Accurate Compensation Research Articles

A geomagnetic vector compensation method compatible with nonlinear interferences based on back propagation network and 3D Helmholtz coil.

Magnetic interferential compensation plays a vital role in geomagnetic vector measurement applications. Traditional compensation accounts for only the permanent interferences, induced field interferences, and eddy-current interferences. However, nonlinear magnetic interferences are found, which also have a great impact on measurement, and it cannot be fully characterized by a linear compensation model. This paper proposes a new compensation method based on a back propagation neural network, which can reduce the influence of the linear model on compensation accuracy due to its good nonlinear mapping capabilities. The high-quality network training requires representative datasets, yet it is a common problem in the engineering field. To provide adequate data, this paper adopts a 3D Helmholtz coil to restore the magnetic signal of a geomagnetic vector measurement system. A 3D Helmholtz coil is more flexible and practical than the geomagnetic vector measurement system itself when generating abundant data under different postures and applications. Simulations and experiments are both conducted to prove the superiority of the proposed method. According to the experiment, the proposed method can reduce the root mean square errors of north, east, and vertical components and the total intensity from 73.25, 68.54, 70.45, and 101.77 nT to 23.35, 23.58, 27.42, and 29.72 nT, respectively, compared with the traditional method.

Simple and Fast Voltage Disturbance Detection and Voltage Reference Generation Approach for Dynamic Voltage Restorer (DVR) to Compensate Unbalanced Voltage Sag and Swell in Three-Phase System: Simulation and Experimental Testing

The dynamic voltage restorer (DVR) is an important device for coping with voltage sag, swell, and unbalance. However, it is a real-time mechanism and must operate as quickly as possible to protect the sensitive and critical load from supply-side voltage anomalies. Hence, fast detection of voltage disturbances and reference voltage generation is essential for the DVR. This paper proposes a simple and fast voltage disturbance detection approach based on a simple three-phase phasor diagram which is easy to implement. The controller employed for the DVR uses a sliding mode control, making the entire system robust and insensitive to system parameter variations. Three different scenarios are simulated according to arbitrarily imposed supply conditions, verified in laboratory tests using the DSP R&D controller board. The results demonstrate a simpler, faster voltage-anomaly detection process which is easier for implementation compared to the other methods in the literature. The best and worst detection times (DTs) of the proposed approach are 1 and 4 ms, respectively. It yields a rapid response, accurate compensation, and robustness in restoring the load voltage to its nominal value within two cycles.

Shrinkage Compensation Technology of Concrete Filled Steel Tubular Structure of Large Cross-Sea Bridge

In view of the poor accuracy and unsatisfactory effect of shrinkage compensation for concrete-filled steel tubular structures of large cross-sea bridge (CSTS-LCSB), a new shrinkage compensation technology for CSTS-LCSB is proposed. The shrinkage mechanism of CSTS-LCSB is analyzed, including plastic shrinkage, dry shrinkage, autogenous shrinkage, and carbonation shrinkage. The proportion of dry shrinkage and autogenous shrinkage in ordinary concrete and high-strength concrete is determined. The CSTS-LCSB has different shrinkage forms in different environments, and the shrinkage strain state of CSTS-LCSB in different environments is calculated according to the difference. The shrinkage area of the concrete structure is determined, and the expansion agent is used to compensate for the shrinkage area of CSTS-LCSB. The experimental results show that the proposed compensation technology has a good effect on shrinkage compensation and has certain feasibility.

Design and Simulation Analysis of Semi-Active Lifting and Sinking Compensation System

The lifting and sinking motion generated by the drilling platform causes large fluctuations in the suspension tension of the large hook, which affects the stability of the drilling pressure acting on the rock at the bottom of the well, greatly reduces the efficiency of drilling and decreases the service life of the drill bit and the drill column under the action of cyclically varying loads, causing an increase in the overall drilling cost. In order to avoid the above situation, a nonlinear model of a semi-active lift-sink compensation system is designed and a method to improve the compensation efficiency of the system is proposed. Firstly, the relevant physical model of the hydraulic system is established, and then its simulation model is built according to the working principle of the semi-active lift and sink compensation system. Then the effects of different factors are added to the simulation model of semi-active lifting and sinking compensation, and finally the effects of different factors on the compensation efficiency of the active lifting and sinking system are compared. The simulation results show that a regular sinusoidal wave with a peak value of 6.5 m and a period of 10 s as the ship's lifting and sinking displacement input will reduce the compensation efficiency of the semi-active lifting and sinking compensation system, while the smaller the stiffness of the wire rope, the better the compensation effect of the drill column and the higher the compensation accuracy. The proposed method can effectively improve the compensation efficiency of semi-active lifting and sinking compensation system.

Strategies for in-situ thin film filter monitoring with a broadband spectrometer.

Optical monitoring of thin film interference filters is of primary importance for two main reasons: possible error compensation and greater thickness accuracy of the deposited layers compared to non-optical methods. For many designs, the latter reason is the most crucial, because for complex designs with a large number of layers, several witness glasses are used for monitoring and error compensation with a classical monitoring approach is no longer possible for the whole filter. One optical monitoring technique that seems to maintain some form of error compensation, even when changing witness glass, is broadband optical monitoring, as it is possible to record the determined thicknesses as the layers are deposited and re-refine the target curves for remaining layers or recalculate the thicknesses of remaining layers. In addition, this method, if used properly, can, in some cases, provide greater accuracy for the thickness of deposited layers than monochromatic monitoring. In this paper, we discuss the process of determining a strategy for broadband monitoring with the goal of minimizing thickness errors for each layer of a given thin film design.

Turbulence compensation for radar imaging carrying orbital angular momentum based on convolutional neural network

The spiral phase front (SPF) and orbital angular momentum (OAM) of vortex electromagnetic waves (VEMW) have attracted extensive attention in radar imaging. However, VEMW is extremely sensitive to atmospheric turbulence (AT), which will lead to distortion of the SPF and diffusion of the OAM modes. Furthermore, refractive-index fluctuations will cause absorption and fluctuations in the speed of VEMW. Specifically, SPF distortion leads to phase errors, which is demonstrated as defocus of the scatterer in the image. Atmospheric absorption and fluctuations in VEMW speed suffer amplitude error and phase error, which are manifested as amplitude variation with range and positioning errors, respectively. Generally, refractive-index fluctuations feature significant spatial and temporal variability, making it difficult for conventional algorithms to obtain accurate compensation. In this paper, a data-driven-based convolutional neural network (CNN) approach is proposed to improve imaging performance. The CNN is taken to learn the mapping function of images with atmospheric errors to label images without turbulence effects, and then the trained CNN model is integrated into imaging system to improve the imaging quality. The numerical simulation verifies that the method can effectively compensate for turbulence effects and obtain high-resolution images.

An ADRC-based triple-loop control strategy of ship-mounted Stewart platform for six-DOF wave compensation

The ship-mounted Stewart platform can accurately compensate the 6-degree-of-freedom (6-DOF) wave motion of offshore vessels to facilitate the transfer of personnel and cargoes. They usually equip high-power electric or hydraulic actuators with high nonlinearity, large inertia and parameter perturbation. The lower platform is exposed to random wave motion and the upper platform is subjected to time-varying load interference. In addition, there are strong coupled inertia between the limbs of Stewart platform. These problems make it difficult for the ship-mounted Stewart platform to achieve accurate 6-DOF wave compensation. In this paper, a triple-loop control strategy based on active disturbance rejection control (ADRC) is proposed for the electric-driven ship-mounted Stewart platform, where the internal model controller (IMC) in the current-loop is designed to realize rapid dynamic adaptation of torque, the sliding model controller (SMC) in the velocity-loop is designed to adjust the velocity steadily, and the ADRC in the position-loop is designed to estimate and compensate the total position disturbance. The results show that the proposed control strategy has excellent performance in the power reduction, decoupling control and disturbance resistance. Under the random wave excitation in 4-level sea state, the proposed control strategy can improve compensation deviation by about 4.4 times and compensation stationarity by 4 times compared with PI controller.

Compensation cycle consistent generative adversarial networks (Comp-GAN) for synthetic CT generation from MR scans with truncated anatomy.

MR scans used in radiotherapy can be partially truncated due to the limited field of view (FOV), affecting dose calculation accuracy in MR-based radiation treatment planning. We proposed a novel Compensation-cycleGAN (Comp-cycleGAN) by modifying the cycle-consistent generative adversarial network (cycleGAN), to simultaneously create synthetic CT (sCT) images and compensate the missing anatomy from the truncated MR images. Computed tomography (CT) and T1 MR images with complete anatomy of 79 head-and-neck patients were used for this study. The original MR images were manually cropped 10-25mm off at the posterior head to simulate clinically truncated MR images. Fifteen patients were randomly chosen for testing and the rest of the patients were used for model training and validation. Both the truncated and original MR images were used in the Comp-cycleGAN training stage, which enables the model to compensate for the missing anatomy by learning the relationship between the truncation and known structures. After the model was trained, sCT images with complete anatomy can be generated by feeding only the truncated MR images into the model. In addition, the external body contours acquired from the CT images with full anatomy could be an optional input for the proposed method to leverage the additional information of the actual body shape for each test patient. The mean absolute error (MAE) of Hounsfield units (HU), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) were calculated between sCT and real CT images to quantify the overall sCT performance. To further evaluate the shape accuracy, we generated the external body contours for sCT and original MR images with full anatomy. The Dice similarity coefficient (DSC) and mean surface distance (MSD) were calculated between the body contours of sCT and original MR images for the truncation region to assess the anatomy compensation accuracy. The average MAE, PSNR, and SSIM calculated over test patients were 93.1 HU/91.3 HU, 26.5dB/27.4dB, and 0.94/0.94 for the proposed Comp-cycleGAN models trained without/with body-contour information, respectively. These results were comparable with those obtained from the cycleGAN model which is trained and tested on full-anatomy MR images, indicating the high quality of the sCT generated from truncated MR images by the proposed method. Within the truncated region, the mean DSC and MSD were 0.85/0.89 and 1.3/0.7mm for the proposed Comp-cycleGAN models trained without/with body contour information, demonstrating good performance in compensating the truncated anatomy. We developed a novel Comp-cycleGAN model that can effectively create sCT with complete anatomy compensation from truncated MR images, which could potentially benefit the MRI-based treatment planning.

A High Precision Analog Temperature Compensated Crystal Oscillator Using a New Temperature Compensated Multiplier

The development and application of various precision electronic devices require a large number of high-precision and low-cost temperature-compensated crystal oscillators (TCXO) to generate frequency references. In order to achieve higher compensation accuracy at lower cost, a new fully integrated analog-TCXO (ATCXO) is proposed in this paper. It uses an innovative temperature-compensated multiplier to generate cubic and quintic voltages. The experimental results show that it can achieve the ultra-high fitting of the frequency-temperature characteristic curve of the crystal. This effectively improves the compensation accuracy of the TCXO. The proposed ATCXO achieves a frequency stability of ± 0.8 ppm in the temperature range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$- 40\,\,^{\circ }\text{C}$ </tex-math></inline-formula> to 95 °C. At the same time, the gain-temperature error of the proposed temperature compensated analog multiplier is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\le 0.13$ </tex-math></inline-formula> dB. This paper is based on SMIC 130 nm process, the core area of the chip is only 0.124 mm2. Multiple modules such as bandgap circuit, n-th power voltage generation circuit, summation circuit, gain control circuit and voltage controlled oscillator using variable capacitor array are integrated.

Research on PMSM control system based on high order sliding mode method

A high-order sliding mode viewer using the stator current and rotor magnetic chain as state quantities is designed and implemented, which is based on the fourth-order state equation and can directly output the observed values of the rotor magnetic chain. To avoid the phase change of the magnetic chain due to the introduction of a low-pass filter, a vector equation of state filtering method is proposed to filter the dither signal through the magnetic chain equation by taking the observed deviation of the current as the sliding mode surface and inputting the equivalent control signal directly into the magnetic chain equation. Simulation results show that the designed extended sliding mode observer is able to accurately estimate the rotor position and speed at lower speeds without accurate compensation of the observed values for rotor information collection present in the counter potential and the rotor magnetic chain. The sensorless vector control system is characterized by robustness, wide speed range, and higher feasibility and effectiveness.

Real-time path correction of industrial robots in machining of large-scale components based on model and data hybrid drive

Industrial robots are increasingly used in machining of large-scale components due to advantages of high repeatability, large workspace and low cost. Nevertheless, applying industrial robots to high-accuracy machining of large-scale components remains a challenge, where the major hurdle is the insufficient manipulator stiffness due to joint flexibility. When the robot is performing a machining task, joint flexibility-induced position errors between motor and link called joint position errors (JPEs), as the main source of robot deformations, make the robot deviate from the desired path. For most industrial robots, due to the lack of link-side encoders, it is difficult to obtain the JPEs by direct measurement and compensate them in the controller, which deteriorates the path accuracy of the robot during machining greatly. To address this problem, this paper presents a real-time path correction approach of industrial robots based on JPE estimation and compensation with requiring only motor-side measurements and external wrenches. The proposed approach is divided into three steps. First, to estimate the actual link position of the robot in real-time, the dynamics of a manipulator with joint flexibility called flexible dynamics (FD) is introduced. Second, by taking both FD and disturbance dynamics into account, a novel link state estimator called flexible-dynamics based disturbance Kalman filter (FDBDKF) is developed, and thus JPEs can be estimated in real-time. Third, a data-driven locally weighted projection regression (LWPR)-based JPE prediction and compensation method is developed to further improve the compensation accuracy of the JPEs. Simulation and experimental results, obtained on a 6-DOF industrial robot, demonstrate the feasibility and effectiveness of the proposed approach. Experimental results show significant improvement (>80%) in the path accuracy of a simple material removal process corrected using the proposed approach.

Precise Measurement and Compensation of the Micro Product of Inertia for Float Assembly in Pendulous Integrating Gyroscopic Accelerometers.

Nonlinear error has become the most critical factor restricting the measurement accuracy of pendulous integrating gyroscopic accelerometers (PIGA) during their improvement. The key to nonlinear error suppression for PIGA is the precise measurement and compensation of the micro product of inertia (MPOI) of the float assembly. However, the existing equipment and procedure for product of inertia (POI) measurement and compensation do not meet the accuracy requirements for MPOI. To solve this problem, novel equipment and procedures are proposed for the measurement and compensation of MPOI. The principle of the proposed measurement method is to simulate the error produced by MPOI in PIGA by using a single-axis turntable to rotate the float assembly along the eccentric axis to generate a centrifugal moment due to MPOI. The principle of the proposed compensation method is to remove the asymmetric mass to reduce the MPOI to zero. Through experimental validation, it is concluded that: (1) the measurement and compensation accuracy of the proposed method are better than 1 × 10-10 kg·m2 and 3 × 10-10 kg·m2, respectively; (2) the proposed method is validated as the MPOI is reduced from 7.3 × 10-9 kg·m2 to 3 × 10-10 kg·m2 for a real float assembly in PIGA, and the quadratic error of PIGA is reduced from 10-5/g0 to 3 × 10-7/g0.

A sufficient condition for free-stream preserving WENO schemes on curvilinear grids of complex geometries

The well developed conservative finite-difference-method based on upwind schemes, such as the weighted essentially nonoscillatory (WENO) schemes, may violate the free-stream preserving (FP) property when applied to curvilinear grids due to the loss of the geometric conservation law. Recent developments in FP techniques have disregarded the balance between the computational accuracy and efficiency, and more importantly, the general regularity for the FP property is not available. In this paper, we rigorously prove that the upwind dissipation satisfies the FP property as long as the sub-stencil reconstructions of the metrics are identical by rearranging the dissipation part as an accumulative form composed of the sub-stencil reconstructions. With this, the novel FP metrics are constructed straightforwardly for various WENO reconstructions, introducing less complexity to implement the schemes with a merely simple accuracy compensation by replacing the central fluxes with high-order ones. Applications of such an implementation to the isotropic vortex convection and double Mach problem etc. validate the accuracy and robustness of the novel FP method in simulating both the smooth flows and discontinuities at lower computational costs than the previous methods. Besides, further viscous computations for the three-element airfoil and the 3D wing are conducted to show the good capability of the present method on complex geometries.

DTATrans: Leveraging Dynamic Token-Based Quantization With Accuracy Compensation Mechanism for Efficient Transformer Architecture

Models based on the attention mechanism, i.e., transformers, have shown extraordinary performance in natural language processing (NLP) tasks. However, their memory footprint, inference latency, and power consumption are still prohibitive for efficient inference at edge devices, even at data centers. To tackle this issue, we present an algorithm-architecture co-design named DTATrans. We find empirically that the tolerance to the noise varies from token to token in attention-based NLP models. This finding leads us to dynamically quantize different tokens with mixed levels of bits. Furthermore, we find that the overstrict quantization method causes a dilemma of the model accuracy and model compression ratio, which impels us to explore a method to compensate for the model accuracy when the compression ratio is high. Thus, in DTATrans, we design a compression framework that: 1) dynamically quantizes tokens while they are forwarded in the models; 2) jointly determines the ratio of each precision; and 3) compensate the model accuracy by exploiting lightweight computing on the 0-bit tokens. Moreover, due to the dynamic mixed-precision tokens caused by our framework, previous matrix-multiplication accelerators (e.g., systolic array) cannot effectively exploit the benefit of the compressed attention computation. We thus design our transformer accelerator with the variable-speed systolic array (VSSA) and propose an effective optimization strategy to alleviate the pipeline-stall problem in VSSA without hardware overhead. We conduct experiments with existing attention-based NLP models, including BERT and GPT-2 on various language tasks. Our results show that DTATrans outperforms the previous neural network accelerator Eyeriss by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$16.04\times $ </tex-math></inline-formula> in terms of speedup and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.62\times $ </tex-math></inline-formula> in terms of energy saving. Compared with the state-of-the-art attention accelerator SpAtten, our DTATrans achieves at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.62\times $ </tex-math></inline-formula> speedup and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.22\times $ </tex-math></inline-formula> energy efficiency improvement.

Motion Error Estimation and Compensation of Airborne Array Flexible SAR Based on Multi-Channel Interferometric Phase

Airborne array synthetic aperture radar (SAR) has made a significant breakthrough in the three-dimensional resolution of traditional SAR. In the airborne array SAR 3D imaging technology, the baseline length is the main factor restricting the resolution. Airborne array flexible SAR can increase the baseline length to improve the resolution and interference performance by mounting antennae on the wing. The existing research lacks results obtained using flexible actual data processing and specific motion compensation methods. Thus, this paper proposes a motion error estimation and compensation method for an airborne array flexible SAR based on a multi-channel interferometric phase. Firstly, a flexible channel motion compensation model is established based on the multi-channel interference phase of airborne array flexible SAR. Then, based on the rigid multi-channel data, combined with the ground control points, the least square method, and the global optimal search algorithm, the accurate rigid baseline length and the central incidence angle are obtained. Finally, according to the multi-channel interference phase inversion of the flexible motion error and combined with the motion compensation model, the flexible data are compensated in the time domain. The actual results indicate that, compared with traditional motion compensation methods, our method can obtain accurate flexible compensation data. This study improves the interference performance of multi-channel data of airborne array flexible SAR and lays a solid foundation for the high-precision 3D reconstruction of airborne array flexible SAR.

A combined vertical accuracy compensation method for automatic drilling and riveting of aircraft panels with variable curvatures

PurposeAircraft structures are mainly connected by riveting joints, whose quality and mechanical performance are directly determined by vertical accuracy of riveting holes. This paper proposed a combined vertical accuracy compensation method for drilling and riveting of aircraft panels with great variable curvatures.Design/methodology/approachThe vertical accuracy compensation method combines online and offline compensation categories in a robot riveting and drilling system. The former category based on laser ranging is aimed to correct the vertical error between actual and theoretical riveting positions, and the latter based on model curvature is used to correct the vertical error caused by the approximate plane fitting in variable-curvature panels.FindingsThe vertical accuracy compensation method is applied in an automatic robot drilling and riveting system. The result reveals that the vertical accuracy error of drilling and riveting is within 0.4°, which meets the requirements of the vertical accuracy in aircraft assembly.Originality/valueThe proposed method is suitable for improving the vertical accuracy of drilling and riveting on panels or skins of aerospace products with great variable curvatures without introducing extra measuring sensors.

Research on nonlinear compensation scheme of yarn tension sensor using SAW devices based on SSA–SVR model

The detection accuracy of a yarn tension sensor using surface acoustic wave devices has become increasingly important. We investigate a nonlinear compensation scheme based on sparrow search algorithm (SSA) and support vector regression (SVR) models to improve its detection accuracy, and the principle of SSA–SVR model and training method are also explored. We take the output frequency of the two sensors as input, the yarn tension applied to the working sensor as output, train an SSA–SVR model and use it for nonlinear compensation. We analyze and calculate the linearity, compensation accuracy and robustness of the SSA-SVR model, and compared it with the multiple regression model and BP neural network. The comparison results show that the SSA–SVR model has the best linearity, the highest compensation accuracy and the most robust. Finally, a novel nonlinear compensation scheme is proposed.

Data cleaning method for the process of acid production with flue gas based on improved random forest

Acid production with flue gas is a complex nonlinear process with multiple variables and strong coupling. The operation data is an important basis for state monitoring, optimal control, and fault diagnosis. However, the operating environment of acid production with flue gas is complex and there is much equipment. The data obtained by the detection equipment is seriously polluted and prone to abnormal phenomena such as data loss and outliers. Therefore, to solve the problem of abnormal data in the process of acid production with flue gas, a data cleaning method based on improved random forest is proposed. Firstly, an outlier data recognition model based on isolation forest is designed to identify and eliminate the outliers in the dataset. Secondly, an improved random forest regression model is established. Genetic algorithm is used to optimize the hyperparameters of the random forest regression model. Then the optimal parameter combination is found in the search space and the trend of data is predicted. Finally, the improved random forest data cleaning method is used to compensate for the missing data after eliminating abnormal data and the data cleaning is realized. Results show that the proposed method can accurately eliminate and compensate for the abnormal data in the process of acid production with flue gas. The method improves the accuracy of compensation for missing data. With the data after cleaning, a more accurate model can be established, which is significant to the subsequent temperature control. The conversion rate of SO2 can be further improved, thereby improving the yield of sulfuric acid and economic benefits.

A wind power smoothing strategy based on two-layer model algorithm control

The inherent uncertainty of wind power generation leads to a mismatch between actual wind power generation and electric grid demand power, while the occurrence of sudden loads makes real-time scheduling of wind farms difficult. To address these issues, a cooperative compensation strategy of battery is proposed to compensate for the unbalanced power and sudden loads. Positive unbalanced power is used directly to compensate for sudden loads, and the energy storage absorbs the remaining positive unbalanced power to indirectly compensate for negative unbalanced power and sudden loads when the energy storage has excess power. The fluctuation rate of wind power after compensation is considered, and a smoothing model based on two-layer model algorithm control (MAC) is established. A variable mode decomposition (VMD) adaptive frequency division method is proposed to decompose the compensated power in order to smooth the high-frequency and low-frequency parts of the compensated power using different components of the hybrid energy storage to achieve accurate compensation.

Improved ship imaging algorithm for geosynchronous synthetic aperture radar (SAR) featured by subaperture time window selection optimization and inverse SAR translational compensation

An inverse synthetic aperture radar processing-based algorithm is improved for ship imaging in geosynchronous synthetic aperture radars (GEO SARs) to solve the technical challenges including long accumulation time and complex target motion characteristics. The improvement on the existing algorithm mainly involves four aspects. First, the formula for calculating the appropriate time length of subaperture is derived, according to the principle that the accumulated power of the ship’s echo corresponding to the subaperture duration ensures that the signal-to-noise ratio satisfies the requirement of GEO SARs. The derived formula solves the problem that how long the subaperture length should be taken with regards to a long accumulation time of GEO SAR when imaging ships. Second, we propose an optimization criterion for determining the appropriate subaperture time window by ensuring that the maximum number of ship pixels is detected in the subaperture image. The proposed criterion is used to optimize the location of the subaperture time window in the long accumulation time. Third, the SPECAN algorithm used in the scene imaging process is replaced by an improved nonlinear chirp scaling (NLCS) algorithm to improve the imaging accuracy of the scene. Our improvement on the traditional NLCS algorithm focuses on improving precisions of some of the formulas in the traditional algorithm. Furthermore, a translational compensation algorithm is proposed by considering the influence of spatial variance of slant range history of GEO SARs. The proposed translational compensation algorithm improves the compensation accuracy since the spatial variance of different scatterers in the scene is considered. A series of simulation experiments related with ship imaging in GEO SARs were carried out to verify the correctness of the proposed algorithm and the improvement on the imaging quality compared with that of the existing algorithm.