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The density inversion of gravity gradiometry data has attracted considerable attention; however, in large datasets, the multiplicity and low depth resolution as well as efficiency are constrained by time and computer memory requirements. To solve these problems, we improve the reweighting focusing inversion and probability tomography inversion with joint multiple tensors and prior information constraints, and assess the inversion results, computing efficiency, and dataset size. A Message Passing Interface (MPI)-Open Multi-Processing (OpenMP)-Computed Unified Device Architecture (CUDA) multilevel hybrid parallel inversion, named Hybrinv for short, is proposed. Using model and real data from the Vinton Dome, we confirm that Hybrinv can be used to compute the density distribution. For data size of 100×100×20, the hybrid parallel algorithm is fast and based on the run time and scalability we infer that it can be used to process the large-scale data.

This research proposes a novel three-dimensional gravity inversion based on sparse recovery in compress sensing. Zero norm is selected as the objective function, which is then iteratively solved by the approximate zero norm solution. The inversion approach mainly employs forward modeling; a depth weight function is introduced into the objective function of the zero norms. Sparse inversion results are obtained by the corresponding optimal mathematical method. To achieve the practical geophysical and geological significance of the results, penalty function is applied to constrain the density values. Results obtained by proposed provide clear boundary depth and density contrast distribution information. The method’s accuracy, validity, and reliability are verified by comparing its results with those of synthetic models. To further explain its reliability, a practical gravity data is obtained for a region in Texas, USA is applied. Inversion results for this region are compared with those of previous studies, including a research of logging data in the same area. The depth of salt dome obtained by the inversion method is 4.2 km, which is in good agreement with the 4.4 km value from the logging data. From this, the practicality of the inversion method is also validated.

Based-on the previous study on the theory of the sequential pyramid wavefront sensor (SPWFS), in this paper, the SPWFS is first applied to the coherent free space optical communications (FSOC) with more flexible spatial resolution and higher sensitivity than the Shack-Hartmann wavefront sensor, and with higher uniformity of intensity distribution and much simpler than the pyramid wavefront sensor. Then, the mixing efficiency (ME) and the bit error rate (BER) of the coherent FSOC are analyzed during the aberrations correction through numerical simulation with binary phase shift keying (BPSK) modulation. Finally, an experimental AO system based-on SPWFS is setup, and the experimental data is used to analyze the ME and BER of homodyne detection with BPSK modulation. The results show that the AO system based-on SPWFS can increase ME and decrease BER effectively. The conclusions of this paper provide a new method of wavefront sensing for designing the AO system for a coherent FSOC system.

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.

The subsurface three-dimensional (3D) model of density distribution is obtained by solving an under-determined linear equation that is established by gravity data. Here, we describe a new fast gravity inversion method to recover a 3D density model from gravity data. The subsurface will be divided into a large number of rectangular blocks, each with an unknown constant density. The gravity inversion method introduces a stabiliser model norm with a depth weighting function to produce smooth models. The depth weighting function is combined with the model norm to counteract the skin effect of the gravity potential field. As the numbers of density model parameters is NZ (the number of layers in the vertical subsurface domain) times greater than the observed gravity data parameters, the inverse density parameter is larger than the observed gravity data parameters. Solving the full set of gravity inversion equations is very time-consuming, and applying a new algorithm to estimate gravity inversion can significan...

The mechanical configuration of an independent pitch control system (IPCS) for coaxial dual-rotor compound helicopter (CDCH) was presented, which is mainly constituted by parallel mechanism, spatial orientation, lower rotor and upper rotor. The solving path and model division for the IPCS based on the working principle can be explained to achieve azimuth attitude precise control of upper and lower propeller for the CDCH. The completely mathematical model of attitude control system for the CDCH was obtained by using lumped parameters method and sub-total solution model which the forward and reverse positional attitude solution were deducted by the coordinate space transformation and kinematic analysis method. The co-simulation analysis which based on the MATLAB and Recurdyn software was done and the numerical comparative results show that the theoretical analysis of the mathematical model for attitude control system was reasonable and applicable by means of comparison with semi-physical model in the various boundary conditions and parameters of parallel mechanism, spatial orientation, lower rotor and upper rotor, respectively.

Borehole gravity is increasingly used in mineral exploration due to the advent of slim-hole gravimeters. Given the full-tensor gradiometry data available nowadays, joint inversion of surface and borehole data is a logical next step. Here, we base our inversions on cokriging, which is a geostatistical method of estimation where the error variance is minimised by applying cross-correlation between several variables. In this study, the density estimates are derived using gravity-gradient data, borehole gravity and known densities along the borehole as a secondary variable and the density as the primary variable. Cokriging is non-iterative and therefore is computationally efficient. In addition, cokriging inversion provides estimates of the error variance for each model, which allows direct assessment of the inverse model. Examples are shown involving data from a single borehole, from multiple boreholes, and combinations of borehole gravity and gravity-gradient data. The results clearly show that the depth resolution of gravity-gradient inversion can be improved significantly by including borehole data in addition to gravity-gradient data. However, the resolution of borehole data falls off rapidly as the distance between the borehole and the feature of interest increases. In the case where the borehole is far away from the target of interest, the inverted result can be improved by incorporating gravity-gradient data, especially all five independent components for inversion.

Degradation of bit-error-rate (BER), caused by atmospheric turbulence, seriously hinders the performance of coherent Free Space Optical (FSO) communication systems. An adaptive optics system proves to be effective in suppressing the atmospheric turbulence. The holographic modal wavefront sensor (HMWFS) proposed in our previous work, noted for its fast detecting rates and insensitivity to beam scintillation, is applied to the coherent FSO communication systems. In this paper, based on our previous work, we first introduce the principle of the HMWFS in brief and give the BER of the coherent FSO with homodyne detection in theory, and then analyze the improvement of BER for a coherent FSO system based on our previous simulation works. The results show that the wavefront sensor we propose is better for weak atmospheric turbulence. The most obvious advantages of HMWFS are fast detecting rates and insensitivity to beam scintillation.

For a coherent lidar, the efficiency of homodyne detection is a significant factor. Adaptive optics (AO) is an effective way to correct the turbulence-induced wavefront distortions. Based on our previous works, an expression for the homodyne detection efficiency is given. The results of the numerical simulation show that the atmospheric coherent length has an influence on the homodyne detection efficiency for a fixed atmospheric Greenwood frequency and a closed-loop control bandwidth. In addition, an experimental AO system is employed to verify the effect of the AO on the coherent lidar. The results show that the homodyne detection efficiency is obviously improved after aberrations are corrected. The conclusion of this paper provides a reference for designing an AO system for a coherent lidar.

Full tensor gradient (FTG) data is highly useful in hydrocarbon exploration and the detection of some geological targets with small size as its higher detailed information abundance and finer resolution. At the same time, there are some high-frequency Gaussian white noise mixed in the target signal and which has closer frequency range than the conventional gravity data. Thus, one key step before inversion is to remove as much Gaussian white noise as possible and reserve the subtle details. For this pre-processing step, several effective methods have been used, including low-pass filters, least square fitting methods based on Laplace equation and wavelet filtering methods. In this paper, we would utilize the translation invariant wavelet for the reason that it can suppress Gaussian white noise through multi-resolution analysis and at the same time can avoid pseudo-Gibbs phenomenon. The other point different from wavelet method used before is that we applied a mixed threshold constructed according to the curve of both soft threshold and hard threshold. Compared to soft and hard threshold, mixed threshold can keep more details and remove more noise respectively in terms of the energy distribution of signal and noise. Then we process wavelet coefficients with mixed threshold and do inverse transform to recover the data. The results demonstrate that translation invariant wavelet can not only remove the major part of Gaussian white noise, but also reserves high-frequency detailed information of FTG data. Obviously, translation invariant wavelet with mixed thresholding has preferable application effect in filtering FTG data.

This paper proposes a new semi-automatic inversion method for magnetic anomaly data interpretation that uses the combination of analytic signals of the anomaly at different heights to determine the depth and the structural index N of the sources. The new method utilizes analytic signals of the original anomaly at different height to effectively suppress the noise contained in the anomaly. Compared with the other high-order derivative calculation methods based on analytic signals, our method only computes first-order derivatives of the anomaly, which can be used to obtain more stable and accurate results. Tests on synthetic noise-free and noise-corrupted magnetic data indicate that the new method can estimate the depth and N efficiently. The technique is applied to a real measured magnetic anomaly in Southern Illinois caused by a known dike, and the result is in agreement with the drilling information and inversion results within acceptable calculation error.

Gravity data, which are critical in mineral, oil, and gas exploration, are obtained from the vertical component of the gravity field, while gravity gradient data are measured from changes in the gravity field in three directions. However, few studies have sought to improve exploration techniques by integrating gravity and gravity gradient data using inversion methods. In this study, we developed a new method to integrate gravity and gravity gradient data in a 3D density inversion using the non-linear conjugate gradient (NLCG) method and the minimum gradient support (MGS) functional to regularize the 3D inverse problem and to obtain a clear and accurate image of the anomalous body. The NLCG algorithm, which is suitable for solving large-scale nonlinear optimization problems and requires no memory storage, was compared to the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton algorithm and the results indicated that the convergence rate of NLCG is slower, but that the storage requirement and computation time is lower. To counteract the decay in kernel function, we introduced a depth weighting function for anomalous bodies at the same depth, with information about anomalous body depth obtained from well log and seismic exploration data. For anomalous bodies at different depths, we introduced a spatial gradient weighting function to incorporate additional information obtained in the inversion. We concluded that the spatial gradient weighting function enhanced the spatial resolution of the recovered model. Furthermore, our results showed that including multiple components for inversion increased the resolution of the recovered model. We validated our model by applying our inversion method to survey data from Vinton salt dome, Louisiana, USA. The results showed good agreement with known geologic information; thus confirming the accuracy of this approach.

Geophysical exploration generates a very large amount of data, which require special techniques to process meaningfully. This paper presents a modification of the inversion method of probability tomography and a practical application of the method for the joint inversion with multiple gravity gradiometry tensors. The depth-weighting matrix is introduced to increase the vertical resolution. The problems associated with choosing tensors are discussed. We combine the high-performance computing techniques, Message Passing Interface with Compute Unified Device Architecture, for hybrid programming to build a faster parallel program. In the synthetic model tests, it is found that the joint inversion with multiple tensors is superior to the classical algorithm with a single tensor for delineating the boundary of the adjacent geological bodies. The hybrid parallel program has a speedup of far more than 100, which is higher than the program using one parallel technique alone; thus, the program could be used for large-scale data. The parallel algorithm is applied to real geophysical exploration data from Vinton Dome and we obtained a good density result. Our algorithm is demonstrated to be reliable and feasible.

Magnetic exploration plays a significant role in regional geological investigation and detection of underground geological bodies with magnetic anomaly. At the moment, aeromagnetic survey is widely applied for its high efficiency, low cost and less subject to terrain restrict. Magnetic compensation is a key step in pre-processing survey data and several methods have been used. In this paper, we would use partial least square method to complete aeromagnetic compensation. Partial least square regression is frequently used to find the fundamental relations between two matrices. It combines linear regression analysis, canonical correlation analysis and principal components analysis. It can be applied into data with multicollinearity among independent variables and the number of variables is larger than that of observations. Before compensation, we should have several pre-processing steps such as parallax correction, diurnal variations correction, geomagnetic field correction and high-frequency noise removal. This will provide us magnetic data with higher quality and make compensation process more accurate. We set synthetic aeromagnetic data with interference of aircraft’s maneuvers and used partial least square method to do compensation. From the results of simulation, we can see that the interference signal is reduced to a low degree and satisfied compensation effect is obtained. Partial least square regression is a stable and effective method in the application of aeromagnetic compensation.

We modify the classical preconditioned conjugate gradient method for full tensor gravity gradiometry data. The resulting parallelized algorithm is implemented on a cluster to achieve rapid density inversions for various scenarios, overcoming the problems of computation time and memory requirements caused by too many iterations. The proposed approach is mainly based on parallel programming using the Message Passing Interface, supplemented by Open Multi-Processing. Our implementation is efficient and scalable, enabling its use with large-scale data. We consider two synthetic models and real survey data from Vinton Dome, US, and demonstrate that our solutions are reliable and feasible.

Cytoplasmic male sterile (CMS) lines varied at pollen abortive phenotypes (PAP) have been used effectively for production of hybrid seeds in rice. To investigate the relationship between PAP of CMS lines and CMS-specific mitochondrial genes or structures in rice, CMS lines varied at PAP developed on 18 cytoplasmic sources were examined with seven PCR primers specific to three CMS-specific mitochondrial regions. The 18 CMS lines were classified into stained abortive (SA) and typical abortive (TA) types according to their PAP. Two CMS cytoplasms-specific PCR fragments, by which genotypes between the CMS lines and their maintainers were distinguished, were identified with primer LD29 or LD30. Furthermore, it was discovered that phenotypes of SA-CMS and TA-CMS were related to CMS-specific mitochondrial genes or structures, LD-orf310, atp6-orf79-like, and orf288-like structures. The results suggested that CMS phenotypes were mainly controlled by cytoplasmic genes, and it could be speculated that the SA-CMS phenotype was related to LD-orf310 and atp6-orf79-like structure, while TA-CMS phenotype was related to WA352.

In this study, Chinese upland rice cultivars including Handao297 and Handao502 were transformed with the anti-herbicide bar gene in order to achieve efficient weed control. PCR amplification, Southern blot analysis and field Basta resistance identification in early T0, T1, and late generation T6 and T11–T13 illustrated that the exogenous bar gene had been integrated into the genome of the upland rice varieties with stable expression in successive generations. Different transformants had a different gene copy numbers, which was not related to Basta resistance. Some of the transgenic lines showed gene silencing, whereas multiple copies of the bar gene were observed in other late generation transgenic lines. Basta resistance can thus be inherited stably among generations, and an optimal Basta concentration and selective pressure are suitable for resistance segregation and breeding of homozygous progenies with high resistance. After three generations of successive Basta resistance selection in 207 T0 plants, we obtained 555 T3 lines. Comprehensive identification and selection for Basta resistance, drought resistance, yield, and other agronomic traits in nine generations yielded two promising transgenic lines, HD297T-31 and HD297T-523. Although both varieties were resistant to 0.1 % Basta, HD297T-31 possessed high (100 %) resistance to Basta while HD297T-523 showed moderate (95 %) resistance. Moreover, during the reproductive stage, the stems, sheaths, leaves, and panicles of HD297T-31 were immune-highly resistant to highly-moderately resistant to 0.5 % Basta, whereas, they were highly resistant–moderately resistant to 1 % Basta. HD297T-523 was immune-highly resistant and immune-highly resistant to 0.5 and 1 % Basta respectively. The plant and stem percentage sensitive to 0.5 % Basta was lower than 1 and 3 % respectively. Since HD297T-31 showed isozygosity, it could be used as a new variety in production.

A derivative formula for interface inversion using gravity anomalies, combining the Parker–Oldenburg method for calculating and inverting gravity anomalies with Xu’s iteration method for continuing potential fields, leads to a convergent inversion algorithm and an optimally located density interface geometry. In this algorithm, no filtering or any other convergence control techniques are needed during iteration. The method readily iterates the variable depth of the gravity interface by means of upward continuation in a form equivalent to inversion iteration in the Fourier domain instead of the divergent, downward continuation term. This iteration algorithm not only efficiently solves the divergence problem in the inversion iteration procedure but also validly obtains an excellent result for the density interface. A numerical example is presented to illustrate perfect execution of this approach in gravity exploration, and a real geophysical example of inversion of the Moho depth by means of this approach using a set of measured gravity anomalies over the Qinghai–Tibet Plateau in China is offered.

Edge detection is a useful tool in the interpretation of potential field data, and the existing edge detection filters are almost functions of first-order horizontal and vertical derivatives. We propose step-edge detection filters to improve the resolution of edge detection results, which use the functions of different-order derivatives to accomplish the edge detection task. We demonstrate the proposed filters on synthetic potential field data, and the results show that the new methods can recognize the edges of the sources more precisely and clearly. We also discuss the application effect of different step-edge detection filters. Lastly, we apply the proposed filters to real potential field data, and the recognized edges of the stratigraphic markers are more precise and clear.

The Greenwood frequency (GF) is influential in performance improvement for the coherent free space optical communications (CFSOC) system with a closed-loop adaptive optics (AO) unit. We analyze the impact of tilt and high-order aberrations on the mixing efficiency (ME) and bit-error-rate (BER) under different GF. The root-mean-square value (RMS) of the ME related to the RMS of the tilt aberrations, and the GF is derived to estimate the volatility of the ME. Furthermore, a numerical simulation is applied to verify the theoretical analysis, and an experimental correction system is designed with a double-stage fast-steering-mirror and a 97-element continuous surface deformable mirror. The conclusions of this paper provide a reference for designing the AO system for the CFSOC system.