A new method for underwater dynamic gravimetry based on multisensor integrated navigation

Underwater gravity information plays a major role in deepwater oil and gas exploration. To realize underwater dynamic gravimetry, we have developed a strapdown gravimeter mounted in a pressure capsule for adaption to the underwater environment and we adopted a two-stage towed underwater gravimetry scheme. An improved strapdown gravimeter and other underwater sensors were installed in a towed vessel to form an underwater dynamic gravimetry system. Because the global navigation satellite system cannot be used for underwater dynamic gravimetry, we developed a new method based on underwater multisensor integrated navigation, in which a federal Kalman filter was applied for error estimation. This new method allowed us to obtain the accurate attitude, velocity, and position necessary for gravity estimation. In addition, the gravity data can then be extracted from the noisy data through finite impulse response low-pass filtering. We acquired the underwater gravity data at a depth of 300 m to test the validity of the new method and evaluate the accuracy of the underwater gravity system. The results indicated a repeatability from 0.85 to 0.96 mGal at a half wavelength of approximately 0.2 km and also indicated good consistency with the marine gravity data.

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Sea Ice Remote Sensing Using GNSS-R: A Review

Remote Sensing ◽

10.3390/rs11212565 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2565 ◽

Cited By ~ 4

Author(s):

Qingyun Yan ◽

Weimin Huang

Keyword(s):

Remote Sensing ◽

Sea Ice ◽

Oil And Gas ◽

Satellite System ◽

Sea Ice Concentration ◽

Sea Ice Thickness ◽

Oil And Gas Exploration ◽

Offshore Oil And Gas ◽

Ice Detection ◽

Global Navigation Satellite

Knowledge of sea ice is critical for offshore oil and gas exploration, global shipping industries, and climate change studies. During recent decades, Global Navigation Satellite System-Reflectometry (GNSS-R) has evolved as an efficient tool for sea ice remote sensing. In particular, thanks to the availability of the TechDemoSat-1 (TDS-1) data over high-latitude regions, remote sensing of sea ice based on spaceborne GNSS-R has been rapidly growing. The goal of this paper is to provide a review of the state-of-the-art methods for sea ice remote sensing offered by the GNSS-R technique. In this review, the fundamentals of these applications are described, and their performances are evaluated. Specifically, recent progress in sea ice sensing using TDS-1 data is highlighted including sea ice detection, sea ice concentration estimation, sea ice type classification, sea ice thickness retrieval, and sea ice altimetry. In addition, studies of sea ice sensing using airborne and ground-based data are also noted. Lastly, applications based on various platforms along with remaining challenges are summarized and possible future trends are explored. In this review, concepts, research methods, and experimental techniques of GNSS-R-based sea ice sensing are delivered, and this can benefit the scientific community by providing insights into this topic to further advance this field or transfer the relevant knowledge and practice to other studies.

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Measurements and Accuracy Evaluation of a Strapdown Marine Gravimeter Based on Inertial Navigation

Sensors ◽

10.3390/s18113902 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3902 ◽

Cited By ~ 3

Author(s):

Wei Wang ◽

Jinyao Gao ◽

Dongming Li ◽

Tao Zhang ◽

Xiaowen Luo ◽

...

Keyword(s):

Coupling Effect ◽

Inertial Navigation ◽

Satellite System ◽

Gravity Survey ◽

Accuracy Evaluation ◽

Earth’S Gravity Field ◽

Marine Gravity ◽

Global Navigation Satellite ◽

Measuring Unit ◽

Rough Sea

The strapdown gravimetry system uses the combination of an Inertial Measuring Unit (IMU) and a Global Navigation Satellite System (GNSS) to measure the Earth’s gravity field. Due to limited accuracies of IMU and GNSS, early strapdown gravimetry systems were more often used in airborne surveys, but less used in marine surveys. We developed a strapdown inertial navigation system (SINS), the Sea-Air Gravimeter-2Marine (SAG-2M), using novel IMU components, whose accuracy was further improved with the application of Precise Point Positioning (PPP) and enhanced algorithm, making it possible to be used in marine gravity survey. The testing results of the SAG-2M were compared to those of the Lacoste and Romberg S-129 gravimeter on the same ship in the South China Sea basin. The cruise lasted for 50 days, during which 134 effective gravity profiles were measured, resulting in 174 crossover points. The results showed that, for the SAG-2M, the root mean square (RMS) crossover points were 1.35 mGal before difference adjustment and 0.69 mGal after difference adjustment; for the S-129 gravimeter, they were 5.62 mGal and 0.95 mGal, correspondingly. In calm sea conditions, the results of the two systems were relatively consistent at all wavelengths. However, in rough sea conditions, since the SAG-2M was not affected by the cross-coupling effect, its data demonstrated less high-frequency jump. A physical platform adopted in SAG-2M can further make the transition data effective when the ship is turning around. Therefore, SAG-2M was able to improve the proportion of valid data and the efficiency of data post-processing for measurements taken during the cruise. The testing results indicate that in terms of accuracy and efficiency in the marine gravity survey, SAG-2M is better than S-129. In addition, as the miniaturization and precision of inertial components are developing continuously, SAG-2M also shows great potential in miniaturization.

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A New Method to Improve the Detection of Co-Seismic Ionospheric Disturbances using Sequential Measurement Combination

Sensors ◽

10.3390/s19132948 ◽

2019 ◽

Vol 19 (13) ◽

pp. 2948 ◽

Cited By ~ 1

Author(s):

Seonho Kang ◽

Junesol Song ◽

Deokhwa Han ◽

Bugyeom Kim ◽

Hyoungmin So ◽

...

Keyword(s):

Time Derivative ◽

Tohoku Earthquake ◽

Satellite System ◽

Detection Performance ◽

Ionospheric Delay ◽

New Method ◽

Ionospheric Disturbances ◽

The 2011 Tohoku Earthquake ◽

Sequential Measurement ◽

Global Navigation Satellite

Earthquakes generate energy that propagates into the ionosphere and incurs co-seismic ionospheric disturbances (CIDs), which can be observed in ionospheric delay measurements. In most cases, the CID has a weak signal strength, because the energy in the atmosphere transferred from the earthquake dissipates as it travels toward the ionosphere. It is particularly hard to observe at reference stations that are located far from the epicenter. As the number of Global Navigation Satellite System stations and their positions are restricted, it is important to employ weak CID data in the analysis by improving the detection performance of CIDs. In this study, we suggest a new method of detecting CIDs, which mainly uses a sequential measurement combination of the carrier phase-based ionospheric delay data, with a 1-second interval. The proposed method’s performance was compared with conventional methods, including band-pass filters and a representative time-derivative method, using data from the 2011 Tohoku earthquake. As a result, the maximum CID-to-noise ratio can be increased by a maximum of 13% when the proposed method is used, and consequently, the detection performance of the CID can be improved.

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Constrained Unscented Particle Filter for SINS/GNSS/ADS Integrated Airship Navigation in the Presence of Wind Field Disturbance

Sensors ◽

10.3390/s19030471 ◽

2019 ◽

Vol 19 (3) ◽

pp. 471 ◽

Cited By ~ 1

Author(s):

Zhaohui Gao ◽

Dejun Mu ◽

Yongmin Zhong ◽

Chengfan Gu

Keyword(s):

Wind Speed ◽

Particle Filter ◽

State Estimation ◽

Wind Field ◽

Satellite System ◽

Integrated Navigation ◽

Unscented Particle Filter ◽

Field Disturbance ◽

Global Navigation Satellite ◽

Optimal State Estimation

Due to the disturbance of wind field, it is difficult to achieve precise airship positioning and navigation in the stratosphere. This paper presents a new constrained unscented particle filter (UPF) for SINS/GNSS/ADS (inertial navigation system/global navigation satellite system/atmosphere data system) integrated airship navigation. This approach constructs a wind speed model to describe the relationship between airship velocity and wind speed using the information output from ADS, and further establishes a mathematical model for SINS/GNSS/ADS integrated navigation. Based on these models, it also develops a constrained UPF to obtain system state estimation for SINS/GNSS/ADS integration. The proposed constrained UPF uses the wind speed model to constrain the UPF filtering process to effectively resist the influence of wind field on the navigation solution. Simulations and comparison analysis demonstrate that the proposed approach can achieve optimal state estimation for SINS/GNSS/ADS integrated airship navigation in the presence of wind field disturbance.

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A Novel GNSS Attitude Determination Method Based on Primary Baseline Switching for A Multi-Antenna Platform

Remote Sensing ◽

10.3390/rs12050747 ◽

2020 ◽

Vol 12 (5) ◽

pp. 747

Author(s):

Peng Zhang ◽

Yinzhi Zhao ◽

Huan Lin ◽

Jingui Zou ◽

Xinzhe Wang ◽

...

Keyword(s):

Attitude Determination ◽

Low Cost ◽

Satellite System ◽

Poor Quality ◽

Integrated Navigation ◽

Determination Method ◽

Integrated Navigation System ◽

Determination System ◽

Vehicle Test ◽

Global Navigation Satellite

The global navigation satellite system (GNSS)-based attitude determination system has attracted more and more attention with the advantages of having simplified algorithms, a low price and errors that do not accumulate over time. However, GNSS signals may have poor quality or lose lock in some epochs with the influence of signal fading and the multipath effect. When the direct attitude determination method is applied, the primary baseline may not be available (ambiguity is not fixed), leading to the inability of attitude determination. With the gradual popularization of low-cost receivers, making full use of spatial redundancy information of multiple antennas brings new ideas to the GNSS-based attitude determination method. In this paper, an attitude angle conversion algorithm, selecting an arbitrary baseline as the primary baseline, is derived. A multi-antenna attitude determination method based on primary baseline switching is proposed, which is performed on a self-designed embedded software and hardware platform. The proposed method can increase the valid epoch proportion and attitude information. In the land vehicle test, reference results output from a high-accuracy integrated navigation system were used to evaluate the accuracy and reliability. The results indicate that the proposed method is correct and feasible. The valid epoch proportion is increased by 16.2%, which can effectively improve the availability of attitude determination. The RMS of the heading, pitch and roll angles are 0.52°, 1.25° and 1.16°.

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VISUAL ANALYSIS OF RECURRENCE OF TIME SERIES OF THE COORDINATES ENU IN THE GPS STATIONS

Boletim de Ciências Geodésicas ◽

10.1590/s1982-21702018000400029 ◽

2018 ◽

Vol 24 (4) ◽

pp. 470-484

Author(s):

Alfonso Tierra ◽

Rubén León ◽

Alexis Tinoco-S ◽

Carolina Cañizares ◽

Marco Amores ◽

...

Keyword(s):

Time Series ◽

Continuous Monitoring ◽

Visual Analysis ◽

Finite Impulse Response ◽

Satellite System ◽

Nearest Neighbours ◽

Low Pass ◽

Global Navigation Satellite ◽

Low Pass Filters ◽

Content Information

Abstract The time series content information about the dynamic behavior of the system under study. This behavior could be complex, irregular and no lineal. For this reason, it is necessary to study new models that can solve this dynamic more satisfactorily. In this work a visual analysis of recurrence from time series of the coordinate’s variation ENU (East, North, Up) will be made. This analysis was obtained from nine continuous monitoring stations GPS (Global Navigation Satellite System); the intention is to study their behavior, they belong to the Equatorian GPS Network that materializes the reference system SIRGAS - ECUADOR. The presence of noise in the observations was reduced using digital low pass filters with Finite Impulse Response (FIR). For these series, the time delay was determined using the average mutual information, and for the minimum embedding dimension the False Nearest Neighbours (FNN) method was used; the purpose is to obtain the recurrent maps of each coordinates. The results of visual analysis show a strong tendency, especially in the East and North coordinates, while the Up coordinates indicate discontinued, symmetric and periodic behavior.

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Initial exploration of Hydrocarbon resources by Gravity Data: A Case Study in the South of Qom Province, Iran

JOURNAL OF ADVANCES IN NATURAL SCIENCES ◽

10.24297/jns.v2i1.5034 ◽

2015 ◽

Vol 2 (1) ◽

pp. 52-57

Author(s):

Payam Salimi

Keyword(s):

Oil And Gas ◽

Gravity Data ◽

Geophysical Methods ◽

Local Effect ◽

Oil And Gas Exploration ◽

Residual Gravity ◽

3D Geometry ◽

Residual Gravity Anomaly ◽

Matlab Programming

Geophysical methods widely used in oil and gas exploration. Modeling of gravity data is used extensively to illustrate the geometry and interface between the sediments and bedrock. Which can help the salt dome, anticline folds, dome-shaped uplift of the continental platform and reef masses to be identified. There are various methods to illustrate the bedrock topography, and we will describe one of these methods in present paper. Using the upward continuation, we extract the residual gravity anomaly which in fact shows the local effect of bedrock gravity on the observed gravity. Then, according to the Oldenburg - Parker method, the residual gravity data are inversed and finally the 3D geometry the bedrock is illustrated. It should be noted that some software's like Surfer and Excel are used in this research but the program main code is written using Matlab programming.

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Subsalt imaging in northern Germany using multiphysics (magnetotellurics, gravity, and seismic)

Interpretation ◽

10.1190/int-2020-0026.1 ◽

2020 ◽

Vol 8 (4) ◽

pp. SQ15-SQ24

Author(s):

Christian H. Henke ◽

Markus H. Krieger ◽

Kurt Strack ◽

Andrea Zerilli

Keyword(s):

Oil And Gas ◽

Gravity Data ◽

Salt Dome ◽

Gravity Modeling ◽

Field Source ◽

Oil And Gas Exploration ◽

Exploration Drilling ◽

Seismic Depth Migration ◽

Improved Model ◽

Subsalt Imaging

Imaging subsalt is still a challenging task in oil and gas exploration. We have used magnetotellurics (MT) to improve the integration of seismic and gravity data to image the Wedehof salt dome, located in the Northern German Basin. High-density natural field source broadband MT data were acquired and enhanced the definition of the top and overhanging salt structures in addition to imaging the salt dome root. Salt boundaries show strong resistivity contrasts with the surrounding sediments and thus represent a good target for electromagnetic measurements, especially for top salt and salt flanks imaging. With integrated 3D gravity modeling focusing on the salt dome’s flanks at intermediate depths, an improved model was achieved. The new model provided sound input to a follow-up seismic depth migration that led to an improved imaging of the subsalt target proven by subsequent exploration drilling. The integrated interpretation of MT, gravity, and seismic combines the strengths of the different physics, thus increasing imaging reliability and reducing exploration drilling risks. Using a conservative workflow that included a feasibility study with field noise evaluation and careful acquisition parameter testing prior to survey start, a broadband array data acquisition, and advanced processing, the survey area's severe cultural noise issues could be overcome.

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Sparse GLONASS Signal Acquisition Based on Compressive Sensing and Multiple Measurement Vectors

Mathematical Problems in Engineering ◽

10.1155/2020/9654120 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Guodong He ◽

Maozhong Song ◽

Shanshan Zhang ◽

Peng Song ◽

Xinwen Shu

Keyword(s):

Compressive Sensing ◽

Satellite System ◽

New Method ◽

Signal Acquisition ◽

Multiple Measurement ◽

Multiple Measurement Vectors ◽

Navigation Data ◽

Long Time ◽

Global Navigation Satellite ◽

Sparse Features

A sparse global navigation satellite system (GLONASS) signal acquisition method based on compressive sensing and multiple measurement vectors is proposed. The nonsparse GLONASS signal can be represented sparsely on our proposed dictionary which is designed based on the signal feature. Then, the GLONASS signal is sensed by a normalized orthogonal random matrix and acquired by the improved multiple measurement vectors acquisition algorithm. There are 10 cycles of pseudorandom codes in a navigation message, and these 10 pseudorandom codes have the same row sparse structure. So, the acquisition probability can be raised by row sparse features theoretically. A large number of simulated GLONASS signal experiments show that the acquisition probability increases with the increase in the measurement vector column dimension. Finally, the practical availability of the new method is verified by acquisition experiments with the real record GLONASS signal. The new method can reduce the storage space and energy loss of data transmission. We hope that the new method can be applied to field receivers that need to record and transmit navigation data for a long time.

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A Hybrid Intelligent Algorithm DGP-MLP for GNSS/INS Integration during GNSS Outages

Journal of Navigation ◽

10.1017/s0373463318000760 ◽

2018 ◽

Vol 72 (2) ◽

pp. 375-388 ◽

Cited By ~ 8

Author(s):

Yuexin Zhang ◽

Lihui Wang

Keyword(s):

Satellite System ◽

Micro Electro Mechanical System ◽

Real Field ◽

Prediction Errors ◽

Integrated Navigation ◽

Intelligent Algorithm ◽

Position Information ◽

Hybrid Intelligent Algorithm ◽

Global Navigation Satellite ◽

Adaptively Adjusting

The performance of Global Navigation Satellite System (GNSS) and Micro-Electro-Mechanical System (MEMS)-based Inertial Navigation System (INS) integrated navigation is reduced during GNSS outages. To bridge the period during GNSS outages, a novel hybrid intelligent algorithm incorporating a Discrete Grey Predictor (DGP) and a Multilayer Perceptron (MLP) neural network (DGP-MLP) is proposed. The DGP-MLP is used to provide a pseudo-GNSS position to correct the INS errors during GNSS outages; the DGP uses the GNSS position information of the latest few moments to predict the position of future moments; in the process of DGP-MLP, the MLP is used to modify the prediction errors of DGP, and the MLP is improved by adding momentum terms and adaptively adjusting the learning rate and momentum factor. To evaluate the effectiveness of the proposed methodology, four GNSS outages in different cases over a real field test data were employed. The experimental results demonstrate that the proposed methodology can significantly improve positioning accuracy during GNSS outages.

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