In the field of high accuracy dual-axis rotational inertial navigation system (RINS), the calibration accuracy of the gyroscopes and accelerometers is of great importance. Although rotation ...modulation can suppress the navigation error caused by scale factor error and bias error in a static condition, it cannot suppress the scale factor errors thoroughly during the maneuvering process of the vehicle due to the two degrees of rotation freedom. The self-calibration method has been studied by many researchers. However, traditional calibration methods need several hours to converge, which is unable to meet the demand for quick response to positioning and orientation. To solve the above problems, we do the following work in this study: (1) we propose a 39-dimensional online calibration Kalman filtering (KF) model to estimate all calibration parameters; (2) Error relationship between calibration parameters error and navigation error are derived; (3) A backtracking filtering scheme is proposed to shorten the calibration process. Experimental results indicate that the proposed method can shorten the calibration process and improve the calibration accuracy simultaneously.
On 15 January 2022, the Hunga Tonga‐Hunga Ha’apai submarine volcano erupted violently and triggered a giant atmospheric shock wave and tsunami. The exact mechanism of this extraordinary eruptive ...event, its size and magnitude are not well understood yet. In this work, we analyze data from the nearest ground‐based receivers of Global Navigation Satellite System to explore the ionospheric total electron content (TEC) response to this event. We show that the ionospheric response consists of a giant TEC increase followed by a strong long‐lasting depletion. We observe that the explosive event of 15 January 2022 began at 04:05:54UT and consisted of at least five explosions. Based on the ionospheric TEC data, we estimate the energy released during the main major explosion to be between 9 and 37 Megatons in trinitrotoluene equivalent. This is the first detailed analysis of the eruption sequence scenario and the timeline from ionospheric TEC observations.
Plain Language Summary
On 15 January 2022, the giant explosion of the Hunga Tonga‐Hunga Ha’apai volcano shook the atmosphere of the Earth and generated a tsunami. The exact mechanism and timing of the eruption are not well understood yet, nor is the series of events that occurred directly following the first event. Many scientists are trying to understand the chronology of the eruption using different types of data. Here we investigate the signature of the eruption as recorded in Earth’s ionosphere, the electrically conductive layer of the atmosphere from about 85 to 800 km of altitude. We observe variations in the total electron content (TEC) of the ionosphere using Global Navigation Satellite System receivers (commonly known as GPS receivers). Variations in the TEC through time and space are caused by sound waves from the eruption traveling through the ionosphere. We use these variations to constrain the timing of the eruptive events, identifying at least five major explosions during this eruption. In addition, we use the amplitude of TEC variations to estimate that the largest explosion released energy of about 9–37 Megaton in trinitrotoluene equivalent. This is the first detailed analysis of the eruption scenario and the timeline from ionospheric TEC observations.
Key Points
Ionospheric total electron content (TEC) data reveal that the 15 January 2022 Hunga Tonga volcanic eruption involved at least five large explosions between 4 and 5UT
From TEC observations, we estimate the onset time to be 04:05:54UT and the main explosion energy release of 9–37 Megatons trinitrotoluene equivalent
The eruption‐driven shock wave caused an unprecedentedly strong and long‐lasting depletion in the ionosphere
The first two Medium Earth Orbit (MEO) satellites of the third generation of BeiDou satellite navigation System (BDS-3) were successfully launched on November 5, 2017. This historical launch starts ...the new era of the global navigation satellite system of BeiDou. Before the first two satellites of BDS-3, a demonstration system for BDS-3 with five satellites, including two Inclined Geosynchronous Orbit satellites (IGSO) and three MEO satellites, was established between 2015 and 2016 for testing the new payloads, new designed signals and new techniques. In the demonstration system, the new S frequency signal and satellite hydrogen clock as well as inter-satellite link (ISL) based on Ka-band signals with time-division multiple addresses (TDMA) were tested. This paper mainly analyzes the performances of the demonstration system, including the signalto- noise ratios, pseudorange errors and the multipath errors of the civilian signals of BDS-3. The qualities of signals in space, time synchronization and timing precision were tested as well. Most of the performances were compared with those of the regional BeiDou satellite navigation system (BDS-2). At last, the performances of positioning, navigation and timing (PNT) of the future BeiDou global system (BDS-3) were evaluated based on the signal quality of the present demonstration satellite system.
This article discusses the design of the rubidium - 87 quantum frequency standard for satellite navigation systems. Also it is proposed a method for improving the parameters of the microwave ...excitation signal to improve the short-term and long-term stability of the frequency standard. The results of experimental research are presented.
Ultra-fast satellite clock bias (SCB) products play an important role in real-time precise point positioning. Considering the low accuracy of ultra-fast SCB, which is unable to meet the requirements ...of precise point position, in this paper, we propose a sparrow search algorithm to optimize the extreme learning machine (SSA-ELM) algorithm in order to improve the performance of SCB prediction in the Beidou satellite navigation system (BDS). By using the sparrow search algorithm's strong global search and fast convergence ability, we further improve the prediction accuracy of SCB of the extreme learning machine. This study uses ultra-fast SCB data from the international GNSS monitoring assessment system (iGMAS) to perform experiments. First, the second difference method is used to evaluate the accuracy and stability of the used data, demonstrating that the accuracy between observed data (ISUO) and predicted data (ISUP) of the ultra-fast clock (ISU) products is optimal. Moreover, the accuracy and stability of the new rubidium (Rb-II) clock and hydrogen (PHM) clock onboard BDS-3 are superior to those of BDS-2, and the choice of different reference clocks affects the accuracy of SCB. Then, SSA-ELM, quadratic polynomial (QP), and a grey model (GM) are used for SCB prediction, and the results are compared with ISUP data. The results show that when predicting 3 and 6 h based on 12 h of SCB data, the SSA-ELM model improves the prediction model by ~60.42%, 5.46%, and 57.59% and 72.27%, 44.65%, and 62.96% as compared with the ISUP, QP, and GM models, respectively. When predicting 6 h based on 12 h of SCB data, the SSA-ELM model improves the prediction model by ~53.16% and 52.09% and by 40.66% and 46.38% compared to the QP and GM models, respectively. Finally, multiday data are used for 6 h SCB prediction. The results show that the SSA-ELM model improves the prediction model by more than 25% compared to the ISUP, QP, and GM models. In addition, the prediction accuracy of the BDS-3 satellite is better than that of the BDS-2 satellite.
The integrated navigation system for strap-down inertial navigation system and ultrashort baseline (SINS/USBL) is one of the main approaches to realize the high-precision navigation and positioning ...of autonomous underwater vehicle (AUV). The relatively low frequency with seconds and the noise caused by the complex environment for USBL measurements have an obviously influence on the accuracy of positioning system. To solve the above problems, a correct method for USBL range measurement and a robust filter based on maximum correntropy criterion (MCC) are proposed in this article. First, the influence of motion effect on the range calculation results in the process of USBL transmission and reception is analyzed. Then, a simple correction method based on short-term high-precision characteristics of SINS is proposed. The short-term high-precision attitude, velocity, and position information of SINS in the process of USBL transmission and reception is used to correct the range error caused by motion effect. Finally, an adaptive filter based on MCC and dynamic model error adaptive factor is proposed to suppress the influence of outliers on positioning accuracy. The simulation and Yangzi River experiments are conducted to evaluate the feasibility of the proposed algorithm. The results shows that the proposed range correction method has a good correction effect on range error between sending and receiving epoch, and the proposed algorithm has better ability to suppress outliers.
The Technion autonomous underwater vehicle (TAUV) is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate ...acoustic communication. Its navigation system is based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL), magnetometer, and pressure sensor (PS). In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL) can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC) approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF) simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown.
Background
The use of portable navigation systems (PNS) in total hip arthroplasty (THA) has become increasingly prevalent, with second-generation PNS (sPNS) demonstrating superior accuracy in the ...lateral decubitus position compared to first-generation PNS. However, few studies have compared different types of sPNS. This study retrospectively compares the accuracy and clinical outcomes of two different types of sPNS instruments in patients undergoing THA.
Methods
A total of 158 eligible patients who underwent THA at a single institution between 2019 and 2022 were enrolled in the study, including 89 who used an accelerometer-based PNS with handheld infrared stereo cameras in the Naviswiss group (group N) and 69 who used an augmented reality (AR)-based PNS in the AR-Hip group (group A). Accuracy error, navigation error, clinical outcomes, and preparation time were compared between the two groups.
Results
Accuracy errors for Inclination were comparable between group N (3.5° ± 3.0°) and group A (3.5° ± 3.1°) (
p
= 0.92). Accuracy errors for anteversion were comparable between group N (4.1° ± 3.1°) and group A (4.5° ± 4.0°) (
p
= 0.57). The navigation errors for inclination (group N: 2.9° ± 2.7°, group A: 3.0° ± 3.2°) and anteversion (group N: 4.3° ± 3.5°, group A: 4.3° ± 4.1°) were comparable between the groups (
p
= 0.86 and 0.94, respectively). The preparation time was shorter in group A than in group N (
p
= 0.036). There were no significant differences in operative time (
p
= 0.255), intraoperative blood loss (
p
= 0.387), or complications (
p
= 0.248) between the two groups.
Conclusion
An Accelerometer-based PNS using handheld infrared stereo cameras and AR-based PNS provide similar accuracy during THA in the lateral decubitus position, with a mean error of 3°–4° for both inclination and anteversion, though the AR-based PNS required a shorter preparation time.
The Position and Orientation measurement System (POS) is a dedicated Strapdown Inertial Navigation System (SINS)/Global Positioning System (GPS) integrated system for airborne remote sensing. ...In-flight alignment (IFA) is an effective way to improve the accuracy and speed of initial alignment for an airborne POS. During IFA, the GPS provides the position and velocity references for the SINS, so the alignment accuracy will be degraded by unstable GPS measurements. To improve the alignment accuracy under unstable GPS measurement, an adaptive filtering algorithm of an extended Kalman filter (EKF) combined with innovation-based adaptive estimation is proposed, which introduces the calculated innovation covariance into the computation of the filter gain matrix directly. Then, this innovation adaptive EKF algorithm is used for the IFA of the POS with a large initial heading error. Moreover, it is optimized by blocked matrix multiplication to reduce the computational burden and improve the real-time performance. To validate the proposed algorithm, the car-mounted IFA experiment is carried out for the prototype of the airborne POS (TX-D10) under a turning maneuver, taking Applanix's POS/AV510 as a reference and changing the GPS measurement artificially. The experiment results demonstrate that the proposed algorithm can reach a better alignment accuracy than the EKF under unknown GPS measurement noises.
•Introducing factor graph into integrated navigation system.•Considering the key parameters, expanding the state parameters to improve positioning accuracy.•The INS / GPS / OD factor graph model is ...constructed by using factor graph technology.•Setting up a weight function to improve the navigation performance and robustness of algorithm.
To improve the navigation performance and robustness of integrated navigation algorithm based on factor graph under the condition that the performance of each sensor changes and the output is abnormal in the actual complex navigation environment, an improved factor graph method based on enhanced robustness is proposed. Taking the INS / GPS / OD integrated navigation system as the research object, on the basis of fully considering the key parameters of each sensor in the integrated navigation system, the INS / GPS / OD factor graph model is constructed by using factor graph technology, and designing a dynamic weight function to adjust the weight of each factor reasonably and dynamically, thereby improving the navigation performance and robustness of factor graph algorithm. Field test data are collected to evaluate the proposed method, the results showed that compared with the integrated navigation method based on extended Kalman filter and the existing integrated navigation method based on factor graph, the proposed method has better robustness and performance, navigation accuracy increased by more than 40%.
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