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

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3902 ◽  
Author(s):  
Wei Wang ◽  
Jinyao Gao ◽  
Dongming Li ◽  
Tao Zhang ◽  
Xiaowen Luo ◽  
...  

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.

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. G69-G80
Author(s):  
Zhiming Xiong ◽  
Juliang Cao ◽  
Kaixun Liao ◽  
Meiping Wu ◽  
Shaokun Cai ◽  
...  

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.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Xingxing Li ◽  
Xuanbin Wang ◽  
Jianchi Liao ◽  
Xin Li ◽  
Shengyu Li ◽  
...  

AbstractBecause of its high-precision, low-cost and easy-operation, Precise Point Positioning (PPP) becomes a potential and attractive positioning technique that can be applied to self-driving cars and drones. However, the reliability and availability of PPP will be significantly degraded in the extremely difficult conditions where Global Navigation Satellite System (GNSS) signals are blocked frequently. Inertial Navigation System (INS) has been integrated with GNSS to ameliorate such situations in the last decades. Recently, the Visual-Inertial Navigation Systems (VINS) with favorable complementary characteristics is demonstrated to realize a more stable and accurate local position estimation than the INS-only. Nevertheless, the system still must rely on the global positions to eliminate the accumulated errors. In this contribution, we present a semi-tight coupling framework of multi-GNSS PPP and Stereo VINS (S-VINS), which achieves the bidirectional location transfer and sharing in two separate navigation systems. In our approach, the local positions, produced by S-VINS are integrated with multi-GNSS PPP through a graph-optimization based method. Furthermore, the accurate forecast positions with S-VINS are fed back to assist PPP in GNSS-challenged environments. The statistical analysis of a GNSS outage simulation test shows that the S-VINS mode can effectively suppress the degradation of positioning accuracy compared with the INS-only mode. We also carried out a vehicle-borne experiment collecting multi-sensor data in a GNSS-challenged environment. For the complex driving environment, the PPP positioning capability is significantly improved with the aiding of S-VINS. The 3D positioning accuracy is improved by 49.0% for Global Positioning System (GPS), 40.3% for GPS + GLOANSS (Global Navigation Satellite System), 45.6% for GPS + BDS (BeiDou navigation satellite System), and 51.2% for GPS + GLONASS + BDS. On this basis, the solution with the semi-tight coupling scheme of multi-GNSS PPP/S-VINS achieves the improvements of 41.8–60.6% in 3D positioning accuracy compared with the multi-GNSS PPP/INS solutions.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Daehee Won ◽  
Jongsun Ahn ◽  
Sangkyung Sung ◽  
Moonbeom Heo ◽  
Sung-Hyuck Im ◽  
...  

A navigation algorithm is proposed to increase the inertial navigation performance of a ground vehicle using magnetic measurements and dynamic constraints. The navigation solutions are estimated based on inertial measurements such as acceleration and angular velocity measurements. To improve the inertial navigation performance, a three-axis magnetometer is used to provide the heading angle, and nonholonomic constraints (NHCs) are introduced to increase the correlation between the velocity and the attitude equation. The NHCs provide a velocity feedback to the attitude, which makes the navigation solution more robust. Additionally, an acceleration-based roll and pitch estimation is applied to decrease the drift when the acceleration is within certain boundaries. The magnetometer and NHCs are combined with an extended Kalman filter. An experimental test was conducted to verify the proposed method, and a comprehensive analysis of the performance in terms of the position, velocity, and attitude showed that the navigation performance could be improved by using the magnetometer and NHCs. Moreover, the proposed method could improve the estimation performance for the position, velocity, and attitude without any additional hardware except an inertial sensor and magnetometer. Therefore, this method would be effective for ground vehicles, indoor navigation, mobile robots, vehicle navigation in urban canyons, or navigation in any global navigation satellite system-denied environment.


2021 ◽  
Vol 11 (20) ◽  
pp. 9572
Author(s):  
Yongjian Zhang ◽  
Lin Wang ◽  
Guo Wei ◽  
Chunfeng Gao

Aircraft flying the trans-arctic routes usually apply inertial navigation mechanization in two different navigation frames, e.g., the local geographic frame and the grid frame. However, this change of navigation frame will cause filter overshoot and error discontinuity. To solve this problem, taking the inertial navigation system/global navigation satellite system (INS/GNSS) integrated navigation system as an example, an integrated navigation method based on covariance transformation is proposed. The relationship of the system error state between different navigation frames is deduced as a means to accurately convert the Kalman filter’s covariance matrix. The experiment and semi-physical simulation results show that the presented covariance transformation algorithm can effectively solve the filter overshoot and error discontinuity caused by the change of navigation frame. Compared with non-covariance transformation, the system state error is thereby reduced significantly.


2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jan M. Kelner ◽  
Cezary Ziółkowski

Currently, almost unrestricted access to low-lying areas of airspace creates an opportunity to use unmanned aerial vehicles (UAVs), especially those capable of vertical take-off and landing (VTOL), in transport services. UAVs become increasingly popular for transporting postal items over small, medium, and large distances. It is forecasted that, in the near future, VTOL UAVs with a high take-off weight will also deliver goods to very distant and hard-to-reach locations. Therefore, UAV navigation plays a very important role in the process of carrying out transport services. At present, during the flight phase, drones make use of the integrated global navigation satellite system (GNSS) and the inertial navigation system (INS). However, the inaccuracy of GNSS + INS makes it unsuitable for landing and take-off, necessitating the guidance of a human UAV operator during those phases. Available navigation systems do not provide sufficiently high positioning accuracy for an UAV. For this reason, full automation of the landing approach is not possible. This paper puts forward a proposal to solve this problem. The authors show the structure of an autonomous system and a Doppler-based navigation procedure that allows for automatic landing approaches. An accuracy evaluation of the developed solution for VTOL is made on the basis of simulation studies.


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