error increases sharply to 601.1 m owing to the re-acquisition, while the VTL is not affected by the signal interruption. In the os4 scenario, the RMS value of its position solution deviation was reduced by 66.35% and 80.83% compared with that of the STL before and after signal interruption, respectively. The study demonstrates that VTL, empowered by an Extended Kalman Filter (EKF) and interchannel cooperation, possesses significant anti-spoofing advantages in adverse environments. These findings highlight the significant advantages of VTL in improving the endogenous security of GNSS receivers and provide key insights for designing anti-spoofing algorithms for challenging environments.