833 results about "Sky" patented technology

A system includes a plurality of satellites orbiting around a celestial body in a plurality of orbital planes. Each satellite includes an imaging device having a field of view (FOV) to capture an image of a sky that includes celestial image features of resident space object (RSO), stars, and / or planets. The satellite processor is configured to input the image data for each image into a pre-processing software pipeline to generate for each image a contrast-enhanced image data replica of each image, and an enhanced image data replica of each image, to receive from an output of a known-unknown RSO split data processing pipeline, a determination that a candidate RSO is a known RSO stored in an RSO catalog, or an unknown RSO, and to assign to the candidate RSO based on the determination, an RSO ID of the known RSO listed in the RSO catalog, or a new RSO ID.

The invention provides a small and medium-sized reservoir operation safety evaluation system based on sky-ground work, and belongs to the technical field of hydrological monitoring. The device comprises a space-time alignment layer, a feature weighting layer and a dynamic coupling layer which are connected in sequence, the space-time alignment layer is used for performing time alignment and space alignment on the input data of the sky-land water conservancy project; the feature weighting layer is used for quantifying contribution degrees of different monitoring features to safety assessment according to the data after time-space alignment; and the dynamic coupling layer adopts a dynamic weight distribution strategy for different modules through a multi-module coordination engine, fuses feature weighting to obtain a fusion result, and outputs a small and medium-sized reservoir operation safety index according to the fusion result. The evaluation result is more accurate, and the timeliness is better.

The invention discloses a land-sea-air-space holographic sensing and collaborative decision-making system based on multi-mode edge intelligence. The system comprises a sensing layer which is used for carrying out three-dimensional monitoring on a ship driving process, the sea, the sky, a shore base and a space formed by the ship driving process, the sea, the sky, the shore base and the sea, the sky and the shore base; the network layer is used for constructing a global communication basis, preprocessing monitoring data, judging whether the ship has an abnormal condition or not, and realizing data transmission of the ocean, the sky, a shore base and a space formed by the ocean, the sky and the shore base; and the application layer is used for judging whether an abnormal condition exists in the ship driving process or not based on the data of the ocean, the sky, the shore base and the space formed by the ocean, the sky and the shore base transmitted by the network layer, performing collision early warning decision based on the abnormal condition, and performing dynamic channel capacity prediction. And navigation guidance and route tracking in extreme weather are carried out based on environmental risk early warning, underwater obstacle collision is avoided, and early warning information and decision information are fed back to a sensing layer.

The invention discloses a photovoltaic ultra-short-term power prediction method and system based on multi-modal information fusion, and belongs to the technical field of photovoltaic power generation prediction. The method comprises the steps: obtaining an all-sky image sequence, segmenting a cloud layer and a sky region, and extracting cloud layer boundary features; thickness features are analyzed by calculating cloud pixel point brightness indexes, overall motion features of a cloud layer are determined based on adjacent frame displacement vectors, a time sequence sub-image covering a sun area in the future is reversely captured in combination with sun position coordinates, and then time sequence features and image features are extracted by adopting a dual-channel fusion mechanism. And finally, introducing a weather-dependent decoder: identifying weather types through a lightweight classifier, dynamically weighting the fused features based on the types, and outputting a photovoltaic power prediction result. According to the invention, through a multi-scale feature cooperation and dynamic weighting mechanism, the prediction robustness under a complex meteorological condition is significantly improved.

The invention discloses a multi-modal photovoltaic power prediction method based on double-layer Transform, and the method comprises the steps: firstly carrying out the preprocessing of a sky image and historical meteorological data, and carrying out the similar day selection based on dynamic time warping and k-means clustering, so as to construct a historical data set similar to the current meteorological condition; inputting the sky image into a double-layer Transform structure, extracting spatial features and time features in a layered manner, and extracting meteorological features from historical meteorological data by using expansion convolution; and performing interactive fusion on the multi-source features through a cross-modal attention mechanism, and enhancing a global dependency relationship in combination with self-attention to obtain a multi-modal prediction result. And on the other hand, a photovoltaic power sequence is separated from historical meteorological data, a single-factor prediction result is generated by using a long short-term memory (LSTM) network, dynamic weighted fusion is performed on the two types of prediction results through adaptive gating, and a final photovoltaic power prediction value is output.

A system includes a plurality of satellites orbiting around a celestial body in a plurality of orbital planes. Each satellite includes an imaging device having a field of view (FOV) to capture an image of a sky that includes celestial image features of resident space object (RSO), stars, and / or planets. The satellite processor is configured to input the image data for each image into a pre-processing software pipeline to generate for each image a contrast-enhanced image data replica of each image, and an enhanced image data replica of each image, to receive from an output of a known-unknown RSO split data processing pipeline, a determination that a candidate RSO is a known RSO stored in an RSO catalog, or an unknown RSO, and to assign to the candidate RSO based on the determination, an RSO ID of the known RSO listed in the RSO catalog, or a new RSO ID.

The invention discloses a global enhancement method for a wide-area astronomical image. The method comprises the following steps: carrying out high-frame-frequency image acquisition on a starry sky area; converting the reference star from a star catalogue position to an observation position, and resolving a linear negative film model; geometric distortion correction is carried out based on the resolving result; based on the image after geometric distortion correction, matching and identifying a reference star in a full view field, and obtaining celestial coordinate information of all fixed star images in the view field; on the basis of celestial coordinate information, correcting a poorer astronomical effect of the astronomical image, establishing an ideal coordinate system taking the center of a view field as a tangency point, and projecting a time sequence observation image to the ideal coordinate system; translating the processed graph, accumulating all translated images, and averaging all accumulated pixel positions to realize image superposition enhancement, thereby effectively improving the dynamic range of a detector and the detection capability of a wide-area astronomical observation system; and meanwhile, the signal-to-noise ratio of the astronomical image can be effectively improved, and the astronomical image centering and light measuring precision can be further improved.

The invention relates to the technical field of weather forecast, discloses a method for classifying severe convection weather forecast, and aims to solve the problem that complexity of severe convection weather requires multi-dimensional data support, so that a three-dimensional data acquisition network covering'ground-air-sky 'needs to be constructed. Ground observation data need to include minute-level rainfall, hourly air temperature and humidity (emphatically paying attention to humidity difference between 850hPa and 500hPa and reflecting unstable stratification) and 10-minute average wind speed of a meteorological station, and high-altitude detection data need to extract temperature vertical profiles (calculating convective condensation height LCL) and wind speed vertical shear (shear values of 0-3km and 0-6km) at 08 o'clock and 20 o'clock every day. According to the method for classifying severe convection weather forecast, new signals (such as sudden cloud top brightness temperature drop) observed in real time are rapidly absorbed, and meanwhile, the method is adaptive to severe convection characteristic differences of different areas (such as mountainous areas and plains) and different seasons, so that the forecast precision is improved, and the requirements of refined disaster prevention for high-accuracy and high-timeliness forecast are met.

The invention discloses a data assimilation method for infrared hyperspectral data of a clear sky channel. The data assimilation method comprises the following steps: acquiring the infrared hyperspectral data of the clear sky channel; a linear or non-linear relationship to convert variables from a mode space to an observation space using a fast radiation transfer mode; satellite infrared hyperspectral atmospheric vertical detection data channel screening is carried out in combination with a principal component method; a channel which is not influenced by cloud pollution is searched by observing the difference between the brightness temperature observed by the infrared and the brightness temperature simulated by the background field; eliminating the statistical deviation between the radiation value observed by the satellite instrument and the radiation value simulated and calculated according to the background field profile; eliminating observation data with errors exceeding a preset threshold value on the mixed earth surface type; and outputting a data assimilation result of the infrared hyperspectral data of the clear sky channel. Analysis fields of all layers of the global atmosphere are improved, the numerical forecasting level is effectively improved, typhoon forecasting intensity errors are remarkably improved, and path errors before landing are superior to conventional observation data tests.

The invention discloses a large-range high-frequency all-sky earth surface solar irradiance machine learning estimation method and system suitable for a cloudy area, and relates to the technical field of irradiance estimation, and the method comprises the steps: obtaining earth surface radiation observation data, generating a station position table, and constructing a training data set; constructing a ground solar radiation degree model, and dividing the training data set into a training set and a test set according to a proportion of 80% to 20%; determining hyper-parameters of the Xgboost algorithm through parameter search, training the model on the training set, and checking the model by using the test set; new satellite reflectivity is used for observing data and meteorological elements, data cleaning is carried out, and the model is input to estimate the space-time distribution of the total solar radiation irradiance of the earth surface. According to the method, the space and time precision of radiation inversion is improved, the complex nonlinear characteristics and data interaction relation are accurately captured, efficient inversion of the earth surface solar radiation degree is achieved, and the prediction performance and generalization ability of the model are remarkably improved.

The invention discloses a sky-ground integrated sunlight-induced vegetation chlorophyll fluorescence monitoring system, and belongs to the technical field of remote sensing monitoring. The system provides functions, parameter constraints and cooperation relations of space-based, empty-based and foundation chlorophyll fluorescence information acquisition and data analysis processing and application modules. Spatial scale matching, spectral scale matching, observation angle matching and atmospheric element matching are performed on the acquired sky-ground multi-element data with different scales, so that reflection characteristics, heat dissipation, photochemical indexes, fluorescence emission and atmospheric transmission characteristics during vegetation photosynthesis can be completely acquired; the invention provides a parameter relation and a method for extracting a fluorescence full-spectrum radiation information curve based on oxygen absorption and Fraunhofer dark line. On the basis of sky and landmark calibration and model verification, chlorophyll fluorescence detection of different fineness degrees of global large-range, key areas and ground crown planting scales can be carried out, various stress effects of vegetation can be monitored in real time, and the primary total productivity of the vegetation can be accurately estimated.

The present invention discloses an apparatus for quickly finding a planet by using a mobile phone, including: a digital telescope, an electronic compass, a pan / tilt configured to install the digital telescope, a mobile phone, a PC terminal, and a data converter. The digital telescope includes a telescope housing. A main camera configured to photograph target starry sky and a planet-finding camera configured to search for and photograph a target planet are disposed at one end that is of the telescope housing and that faces starry sky. The present invention is used more easily when a user's professional level is reduced.

The invention discloses an attention pyramid network-based all-sky cloud picture detection and classification method, and aims to solve the problems of accuracy and efficiency of an existing cloud detection technology in processing multi-cloud layer coverage, cloud type diversity and dynamic cloud layer change. According to the method, a deep learning technology and an advanced attention mechanism are utilized, and a pyramid space pooling (PSP) module and a convolutional block attention module (CBAM) are combined, so that the recognition and classification capability of cloud features is effectively improved. By applying the method, various cloud types including but not limited to cirrus cloud, layer cloud, cumulus cloud and the like can be accurately identified and classified in the all-sky cloud picture, and more accurate data support is provided for meteorological monitoring and climate research. The method has the advantages of being high in precision, high in efficiency, high in adaptability and the like, cloud detection and classification performance can be remarkably improved, and the method is particularly suitable for meteorological analysis under complex weather conditions.

The invention relates to the technical field of GNSS observation environment evaluation, in particular to a GNSS observation environment complexity measurement method, device and equipment and a medium, and the method comprises the steps: obtaining a sky image of a target area through a fisheye camera, and carrying out the recognition of the sky image through an image processing algorithm, and obtaining a sky recognition result; calculating trajectories of all satellites based on almanac information, and obtaining an openness index of the target region in combination with a sky recognition result; gNSS observation data are obtained, and a quality index is calculated according to the GNSS observation data; and combining the openness index with the quality index through a gradient lifting regression algorithm, predicting the calculation precision, and converting the predicted calculation precision into environment complexity. According to the GNSS observation environment evaluation method, the machine learning algorithm is combined with the sky view and the data quality index, the evaluation accuracy of the GNSS observation environment under the complex environment is improved, and the GNSS observation environment evaluation method is suitable for GNSS observation environment evaluation under various complex terrain conditions.

A system includes a plurality of satellites orbiting around a celestial body in a plurality of orbital planes. Each satellite includes an imaging device having a field of view (FOV) to capture an image of a sky that includes celestial image features of resident space object (RSO), stars, and / or planets. The satellite processor is configured to input the image data for each image into a pre-processing software pipeline to generate for each image a contrast-enhanced image data replica of each image, and an enhanced image data replica of each image, to receive from an output of a known-unknown RSO split data processing pipeline, a determination that a candidate RSO is a known RSO stored in an RSO catalog, or an unknown RSO, and to assign to the candidate RSO based on the determination, an RSO ID of the known RSO listed in the RSO catalog, or a new RSO ID.

The invention discloses a sky polarization navigation system and method suitable for a marine environment, and belongs to the technical field of navigation. In the system, a gyrostabilized platform is fixed on the ground of a ship body, a DOFP polarization imager is detachably assembled on the gyrostabilized platform, a fisheye lens is installed at the front end of the DOFP polarization imager, and a band-pass filter is arranged in a C-mount interface of the DOFP polarization imager and located behind a light outlet of the fisheye lens. The system is used for capturing a real-time sky polarization mode image, calculating a polarization degree DOP value, a polarization angle AOP value and a DOP gradient value, identifying an output neutral point position based on a calculation result, and performing sun meridian detection and extraction on the AOP image converted to an incident light coordinate system; and determining the course angle of the carrier based on the extracted neutral point position and the sun meridian. According to the invention, real-time and high-precision polarization mode measurement and course angle calculation are realized.

The invention provides a parameter acquisition method of a photovoltaic tracking system, which comprises the following steps of: acquiring longitude and latitude, time and date of a device installation place by using GPS (Global Positioning System) positioning, and describing the relative position of the sun through a sun-oriented movement trajectory tracking algorithm; calculating a tracking angle at which the camera should rotate by using the known relative position of the sun and the direction vector and the position vector of the tracking camera; the camera is driven to rotate to a theoretical angle, and then position tracking of the sun is achieved through the angle sensor; in the tracking process, eight-quadrant illumination intensity data is collected through a self-adaptive weight distribution algorithm model. According to the invention, real-time tracking of the sun is realized, and effective picture data acquisition work for the sun area in the sky is completed. The illumination intensity value calculated by using the adaptive weight distribution algorithm model can reduce the influence of the external environment on the data to a certain extent, balance the error and deviation between the sensors, and finally improve the measurement precision of the illumination intensity.

The invention belongs to the technical field of inertial navigation, relates to a high-precision calibration method for residual drift of a rotation modulation inertial navigation system, and is suitable for a long-endurance flight environment of an aircraft. According to the method, a mathematical model of the longitude and latitude navigation error of the rotary inertial navigation geographical system and the sky-direction residual drift, the north-direction residual drift and the sky-direction mathematical platform error angle of the geographical system is established, and the long-endurance navigation test of eight positions at the azimuth angle interval of 0-360 degrees and 45 degrees is designed; accurate identification of sky-direction and north-direction residual drifts and alignment course errors in different directions is realized. The method has the advantages of high residual drift identification precision, obvious improvement of long-endurance navigation performance, strong autonomy and easy realization.

The invention belongs to the technical field of sea fog monitoring, and particularly relates to a sea fog monitoring method and system based on multi-source satellite remote sensing data, and the method comprises the steps: collecting satellite radiation and microwave observation data, discriminating the cloud top phase state in combination with infrared ground microwave channel response differences, dividing clear sky and low cloud shielding scenes, and outputting identification data. And sea fog is detected in combination with the single-time infrared brightness temperature difference and the empty pixel parameters, optical parameters are inverted, and a sub-scene sea fog physical parameter set is formed. Carrying out normalized coupling reconstruction on the parameter set, constructing a sea fog exclusive feature space, separating a fog region from a non-fog region through phase state constraint to obtain an initial judgment feature field, correcting the edge of the fog region through neighborhood correlation and brightness temperature gradient constraint, strengthening spatial continuity to generate a spatial distribution field, locking a credible region, and outputting a final sea fog detection result. According to the invention, through layer-by-layer progressive design of scene division, feature optimization and multi-source verification, the precision and integrity of sea fog identification are significantly improved.

The invention relates to the technical field of wind power generation equipment monitoring, in particular to a draught fan tower footing settlement monitoring method and system based on Beidou high-precision positioning, and the method comprises the steps: S1, setting at least three positioning points below a draught fan tower footing, and installing a Beidou positioning instrument; s2, acquiring longitude and latitude height coordinates of the positioning point, and converting the longitude and latitude height coordinates into earth-centered earth-fixed coordinates; s3, converting the earth-centered earth-fixed coordinate into an east-north-sky coordinate; s4, drawing a monitoring space plane in the three-dimensional space by using the east-north-sky coordinates, and calculating geometric features of the monitoring space plane; s5, building a tower footing position state model based on geometric features of the monitoring space plane; and S6, repeating the steps S2 to S5, and judging whether the tower footing is settled or not and judging the settlement degree by comparing the front and back changes of the tower footing position state model. According to the method disclosed by the invention, millimeter-level monitoring on the settlement of the tower footing of the fan is realized by utilizing the high-precision positioning capability of the Beidou satellite navigation system.

The invention discloses an atmosphere and ocean integrated atmosphere temperature and humidity profile inversion method based on multiple sources and multiple frequency bands. The method comprises the following steps: S1, acquiring multi-source collaborative observation data, and preprocessing the acquired data; s2, constructing an integrated state vector and coupling forward model, and obtaining an integrated state vector X; s3, performing optimal estimation based on the preprocessed data and the integrated state vector X, and performing joint inversion to realize integrated inversion solution; and S4, outputting an inversion result and theoretical uncertainty output. According to the method, integrated cooperative inversion is carried out through a physical model and an optimal estimation theory, and the inversion precision of the atmosphere temperature and humidity profile in the clear sky and in the presence of clouds, especially in the air above the ocean, is remarkably improved.

The invention discloses a method and a system for measuring gravitational potential by a satellite-air-ground optical clock time-frequency comparison system. According to the method for measuring the gravitational potential, an optical clock superior to 110-18 orders of magnitude serves as the basis, a free space time-frequency comparison link based on an optical frequency comb serves as a bridge, the optical clocks among the satellite, the air and the ground are connected, high-precision time-frequency transmission is carried out, a gravity frequency shift signal is accurately extracted through time-frequency comparison of a remote clock, and the gravitational potential is measured. And then the gravity potential difference of the position where the remote clock is located is obtained by using a gravity frequency shift equation, and the gravity potential difference between air and ground or between any ground stations is determined.

The invention relates to a method for verifying a Mars sky radiance simulation result based on a Mars real-shot photo, and belongs to the technical field of Mars sky background radiance. Comprises: image acquisition; performing radiation calibration; correcting dark current; performing flat field correction; converting a radiation value; and geometric correction. The Mars sky radiance simulation method breaks through the dependence of an existing model on idealized hypothesis, performs dynamic verification by using actual shot image data, remarkably improves the authenticity and reliability of a Mars sky radiance simulation result, and effectively solves the problem of systematic deviation under a specific wave band; by constructing a complete process from image acquisition, radiation calibration, geometric modeling to brightness inversion and comparison verification, dynamic feedback and closed-loop correction of a theoretical radiation model are realized, model adaptability is improved, and fine modeling under multi-temporal and multi-meteorological conditions is supported; the method can be applied to an existing Mars rover navigation camera and an image processing link of the Mars rover navigation camera, does not need additional modification, has good engineering practicability and task compatibility, and is convenient to popularize and apply.

A method for spatial reconstruction and downscaling of all-sky surface temperature belongs to the field of remote sensing science and technology. It contains the following main steps: acquisition and preprocessing of multi-source remote sensing data and atmospheric driven data, spatial reconstruction of all-sky surface temperature data, and spatial downscaling of all-sky surface temperature data. The operability and universality of the present invention in practical applications will promote the popularization and application of surface temperature data in the fields of climate change, dynamic monitoring and assessment of hydrological and ecological environment, land surface radiation budget and energy balance, and further promote the development of thermal infrared remote sensing science.

The invention discloses a background spectrum accurate acquisition method for infrared remote measurement in a complex scene, and the method comprises the steps: carrying out the division of sky and ground object backgrounds for an input background image, and selecting different radiation spectrum generation modes based on a division result; if yes, sky radiation spectrum extraction is carried out based on an MODTRAN radiation transfer model; if the background is judged to be a single ground object background, performing background spectrum extraction by adopting ELM-EMD (Extreme Learning Mode-Empirical Mode Decomposition) which is extracted in real time based on a measurement spectrum and changes slowly at low frequency; and if the background is not single, fusion of the two spectrum extraction modes is adopted. The method has the advantages that the background classification method with the visible image as the reference is adopted, the difference of infrared radiation characteristics of the sky background and the ground feature background is analyzed, different spectrum extraction modes are selected according to the difference, and therefore accurate obtaining of the target smoke plume transmittance spectrum is achieved.

1. The name of this design product: Starry Sky Lamp (Astronaut). 2. Purpose of this design product: for projection and lighting. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: Stereoscopic diagram 1.

The invention discloses a radiation correction method and system for an airborne hyperspectral imager. The radiation correction method and system are used for improving the radiation correction precision in complex weather. The method comprises the following steps: calculating a theoretical sun position based on unmanned aerial vehicle initial coordinates, ephemeris data and atmospheric parameters; performing course and differential compensation on a solar azimuth angle by combining IMU course and wind speed and direction data, performing refraction correction on an elevation angle, and outputting a high-precision sun position parameter; hyperspectral images and irradiance data are synchronously acquired, quaternion interpolation is combined with IMU data to realize space-time alignment, and attitude disturbance is eliminated; a hemispherical space irradiance model is constructed based on alignment data, cloud layer modes (clear sky, thin cloud and thick cloud) are divided according to atmospheric optical thickness variance, and Lambert body proportion correction, a discrete longitudinal standard method or a deep convolutional spectral network are respectively adopted for radiation correction. The method remarkably improves the correction precision and generalization ability, supports large-area image splicing, and is suitable for quantitative application of geological exploration, environment monitoring and the like.

The invention discloses an engineering calculation method and device for back irradiance of a high-precision double-sided photovoltaic module. The calculation method comprises the following steps: (1) inputting related parameter information of a photovoltaic power station; (2) the array is simplified into a two-dimensional diagram, and the sun position including the zenith angle and the azimuth angle is calculated; (3) calculating the ground shadow condition according to the geometric information of the component and the sun position; (4) calculating a sky view angle factor between rows which can be seen by each ground section according to the geometric parameters of the array; calculating an incident angle according to the dip angle, the component azimuth, the solar azimuth and the zenith angle; using a Perez model to decompose the input horizontal direct radiation irradiance and horizontal diffusion irradiance into a direct radiation part, an isotropic diffusion part, an annular solar region diffusion part, a horizon line scattering part and a ground reflection part; using a Perez model to calculate the diffused irradiance of the inclined plane; and (5) calculating the back irradiance after all the steps are completed. According to the method, a three-dimensional scene is simplified into a two-dimensional scene, a View Factor method, back shadow analysis and a sky view angle factor algorithm are simplified, the irradiance received by the ground is accurately considered, and the irradiance received by the back is calculated by using angle-by-angle incidence loss, so that the accuracy is not lacked, and the operation efficiency is high.

The invention discloses a meteorological satellite multispectral imaging observation-based subtropical high voltage parameter extraction method, which comprises the following steps of: S1, projecting target data into a static meteorological satellite observation view field to calculate a subtropical high voltage influence area, and performing space-time matching on the subtropical high voltage influence area, historical observation data and sea-land template data; s2, randomly sampling the space-time matching data set, selecting time or space discrete points, and dividing a plurality of sampling areas according to different sky states; s3, sample sets of the multiple sampling areas are divided into a training set and a test set, an XGBoost classification decision tree is adopted to establish an identification inversion model, and Bayesian iterative optimization is adopted to establish an identification optimal model; s4, inputting real-time static observation data, and identifying the subtropical high-voltage influence area by using the model to obtain the influence probability of each point; s5, dividing according to a probability threshold value; s6, performing projection conversion on a division result, and applying Canny edge detection on a specified range to extract a subtropical high-voltage outer boundary; and S7, calculating the area index or the strength index of the subtropical high pressure.

We present a ground-based laser system for searching, ranging, and tracking that actively illuminates small resident space objects (RSOs) in low Earth orbit (LEO) and observes position and transit-time of reflections, enabling orbital custody of most one-to-few centimeter-sized objects. A diode-pumped alkali laser (DPAL) augmented with mode-locking and Q-switching serves as an illuminator and offers exceptionally high spectral brightness due to its output beam's sub-nanosecond pulse duration and picometer-level spectral linewidth. Kilohertz fast-rastering enables interrogations of distinct few-meter-sized sky-patches at megahertz rates. Paired on the observation side with one or more telescopes outfitted with Faraday anomalous dispersion optical filters (FADOFs), image intensifiers, multi-pixel arrays, and nanosecond timing, the combined system could offer nearly background-free discoveries of RSOs every hour, even during daytime. Periodically re-flashing previously discovered objects to maintain orbit custody expends only a small fraction of total observing time.