Real-time precise point positioning (RTPPP) is a popular positioning method that uses a real-time service (RTS) product to mitigate various Global Navigation Satellite Systems (GNSS) errors. However, communication links are not available in the ocean. The use of a communication satellite for data transmission is so expensive that normal users could not afford it. The BeiDou short-message service provides an efficient option for data transmission at sea, with an annual fee of approximately 160 USD. To perform RTPPP using BeiDou short messages, the following two challenges should be appropriately addressed: the maximum size of each BeiDou message is 78 bytes, and the communication frequency is limited to once a minute. We simplify the content of RTS data to minimize the required bandwidth. Moreover, the orbit and clock corrections are predicted based on minute-interval RTS orbital and clock corrections. An experiment was conducted to test the performance of the proposed method. The numerical results show that the three-dimensional positioning precision can reach approximately 0.4 m with combined GPS + GLONASS and approximately 0.2 m with combined GPS + GLONASS + Galileo + BeiDou.

Traditional coseismic displacement retrieval generally uses real-time kinematic (RTK) and precise point positioning (PPP) services. However, both RTK and real-time PPP need a network link to transmit the corrected data. Although the network link may be interrupted when an earthquake happens, the PPP-B2b service broadcasted by geostationary orbit (GEO) satellites will not be affected. Its service range mainly covers China and the surrounding areas. In this research, the PPP method with PPP-B2b service based on constrained coordinates is proposed and overcomes the limitation of the network link and long convergence time. First, the accuracy of orbits and clock offsets for the PPP-B2b service is evaluated and compared with real-time service (RTS). Then, the simulated experiments are carried out using the PPP method with PPP-B2b service based on constrained coordinates, which tests the accuracy by calculating the coordinate displacement of the measurement station. The results show that the accuracy of PPP-B2b orbits in the radial direction is within 0.1 m. Moreover, regarding the accuracy of clock offsets, the PPP-B2b service is no more than 3.5 cm. This validates the feasibility of replacing RTS products with PPP-B2b. In the 15 min simulated experiments, the root mean square (RMS) of horizontal and vertical directions is maintained within 3 cm.

The differential global navigation satellite system (DGNSS) is an enhancement system that is widely used to improve the accuracy of single-frequency receivers. However, distance-dependent errors are not considered in conventional DGNSS, and DGNSS accuracy decreases when baseline length increases. In network real-time kinematic (RTK) positioning, distance-dependent errors are accurately modelled to enable ambiguity resolution on the user side, and standard Radio Technical Commission for Maritime Services (RTCM) formats have also been developed to describe the spatial characteristics of distance-dependent errors. However, the network RTK service was mainly developed for carrier-phase measurements on professional user receivers. The purpose of this study was to modify the local-area DGNSS through the use of network RTK corrections. Distance-dependent errors can be reduced, and accuracy for a longer baseline length can be improved. The results in the low-latitude areas showed that the accuracy of the modified DGNSS could be improved by more than 50% for a 17.9 km baseline during solar active years. The method in this paper extends the use of available network RTK corrections with high accuracy to normal local-area DGNSS applications.

Current studies of global navigation satellite systems (GNSS)-based bistatic synthetic aperture radar (GNSS-SAR) is focused on static objects on land. However, moving target imaging is also very significant for modern SAR systems. Imaging a moving target has two main problems. One is the unknown range cell migration; the other is the motion parameter estimation, such as the target’s velocity. This paper proposes a moving target imaging formation algorithm for GNSS-SAR. First, an approximate bistatic range history is derived to describe the phase variation of the target signal along the azimuth time. Then, a keystone transform is employed to correct the range cell migration. To address the motion parameter estimation, a chirp rate estimation method based on short-time Fourier transform and random sample consensus is proposed with high processing efficiency and robust estimation errors in low signal-to-noise ratio scenes. The estimated chirp rate can calculate the target’s velocity. Finally, azimuth compression derivation is performed to accomplish GNSS-SAR imaging. A maritime experimental campaign is conducted to validate the effectiveness of the proposed algorithm. The two cargo ships in the SAR images have good accordance with the ground truth in terms of the target-to-receiver vertical distances along the range and the ships’ length along the cross-range.

Spherical images have the advantage of recording full scenes using only one camera exposure and have been becoming an important data source for 3D reconstruction. However, geometric distortions inevitably exist due to the spherical camera imaging model. Thus, this study proposes a reliable feature matching algorithm for spherical images via the combination of local geometric rectification and CNN (convolutional neural network) learned descriptor. First, image patches around keypoints are reprojected to their corresponding tangent planes based on a spherical camera imaging model, which uses scale and orientation data from the keypoints to achieve both rotation and scale invariance. Second, feature descriptors are then calculated from the rectified image patches by using a pre-trained separate detector and descriptor learning network, which improves the discriminability by exploiting the high representation learning ability of the CNN. Finally, after classical feature matching with the ratio test and cross check, refined matches are obtained based on an essential matrix-based epipolar geometry constraint for outlier removal. By using three real spherical images and an incremental structure from motion (SfM) engine, the proposed algorithm is verified and compared in terms of feature matching and image orientation. The experiment results demonstrate that the geometric distortions can be efficiently reduced from rectified image patches, and the increased ratio of the match numbers ranges from 26.8% to 73.9%. For SfM-based spherical image orientation, the proposed algorithm provides reliable feature matches to achieve complete reconstruction with comparative accuracy.

The geostationary earth orbit (GEO) and inclined geosynchronous orbit (IGSO) satellites of the Beidou navigation satellite system are maneuvered frequently. The broadcast ephemeris can be interrupted for several hours after the maneuver. The orbit-only signal-in-space ranging errors (SISREs) of broadcast ephemerides available after the interruption are over two times larger than the errors during normal periods. To shorten the interruption period and improve the ephemeris accuracy, we propose a two-step orbit recovery strategy based on a piecewise linear thrust model. The turning points of the thrust model are firstly determined by comparison of the kinematic orbit with an integrated orbit free from maneuver; afterward, precise orbit determination (POD) is conducted for the maneuvered satellite by estimating satellite orbital and thrust parameters simultaneously. The observations from the IGS Multi-Global Navigation Satellite System (GNSS) Experiment (MGEX) network and ultra-rapid products of the German Research Center for Geosciences (GFZ) are used for orbit determination of maneuvered satellites from Sep to Nov 2017. The results show that for the rapidly recovered ephemerides, the average orbit-only SISREs are 1.15 and 1.0 m 1 h after maneuvering for GEO and IGSO respectively, which is comparable to the accuracy of Beidou broadcast ephemerides in normal cases.