Autonomous observation mission generation method for low-orbit remote sensing satellite based on on-orbit cloud judgment

Abstract

The present invention proposes a method for generating autonomous observation tasks based on on-orbit cloud judgment for a low-orbit remote sensing satellite, comprising: an on-board data processor sends a first cloud judgment result P1 to a central processing computer in a first fixed time period; a multi-angle polarization imager sends a second cloud judgment result P2 to the central processing computer in the first fixed time period; the central processing computer comprehensively calculates the cloud amount within the first fixed time period based on the first cloud judgment result P1 and the second cloud judgment result P2 within the first fixed time period; and determines the cloud conditions within the first fixed time period and the duration of the cloud conditions; a GPS receiver predicts future sub-satellite surface properties in real time and sends the predictions to the central processing computer via a satellite bus; and the central processing computer autonomously generates on-board observation tasks based on the working conditions of the observation tasks.

Description

Technical Field

[0001] The present invention belongs to the field of autonomous observation of low-orbit remote sensing satellites, and specifically relates to a method for realizing autonomous identification of cloud image products through multi-source data fusion on board the satellite, and introducing cloud judgment results into the autonomous mission planning process on board the satellite. The method is suitable for low-orbit optical remote sensing satellites carrying optical cameras and laser payloads and for surveying, mapping, and reconnaissance, etc., which have imaging conditions with cloud coverage requirements. Background Art

[0002] Low-orbit optical remote sensing satellites use remote sensing technology and remote sensing equipment, and under autonomous control on the ground or on board, generate and execute missions based on mission objectives and satellite attribute information (target position, satellite orbit, payload status, etc.), to observe surface cover and natural phenomena, and serve the fields of land and resources exploration, environmental monitoring and protection, disaster prevention and mitigation, and space science experiments.

[0003] The current observation mission process of low-orbit optical remote sensing satellites generally includes two methods: 1) The user submits an imaging mission request, and the ground performs mission planning based on the mission and satellite attribute information (target position, satellite orbit, payload status, etc.). The mission planning results are converted into satellite mission instructions, which are sent to the satellite for execution through the ground station; 2) The satellite calculates the satellite attitude and position information in real time according to the pre-set mission objectives, reasonably allocates satellite resources, eliminates resource usage conflicts between tasks, and autonomously generates and executes satellite observation tasks.

[0004] Regardless of which of the above methods is adopted, the current satellite mission model has the problem of a low proportion of effective tasks and low satellite utilization efficiency. This is mainly due to the fact that up to 60%-70% of the data in optical remote sensing satellite image products are covered by clouds to varying degrees, and there is a significant difference in the economic value of cloud-covered and cloud-free images. On the one hand, there is no identification of cloud-covered and cloud-free images on the satellite. Instead, cloud-covered and cloud-free images are indiscriminately compressed, stored, and transmitted back to the ground using a unified standard, resulting in a waste of onboard computing resources and satellite-to-ground channel resources. On the other hand, when generating tasks on the ground or on the satellite, it is impossible to predict the weather conditions at the target location at the time of mission execution. When there is cloud cover, a large number of invalid tasks will be generated. The execution of a large number of invalid tasks will directly affect the startup time and light output of the laser payload, reducing the on-orbit service life of such equipment.

[0005] How to effectively increase the proportion of effective satellite missions, extend the service life of payloads, and reduce the waste of on-board resources and satellite-to-ground channel resources are issues that urgently need to be addressed in the mission generation and execution of current optical remote sensing satellites, and are also difficult problems faced in the overall design of satellite working modes. Summary of the Invention

[0006] In view of this, the present invention provides a method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment, comprising:

[0007] Step 1: The onboard data processor receives image data from a wide-angle forward-looking camera and sends a first cloud judgment result P1 to a central processing computer at a first fixed time period based on the image data.

[0008] Step 2: The multi-angle polarization imager sends a second cloud judgment request at a second fixed time period. After receiving the imaging point angle, longitude and latitude information, surface reflectivity information, and corresponding time code information fed back by the central processing computer, the multi-angle polarization imager calculates and sends a second cloud judgment result P2 to the central processing computer at the first fixed time period based on the image data corresponding to the time code information.

[0009] Step 3: The central processing computer combines the first cloud determination result and the second cloud determination result within the first fixed time period to calculate the cloud cover within the first fixed time period; and determines the cloud condition within the first fixed time period and the duration of the cloud condition;

[0010] Step 4: The GPS receiver predicts the surface properties of the sub-satellite point in real time 10 minutes in the future, and sends the predictions to the central processing computer via the satellite bus at the first fixed time period.

[0011] Step 5: The central processing computer autonomously generates an on-board observation task according to the observation task working conditions.

[0012] In particular, step 1 specifically includes: the on-board data processor receives image data from a wide-angle forward-looking camera and divides the original image data into blocks; the on-board data processor calculates and identifies cloud features for each block, uses an SVM classifier to implement cloud feature classification, obtains cloud images and non-cloud images, and obtains the first cloud judgment result after statistics.

[0013] In particular, the step 2 specifically includes: the multi-angle polarization imager submits the second cloud judgment calculation request at the second fixed period, and notifies the control computer to calculate the observation point angle and longitude and latitude information of the eight imaging points of the multi-angle polarization imager through the satellite bus;

[0014] The control computer predicts the angle and longitude and latitude information of the imaging point observation point at a certain time in the future relative to the current satellite time within a third fixed period, and sends the prediction result to the central processing computer via the satellite bus within the first fixed period;

[0015] After receiving the second cloud judgment calculation request from the multi-angle polarization imager, the central processing computer sends the latitude and longitude information of the eight most recently received imaging points to the GPS receiver via the satellite bus. After receiving the latitude and longitude information, the GPS receiver completes the table lookup calculation of the surface reflectivity information corresponding to the latitude and longitude within 2 seconds, and sends the result to the central processing computer via the satellite bus;

[0016] Within 3 seconds after the multi-angle polarization imager makes the second cloud judgment calculation request, the central processing computer sends the received observation point angle, longitude and latitude information, surface reflectivity information and corresponding time code information of the imaging point to the multi-angle polarization imager via the satellite bus;

[0017] After the multi-angle polarization imager receives the observation point angle, longitude and latitude information, surface reflectivity information and corresponding time code information of the imaging point sent by the central processing computer, it calculates the image data corresponding to the time code information and sends the second cloud judgment result P2 to the central processing computer through the satellite bus in the first fixed time period.

[0018] In particular, the observation point angles of the imaging points include the solar zenith angle, the observation zenith angle, and the observation relative azimuth angle.

[0019] Specifically, in step 3, the central processing computer comprehensively calculates the cloud detection results P1 and P2 from the onboard data processor and the multi-angle polarization imager within the same first fixed period, and calculates the cloud cover at that moment according to the formula P_0 = (K_1P_1+K_2P_2) / (K_1+K_2), which is recorded as P_0. K_1 and K_2 are weight coefficients that can be modified on-board. The calculation result is compared with the threshold P:

[0020] a. If P0 ≥ P, the cloud condition at that moment is considered to be cloudy, and the central processing computer records and counts the time and duration of cloudiness;

[0021] b. If P0 < P, the cloud condition at that moment is considered to be cloudless, and the central processing computer records and counts the cloudless time and duration.

[0022] In particular, in step 5, an on-board autonomous observation task is generated based on the predicted surface properties of the sub-satellite point, the cloud conditions, the observation task type, and the working duration of a single task.

[0023] In particular, when the duration of the cloud-covered moments obtained from statistics is longer than a threshold, the onboard payload equipment is turned on; or when the duration of the cloud-free moments obtained from statistics is longer than a threshold, the onboard payload equipment is turned off.

[0024] In particular, the satellite can also perform on-orbit cloud image removal on other payload image products generated by ground-based injection missions based on the cloud conditions.

[0025] Compared with the existing technology, the technical advantages of this invention are as follows:

[0026] 1) Onboard autonomous missions introduce cloud judgment results, generating missions based on the calculation results of future off-board point cloud coverage. This effectively reduces the number of invalid on-board missions, significantly increases the proportion of valid satellite missions, reduces the ineffective startup time of the payload on orbit, and extends the payload's service life.

[0027] 2) Based on the cloud judgment results, the satellite can remove the cloud images of other payload image products generated by ground-based injection missions, saving on-board resources and satellite-to-ground channel resources, transmitting more high-quality remote sensing image data back to the ground, and improving the efficiency of remote sensing satellite use;

[0028] 3) The cloud detection introduction conditions are flexible and configurable. The weight values ​​of the cloud detection results of the wide-angle forward-looking camera and the multi-angle polarization imager in the cloud detection calculation can be set on-orbit. The cloud and cloud-free duration thresholds can be set on-orbit according to the payload operating conditions.

[0029] 4) The multi-angle polarization imager is linked with the control computer, central processing computer, and GPS receiver to complete cloud judgment in a short time, improving the operating efficiency of remote sensing satellites;

[0030] 5) The imaging point of the multi-angle polarization imager has multiple observation angles including solar zenith angle, observation zenith angle, observation relative azimuth angle, etc., which can fully and accurately realize cloud judgment;

[0031] 6) Achieve the goal of starting up the payload for imaging in cloudless areas and shutting down the payload in cloudy areas, and at the same time adopt a payload safety protection mechanism to avoid repeated startup and shutdown operations of the payload equipment in a short period of time. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Schematic diagram of the process of cloud judgment performed by the on-board data processor in the present invention;

[0033] Figure 2 This is a schematic diagram of the cloud judgment process of the multi-angle polarization imager in the present invention;

[0034] Figure 3 This is a schematic diagram of the central processing computer cloud probability calculation process in the present invention;

[0035] Figure 4 This is a structural diagram of the autonomous task generation system introduced in the present invention based on on-orbit cloud judgment. DETAILED DESCRIPTION

[0036] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0037] The present invention provides a method for autonomous mission generation for low-orbit optical remote sensing satellites based on on-orbit cloud detection, addressing the current situation of a low proportion of effective missions and low satellite utilization efficiency in optical remote sensing satellites. The present invention designs and implements a method for autonomous mission generation for low-orbit optical remote sensing satellites based on on-orbit cloud detection. The technical approach utilizes image data from a large-angle forward-looking camera mounted on the satellite for on-orbit cloud image recognition. Based on the cloud detection results, statistics are generated to determine the cloudiness or cloudlessness of the satellite's subsatellite points over a period of time. Based on the surface properties of the subsatellite points predicted for a period of time over a period of time on the satellite, combined with the operating conditions of the payload equipment, cloud-free areas are selected to generate observation missions. This achieves the goal of enabling payload imaging in cloud-free areas and shutting down payloads in cloudy areas. At the same time, a payload safety protection mechanism is implemented to prevent the payload equipment from being repeatedly turned on and off multiple times in a short period of time.

[0038] The technical solution of the present invention comprises a central processing computer, a wide-angle forward-looking camera, an onboard data processor, a multi-angle polarization imager, a satellite control computer, a GPS receiver, and a set of satellite bus cables. Each device is connected via a satellite bus, and the central processing computer controls information exchange on the satellite bus. The main steps of this solution include:

[0039] 1) The onboard data processor generates the first cloud judgment result P1

[0040] like Figure 1 As shown, the steps for generating the first cloud judgment result P1 of the on-board data processor are as follows:

[0041] a. The onboard data processor receives the image data from the wide-angle forward-looking camera and divides the original image data into blocks of 512*512 size;

[0042] b. The onboard data processor calculates and identifies cloud features (texture statistical features, grayscale differential features, etc.) for each block, uses the SVM classifier to classify cloud features, and completes the detection of cloud images and non-cloud images;

[0043] c. Each block of cloud judgment results is represented by 1 bit, with "1" indicating cloud and "0" indicating no cloud. The onboard data processor counts the cloud judgment results in 16-bit words, with the upper 12 bits representing the cloud judgment result and the lower 4 bits filled with 0s. Each bit of cloud judgment result corresponds to a 512*512 block. When generating the cloud judgment result, the onboard data processor adds 4 bytes of satellite full-second time before each word of cloud judgment result.

[0044] d. The onboard data processor sends the cloud judgment result to the central processing computer through the satellite bus once every second at a fixed period. The length of each data transmission is 24 bytes, including 16 bytes of satellite full second time data and 4 words of cloud judgment result data.

[0045] 2) The multi-angle polarization imager generates the second cloud judgment result P2

[0046] like Figure 2 As shown in Figure 1, the multi-angle polarization imager uses the target pixel's real-time solar zenith angle, observation zenith angle, observation relative azimuth, and surface reflectivity to obtain the optical thickness of each point cloud. The cloud optical thickness measured using the image is then used, and finally a threshold is applied to obtain the second cloud detection result, P2. The steps for generating the cloud detection result are as follows:

[0047] a. The multi-angle polarization imager submits a cloud judgment calculation request at a fixed period (5.04 seconds) and notifies the control computer through the satellite bus to calculate the observation point angles (solar zenith angle, observation zenith angle, observation relative azimuth angle) and longitude and latitude information of the eight imaging points of the multi-angle polarization imager;

[0048] b. The control computer predicts the imaging point observation point angle and latitude and longitude information at a fixed period (1 second) 3701.334 milliseconds in the future relative to the current satellite time, and sends the forecast results to the central processing computer via the satellite bus within the same second. The observation point angle and latitude and longitude of each imaging point are represented by 2 bytes, for a total of 10 bytes. The forecast result is 84 bytes long, including a 4-byte observation point angle information corresponding to the time code and an 80-byte imaging point observation point angle and latitude and longitude information.

[0049] c. After receiving the cloud judgment calculation request from the multi-angle polarization imager, the central processing computer sends the latitude and longitude information of the latest 8 imaging points to the GPS receiver via the satellite bus. After receiving the latitude and longitude information, the GPS receiver completes the table lookup calculation of the latitude and longitude corresponding to the surface reflectivity information within 2 seconds and sends the result to the central processing computer via the satellite bus. Each surface reflectivity information is represented by 2 bytes. The output surface reflectivity information includes 4 bytes of surface reflectivity information corresponding to the time code and 16 bytes of surface reflectivity information.

[0050] d. Within 3 seconds after the multi-angle polarization imager submits a cloud judgment calculation request, the central processing computer sends the received imaging point angle, longitude and latitude information, surface reflectivity information, and corresponding time code information to the multi-angle polarization imager via the satellite bus;

[0051] e. After receiving the imaging point angle, longitude and latitude information, surface reflectivity information, and corresponding time code information from the central processing computer, the multi-angle polarimeter calculates the cloud detection result based on the image data corresponding to the time code information and transmits it to the central processing computer via the satellite bus. The multi-angle polarimeter cloud detection result consists of 32 lines. The first line corresponds to the imaging time observed at the maximum forward viewing angle. Each line has 16 bits, and each 2 bits represents a cloud detection result. "00" indicates clear sky, "01" indicates suspected clear sky, "10" indicates suspected cloud, and "11" indicates confirmed cloud. The multi-angle polarimeter takes no more than 5.04 seconds from the time the cloud detection calculation request is submitted to the completion of the calculation and output of the cloud detection result.

[0052] 3) CPU fully autonomous observation task generation

[0053] like Figure 3 and Figure 4 As shown in the figure, the central processing computer continuously receives the first cloud judgment result P1 and the second cloud judgment result P2 generated by the onboard data processor and multi-angle polarization imager through the satellite bus at a fixed period (1 second), caches the received cloud judgment results, calculates the cloud probability in real time, and autonomously generates observation tasks based on the cloud probability. The calculation process is as follows:

[0054] 1) The central processing computer integrates the cloud judgment results of the onboard data processor and the multi-angle polarization imager within the same full second, and calculates the cloud cover within that second according to formula (1), which is recorded as P0, where K1 and K2 are weight coefficient values, which can be modified on-board and the default value is 20. When K1 and K2 are both 0, P0 is 0;

[0055]

[0056] 2) Compare the calculated result with the threshold P (the default value is 90):

[0057] a. If P0 ≥ P, it is considered that there is cloud at that second, and the central processing computer records and counts the time and duration of cloud;

[0058] b. If P0 < P, it is considered that there is no cloud at that second, and the central processing computer records and counts the cloudless time and duration.

[0059] 3) The GPS receiver predicts the surface attributes of the sub-satellite point in real time 10 minutes in the future and sends it to the central processing computer via the satellite bus at a fixed period (1 second). The length of the predicted sub-satellite point surface attributes is 6 bytes, including the 4-byte satellite full second time corresponding to the surface attribute forecast result and the 2-byte predicted sub-satellite point surface attributes. The 2-byte surface attributes are represented by B0-B15, B0-B3 represent land and ocean attributes (0x5 represents land, 0xA represents ocean), B4-B7 represent sunshine and shadow attributes (0x5 represents sunshine, 0xA represents shadow), B8-B11 represent domestic and foreign attributes (0x5 represents domestic, 0xA represents foreign), and B12-B15 are fixedly filled with 0xF;

[0060] 4) The central processing computer autonomously generates observation tasks based on the predicted surface properties of the sub-satellite point and the calculated cloud coverage, combined with the observation task working conditions. The working conditions for typical satellite observation tasks are shown in the following table:

[0061]

[0062]

[0063] It can be seen that the on-board autonomous observation mission is generated based on the predicted surface properties of the sub-satellite point, the cloud conditions, the observation mission type and the working time of a single mission.

[0064] At the same time, based on the cloud judgment results, other payload image products generated by ground-based injection missions can be removed from the on-orbit cloud maps, saving on-board resources and satellite-to-ground channel resources, transmitting more high-quality remote sensing image data back to the ground, and improving the efficiency of remote sensing satellite use.

[0065] When the duration of cloud coverage exceeds a threshold (e.g., 2 minutes or longer), the onboard payload is powered on. Alternatively, when the duration of cloud-free periods exceeds a threshold, the onboard payload is powered off. This approach enables onboard payload imaging in cloud-free areas and shutdown in cloudy areas. A payload safety mechanism is also implemented to prevent repeated power-on and power-off operations within a short period of time.

[0066] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0067] It is obvious to those skilled in the art that the embodiments of the present invention are not limited to the details of the above-mentioned exemplary embodiments, and that the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or essential features of the embodiments of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the embodiments of the present invention. Any figure marks in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units, modules or devices stated in the system, device or terminal claims may also be implemented by the same unit, module or device through software or hardware. Words such as first and second are used to indicate names and do not indicate any particular order.

[0068] Finally, it should be noted that the above implementation methods are only used to illustrate the technical solutions of the embodiments of the present invention and are not limiting. Although the embodiments of the present invention are described in detail with reference to the above preferred implementation methods, ordinary technicians in this field should understand that the technical solutions of the embodiments of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment, characterized in that: include: Step 1: The onboard data processor receives image data from a wide-angle forward-looking camera and sends a first cloud judgment result P1 to a central processing computer at a first fixed time period based on the image data. Step 2: The multi-angle polarization imager submits a second cloud judgment calculation request at a second fixed time period, and notifies the control computer via the satellite bus to calculate the observation point angles and longitude and latitude information of the eight imaging points of the multi-angle polarization imager; The control computer predicts the angle and longitude and latitude information of the imaging point observation point at a certain time in the future relative to the current satellite time within a third fixed time period, and sends the prediction result to the central processing computer via the satellite bus within the first fixed time period; After receiving the second cloud judgment calculation request from the multi-angle polarization imager, the central processing computer sends the latitude and longitude information of the eight most recently received imaging points to the GPS receiver via the satellite bus. After receiving the latitude and longitude information, the GPS receiver completes the table lookup calculation of the surface reflectivity information corresponding to the latitude and longitude within 2 seconds, and sends the result to the central processing computer via the satellite bus; Within 3 seconds after the multi-angle polarization imager makes the second cloud judgment calculation request, the central processing computer sends the received observation point angle, longitude and latitude information, surface reflectivity information and corresponding time code information of the imaging point to the multi-angle polarization imager via the satellite bus; After receiving the observation point angle, longitude and latitude information, surface reflectivity information, and corresponding time code information of the imaging point from the central processing computer, the multi-angle polarization imager calculates and sends a second cloud judgment result P2 to the central processing computer via the satellite bus in the first fixed time period based on the image data corresponding to the time code information; Step 3: The central processing computer calculates the cloud cover within the first fixed time period by combining the first cloud judgment result P1 and the second cloud judgment result P2 within the first fixed time period; and determines the cloud condition within the first fixed time period and the duration of the cloud condition; Step 4: The GPS receiver predicts the surface properties of the sub-satellite point in real time 10 minutes in the future, and sends the predictions to the central processing computer via the satellite bus at the first fixed time period. Step 5: The central processing computer autonomously generates an on-board observation task according to the observation task working conditions.

2. The method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment according to claim 1, characterized in that: The step 1 specifically includes: the onboard data processor receives image data from a wide-angle forward-looking camera and divides the original image data into blocks; the onboard data processor calculates and identifies cloud features for each block, uses an SVM classifier to implement cloud feature classification, obtains cloud images and non-cloud images, and obtains the first cloud judgment result after statistics.

3. The method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment according to claim 2, characterized in that: The observation point angles of the imaging point include the solar zenith angle, the observation zenith angle, and the observation relative azimuth angle.

4. The method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment according to any one of claims 1 to 3, characterized in that: In step 3, the central processing computer comprehensively calculates the cloud judgment results P1 and P2 of the onboard data processor and the multi-angle polarization imager within the same first fixed time period, according to the formula Calculate the cloud cover at that moment, denoted as P0, where K1 and K2 are weight coefficients that can be modified on-orbit; compare the calculated result with the threshold P: a. If P0 ≥ P, the cloud condition at that moment is considered to be cloudy, and the central processing computer records and counts the time and duration of cloudiness; b. If P0 < P, the cloud condition at that moment is considered to be cloudless, and the central processing computer records and counts the cloudless time and duration.

5. The method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment according to any one of claims 1 to 3, characterized in that: In step 5, an on-board autonomous observation task is generated based on the predicted surface properties of the sub-satellite point, the cloud conditions, the observation task type, and the working duration of a single task.

6. The method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment according to claim 5, characterized in that: When the duration of the cloud-covered moments obtained by statistics is longer than the threshold, the onboard payload equipment is turned on; or when the duration of the cloud-free moments obtained by statistics is longer than the threshold, the onboard payload equipment is turned off.

7. The method for generating autonomous observation tasks for a low-orbit remote sensing satellite based on on-orbit cloud judgment according to any one of claims 1 to 3, characterized in that: The satellite can also remove on-orbit cloud images of other payload image products generated by ground-based injection missions based on the cloud conditions.

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