Short Baseline Research Articles

Observing glacier dynamics with low-cost, multi-GNSS positioning in Victoria Land, Antarctica

Abstract This study examines the performance of low-cost, low-power GNSS positioning systems for glacier monitoring in high-latitude environments. We compare the positioning performance of co-located low-cost u-blox ZED-F9P GNSS units (a few hundred USDs) and survey-grade Trimble R10 units (> $10,000 USD) under stationary (on land) and dynamic (on glacier) conditions near Terra Nova Bay, Antarctica. Low-cost and survey-grade systems yield almost identical error magnitudes under short (3 m), medium (34 km) and long (390 km) baseline kinematic-positioning scenarios. We further examined the efficacy of low-cost GNSS for glaciological applications by installing four u-blox and two Trimble receivers on Priestley Glacier to observe tide-modulated ice flexure. All receivers successfully detected subtle tidal oscillations with amplitudes < 3 cm, consistent with the predicted phasing from a tide model. These experiments offer a strong rationale for the widespread use of low-cost receivers to expand and densify GNSS monitoring networks, both in Antarctica and in glaciated regions worldwide.

Estimating the period of probable landslide event using advanced D-InSAR technique for time-series deformation study of Kotrupi region

Himalayan region is prone to landslides and every year many landslides occur. Some of these events are reported while, many of these landslides are not reported due to their remote location of occurrence, or nature of impact, and its date of occurrence is also unknown. This study tries to find a method to estimate the probable dates of landslide occurrences using time-series deformation analysis applying advanced DInSAR approach by adopting a short temporal baseline graph. We used 118 Sentinel 1-A SLC images to identify the nature, pattern, and trends of landslide deformation. Based on the time series cumulative deformation values, we found a ‘V’-shaped kink that matches with the landslide events. Such kinks were observed around 12 June 2015, 25 May 2016, 05 August 2016, 23 June 2017, 15 September 2019, 27 May 2018, 08 June 2018, and 15 July 2020. The majority of these kinks are visible during monsoon season which is expected. High-resolution Planet satellite data around these time ranges were used to verify the existence of new landslides. Moreover, the performance is evaluated using AUC-ROC, precision, recall; and F-Score. This approach has good prediction capabilities with the precision of 87%, AUC-ROC of 77% and F-score of 74%.

Machine learning-based multipath modeling in spatial domain applied to GNSS short baseline processing

Multipath is the main unmodeled error source hindering high-precision Global Navigation Satellite System data processing. Conventional multipath mitigation methods, such as sidereal filtering (SF) and multipath hemispherical map (MHM), have certain disadvantages: They are either not easy to use or not effective enough for multipath mitigation. In this study, we propose a machine learning (ML)-based multipath mitigation method. Multipath modeling was formulated as a regression task, and the multipath errors were fitted with respect to azimuth and elevation in the spatial domain. We collected 30 days of 1 Hz GPS data to validate the proposed method. In total, five short baselines were formed and multipath errors were extracted from the postfit residuals. ML-based multipath models, as well as observation-domain SF and MHM models, were constructed using 5 days of residuals before the target day and later applied for multipath correction. It was found that the XGBoost (XGB) method outperformed SF and MHM. It achieved the highest residual reduction rates, which were 24.9%, 36.2%, 25.5% and 20.4% for GPS P1, P2, L1 and L2 observations, respectively. After applying the XGB-based multipath corrections, kinematic positioning precisions of 1.6 mm, 1.9 mm and 4.5 mm could be achieved in east, north and up components, respectively, corresponding to 20.0%, 17.4% and 16.7% improvements compared to the original solutions. The effectiveness of the ML-based multipath model was further validated using 30 s sampling data and data from a low-cost device. We conclude that the ML-based multipath mitigation method is effective, easy to use, and can be easily extended by adding auxiliary input features, such as signal-to-noise ratio, during model training.

Design a Wilkinson power divider with improved passband and rejection band

ABSTRACT In this paper, a Wilkinson power divider based on a new harmonic suppressor structure is proposed with suppressed harmonics and improved operating band parameters. The proposed suppressor structure consists of three resonators. The first resonator is an elliptic rectangular shaped resonator with a short base line and two slots. These slots decrease the resonant frequency location, without changing the dimensions of the resonator. This mode has been fully analysed by investigating the effect of surface current density. The second resonator is an elliptic resonator with a long base length to suppress the second harmonic. The third resonator is a rectangular suppressor to suppress higher order harmonics. The proposed power divider is fabricated and measured. The operating frequency of this power divider is 1.26 GHz, the return loss is 31.5 dB and the insertion loss is 3.1 dB. The operating bandwidth is from 0.99 to 1.4 GHz with a return loss better than 15 dB which shows the fractional bandwidth of FBW = 34%. The second to sixth harmonics have suppression level better than 50 dB, and for higher harmonics up to the 14th harmonic, they have suppression level better than 25 dB.

A Multi-Scale Anti-Multipath Algorithm for GNSS-RTK Monitoring Application.

During short baseline measurements in the Real-Time Kinematic Global Navigation Satellite System (GNSS-RTK), multipath error has a significant impact on the quality of observed data. Aiming at the characteristics of multipath error in GNSS-RTK measurements, a novel method that combines improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and adaptive wavelet packet threshold denoising (AWPTD) is proposed to reduce the effects of multipath error in GNSS-RTK measurements through modal function decomposition, effective coefficient sieving, and adaptive thresholding denoising. It first utilizes the ICEEMDAN algorithm to decompose the observed data into a series of intrinsic mode functions (IMFs). Then, a novel IMF selection method is designed based on information entropy to accurately locate the IMFs containing multipath error information. Finally, an optimized adaptive denoising method is applied to the selected IMFs to preserve the original signal characteristics to the maximum possible extent and improve the accuracy of the multipath error correction model. This study shows that the ICEEMDAN-AWPTD algorithm provides a multipath error correction model with higher accuracy compared to singular filtering algorithms based on the results of simulation data and GNSS-RTK data. After the multipath correction, the accuracy of the E, N, and U coordinates increased by 49.2%, 65.1%, and 56.6%, respectively.

Text classification with improved word embedding and adaptive segmentation

Text classification first needs to convert the text into embedding vectors. Considering that static word embedding models such as Word2vec do not consider the position information of word and the difference of its role in different documents, while dynamic word embedding models such as Bert consume a large amount of time. An improved word embedding model based on pre-trained Word2vec is proposed, which achieves better classification accuracy and much lower classification time than Bert. At first, the concept of Term Document Frequency (TDF) is proposed on the basis of TF-IDF, and the TF-IDF-TDF of each word in different documents is calculated. Then, The positional encoding is added. Finally, in order to reduce the misleading of words with low importance, a filter is designed to set the embedding vector with low importance to zero. Considering that the sequence length that the deep learning model can handle is limited, and the text sequence exceeding the Maximum Sequence Length (MSL) set by the deep learning model will be directly truncated and discarded, an adaptive segmentation model is proposed, which can set different segmentation strategies for different texts according to the length of the text and the MSL. In order to maintain the continuity of adjacent text after segmentation, an adjacent-segment-vector-attended co-attention network is designed. In addition, the multi-channel convolution and the capsule network are designed to further extract deep hidden features. Multiple comparative experiment results show that the proposed model achieves the best Accuracy and Micro-F1 on five long text baseline datasets and six short text baseline datasets. In addition, when the MSL is not set too large compared with the document length in the dataset, the classification results of the proposed model are not affected by it.

Pioneering time-of-arrival localization with cable-free and battery-free transponders

In traditional underwater acoustic positioning methods, reliance on systems such as Long Baseline (LBL) and Short Baseline (SBL) localization utilize transponders that actively transmit acoustic pulses. These systems are typically powered by cables and often result in constrictive deployment. The adoption of cable-free and battery-free transponders can greatly enhance the flexibility of deployment. This change facilitates large-scale implementation, thereby providing precise positioning services across extensive areas. However, localization with passive transponders faces unique challenges. It has been widely accepted that battery-free nodes are unsuitable for time-of-arrival (ToA) localization. The primary reason is the wakeup delay varies based on location and environment, which introduces an unpredictable offset into the time lapse between the transmitted and received pulses. To overcome this challenge, we model the wakeup delay of passive node, considering the hardware characteristics of the passive node and the multipath acoustic channel. Moreover, we propose a ToA-based localization framework specifically tailored for battery-free transponders. In this paper, we will verify our wakeup delay model and assess the performance of the proposed localization method through experimental results. This new approach marks a significant departure from the existing effort, making localization with passive transponders feasible.

Interferometric Calibration Based on a Constrained Evolutionary Algorithm without Ground Control Points for a Tiangong-2 Interferometric Imaging Radar Altimeter

The interferometric imaging radar altimeter (InIRA), mounted on the Tiangong-2 space laboratory, utilizes a small incidence and a short interferometric baseline to achieve altimetry for wide swathes of ocean surface topography and inland water surface elevation. To obtain a high-precision digital elevation model (DEM), calibration of the interferometric system parameters is necessary. Because InIRA utilizes the small-incidence interference system design, serious coupling occurs between the interferometric parameters. Commonly used interferometric calibration methods tend to fall into the local optimal solution for InIRA. Because evolutionary algorithms have a stronger robustness and global search ability, they are better suited to handling the solution space structure under the coupling of complex interferometric parameters. This article establishes an interferometric calibration optimization model for InIRA by utilizing the relative flatness of the lake surface as an inequality constraint. Furthermore, an adaptive penalty coefficient constraint evolutionary algorithm is designed to solve the model. The proposed method was tested on actual InIRA data, and the results indicate that it efficiently adjusts interferometric parameters, enhancing the precision of measurements for Qinghai Lake elevation.

Preliminary Results of Marine Gravity Recovery by Tiangong-2 Interferometric Imaging Radar Altimeter

This paper presents for the first time the results of marine gravity recovery using the ocean observation data acquired by Tiangong-2 interferometric imaging radar altimeter (TG2 InIRA) which demonstrate not only the balanced accuracies of the north and east components of deflection of the vertical (DOV) as envisaged, but also the improved spatial resolutions of DOV compared with that by conventional altimeters (CAs). Moreover, much higher measurement efficiency owing to the wide-swath capability and the great potential in accuracy improvement of marine gravity field are also demonstrated. TG2 InIRA adopts the interferometry with short baseline and takes small incidence angles, by which wide-swath sea surface height (SSH) can be measured with high accuracy. Gravity recovery experiments in the Western Pacific area are conducted to demonstrate the performance, advantages and capability of TG2 InIRA. SSH data processing algorithms and DOV calculation have been designed by taking the wide-swath feature into account, based on which, the gravity anomalies are then calculated using the inverse Vening Meinesz formula. The derived gravity anomalies are compared with both the published gravity models and the shipborne gravity measurements. The results show that the accuracy of TG2 InIRA is equivalent to, or even a little better than, that of CAs. The fused gravity result using equal TG2 InIRA data and CAs data performs better than those using TG2 InIRA data alone or CAs data alone. Due to the signal bandwidth of TG2 InIRA is only 40 MHz which is much smaller than that of CAs, much higher accuracy can be hopefully achieved for future missions if larger signal bandwidth is used.

Detection and Monitoring of Potential Geological Disaster Using SBAS-InSAR Technology

As a global geological environment problem, geological disasters are more likely to induce severe geological disasters and cause loss of personnel and property due to their suddenness and concealment, frequent heavy rainfall and regular extreme weather. In this paper, Sentinel-1A data and DEM data combined with short baseline synthetic aperture interferar (SBAS-InSAR) technology are used to analyze and calculate the spatial-temporal evolution characteristics of surface deformation in Zibo-Weifang area of Shandong Province during 2016–2019. Linear fitting of InSAR monitoring deformation results is performed using level monitoring data to verify the accuracy of the results. The findings indicate that surface deformation in most of the study area is relatively stable, but in some areas, especially near Lucun Town, the maximum negative deformation rate exceeds 80mm/a. Based on the surface deformation results, a total of 377 potential geological disasters are identified using an integrated multi-source stereo observation system of the sky and ground. This identification is done by observing optical remote sensing images and taking the absolute value of surface deformation rate greater than 10 mm/a as the judgment basis, along with ground investigation and review. Several typical geological disaster sites are screened and they are found to be in unstable state. The research results can provide scientific support for geological disaster prevention and control in Shandong Province.

Studying the Ephemeris Effect on Position Accuracy Based on Criteria Applied to Baseline Lengths by New MATLAB Program (NMP)

Studying the Ephemeris Effect on Position Accuracy Based on Criteria Applied to Baseline Lengths by New MATLAB Program (NMP)

Characterizing the calibration systematics in radio interferometry due to partially modelled extended emission

ABSTRACT Calibration is the process by which we try to remove atmospheric and instrumental errors that corrupt the observations made by interferometers. Calibration is however an imperfect process and when we calibrate with an incomplete sky model systematics or artefacts manifest in our final images. One of the more striking artefacts that can appear in images are ghost sources. This paper explores these ghost artefacts in greater depth. We are particularly interested in the systematics or artefacts that are created if we partially model extended emission. A theoretical model that utilizes an east–west layout is developed (and empirically validated) that can give insight into the systematics so formed. The results from this study reveal that when we only partially model extended emission then the calibration systematics that form can manifest as extended emission in images. The aforementioned systematics alter the original extended source in various ways; the flux density of the extended source is modified and becomes comparable to the flux density of the source in the calibration sky model and its profile is slightly modified (it becomes more point like). More importantly, we found that the shorter baselines that are more sensitive to extended emission are in general more affected by the calibration systematics than the longer baselines are. In related works, it was found that the number of antennas greatly influence the brightness of the created systematics. For the use case, we investigate in the paper, however, we found this to not be the case.

A new inter-system double-difference RTK model applicable to both overlapping and non-overlapping signal frequencies

Aiming at the problem that the traditional inter-system double-difference model is not suitable for non-overlapping signal frequencies, we propose a new inter-system double-difference model with single difference ambiguity estimation, which can be applied for both overlapping and non-overlapping signal frequencies. The single difference ambiguities of all satellites and Differential Inter-System Biases (DISB) are first estimated, and the intra-system double difference ambiguities, which have integer characteristics, are then fixed. After the ambiguities are successfully fixed, high-precision coordinates and DISB can be obtained with a constructed transformation matrix. The model effectively avoids the DISB parameter filtering discontinuity caused by the reference satellite transformation and the low precision of the reference satellite single difference ambiguity calculated with the code. A zero-baseline using multiple types of receivers is selected to verify the stability of the estimated DISB. Three baselines with different lengths are selected to assess the positioning performance of the model. The ionospheric-fixed and ionospheric-float models are used for short and medium-long baselines, respectively. The results show that the Differential Inter-System Code Biases (DISCB) and Differential Inter-System Phase Biases (DISPB) have good stability regardless of the receivers type and the signal frequency used and can be calibrated to enhance the strength of the positioning model. The positioning results with three baselines of different lengths show that the proposed inter-system double-difference model can improve the positioning accuracy by 6–22% compared with the intra-system double-difference model which selects the reference satellite independently for each system. The Time to First Fix (TTFF) of the two medium-long baselines is reduced by 30% and 29%, respectively.

Multi-level autonomous integrity monitoring method for multi-source PNT resilient fusion navigation

For the integrity monitoring of a multi-source PNT (Positioning, Navigation, and Timing) resilient fusion navigation system, a theoretical framework of multi-level autonomous integrity monitoring is proposed. According to the mode of multi-source fusion navigation, the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level. For isolated non-redundant navigation sources, the system level recovery verification model is used. For the isolated multi-redundant navigation sources, the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors, and the isolated fault sensors are verified in real-time. Finally, according to the fault detection and verification results at each level, the observed information in the fusion navigation solution is dynamically adjusted. On this basis, the integrity risk dynamic monitoring tree is established to calculate the Protection Level (PL) and evaluate the integrity of the multi-source integrated navigation system. The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System (INS), Global Navigation Satellite System (GNSS), Long Baseline Location (LBL), and Ultra Short Baseline Location (USBL). The test results show that the proposed method can effectively isolate the fault source within 5 s, and can quickly detect multiple faulty sensors, ensuring that the positioning accuracy of the fusion navigation system is within 5 m, effectively improving the resilience and reliability of the multi-source fusion navigation system.

High-sensitivity Observations of the H2O Megamasers of NGC 1068: Precise Astrometry and Detailed Kinematics

We present High Sensitivity Array observations of the H2O megamasers of NGC 1068. We obtain absolute astrometry with 0.3 mas precision that confirms the association of the disk masers with the nuclear radio continuum source S1. The new observations reveal two new blueshifted groups of disk masers. We also detect the 22 GHz continuum on short interferometric baselines. The position–velocity diagram of the disk masers shows a curve consistent with a nonaxisymmetric distribution of maser spots. This curve is probably the result of spiral arms with a constant pitch angle ∼5°. The disk kinematics are consistent with Keplerian rotation and low turbulent speeds. The inferred central mass is 17 × 106 M ☉. On the basis of disk stability arguments, the mass of the molecular disk is ≈110 × 103 M ☉. The disk masers further resolve into filamentary structures suggesting an ordered magnetic field threading the maser disk. The magnetic field strengths must be ≳2 mG to withstand turbulent motions in the partially ionized molecular gas. We note apparent asymmetries in the molecular disk that might be explained by anisotropic heating by a misaligned inner accretion disk. The new observations also detect the fainter jet masers north of the disk masers. The distribution and kinematics of the jet masers are consistent with an expanding ring of molecular gas.

ML based approach for inverting penetration depth of SAR signals over large desert areas

Penetration depth of synthetic aperture radar (SAR) signals over a desert is a key parameter to understand the internal properties of the desert. Existing approaches for obtaining the penetration depth require good quality interferometric SAR (InSAR) data of very short temporal and long spatial baselines. Such data are often difficult to obtain in a highly dynamic desert. We propose a new machine learning (ML) based approach for inverting penetration depth of SAR signals over large desert areas by jointly using InSAR, polarimetric SAR (PolSAR) and optical remote sensing data. First, SAR scattering parameters and terrain properties are determined based on PolSAR and Landsat 5 TM multispectral data and a DEM. The penetration depth of SAR signals over a small desert area is obtained based on methods such as using a scattering model. A random forest model is then used to establish the relationship between the SAR scattering parameters and site features, and the penetration depth, and then is used to derive the penetration depth over a large desert area. The approach is applied to calculate the penetration depth of ALOS-1 PALSAR L-band signals for a large part of the Kufra Basin, an area of about 60, 000 km2. The penetration depths of four types of typical landforms in area (i.e., sandy plains, paleochannels, rocks and man-made features) are discussed in relation to the geological and climatic conditions. The average signal penetration depths over the paleochannels, sandy plains, and rocks and man-made features are 2.84 m, 1.97 m, 1.21 m, respectively. It is found that the backscattering coefficient, dielectric constant, surface roughness and mineral composition are the most important parameters in determining the signal penetration depths. An interesting point is that the existence of hematite in the sand can increase the dielectric dissipation of the sand medium and shorten the signal penetration depth.

A PPP-RTK APPROACH TO MASS-MARKET APPLICATIONS

Abstract. PPP-RTK has been widely investigated to take the advantages of both real-time kinematic (RTK) and precise point positioning (PPP) techniques. Prior to PPP-RTK, the conventional RTK based on the use of a single base station, on the one hand, has been extended to work within a regional network of multiple base stations, known as network RTK (NRTK). The RTK and NRTK enable fast ambiguity resolution over a short baseline or a local region. PPP, on the other hand, eliminates the need to establish any local network like NRTK, which is able to work in a single receiver mode but it suffers long convergence time in ambiguity resolution. PPP-RTK therefore can provide fast ambiguity resolution capability like RTK and NRTK. Current PPP-RTK techniques however still face challenges in supporting mass-market applications such as mobile devices and autonomous vehicles. Although PPP-RTK system (a combination of RTK and PPP technologies) can help expand the coverage of RTK and speed up the ambiguity resolution in PPP, the deployment and maintenance of a dense network of permanent base stations and a central data processing infrastructure for generation of SSR corrections increases not only the system cost but also the system complexity. This is particularly an obstacle for mass-market applications. In this paper, a new RTK approach is described. First it is based on a single base station state-space-representation (SSR) correction generation strategy to support fast ambiguity resolved PPP. Further it presents a new peer-to-peer propagation strategy to form a real-time dynamically generated network of base stations to support mass-market application users with unbounded coverage. As a result, the new approach eliminates the need to deploy and maintain a dense network of permanent base stations and central data processing infrastructure as required in a conventional PP-RTK system.

A compact underwater stereo vision system for measuring fish

In the context of aquaculture, fish length is a key parameter to assess fish stocks, essential for feeding regime and contributes for decisions at several production levels. However, taking length measurements is a cumbersome task that, when applied to living individuals, can induce considerable stress, increasing the risk of damage or hindering their growth. Computer vision is one of the most used non-contact tools to overcome this issue, being fast, consistent and repeatable. However, its use in aquatic environments is limited by the high cost, the difficulty of calibrating the system in underwater conditions and the complexity of implementation. This paper proposes a low-cost easy-to-use vision system that can take measurements on live fish in aquatic conditions, without the need for a special calibration or a demanding in-water calibration service. The present work implemented a compact stereo vision system and developed a method that estimates the correct length of fish, based on the variation of the angle of incidence of the light rays in the water. Given some structural conditions such as a short baseline, the system is able to measure fish with an error of less than 1%. The short baseline allows to have a compact system and reduces the effect of water refraction on the 3D reconstruction. A set of experiments were performed with real fish, working robustly for a set of orientations of the fish (even when the caudal fin and snout are on different distances to the cameras).

A New Device for Two-Way Time-Frequency Real-Time Synchronization

<p>The netted wireless sensor nodes or coherent accumulation processing in multistatic radar imaging requires high accuracy time synchronization. Although GNSS timing can also be used as a time synchronization method to serve the applications above, its timing accuracy will be limited. In this context, we present the hardware implementation for Two-Way Time-Frequency Real-Time Synchronization (TWTFRTS) with an automatic adaptive jitter elimination algorithm based on Kalman and PID, which is implemented in a real-time, low-cost, portable Xilinx ZYNQ device. A short (2 km) baseline TWTFRTS experiment was done with a pair of devices composed of a master device and a slave device. The result shows a high precision of time synchronization performance with the standard deviation (1 σ) better than 1 ns.</p> <p> </p>

Acoustic communication and imaging sonar guided AUV docking: system infrastructure, docking methodology and lake trials

Autonomous underwater vehicle (AUV) docking technique attracts attention which leverages the long-term, on-station vehicle launch and recovery for the underwater missions. In this paper, an acoustic communication and imaging sonar guided docking method is proposed to improve the docking accuracy for AUV. In docking system, multibeam forward looking sonar (MFLS) is deployed on the submerged docking station to reduce the noise in acoustic images rather than being fixed on AUV, and the ultra short base line (USBL) transceiver with acoustic communication modules is used to achieve positioning while AUV is out of the view of MFLS. For the docking methodology, a dedicated three-stage docking strategy is presented to guide AUV to the docking station. In the homing stage, AUV navigates to a preset homing place not very far from the docking station via the way-point guidance and self-positioning of the on-board inertial navigation system (INS). In the next stage, USBL provides the relative position for AUV controller via acoustic channel. Moreover, an exponential decay model based filtering algorithm is proposed to eliminate the positioning outliers of USBL. It is expected that AUV will be guided into the perceptual field of MFLS in this stage. In the final stage, the docking accuracy in short range should be improved while USBL may generate outliers due to the louder noise. In this case, the relative positioning is implemented by using kernelized correlation filter (KCF), which is a fast objective tracking algorithm to keep track of the AUV feature in acoustic image until AUV navigates into the docking station or out of the view of sensor. To validate feasibility and performance of the proposed system infrastructure and docking methodology, the docking results are analyzed by contrast with the experiments only use USBL during lake trials.