In this paper, we investigate how the proposed navigation mode "dead reckoning + relative ranging + heading constraint" can be used to cooperatively localize a UAV swarm when GNSS (Global Navigation Satellite System) is denied. By focusing on the relative ranging performance, the wireless RF modules mounted on the cost-efficient UAVs are used to provide communication, ranging and positioning at the same time; however, its positioning accuracy is usually degraded by the noise in the actual RSSI (Received Signal Strength Indicator) measurements. To solve this problem, we analyze the influence of antenna pattern inhomogeneity and channel variation, respectively. The former mainly determines an antenna radiation function related to the yaw angle and relative position between the two measuring UAVs. The latter uses overlapping Allan variance to analyze and identify the measurement noises from outfield tests, that is, quantization noise, flicker noise, random walk noise and Gaussian white noise, which to some extent bridges the difference between the theoretical model and the practical measurement of RSSI. We also evaluate the sub-swarm size that guarantees robustness of RSS-based localization. In this way, an improved extended Kalman filter is proposed to predict and correct the colored noise by adaptively integrating the current peer-to-peer radio ranging performance and its Allan variance. To prove the effectiveness of this approach, simulation results based on real environment datasets and practical noise modeling are demonstrated.

The precise point positioning (PPP) technique has been widely used for remote time and frequency transfer. With the development of the multiple global navigation satellite system (multi-GNSS), the PPP technique with multi-GNSS has been studied in order to improve the performance of time and frequency transfer. However, the day boundary problem, model correction residuals, and noise may affect the clock estimation in multi-GNSS PPP. In this study, we refine the receiver clock parameter using a stochastic model of an atomic clock to solve these problems. First, the receiver clock modeling method is proposed to reduce the additional noise in the clock estimation. Second, we present the clock instantaneous reinitialization method to solve the day boundary problem. Finally, an enhanced multi-GNSS time transfer method can be obtained. We combine the observations of the global positioning system, the global navigation satellite system, the BeiDou satellite navigation system, and Galileo for the experiment. Standard deviation (STD) and modified Allan deviation (MDEV) are employed to evaluate our approach. The experimental results showed that after using the enhanced transfer method, the STD values of the time transfer results with respect to the International GNSS Service final products were reduced, with an average reduction ratio of 18.3% for all time links. Meanwhile, the stability of frequency transfer results was effectively improved, especially in the short term. The average reduction ratios of MDEV at 30, 60, and 120 s were up to 55.5%, 39.1%, and 23.2%, respectively. Our approach can effectively solve the problem of discontinuities, model correction residuals, and noise in clock estimation, and significantly improve the performance of multi-GNSS time and frequency transfer.

2020 saw the official completion of the BDS-3 and the start of the PPP-B2b signal-based real-time precise point positioning (PPP) service to users in China and the neighboring areas. In this work, the quality of PPP-B2b products is first evaluated and compared with real-time products from the CNES and the differential code bias (DCB) from the Chinese Academy of Science (CAS). Then, a detailed performance evaluation of the PPP time transfer based on the PPP-B2b service (B2b-RTPPP) is conducted. Three solutions, namely, GPS-only (G), BDS-3-only (C), and GPS + BDS-3 (GC) B2b-RTPPP solutions, are compared and assessed. The results suggest that for the PPP-B2b products, BDS-3 satellites have better orbit and clock offset quality than GPS satellites, while the opposite is true for CNES products. The quality of the PPP-B2b orbit and clock offset is poorer than those of the CNES. The PPP-B2b DCB shows excellent agreement with the CAS DCB. The accuracy of the B2b-RTPPP solutions is sub-nanosecond level. The accuracy of B2b-RTPPP time transfer with DCB correction is approximately improved by 64% compared with that without DCB correction. The GC B2b-RTPPP solution has the greatest frequency stability, while G B2b-RTPPP solution has the poorest. Considering that the receiver may be blocked, the B2b-RTPPP time transfer performance is also evaluated at different cut-off elevation angles. As the angle increases, the B2b-RTPPP time transfer performance decreases. Additionally, the short-term frequency stability remains constant at different cut-off elevation angles, but deteriorates in the long term, especially when the angle is 40°.

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.