Stereo Mapping Research Articles

Low frequency error analysis and calibration for multiple star sensors system of GaoFen7 satellite

ABSTRACT The GaoFen7 (GF7) optical satellite is the first Chinese civilian sub-meter high-resolution stereo mapping satellite and is equipped with a double linear array camera and laser altimeter to achieve large-scale topographic mapping. To improve the accuracy of attitude determination, an attitude determination system comprised of four star sensors is loaded. According to the measurement accuracy and steady performance, the star sensors 1a and 1b is usually used together for satellite attitude calculation, which is called the conventional mode of attitude determination. Then, the combination of star sensors 2a and 2b is called the unconventional mode of attitude determination. Affected by variations in the incident angle of sunlight and solar radiation, thermal deformation occurs in the body and installation structure of the star sensor, which causes Attitude Low-Frequency Error (ALFE) and seriously influences the consistency of attitude determination results of different combination modes for multiple star sensors system. This study proposes an ALFE analysis and calibration approach for the multiple star sensors system of GF7 satellite to ensure the consistency of attitude determination results of different combination modes. Based on the statistical characteristics of the angles of the three axes, the installation parameters of the four star sensors are first calibrated. After analyzing the characteristics of the optical axis angles within 1420 orbit periods over 135 days, the segmented ALFE compensation model between the unconventional and conventional modes is proposed based on the Fourier series model and input parameter of latitude. Based on the on-orbit installation parameters and the ALFE model, the precise attitude determination results of the unconventional mode are calculated. Experimental results show that the attitude determination consistency after compensation is better than 2”. Moreover, the reliable application time range of the compensation model is 30 days to satisfy the requirements for high-precision attitude determination of GF7 satellite.

Aerial photography trajectory-tracking controller design for quadrotor UAV

Quad-rotor unmanned aerial vehicles (UAV) are prone to external interference during aerial photography of farmland environments. For example, they are affected by external airflow and load, resulting in route deviation and irregular image overlap, which seriously affects image quality. An aerial trajectory tracking controller is designed for this aerial photography process. To ensure that a drone can fly according to the established route during the aerial photography process and meet the requirements of large-scale topographic map stereo mapping for the flight control accuracy of the drone platform, the system was divided into a full-drive subsystem and an underactuated subsystem. The full-drive subsystem uses a fast terminal sliding mode controller to ensure that the variable ([Formula: see text]) reaches the desired value. The under-actuated subsystem adopts the second-order sliding mode control was used to achieve effective position and attitude tracking of variables ([Formula: see text]). The flight controllers are derived by using Lyapunov theory. Finally, with the aerial trajectory of a farmland taken as an example, the flight path control of the UAV is simulated. Simulation results show that the designed control system can be applied to the aerial photography process of the UAV and has strong anti-system parameter perturbation, robustness and good trajectory tracking.

A Self-Attentive Hybrid Coding Network for 3D Change Detection in High-Resolution Optical Stereo Images

Real-time monitoring of urban building development provides a basis for urban planning and management. Remote sensing change detection is a key technology for achieving this goal. Intelligent change detection based on deep learning of remote sensing images is a current focus of research. However, most methods only use unimodal remote sensing data and ignore vertical features, leading to incomplete characterization, poor detection of small targets, and false detections and omissions. To solve these problems, we propose a multi-path self-attentive hybrid coding network model (MAHNet) that fuses high-resolution remote sensing images and digital surface models (DSMs) for 3D change detection of urban buildings. We use stereo images from the Gaofen-7 (GF-7) stereo mapping satellite as the data source. In the encoding stage, we propose a multi-path hybrid encoder, which is a structure that can efficiently perform multi-dimensional feature mining of multimodal data. In the deep feature fusion link, a dual self-attentive fusion structure is designed that can improve the deep feature fusion and characterization of multimodal data. In the decoding stage, a dense skip-connection decoder is designed that can fuse multi-scale features flexibly and reduce spatial information losses in small-change regions in the down-sampling process, while enhancing feature utilization and propagation efficiency. Experimental results show that MAHNet achieves accurate pixel-level change detection in complex urban scenes with an overall accuracy of 97.44% and F1-score of 92.59%, thereby outperforming other methods of change detection.

Registration and Combined Adjustment for the Laser Altimetry Data and High-Resolution Optical Stereo Images of the GF-7 Satellite

The GF-7 satellite is China’s first civil sub-meter resolution stereo mapping satellite, aiming at 1:10,000-scale mapping. To achieve this goal, apart from the stereo optical cameras that reach sub-meter resolution, the GF-7 satellite is equipped with a laser altimetry system capable of obtaining three-dimensional laser points (LPs) with high elevation accuracy. However, the combination of laser altimetry data and optical stereo images has not been thoroughly studied. In this paper, we exploit the images recorded by the highly integrated laser footprint cameras and propose a hierarchical phase correlation method based on a geographic pyramid for the registration of laser altimetry data and high-resolution optical stereo images, which lays a solid foundation for the following combined adjustment. Experiments show that the proposed registration method can automatically locate the LPs on high-resolution stereo images and meet the requirements of bundle adjustment. A series of bundle adjustment experiments were carried out, showing that laser altimetry data can significantly enhance the vertical accuracy of optical image stereo mapping and that elevation accuracy can reach roughly 1.0 m (RSME) without ground control points. Therefore, this study could be a good guide for global high-precision DSM acquisition with the GF-7 satellite.

On-Orbit Geometric Calibration and Accuracy Validation for Laser Footprint Cameras of GF-7 Satellite

The Gaofen-7 (GF-7) satellite uses a two-beam laser altimetry system in which each beam is equipped with a laser footprint camera (LFC) to provide geometric processing of the laser footprint images that assist in optical image stereo mapping. Because of the violent vibrations during launch and the difference in the environment before and after entering orbit, the key parameters for geometric processing of the laser footprint images may change, which will cause large geolocation errors. Therefore, it is essential to carry out on-orbit calibration and validation for the laser footprint cameras. This study first constructs a rigorous geometric positioning model for the LFC of the GF-7 satellite and analyses various error sources that affect the geometric positioning accuracy of laser footprint images. Then, a comprehensive calibration method, which effectively eliminates the distortion of the LFC optical system, and the positioning error caused by the long-period jitter of the satellite platform, is proposed based on the multi-scene images combined with image simulation. The proposed method can effectively eliminate various errors that affect the geometric positioning accuracy of the GF-7 laser footprint image. The internal geometric positioning accuracy of the calibrated LFC is better than 0.7 pixels, and the absolute geometric positioning accuracy is within 6.0 m after using precise post-processing orbital and attitude data. Our study will contribute to the processing and application of laser altimetry data from the GF-7 satellite.

On-Orbit Absolute Radiometric Calibration and Validation of ZY3-02 Satellite Multispectral Sensor.

This study described the on-orbit vicarious radiometric calibration of Chinese civilian high-resolution stereo mapping satellite ZY3-02 multispectral imager (MUX). The calibration was based on gray-scale permanent artificial targets, and multiple radiometric calibration tarpaulins (tarps) using a reflectance-based approach between July and September 2016 at Baotou calibration site in China was described. The calibration results reveal a good linear relationship between DN and TOA radiances of ZY3-02 MUX. The uncertainty of this radiometric calibration was 4.33%, indicating that radiometric coefficients of ZY3-02 MUX are reliable. A detailed discussion on the validation analysis of the comparison results between the different radiometric calibration coefficients is presented in this paper. To further validate the reliability of the three coefficients, the calibrated ZY3-02 MUX was compared with Landsat-8 Operational Land Imager (OLI). The results also indicate that radiometric characteristics of ZY3-02 MUX imagery are reliable and highly accurate for quantitative applications.

Long-Periodic Analysis of Boresight Misalignment of Ziyuan3-01 Three-Line Camera

The Ziyuan3-01 (ZY3-01) satellite is China’s first civilian stereo surveying and mapping satellite to meet the 1:50,000 scale mapping requirements, and has been operated in orbit for 10 years. The boresight misalignment of the three-line camera (TLC) is an essential factor affecting the geolocation accuracy, which is a principal concern for stereo mapping satellites. However, the relative relationships of TLC are often regarded as fixed for the same ground scene in most traditional geometric calibrations, without considering the on-orbit long-periodic changes. In this paper, we propose a long-periodic method to analyze and estimate the boresight misalignments between three cameras, with the attitude estimation of a nadir (NAD) camera as the benchmark. Offsets and drifts of the three cameras were calculated and calibrated with different compensation models using scale invariant feature transform (SIFT) points as the ground control. Ten simultaneous NAD–Forward (FWD)–Backward (BWD) imagery of the ZY3-01 satellite acquired from 2012 to 2020 were selected to verify the long-periodic changes in TLC boresight misalignments. The results indicate that the boresight alignment angles of ZY3-01 TLC are dynamic during the long-periodic flight, but the structure of TLC is stable for the misalignments of both FWD and BWD within only 7 arc seconds, which can provide a positive reference for subsequent satellite design and long-periodic on-orbit geometric calibration.

On-Orbit Radiometric Performance of GF-7 Satellite Multispectral Imagery

China’s first civilian, sub-meter, high-resolution stereo mapping satellite, GF-7, launched on 3 November 2019. Radiometric characterization of GF-7 multispectral imagery has been performed in this study. A relative radiometric accuracy evaluation of the GF-7 multispectral imagery was performed using several large uniform scenes, and the results showed that the accuracy is better than 2%. The absolute radiometric evaluation of the GF-7 satellite sensor was conducted at the Baotou and Dunhuang calibration sites, using the reflectance-based vicarious approach. The synchronous measurements of surface reflectance and atmospheric parameters were collected as the input for the radiative transfer model. The official radiometrically calibrated coefficient of the GF-7 multispectral imagery was evaluated with the predicted top-of-atmosphere (TOA) radiance from the radiative transfer model. The results indicated that the absolute radiometric accuracy of GF-7 multispectral imagery is better than 5%. In order to monitor the radiometric stability of the GF-7 satellite multispectral sensor, a relative and absolute radiometric accuracy assessment campaign should be performed several times a year.

Geometric Accuracy Verification of GF-7 Satellite Stereo Imagery Without GCPs

The GaoFen-7 (GF-7) satellite is the China’s first civil optical stereo-mapping satellite with submeter resolution. GF-7 is also equipped with a laser altimeter, which can obtain sparse laser altimetry points (LAPs) to improve the vertical accuracy of stereo images. Verifying the geometric accuracy of GF-7 imagery without ground-control points (GCPs) is of great significance for evaluating the mapping capability of GF-7. In this study, 147 stereo images and 804 LAPs of the GF-7 satellite covering Jiangsu Province, Hebei Province, and Sichuan Province in China were selected as experimental data. Subsequently, 455 high-precision independent check points were used to verify the geometric accuracy of the GF-7 images. The results show that, without GCPs, the root-mean-square errors (RMSEs) in the horizontal direction of the experimental images in flat, hilly, mountainous, and high-mountainous terrains, and over the entire area were 4.91, 3.81, 4.38, 6.39, and 4.91 m, respectively. The RMSEs in the vertical direction were 3.42, 4.68, 3.00, 4.41, and 3.52 m, respectively. After performing combined block adjustments of the LAPs and stereo images, the RMSEs of the experimental images in the vertical direction decreased to 0.43, 0.66, 0.76, 1.14, and 0.68 m, respectively, whereas those in the horizontal direction saw only minor changes. Therefore, in the absence of GCPs, the geometric accuracy of GF-7 imagery can fully meet the accuracy requirements of China’s 1:10 000 scale stereo mapping by using the GF-7 LAPs as control points.

Combined Block Adjustment of Stereo Imagery and Laser Altimetry Points of the ZY3-03 Satellite

The Ziyuan3-03 (ZY3-03) satellite is an optical stereo mapping satellite that is able to synchronously provide triple linear-array stereo images and discrete laser altimetry points (LAPs) for plotting 1:50 000-scale maps. Considering that the relative horizontal error between the ZY3-03 nadir image and synchronously acquired LAPs is very small, this study designed a technical method to obtain accurate image coordinates of LAPs on stereo images, and this method successfully overcomes the shortcomings of previous methods. Subsequently, a combined block adjustment model of stereo images and LAPs was constructed. On this basis, this study proposed a combined block adjustment method using ZY3-03 stereo images and LAPs to improve the vertical accuracy of images. For our research, 19 ZY3-03 triple linear-array stereo images and 87 synchronously acquired LAPs of plain, hilly, and mountainous terrains located in China were selected to conduct the block adjustment experiment. Results indicated that the vertical root-mean-square error of the experimental images decreased from 5.27 to 2.58 m for plain and hilly terrains and decreased from 11.25 to 4.45 m for mountainous terrain. Moreover, the vertical accuracy of the experimental images met the requirement of 1:50 000-scale mapping and also exceeded the accuracy of combined adjustment with Ice, Cloud, and land Elevation Satellite (ICESat)-1 satellite LAPs and the same experimental images.

Production of a Three-Dimensional Triangulated Irregular Network (3D TIN) for Al-Karkh University of Science, Baghdad- Iraq

Many satellite systems take cover images like QuickBird for terrain so that these images scan be used to construct 3D models likes Triangulated Irregular Network (TIN), and Digital Elevation Model (DEM). This paper presents a production of 3D TIN for Al-Karkh University of Science in Baghdad - Iraq using QuickBird image data with pixel resolution of 0.6 m. The recent generations of high-resolution satellite imaging systems open a new era of digital mapping and earth observation. It provides not only multi-spectral and high-resolution data but also the capability for stereo mapping. The result of this study is a production of 3D satellite images of the university by merging 1 m DEM with satellite image for ROI using ArcGIS package Version 10.3.

A Method of Extracting High-Accuracy Elevation Control Points from ICESat-2 Altimetry Data

Due to its high ranging accuracy, spaceborne laser altimetry technology can improve the accuracy of satellite stereo mapping without ground control points. In the past, full-waveform ICE, CLOUD, and Land Elevation Satellite (ICESat) laser altimeter data have been used as one of the main data sources for global elevation control. As a second-generation satellite, ICESat-2 is equipped with an altimeter using photon counting mode. This can further improve the application capability for stereo mapping because of the six laser beams with high along-track repetition frequency, which can provide more detailed ground contour descriptions. Previous studies have addressed how to extract high-accuracy elevation control points from ICESat data. However, these methods cannot be directly applied to ICESat-2 data because of the different modes of the laser altimeters. Therefore, in this paper, we propose a method using comprehensive evaluation labels that can extract high-accuracy elevation control points that meet the different level elevation accuracy requirements for large scale mapping from the ICESat-2 land-vegetation along-track product. The method was verified using two airborne lidar data sets. In flat, hilly, and mountainous areas, by using our method to extract the terrain elevation, the root-mean-square error of elevation control points decrease from 1.249–2.094 m, 2.237–3.225 m, and 2.791–4.822 m to 0.262–0.429 m, 0.484–0.596 m, and 0.611–1.003 m, respectively. The results show that the extraction elevations meet the required accuracy for large scale mapping.

A Planimetric Location Method for Laser Footprints of the Chinese Gaofen-7 Satellite Using Laser Spot Center Detection and Image Matching to Stereo Image Product

Satellite stereo mapping, together with laser altimetry, can be used to obtain three-dimensional geospatial information. Spaceborne laser altimeter can provide high-accuracy elevation information; however, due to the lack of detailed intensity information, its planimetric accuracy is usually worse than the ranging accuracy. The Chinese Gaofen-7 (GF-7) satellite, which was designed for civilian mapping application, was launched on November 3, 2019. The GF-7 satellite’s main payloads are a laser altimeter system (with footprint camera) and a dual-linear charge-coupled device (CCD) mapping camera. According to the pixel coordinate of the laser footprint in the stereo image, the laser altimeter together with the footprint camera can provide planimetric geodetic coordinates for the control points of a higher accuracy than the other traditional satellite laser altimeters, and represents a new technology for satellite mapping. In this article, a laser footprint planimetric location method for the GF-7 satellite is proposed. The method is designed based on the main payload characteristics of GF-7 and the working modes of the laser altimeter by the combined use of subpixel phase correlation image matching and four types of laser spot center detection methods. The planimetric positioning accuracies of the laser spots in urban, suburban, farmland, forest, mountainous, and ice sheet areas were also analyzed. The experimental results show that the accuracy of planimetric location relative to stereo image for the laser footprint is 0.3–1.0 m (except for ice sheets ~12 m) when the footprint camera works under the synchronous mode, and 0.2–0.4 m when the footprint camera works under asynchronous mode (AM).

Urban Building Extraction and Modeling Using GF-7 DLC and MUX Images

Urban modeling and visualization are highly useful in the development of smart cities. Buildings are the most prominent features in the urban environment, and are necessary for urban decision support; thus, buildings should be modeled effectively and efficiently in three dimensions (3D). In this study, with the help of Gaofen-7 (GF-7) high-resolution stereo mapping satellite double-line camera (DLC) images and multispectral (MUX) images, the boundary of a building is segmented via a multilevel features fusion network (MFFN). A digital surface model (DSM) is generated to obtain the elevation of buildings. The building vector with height information is processed using a 3D modeling tool to create a white building model. The building model, DSM, and multispectral fused image are then imported into the Unreal Engine 4 (UE4) to complete the urban scene level, vividly rendered with environmental effects for urban visualization. The results of this study show that high accuracy of 95.29% is achieved in building extraction using our proposed method. Based on the extracted building vector and elevation information from the DSM, building 3D models can be efficiently created in Level of Details 1 (LOD1). Finally, the urban scene is produced for realistic 3D visualization. This study shows that high-resolution stereo mapping satellite images are useful in 3D modeling for urban buildings and can support the generation and visualization of urban scenes in a large area for different applications.

UPDATES OF ‘AW3D30’ ALOS GLOBAL DIGITAL SURFACE MODEL IN ANTARCTICA WITH OTHER OPEN ACCESS DATASETS

Abstract. In 2016, the first processing of the semi-global digital surface models (DSMs) utilizing all the archives of stereo imageries derived from the Panchromatic Remote sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) was successfully completed. The dataset was freely released to the public in 30 m grid spacing as the ‘ALOS World 3D - 30m (AW3D30)’, which was generated from its original version processed in 5 m or 2.5 m grid spacing. The dataset has been updated since then to improve the absolute/relative height accuracies with additional calibrations. However, the most significant update that should be applied for improving the data usability is the filling of void areas, which correspond to approx. 10% of semiglobal coverage, mostly due to cloud covers. In 2020, we completed the filling process by using other open-access digital elevation models (DEMs) such as Shuttle Radar Topography Mission (SRTM) DEM, Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM), ArcticDEM, etc., except for Antarctica. In this paper, we report on the filling process of the remaining voids in Antarctica by using other open-access DEMs such as Reference Elevation Model of Antarctica (REMA) DSM, TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X, TDX) 90m DEM, and ASTER GDEM to complete the void-free semi-global AW3D30 datasets.

Imaging Attitude Control and Image Motion Compensation Residual Analysis Based on a Three-Axis Inertially Stabilized Platform

The airborne area camera has received broad application in aerial reconnaissance, land resource surveying, environmental monitoring, photogrammetry mapping, and natural disaster information acquisition. A three-axis, inertially stabilized platform with a large rotation range for the roll axis is designed, which is based on the cantilever structure, in order to realize a large-angle sweep imaging function for airborne area cameras. An image attitude control algorithm in the inertial space is proposed, which can regulate the line of sight (LOS) as well as the image orientation. The area camera image motion calculation model and image motion compensation residual computing method are proposed, utilizing space position and velocity vector transformation mathematics and derivations. The variation of linear velocity of the image motion in the sensor frame is analyzed, and the changing laws of the maximum deviation of image motion with the image attitude are studied. Flight tests imply that the vertical imaging technique correctly regulates the LOS along the local geodetic vertical. The along-flight overlap rate is greater than 65%, which meets the stereo mapping requirement. The sweep imaging technique considerably enlarges the cross-flight angle of view. The LOS and image orientation during sweep imaging are correctly controlled, and gap-free coverage of the survey area is maintained. The image’s azimuth or roll deviation is less than 0.1°, and the image pitch deviation is less than 0.35°. The quality of the test images is superior. Black and white line pairs for evaluation can be clearly distinguished. The image’s motion is well compensated, and the image motion compensation residual is well constrained. These verify the validity of the proposed imaging technique and the image motion analysis model.

An Optimal Image–Selection Algorithm for Large-Scale Stereoscopic Mapping of UAV Images

Recently, the mapping industry has been focusing on the possibility of large-scale mapping from unmanned aerial vehicles (UAVs) owing to advantages such as easy operation and cost reduction. In order to produce large-scale maps from UAV images, it is important to obtain precise orientation parameters as well as analyzing the sharpness of they themselves measured through image analysis. For this, various techniques have been developed and are included in most of the commercial UAV image processing software. For mapping, it is equally important to select images that can cover a region of interest (ROI) with the fewest possible images. Otherwise, to map the ROI, one may have to handle too many images, and commercial software does not provide information needed to select images, nor does it explicitly explain how to select images for mapping. For these reasons, stereo mapping of UAV images in particular is time consuming and costly. In order to solve these problems, this study proposes a method to select images intelligently. We can select a minimum number of image pairs to cover the ROI with the fewest possible images. We can also select optimal image pairs to cover the ROI with the most accurate stereo pairs. We group images by strips and generate the initial image pairs. We then apply an intelligent scheme to iteratively select optimal image pairs from the start to the end of an image strip. According to the results of the experiment, the number of images selected is greatly reduced by applying the proposed optimal image–composition algorithm. The selected image pairs produce a dense 3D point cloud over the ROI without any holes. For stereoscopic plotting, the selected image pairs were map the ROI successfully on a digital photogrammetric workstation (DPW) and a digital map covering the ROI is generated. The proposed method should contribute to time and cost reductions in UAV mapping.

Fluxional bis(phenoxy-imine) Zr and Ti catalysts for polymerization

Bis(phenoxy-imine) complexes of zirconium or titanium, a type of Fenokishi-Imin catalysts, allow the production of polyethylenes with well-defined bimodal molecular weight distributions. Interestingly, by substitution of phenyl rings in the bis(phenoxy-imine) ligands by perfluorinated phenyl rings, the polymerization reaches a desired unimodal behavior. These catalysts have three isomers of similar energy that can be easily interconverted. It is likely that the bimodal behavior is due to the coexistence of more than one isomer in the reaction vessel. Here, we perform static and dynamic DFT calculations to understand the isomerization of the catalytic active species. We analyze the relative Gibbs energies of the different isomers and the barriers for the isomerization processes. Further characterization of the isomers is obtained through stereo maps, aromaticity measures, and NCI plots. Our results show that by changing the phenyl group by a perfluorinated phenyl ring, one of the isomers is particularly stabilized, thus explaining the unimodal behavior of the polyethylene production process.

Coarse-to-Fine Image Matching-Based Footprint Camera Calibration of the GF-7 Satellite.

The GF-7 satellite is China’s first high-resolution stereo mapping satellite that reaches sub-meter resolution, equipped with new-type payloads, such as an area array footprint camera that can achieve synchronization acquisition of laser spots. When the satellite is in space, the variation of camera parameters may occur due to launch vibration and environmental changes, and on-orbit geometric calibration thereby must be made. Coupled with the data from the GF-7 satellite, this paper constructs a geometric imaging model of the area array footprint camera based on the two-dimensional direction angle, and proposes a coarse-to-fine “LPM-SIFT + Phase correlation” matching strategy for the automatic extraction of calibration control points. The single-image calibration experiment shows that the on-orbit geometric calibration model of the footprint camera constructed in this paper is correct and effective. The matching method proposed is used to register the footprint images with the DOM (Digital Orthophoto Map) reference data to obtain dense control points. Compared with the calibration result using a small number of manually collected control points, the root mean square error (RMSE) of the residual of the control points is improved from half a pixel to 1/3, and the RMSE of the same orbit checkpoints in the image space is improved from 1 pixel to 0.7. It can be concluded that using the coarse-to-fine image matching method proposed in this paper to extract control points can significantly improve the on-orbit calibration accuracy of the footprint camera on the GF-7 satellite.

A novel algorithm for space camera geometry parameters on-orbit calibration

The precision of geometry parameters is important for stereo mapping tasks. The current methods mainly by ground calibration field which exhibit disadvantages. Inspired by simplified method with laser reference beam we proposed in previous work, a novel on-orbit calibration method based on dual vector attitude determination algorithm is proposed, overcoming the limitation of previous methods. First, a single camera calibration model is established with the proposed method. Errors introduced by input parameters are then analyzed and expressed by simplified expressions. Furthermore, residual errors between the two algorithms are calculated. Finally, an experimental system with two-array cameras is set up in a vacuum chamber with well vibration isolation. The results show that the proposed method is well performance in real time with high accuracy. Moreover, the phenomenon of the periodic sinusoidal change of the angle between cameras in a circle is revealed, which is essential to stereo mapping tasks.