Global navigation satellite system (GNSS) displacements at near‐source stations can be biased in both amplitude and phase due to fierce earthquake strike. We propose to inject inertial measurement ...unit (IMU)‐recorded ground motions into GNSS receivers to compensate their phase‐lock loops (PLLs) for seismic motion stress, aiming at keeping steady carrier‐phase tracking. We use a shake table to replay an acceleration record (0.5–2.0 g) from the 2008 Mw7.9 Wenchuan earthquake to test this IMU‐augmented PLL: It achieves a 1.9‐mm amplitude error (RMS) and an 8.0‐ms phase lag against the shake table's recordings, while the conventional PLL languishes to 6.0 mm and 56.5 ms, respectively. Moreover, the IMU‐augmented PLL enables a six‐degree‐of‐freedom integration among the GNSS and IMU data, where the displacement amplitude error and phase lag decline further to 0.9 mm and 3.5 ms, respectively. We believe that the IMU‐augmented GNSS receivers are ideal strong‐motion seismograph to capture trustworthy broadband displacements in the near fields.
Plain Language Summary
Understanding the origin and mechanism of destructive earthquakes is predicated on the faithful recordings of their induced ground displacements near the significantly deformed epicentral regions. Global navigation satellite system (GNSS) receivers have been recognized as the best tool to measure the large epicentral displacements. This is achieved within the GNSS receivers by continuously tracking the satellite carrier‐phase signals. However, GNSS receivers are likely to lose their fidelity in recording complete and accurate displacement waveforms in case of strong ground motions, since their carrier‐phase tracking becomes unstable when strained by such persistent and high dynamic stress. We hence developed an advanced GNSS receiver architecture where the dynamic stress suffered by the carrier‐phase tracking components is compensated for by an embedded inertial measurement unit consisting of one accelerometer and one gyroscope. In this case, the carrier‐phase signals can be tracked steadily by GNSS receivers, and the displacement accuracy can be improved from subcentimeter to millimeter level by about 70% when the ground accelerations reach up to twice the gravitational acceleration. We believe that this advanced GNSS receiver will be an excellent strong‐motion seismometer in recording displacements directly at a few millimeter resolution without missing or distorting any earthquake signals, even in case of fierce ground motions.
Key Points
A new GNSS receiver architecture is developed by embedding both accelerometer and gyroscope to capture fierce seismic displacements
GNSS displacement error and phase lag are both reduced by 70% and 85% to 2 mm and 8.0 ms, respectively, compared to conventional receivers
Six‐degree‐of‐freedom seismogeodesy is achieved with the displacement error and phase lag reduced further to 0.9 mm and 3.5 ms, respectively
In urban environments, Global Navigation Satellite Systems (GNSS) signals are frequently attenuated, blocked or reflected, which degrades the positioning accuracy of GNSS receivers significantly. To ...improve the performance of GNSS receiver for vehicle urban navigation, a GNSS/INS deeply-coupled software defined receiver (GIDCSR) with a low cost micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) ICM-20602 is presented, in which both GPS and BDS constellations are supported. Two key technologies, that is, adaptive open-close tracking loops and INS aided pseudo-range weight control algorithm, are applied in the GIDCSR to enhance the signal tracking continuity and positioning accuracy in urban areas. To assess the performance of the proposed deep couple solution, vehicle field tests were carried out in GNSS-challenged urban environments. With the adaptive open-close tracking loops, the deep couple output carrier phase in the open sky, and improved pseudo-range accuracy before and after GNSS signal blocked. Applying the INS aided pseudo-range weight control, the pseudo-range gross errors of the deep couple decreased caused by multipath. A popular GNSS/INS tightly-coupled vehicle navigation kit from u-blox company, M8U, was tested side by side as benchmark. The test results indicate that in the GNSS-challenged urban areas, the pseudo-range quality of GIDCSR is at least 25% better than that of M8U, and GIDCSR’s horizontal positioning results are at least 69% more accurate than M8U’s.
The main objective of this research was to evaluate the navigation performance of multi-information integration based on a low-end inertial measurement unit (IMU) in precision agriculture by ...utilizing different auxiliary information (i.e., GNSS real-time kinematic (RTK), non-holonomic constraints (NHC) and dual antenna GNSS). A series of experiments with different operation scenes (e.g., open sky in wet and dry soils) were carried out for quantitative analysis. For the position drift error during a 20-s GNSS outage, the dual-antenna GNSS-assisted approach did not provide a reduction, and the NHC reduced the maximum error in the lateral and vertical directions by over 80% in the dry soil test, but only by approximately 30% in the wet soil test. The heading error with continuous GNSS assistance can be less than 0.03° and be reduced by more than 90% with the aid of dual-antenna GNSS. Additionally, the NHC reduced the heading error from 0.54° to 0.21° and from 0.34° to 0.25° in the dry and wet soil tests respectively. The results suggested that the multi-information integration improved the positioning and orientation reliability. Moreover, the lateral positioning accuracy required for the control of agriculture autonomous vehicles was achieved at approximately 3.0 mm with over a 60% accuracy improvement brought by the dual-antenna GNSS assistance. In contrast to the vulnerability of a single system, multi-information integration can provide comprehensive navigation information with higher reliability and lower costs. Hence, multi-information fusion will be a great opportunity for agriculture to meet the high-accuracy and high-reliability requirements of precision agriculture.
An accurate ego-motion estimation solution is vital for autonomous vehicles. LiDAR is widely adopted in self-driving systems to obtain depth information directly and eliminate the influence of ...changing illumination in the environment. In LiDAR odometry, the lack of descriptions of feature points as well as the failure of the assumption of uniform motion may cause mismatches or dilution of precision in navigation. In this study, a method to perform LiDAR odometry utilizing a bird’s eye view of LiDAR data combined with a deep learning-based feature point is proposed. Orthographic projection is applied to generate a bird’s eye view image of a 3D point cloud. Thereafter, an R2D2 neural network is employed to extract keypoints and compute their descriptors. Based on those keypoints and descriptors, a two-step matching and pose estimation is designed to keep these feature points tracked over a long distance with a lower mismatch ratio compared to the conventional strategy. In the experiment, the evaluation of the proposed algorithm on the KITTI training dataset demonstrates that the proposed LiDAR odometry can provide more accurate trajectories compared with the handcrafted feature-based SLAM (Simultaneous Localization and Mapping) algorithm. In detail, a comparison of the handcrafted descriptors is demonstrated. The difference between the RANSAC (Random Sample Consensus) algorithm and the two-step pose estimation is also demonstrated experimentally. In addition, the data collected by Velodyne VLP-16 is also evaluated by the proposed solution. The low-drift positioning RMSE (Root Mean Square Error) of 4.70 m from approximately 5 km mileage shown in the result indicates that the proposed algorithm has generalization performance on low-resolution LiDAR.
The Galileo navigation satellite system (Galileo) E5 Alternative Binary Offset Carrier (AltBOC) signal brings various challenges due to its complex modulation, wide bandwidth, and multi-peaked ...auto-correlation function. While wideband tracking needs to solve the ambiguity problem and design dedicated baseband channels, the single-sideband cannot have the outstanding performance of the AltBOC signal. We propose a new tracking method called “Double Sideband Combined Tracking” (DSCT), which can fully exploit the AltBOC signal’s code tracking accuracy without ambiguity and ensure compatibility with Binary Phase Shift Keying (BPSK) processing channels, easily implemented in hardware. The DSCT employs one phase locked loop and one delay locked loop to track the carrier and code, respectively. The double-sideband correlation results used by the two loops are recovered by coherently combining the single-sideband correlation results of the two BPSK channels. Meanwhile, the combined model, the loop discriminator, and the ambiguity detection of the DSCT are discussed. Furthermore, the code tracking error caused by thermal noise is modeled and analyzed. The test results based on real Galileo E5 signals show that the DSCT exhibits better or comparable code tracking accuracy to the AltBOC wideband tracking method. When the loop falsely locks onto a side-peak, the DSCT can quickly detect and re-lock on the main peak.
A GNSS/INS deeply-coupled system can improve the satellite signals tracking performance by INS aiding tracking loops under dynamics. However, there was no literature available on the complete ...modeling of the INS branch in the INS-aided tracking loop, which caused the lack of a theoretical tool to guide the selections of inertial sensors, parameter optimization and quantitative analysis of INS-aided PLLs. This paper makes an effort on the INS branch in modeling and parameter optimization of phase-locked loops (PLLs) based on the scalar-based GNSS/INS deeply-coupled system. It establishes the transfer function between all known error sources and the PLL tracking error, which can be used to quantitatively evaluate the candidate inertial measurement unit (IMU) affecting the carrier phase tracking error. Based on that, a steady-state error model is proposed to design INS-aided PLLs and to analyze their tracking performance. Based on the modeling and error analysis, an integrated deeply-coupled hardware prototype is developed, with the optimization of the aiding information. Finally, the performance of the INS-aided PLLs designed based on the proposed steady-state error model is evaluated through the simulation and road tests of the hardware prototype.
To meet the requirements of global navigation satellite systems (GNSS) precision applications in high dynamics, this paper describes a study on the carrier phase tracking technology of the ...GNSS/inertial navigation system (INS) deep integration system. The error propagation models of INS-aided carrier tracking loops are modeled in detail in high dynamics. Additionally, quantitative analysis of carrier phase tracking errors caused by INS error sources is carried out under the uniform high dynamic linear acceleration motion of 100 g. Results show that the major INS error sources, affecting the carrier phase tracking accuracy in high dynamics, include initial attitude errors, accelerometer scale factors, gyro noise and gyro g-sensitivity errors. The initial attitude errors are usually combined with the receiver acceleration to impact the tracking loop performance, which can easily cause the failure of carrier phase tracking. The main INS error factors vary with the vehicle motion direction and the relative position of the receiver and the satellites. The analysis results also indicate that the low-cost micro-electro mechanical system (MEMS) inertial measurement units (IMU) has the ability to maintain GNSS carrier phase tracking in high dynamics.
In the Global Positioning System (GPS)/Inertial Navigation System (INS) deep integration system, the pure negative effect of the INS aiding is mainly the INS navigation error that is independent with ...the motion dynamics, which determine whether the INS aiding is worthy. This paper quantitatively assesses the negative effects of the inertial aiding information from different grades of INS by modeling the phase-locked loops (PLLs) based on the scalar-based GPS/INS deep integration system under stationary conditions. Results show that the largest maneuver-independent velocity error caused by the error sources of micro-electro-mechanical System (MEMS) inertial measurement unit (IMU) is less than 0.1 m/s, and less than 0.05 m/s for the case of tactical IMU during the typical GPS update interval (i.e., 1 s). The consequent carrier phase tracking error in the typical tracking loop is below 1.2 degrees for MEMS IMU case and 0.8 degrees for the tactical IMU case, which are much less than the receiver inherent errors. Conclusions can be reached that even the low-end MEMS IMU has the ability of aiding the receiver signal tracking. The tactical grade IMU can provide higher quality aiding information and has potential for the open loop tracking of GPS.
When strong earthquake occurs, global navigation satellite systems (GNSS) measurement errors increase significantly. Combined strategies of GNSS/accelerometer data can estimate better precision in ...displacement, but are of no help to carrier phase measurement. In this paper, strong-motion accelerometer-aided phase-locked loops (PLLs) are proposed to improve carrier phase accuracy during strong earthquakes. To design PLLs for earthquake monitoring, the amplitude-frequency characteristics of the strong earthquake signals are studied. Then, the measurement errors of PLLs before and after micro electro mechanical systems (MEMS) accelerometer aiding are analyzed based on error models. Furthermore, tests based on a hardware simulator and a shake table are carried out. Results show that, with MEMS accelerometer aiding, the carrier phase accuracy of the PLL decreases little under strong earthquakes, which is consistent with the models analysis.
In filtering-based global navigation satellite system (GNSS) / inertial navigation system (INS) integrated navigation systems, the precise INS mechanization has fully considered the impact of the ...Earth rotation, Coriolis acceleration, etc. However, most inertial measurement unit (IMU) preintegration models in factor graph optimization (FGO)-based integrated navigation systems are rough and ignore these factors. We propose an FGO-based GNSS/INS integrated navigation system to analyze and evaluate the impact of the Earth rotation on MEMS-IMU preintegration. The proposed FGO-based integration is based on a refined IMU preintegration, in which the Earth rotation is compensated. The proposed GNSS/INS integration is a sliding-window optimizer in which the GNSS positioning and the IMU preintegration are tightly fused within the FGO framework. The simulated GNSS outage in field tests, an effective method, is adopted to evaluate the IMU preintegration quantitatively. The results demonstrate that the refined IMU preintegration can achieve the same accuracy as the precise INS mechanization. In contrast, the rough IMU preintegration and INS mechanization without compensating for the Earth rotation yields notable accuracy degradation. When the GNSS-outage time is 60 seconds, the degradation can be 200% for the industrial-grade MEMS module and more than 10% for the consumer-grade MEMS chip. Besides, the degradation can be more significant if the GNSS-outage time is longer. The proposed FGO-based GNSS/INS integration ( https://github.com/i2Nav-WHU/OB_GINS ) and the employed datasets ( https://github.com/i2Nav-WHU/awesome-gins-datasets ) are open-sourced on GitHub.
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