Wide Field Of View Camera Research Articles

Stratospheric Night Sky Imaging Payload for Space Situational Awareness (SSA).

Space situational awareness (SSA) refers to collecting, analyzing, and keeping track of detailed knowledge of resident space objects (RSOs) in the space environment. With the rapidly increasing number of objects in space, the need for SSA grows as well. Traditional methods rely heavily on imaging RSOs from large, narrow field-of-view (FOV), ground-based telescopes. This research outlines the technology demonstration payload, Resident Space Object Near-space Astrometric Research (RSONAR)-a star tracker-like, wide FOV camera combined with commercial off-the-shelf (COTS) hardware to image RSOs from the stratosphere, overcoming the disadvantages of ground-based observations. The hardware components and software algorithm are described and evaluated. The eligibility of the payload for SSA is proven by the image processing algorithms, which detect the RSOs in the images captured during flight and the survival of the COTS components in the near-space environment. The payload features a low-resolution, wide FOV camera coupled with a Field Programmable Gate Array (FPGA)-based platform that houses the altitude and time-based image capture algorithm. The newly developed payload in a 2U-CubeSat form factor was flown as a space-ready payload on the CSA/CNES stratospheric balloon research platform to carry out algorithm and functionality tests in August 2022.

Retrieval of aerosol optical depth from GF-6 wide field of view 16-m data based on deep blue algorithm

Aerosol optical depth (AOD) is an important indicator for air pollution monitoring. We obtain AOD from the GF-6 satellite, which was launched on June 2, 2018 by China. Beijing is selected as the study area. Based on the deep blue algorithm, the moderate-resolution imaging spectroradiometer surface reflectance product is used to correct and establish the surface reflectance library, and the AOD is retrieved from the GF-6 wide field of view (WFV) blue band. So, the application of the deep blue algorithm in a GF-6 WFV camera is realized. The aerosol is divided into three models: a custom model, a continental model, and an urban model in second simulation of the satellite signal in the solar spectrum model. To improve the accuracy of retrieval results, we recalculated the aerosol component concentration ratio based on GF-6 WFV data and ground observation as the custom model. The retrieval results of the three aerosol models show that the central and southern urban areas are higher than the mountainous areas in the northwest, indicating that human emission is the main source of air pollution in Beijing. The retrieval results of the custom model, continental model, and urban model are compared with the ground observation. The error of urban model retrieval is large, and the determination coefficient R2 is only 0.3671. The results of the custom model and continental model are similar. The R2 of the custom is 0.8942, which is higher than that of the continental (0.8872). We analyze the relationship between the retrieved AOD of the three aerosol models and top of atmosphere (TOA) reflectance and find that the custom AOD has the best sensitivity to TOA reflectance, whereas the urban AOD has the worst sensitivity. So, the custom aerosol model is closer to the real aerosol situation in Beijing.

Low-cost camera based sense and avoid in unmanned aerial vehicles: Sensing and control methods

Over the past two decades, unmanned aerial vehicles (UAVs) have attracted more and more attention because of their increasing applications in the military and civil sectors. Collision avoidance is a core problem in developing UAVs. In this paper, a low-cost camera based sense and avoid control scheme is proposed. First, for the unmanned aerial vehicle (UAV) sense and avoid problem, we propose and demonstrate a low cost solution with only one monocular, wide field of view camera. We adapted a deep learning based algorithm and made it lightweight enough to run on-board the UAV. We created a synthetic dataset to increase the size of the training data set. Second, we developed a filter to estimate the 3D position and velocity of the moving obstacle. Third, based on the estimated information, we adapted the velocity obstacle approach to work in 3D. Finally, we implemented the algorithms in the software framework of our UAV testbed and conducted flight tests, demonstrating the effectiveness of the solution.

Corner cases and limitations using a DOE based geometric camera calibration

Several years ago, the geometric calibration of cameras based on diffractive optical elements was invented, and since October 2020 the first product is commercially available.A laser beam is expanded, and the plane wave falls onto a diffractive optical element. The DOE generates a regular grid of light dots that virtually originates from infinity.This structure is then captured with the device under test and the dot positions are detected. From the positions, the required values can be calculated.The potential of the method, the compactness of the setup and the ease of use have brought up many desires that so far had not been addressed.Amongst these are: <list list-type="order"> <list-item>Calibration of extreme wide field of view cameras > 140°.</list-item> <list-item>Calibration of cameras/lens combinations with a large entrance pupil.</list-item> <list-item>Increased camera DOE distance to, e.g., measure cameras behind a windshield in automotive applications.</list-item> <list-item>Camera pairs with a stereo base significantly exceeding 60 mm.</list-item> <list-item>Deriving the point spread function of the system at every light dot to use the method for more than just distortion measurement, e.g., MTF determination or visualization.</list-item> </list>There are also a few limitations compared to the conventional methods: <list list-type="lower-alpha"> <list-item>Measurement at infinity only</list-item> <list-item>Stereo basis cannot be measured due to translation invariance of the method</list-item> <list-item>Determination of chromatic aberration</list-item> <list-item>Limited application of a single DOE (due to resolution of the camera and field of view)</list-item> </list>All these desires and limitations are discussed, and solutions are presented where possible.

Radiometric Cross-Calibration of the Wide Field View Camera Onboard GaoFen-6 in Multispectral Bands

GaoFen6 (GF-6), successfully launched on June 2, 2018, is the sixth satellite of the High-Definition Earth observation system (HDEOS). Although GF-6 is the first high-resolution satellite in China to achieve precise agricultural observation, it will be widely used in many other domains, such as land survey, natural resources management, emergency management, ecological environment and so on. The GF-6 was not equipped with an onboard calibration instrument, so on-orbit radiometric calibration is essential. This paper aimed at the on-orbit radiometric calibration of the wide field of view camera (WFV) onboard GF-6 (GF-6/WFV) in multispectral bands. Firstly, the radiometric capability of GF-6/WFV is evaluated compared with the Operational Land Imager (OLI) onboard Landsat-8, Multi Spectral Instrument (MSI) onboard Sentinel-2 and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra, which shows that GF-6/WFV has an obvious attenuation. Consequently, instead of vicarious calibration once a year, more frequent calibration is required to guarantee its radiometric consistency. The cross-calibration method based on the Badain Jaran Desert site using the bi-directional reflectance distribution function (BRDF) model calculated by Landsat-8/OLI and ZY-3/Three-Line Camera (TLC) data is subsequently applied to GF-6/WFV and much higher frequencies of calibration are achieved. Finally, the cross-calibration results are validated using the synchronized ground measurements at Dunhuang test site and the uncertainty of the proposed method is analyzed. The validation shows that the relative difference of cross-calibration is less than 5% and it is satisfied with the requirements of cross-calibration.

Parameters determination and sensor correction method based on virtual CMOS with distortion for the GaoFen6 WFV camera

The GaoFen6 (GF6) satellite is an optical remote sensing satellite in China’s GaoFen series that combines the imaging abilities of high resolution and wide field of view (WFV). The WFV camera, equipped on the GF6, can obtain an image 800 km in width and with a resolution of 16 m, which represents the highest level of observation swath width among similar satellites in the world. Guaranteeing the high geometric quality of the imagery obtained by the WFV camera for subsequent remote sensing applications is a prominent problem that must be solved. This paper presents the key geometry processing method for the WFV camera, in which the parameters relative determination method based on two selected reference bands and the sensor correction based on virtual collinear complementary metal oxide semiconductor (CMOS) with distortion are proposed. To overcome the challenge of matching the tie points between different bands with large radiation differences, two bands—rather than traditional one band—were chosen as the reference bands for the WFV camera to perform the parameters relative determination. The geometric influence of the virtual CMOS is fully analyzed in the along- and across-track directions. Then, the virtual CMOS with a real calibrated distortion was designed; based on this design, a sensor correction was applied to stitch the whole image generated by single images in each band. This experiment verified the effectiveness of the proposed parameters relative determination and sensor correction methods in improving the internal relative accuracy and the registration accuracy; moreover, the mosaicking accuracy is also guaranteed.

Real-Time 3D Motion Tracking and Reconstruction System Using Camera and IMU Sensors

Jointly using the data of visual and inertial sensors to achieve higher accuracy and robustness is a problem of high computational complexity. In this work, this paper presents a 3D motion tracking and reconstruction system on a mobile device using camera and inertial measurement unit (IMU) sensors. The mobile device has very small active infrared projection depth sensors with high-performance IMU and wide field of view cameras. We utilize visual-inertial odometry (VIO) to integrate visual and IMU data. However, traditional VIO method is too complex to apply to a mobile device with limited computing resources in real time. We employ sliding window filter (SWF) for the proposed system to achieve accurate 3D motion tracking and high-quality reconstruction models in real time based on delayed state marginalization. Moreover, we also extensively evaluate in the dataset and real world. Many experiments show the accurate trajectories and high quality 3D reconstruction models by the proposed system. To the end, the qualitative and quantitative experimental results indicate the proposed system based on SWF has much better performance than existing methods in motion tracking and 3D reconstruction models.

Combining Linear Pixel Unmixing and STARFM for Spatiotemporal Fusion of Gaofen-1 Wide Field of View Imagery and MODIS Imagery

Spatiotemporal fusion of remote sensing data is essential for generating high spatial and temporal resolution data by taking advantage of high spatial resolution and high temporal resolution imageries. At present, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is one of the most widely used spatiotemporal fusion technologies of remote sensing data. However, the quality of data acquired by STARFM depends on temporal information from homogeneous land cover patches at the MODIS (Moderate Resolution Imaging Spectroradiometer) imagery, and the estimation accuracy of STARFM degrades in highly fragmentated and heterogeneous patches. To address this problem, we developed an innovative method to improve fusion accuracy, especially in areas of high heterogeneity, by combining linear pixel unmixing and STARFM. This method derived the input data of STARFM by downscaling the MODIS data with a linear spectral mixture model. Through this fusion method, the complement effect of the advantages of remote sensing information can be realized, and the multi-source remote sensing data can be realized for visual data mining. The developed fusion method was applied in Bosten Lake, the largest freshwater lake in China, and our analysis of results suggests that (1) after introducing the linear spectral mixture model, the fusion images illustrated improved spatial details to a certain extent and can be employed to identify small objects, as well as their texture distribution information; (2) for fragmented and highly heterogeneous areas, a stronger correlation between the predicted results and the real images was observed when compared to STARFM with small bias; and (3) the predicted red band and near infrared band can generate high-precision 16-m NDVI (Normalized Difference Vegetation Index) data with advantages in both spatial resolution and temporal resolution. The results are generally consistent with the Gaofen-1 wide field of view cameras (GF-1 WFV) NDVI in the same period and therefore can reflect the spatial distribution of NDVI in detail.

On-Orbit Radiometric Calibration for a Space-Borne Multi-Camera Mosaic Imaging Sensor

As the core and foundational technology, on-orbit radiometric calibration of a space-borne sensor is of great importance for quantitative remote sensing applications. As for the space-borne multi-camera mosaic imaging sensor, however, the currently available on-orbit radiometric calibration method cannot carry out the integrated processing of on-orbit absolute radiometric calibration and relative radiometric correction simultaneously between cameras, influencing the accuracy of quantitative applications. Therefore, taking the GaoFen-1 (GF-1) wide-field-of-view (WFV) sensor as an example in this research, an innovative on-orbit radiometric calibration method is proposed to overcome this bottleneck. Firstly, according to the principle of the cross-calibration approach, we retrieve valid MODIS and GF-1 WFV image pairs over the Dunhuang radiometric calibration sites (DRCS) in China by using a set of criteria and extract the radiometric control points (RCPs) connecting in both images. Secondly, the DEM-aided block adjustment of the rational function model is applied to eliminate the geometrical misalignment of GF-1 WFV images at the same orbit. Then, the average digital numbers of spectral and spatial homogeneous surfaces are calculated and chosen as the radiometric tie points (RTPs) extracted from the overlapping region of the adjacent WFV cameras. Thirdly, the radiometric block adjustment (RBA) algorithm is introduced into on-orbit radiometric calibration of the space-borne multi-camera mosaic imaging sensor. Finally, the radiometric calibration coefficients are solved by the least square method. The validation results indicate that our proposed method can acquire high absolute radiometric calibration accuracy and achieve relative radiometric correction between cameras. Compared with the results using the cross-calibration method to calibrate each WFV camera independently, the advantages of RBA are presented. In addition, the uncertainties caused by RCPs’ distribution are discussed, which is beneficial to further optimize the calibration program.

A new image mosaicking approach for the multiple camera system of the optical remote sensing satellite GaoFen1

ABSTRACTThe GaoFen1 (GF1) optical remote sensing satellite is the first in China’s series of high-resolution civilian satellites and is equipped with four wide field of view (WFV) cameras. High accuracy image mosaicking depends on the geometrical quality of the stitched satellite imagery. This letter proposes a high accuracy image mosaicking approach based on combining multiple WFV cameras into a big virtual camera (BVC). In this method, a BVC is created according to the rigorous imaging model of a single camera, from which a final stitched image and corresponding high accuracy rational function model (RFM) can be obtained simultaneously. WFV images from GF1 and reference digital elevation models from ZiYuan3 are used to validate the proposed method. The experimental results validate that seamless mosaicking can be achieved directly from the geometrical relationship of the imaging model of the BVC and WFV camera. The proposed method is able to maintain the absolute and relative internal positioning accuracy of the original images.

Phenology-based Spartina alterniflora mapping in coastal wetland of the Yangtze Estuary using time series of GaoFen satellite no. 1 wide field of view imagery

Spartina alterniflora is an aggressive invasive plant species that replaces native species, changes the structure and function of the ecosystem across coastal wetlands in China, and is thus a major conservation concern. Mapping the spread of its invasion is a necessary first step for the implementation of effective ecological management strategies. The performance of a phenology-based approach for S. alterniflora mapping is explored in the coastal wetland of the Yangtze Estuary using a time series of GaoFen satellite no. 1 wide field of view camera (GF-1 WFV) imagery. First, a time series of the normalized difference vegetation index (NDVI) was constructed to evaluate the phenology of S. alterniflora. Two phenological stages (the senescence stage from November to mid-December and the green-up stage from late April to May) were determined as important for S. alterniflora detection in the study area based on NDVI temporal profiles, spectral reflectance curves of S. alterniflora and its coexistent species, and field surveys. Three phenology feature sets representing three major phenology-based detection strategies were then compared to map S. alterniflora: (1) the single-date imagery acquired within the optimal phenological window, (2) the multitemporal imagery, including four images from the two important phenological windows, and (3) the monthly NDVI time series imagery. Support vector machines and maximum likelihood classifiers were applied on each phenology feature set at different training sample sizes. For all phenology feature sets, the overall results were produced consistently with high mapping accuracies under sufficient training samples sizes, although significantly improved classification accuracies (10%) were obtained when the monthly NDVI time series imagery was employed. The optimal single-date imagery had the lowest accuracies of all detection strategies. The multitemporal analysis demonstrated little reduction in the overall accuracy compared with the use of monthly NDVI time series imagery. These results show the importance of considering the phenological stage for image selection for mapping S. alterniflora using GF-1 WFV imagery. Furthermore, in light of the better tradeoff between the number of images and classification accuracy when using multitemporal GF-1 WFV imagery, we suggest using multitemporal imagery acquired at appropriate phenological windows for S. alterniflora mapping at regional scales.

Robustness of an artificially tailored fisheye imaging system with a curvilinear image surface

Curved image sensors inspired by animal and insect eyes have provided a new development direction in next-generation digital cameras. It is known that natural fish eyes afford an extremely wide field of view (FOV) imaging due to the geometrical properties of the spherical lens and hemispherical retina. However, its inherent drawbacks, such as the low off-axis illumination and the fabrication difficulty of a ‘dome-like’ hemispherical imager, limit the development of bio-inspired wide FOV cameras. Here, a new type of fisheye imaging system is introduced that has simple lens configurations with a curvilinear image surface, while maintaining high off-axis illumination and a wide FOV. Moreover, through comparisons with commercial conventional fisheye designs, it is determined that the volume and required number of optical elements of the proposed design is practical while capturing the fundamental optical performances. Detailed design guidelines for tailoring the proposed optic system are also discussed.

Angle of sky light polarization derived from digital images of the sky under various conditions.

Skylight polarization is used for navigation by some birds and insects. Skylight polarization also has potential for human navigation applications. Its advantages include relative immunity from interference and the absence of error accumulation over time. However, there are presently few examples of practical applications for polarization navigation technology. The main reason is its weak robustness during cloudy weather conditions. In this paper, the real-time measurement of the sky light polarization pattern across the sky has been achieved with a wide field of view camera. The images were processed under a new reference coordinate system to clearly display the symmetrical distribution of angle of polarization with respect to the solar meridian. A new algorithm for the extraction of the image axis of symmetry is proposed, in which the real-time azimuth angle between the camera and the solar meridian is accurately calculated. Our experimental results under different weather conditions show that polarization navigation has high accuracy, is strongly robust, and performs well during fog and haze, clouds, and strong sunlight.

Radiometric cross Calibration of Gaofen-1 WFV Cameras Using Landsat-8 OLI Images: A Simple Image-Based Method

WFV (Wide Field of View) cameras on-board Gaofen-1 satellite (gaofen means high resolution) provide unparalleled global observations with both high spatial and high temporal resolutions. However, the accuracy of the radiometric calibration remains unknown. Using an improved cross calibration method, the WFV cameras were re-calibrated with well-calibrated Landsat-8 OLI (Operational Land Imager) data as reference. An objective method was proposed to guarantee the homogeneity and sufficient dynamic coverage for calibration sites and reference sensors. The USGS spectral library was used to match the most appropriate hyperspectral data, based on which the spectral band differences between WFV and OLI were adjusted. The TOA (top-of-atmosphere) reflectance of the cross-calibrated WFV agreed very well with that of OLI, with the mean differences between the two sensors less than 5% for most of the reflectance ranges of the four spectral bands, after accounting for the spectral band difference between the two sensors. Given the calibration error of 3% for Landsat-8 OLI TOA reflectance, the uncertainty of the newly-calibrated WFV should be within 8%. The newly generated calibration coefficients established confidence when using Gaofen-1 WFV observations for their further quantitative applications, and the proposed simple cross calibration method here could be easily extended to other operational or planned satellite missions.

MTF Measurements of Wide Field of View Cameras

In this paper we present an algorithm for estimating camera system modulation transfer functions (MTF) from highly distorted images. This algorithm estimates multiple oversampled line spread functions using different order polynomials and binning. The ensemble of oversampled line spread functions (LSF) are used to estimate the final system MTF. Moreover, the LSF derived from the highest order polynomial without overfitting is used to estimate the system MTF. We show the performance of this algorithm on synthetically generated images and on image captures from a commercially available camera. We compare this algorithm to the ISO 12233 standard.

Radiometric cross-calibration of Gaofen-1 WFV cameras using Landsat-8 OLI images: A solution for large view angle associated problems

Abstract Four wide-field-of-view (WFV) instruments are onboard the Gaofen-1 (or GF-1) satellite, providing a combined swath of ~ 800 km. However, observations with large view angles pose new challenges for radiometric cross-calibration with a simple image-based method when using Landsat-8 Operational Land Imager (OLI) data as a reference. Based on radiative transfer modeling, a novel radiometric cross-calibration method has been proposed in this study to solve large view angle-associated problems. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products were used to simulate the top of atmosphere (TOA) signal of the reference and target instruments, and the unequal bidirectional effects were corrected using MODIS bi-directional reflectance distribution function (BRDF) products. Extensive validations with both satellite data and in situ measurements revealed an uncertainty of ~ 8% for the newly produced cross-calibration coefficients when they were used to calibrate TOA reflectance for both close-nadir and off-nadir instruments. The improvements are discernable when compared with the official provided coefficients and that were derived using the image-based cross-calibration method. This study demonstrated not only the usefulness of Landsat-8 OLI data in sensor radiometric calibration but also the impressive accuracy of the MODIS BRDF and aerosol products in radiative transfer simulations. The proposed method can be used in the future to monitor and correct potential radiometric degradations of the GF-1 WFV instruments, and it also can be easily extended to other similar satellite missions to conduct radiometric cross-calibrations.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring.

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA.

Polarized Imaging Nephelometer for in situ airborne measurements of aerosol light scattering.

Global satellite remote sensing of aerosols requires in situ measurements to enable the calibration and validation of algorithms. In order to improve our understanding of light scattering by aerosol particles, and to enable routine in situ airborne measurements of aerosol light scattering, we have developed an instrument, called the Polarized Imaging Nephelometer (PI-Neph). We designed and built the PI-Neph at the Laboratory for Aerosols, Clouds and Optics (LACO) of the University of Maryland, Baltimore County (UMBC). This portable instrument directly measures the ambient scattering coefficient and phase matrix elements of aerosols, in the field or onboard an aircraft. The measured phase matrix elements are the P(11), phase function, and P(12). Lasers illuminate the sampled ambient air and aerosol, and a wide field of view camera detects scattered light in a scattering angle range of 3° to 176°. The PI-Neph measures an ensemble of particles, supplying the relevant quantity for satellite remote sensing, as opposed to particle-by-particle measurements that have other applications. Comparisons with remote sensing measurements will have to consider aircraft inlet effects. The PI-Neph first measured at a laser wavelength of 532nm, and was first deployed successfully in 2011 aboard the B200 aircraft of NASA Langley during the Development and Evaluation of satellite ValidatiOn Tools by Experimenters (DEVOTE) project. In 2013, we upgraded the PI-Neph to measure at 473nm, 532nm, and 671nm nearly simultaneously. LACO has deployed the PI-Neph on a number of airborne field campaigns aboard three different NASA aircraft. This paper describes the PI-Neph measurement approach and validation by comparing measurements of artificial spherical aerosols with Mie theory. We provide estimates of calibration uncertainties, which show agreement with the small residuals between measurements of P(11) and -P(12)/P(11) and Mie theory. We demonstrate the capability of the PI-Neph to measure ambient aerosol with two data sets from the Deep Convective Clouds and Chemistry (DC3) field campaign, from flights over Colorado in June 2012.

Photometric visual servoing for omnidirectional cameras

2D visual servoing consists in using data provided by a vision sensor for controlling the motions of a dynamic system. Most of visual servoing approaches has relied on the geometric features that have to be tracked and matched in the image acquired by the camera. Recent works have highlighted the interest of taking into account the photometric information of the entire image. This approach was tackled with images of perspective cameras. We propose, in this paper, to extend this technique to central cameras. This generalization allows to apply this kind of method to catadioptric cameras and wide field of view cameras. Several experiments have been successfully done with a fisheye camera in order to control a 6 degrees of freedom robot and with a catadioptric camera for a mobile robot navigation task.

The Method of Measurements of Celestial Coordinates in Wide-Field TV-Frames

We present a method for calculations of equatorial coordinates of any point in the single frame of the wide-field TV systems. This method can be applying for the different television systems [wide-field cameras, all-sky cameras, the cameras with the hybrid TV-system (the system with coupled of the Image Intensifier) et al.]. In that system the calculations of distortions are difficult. Therefore, we devised this method which helps decrease errors (due to distortion and the electro-optical system).The method can be used for measuring of equatorial coordinates of meteor tracks under difficult conditions during the observations such as partial cloudiness, small number of stars and large distortions of the coordinate grid in the frame. These restrictions cannot be overcome by other methods. In the case of the small number of stars the present method using of the reference stars received on a series of frames during the observation period. The accuracy of the method has been estimated to be 4′–8′ (for cameras with fov 50° × 40° at the CCD 720 × 576 pixels) for maximum number of reference points in the frame. The method used 3 reference points for calculation of the equatorial coordinates of the object. One can use this method if the camera was re-oriented as well. We use this method for our wide field of view cameras.