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1.INTRODUCTIONIn recent years, various sudden surface anomalies (such as natural disasters, environmental pollution, ecological damage, safety accidents, illegal development, etc.) caused by natural and human factors in China have occurred frequently, and have shown the characteristics of wide distribution, high occurrence frequency, fast evolution speed, large impact range, and heavy economic losses. They have caused serious losses to people’s lives and property, and also had a huge impact on the production and life of the entire society. Especially with global climate change and rapid economic development, the connotation and extension of surface anomalies continue to deepen and expand. Various surface anomalies are intertwined and stacked with each other, making local surfaces more fragile and sensitive. The various risks that may arise further intensify, and the constraints on the healthy and sustainable development of China’s economy and society become more apparent. Therefore, the occurrence of various surface anomalies Timely monitoring and early warning of the development process has become a top priority in ensuring social security and stability, high-quality economic development, and ecological civilization construction in China’s new development stage1. The surface anomaly situation awareness is mainly combined by manual patrol inspection, sensors for monitoring and early warning, micro motion monitoring technology, 3D Digital Photogrammetry technology, 3D laser scanning technology, active/passive remote sensing technology and other ways. It is mainly concentrated on the surface anomaly changes or disasters, inevitably wasting a lot of human and financial resources, and the current situation of frequent geological disasters is difficult to effectively solve2. Satellite remote sensing has the characteristics of large detection range, continuous space, rich information, and good dynamism, making it the most effective method for detecting large-scale surface anomalies3-4. However, due to the suddenness, diversity, randomness, concealment, and complexity of the surface anomalies we are concerned about, a large number of surface anomalies are often not detected in the actual detection process, especially if they are not detected and warned in the first place. The time efficiency and accuracy of satellite detection are far from meeting the needs of emergency rescue, accident handling, pollution control5-6. The need for real-time remote sensing services characterized by minute level response, such as supervision and law enforcement. The existing space-based remote sensing capabilities are also limited to data acquisition and preprocessing. From remote sensing features to the remote sensing knowledge information that users need, a series of lengthy links such as on-board data acquisition and preprocessing, satellite to ground data transmission, ground data processing, and data distribution need to reach users, making it difficult to meet the remote sensing needs of sudden anomalies7. Therefore, it is urgent to vigorously develop real-time and intelligent research and application of remote sensing detection of surface anomalies, By instantly discovering, identifying, and transmitting anomalies, traditional data remote sensing information can be transformed into new knowledge remote sensing information, enabling users to have “what they see is what they get” for abnormal remote sensing information, thus gaining the initiative in emergency response to surface anomaly events, effectively alleviating the investment of a large amount of human and material resources, and improving the coverage of surface anomaly monitoring, the timeliness, scientificity, and effectiveness of disaster rescue. Based on the analysis of surface anomaly classification and remote sensing features, this article proposes the use of distributed constellation to solve the problems of detection coverage and response efficiency in surface anomaly detection. The working mode of the satellite cluster system is studied, and the characteristics of system coverage efficiency and information transmission timeliness are analyzed. Several key issues in establishing a real-time detection system for surface anomalies are summarized, and solutions and ideas are proposed, this provides a reference for future space-based detection of surface anomalies. 2.ARCHITECTURE OF SPACE-BASED SURFACE INSTANT DETECTION SYSTEM2.1Classification and recognition of surface anomaliesThere are many types of known surface anomalies, including acute and destructive disasters such as natural disasters and human accidents, as well as hundreds of chronic and large-scale events such as environmental pollution and ecological damage8. The remote sensing characteristics of these anomalies are summarized and summarized, and surface anomalies are divided into typical categories, including water environment anomalies, land environment anomalies, atmospheric environment anomalies, etc9. Establishing a threshold lookup table for surface anomaly remote sensing elements. The remote sensing elements of relevant ground features include but are not limited to radiation features, spectral features, geometric features, texture features, scattering features, etc. Each ground feature can be quantitatively described through the above remote sensing elements. According to the correlation degree of various anomalies and corresponding features, it is divided into strong anomalies (single element recognition) and weak anomalies (multi element recognition), as shown in Table 1. Table 1.Margins and print area specifications.
By using image background target threshold segmentation and edge detection to preliminarily determine suspected surface anomaly areas, an index response model is used to establish a remote sensing element threshold lookup table corresponding to remote sensing response characteristics10. Based on prior remote sensing information, the threshold range corresponding to the normal remote sensing feature index of ground features is determined. After the remote sensing element threshold exceeds the normal range, it can be determined that an anomaly has occurred, the surface anomaly is roughly identified through the threshold range of the multi feature index, and further refined identification is carried out in combination with geometric and structural features to identify the specific type and severity level of the anomaly. The satellite system will transform the responsive remote sensing information into more advanced Semantic information, which will reach users through multiple communication links. 2.2Architecture of surface anomaly detection systemThe constellation for real-time detection of surface anomalies uses a distributed satellite system architecture, where multiple satellites are distributed to form virtual satellites through inter satellite tasks and information interconnection. The ground remote sensing information processing center is retained to configure the remote sensing cloud computing layer, achieving continuous iterative updates of anomaly remote sensing thresholds and exponential feature models; At the same time, on the basis of traditional distributed satellite information and information interconnection and collaborative control, space based edge computing is used to realize inter satellite collaborative hierarchical anomaly recognition11, and emergency ground anomaly information is quickly transmitted to users. In the real-time detection system, satellites are used as the endpoints of system information acquisition, and distributed constellation are used as the basic functional units of anomaly recognition, Establish a distributed satellite cluster fog computing layer, utilizing the advantages of fog computing to solve the problems of high transmission delay of remote sensing information and untimely acquisition of abnormal information; The traditional ground station downlink and uplink functions are retained on the information transmission link, while adding a space-based communication system that utilizes relay satellites and Beidou short messages to achieve the transmission of abnormal information slicing and emergency abnormal semantic short messages, shortening the transmission path of emergency abnormal information, as shown in Figure 1. 3.RESEARCH ON THE WORKING MODE OF THE REAL-TIME DETECTION SYSTEM FOR SPACE-BASED SURFACE ANOMALIESThe task of remote sensing of surface anomalies has the characteristics of uncertain observation areas and complex observation elements12. It requires satellites to observe the Earth for a long time13, traverse the surface environment, independently discover and identify anomalies, and transmit anomaly information. The working mode adopts the satellite cluster integration mode, and the working mode of census and detailed survey is adopted for multiple satellites in each small satellite cluster. The task planning model is closely integrated with the on orbit intelligent processing algorithm based on the remote sensing response feature threshold. The remote sensing task of surface anomaly needs to decompose the anomaly remote sensing task according to whether it is a strong feature according to the anomaly type obtained by the census satellite, and the subsequent detailed survey satellites further identify the anomaly to form Semantic information, it can be directly distributed to users, as shown in Figure 2. Based on the above work characteristics, a distributed constellation composed of census satellites and several detailed survey satellites is the basic unit of the real-time detection constellation for surface anomalies. The distributed constellation is composed of different types of satellites, and its connotation is a multi-modal satellite formation with both multi-functional and time difference remote sensing capabilities. Multiple satellites within and between the constellation collaborate to complete observation tasks. The connection is established through inter satellite communication links within the satellite distributed constellation, and the system operates within the constellation through the following process.
The remote sensing constellation for surface anomalies is composed of several distributed constellation. After construction, the entire constellation system has a huge scale, and matching between different populations within and between clusters is already a relatively complex problem. How to achieve the optimal adaptive matching under specific constraints (such as the number of satellites, observation time, etc.) is a more complex planning problem. Based on the characteristics of surface anomaly observation tasks, a hierarchical satellite cluster task planning method is proposed. The entire anomaly identification and task planning process is shown in Figure 3. 4.RESEARCH ON THE WORKING MODE OF THE REAL-TIME DETECTION SYSTEM FOR SPACE-BASED SURFACE ANOMALIES4.1System information transmission linkIn order to solve the problem of long transmission links and delayed response in existing satellite systems, the surface anomaly real-time detection system has established a self-circulating communication link, ensuring the real-time or near real-time communication ability of self-communication within the distributed satellite cluster, which can achieve information circulation within the constellation. The survey satellite also serves as a communication node satellite, and information can be transmitted within and between the constellation, Any information within a distributed constellation can be transmitted to the ground station and can serve as a communication node for other distributed constellation, achieving the communication ability of the constellation system to “see a single satellite to the ground, and transmit constellation information as needed”, fundamentally solving the problem of weak information transmission ability. As shown in Figure 4, the schematic diagram shows the information transmitted back to the domestic ground station through the inter satellite link after the real-time detection constellation of surface anomalies discovers anomalies. The constellation that meets the real-time transmission of information mentioned above can be considered as a “inter visibility” type constellation with real-time monitoring and communication capabilities. To meet the “inter visibility” capability of the constellation, the geometric relationship of the satellites is analyzed, as shown in Figure 5. Obtain the relationship between satellite orbit height and geocentric angle based on geometric relationships. Wherein, α refers to the geocentric angle between satellites, R refers to the Earth radius, h0 refers to the altitude of the low layer surface atmosphere affecting the intersatellite laser communication transmission, h refers to the satellite orbit altitude, and L refers to the satellite spacing. Then the relationship between the orbital height of the “intervisibility” satellite constellation and the satellite spacing is shown in Figure 6. According to the calculation results, as the number of satellites increases, the corresponding orbital altitude and inter satellite distance decrease, and the difficulty of launch and communication efficiency increase. However, the construction cost also increases. Therefore, in the design phase, it is necessary to balance the single satellite design and the overall layout of the constellation. 4.2Transmission duration analysisThe surface anomaly real-time detection system has communication capability within and between distributed constellation, and the whole system has self-circulation and external circulation communication capabilities, as shown in Figure 7, which is the information flow diagram of the surface anomaly real-time detection constellation. From the discovery of surface anomalies to the arrival of abnormal information in the hands of users, the following process is required:
The real-time detection system for surface anomalies, from discovering anomalies to transmitting abnormal information to users, can achieve the fastest information transmission of 66.069s by completely using the constellation system itself as a communication and remote fusion system for data transmission, as shown in Table 2. When the system coverage density is sufficient, the real-time detection system for surface anomalies has the ability to detect and transmit surface anomalies in real time. At the same time, by using existing relay systems, Beidou short message systems, and future satellite network systems, it can better complete the task of real-time detection of surface anomalies. Table 2.Information Transmission delay
5.CONCLUSIONThe construction of a satellite system for real-time detection of surface anomalies involves theoretical reconstruction and methodological reconstruction of the entire process of acquiring, processing, transmitting, and applying remote sensing data of surface anomalies. A theoretical and methodological system for real-time detection of surface anomalies is created, characterized by inter satellite interconnection, inter satellite feedback, on satellite processing, and direct transmission through satellite chains, To provide a scientific basis for the system to solve the international problem of “invisible, unclear, fast, and distant” in remote sensing detection of surface anomalies, and to lay a theoretical foundation for the implementation of real-time remote sensing detection products and services for surface anomalies up to user mobile terminals. There are still some key technologies that need to be urgently addressed in the construction of constellation systems, such as the determination of real-time detection feature thresholds and comprehensive indices for full spectrum remote sensing of surface anomalies, intelligent recognition technology for on satellite surface anomalies based on comprehensive thresholds, nonlinear response detection technology for pixel level super large dynamic range of surface anomalies in complex scenes, and a series of software and hardware technologies such as constellation intelligent task planning response mechanism driven by diversified abnormal events, Ultimately, establish a space-based system that can detect, diagnose, and warn in orbit in real-time. ACKNOWLEDGEMENTThis project was supported by National Natural Science Foundation of China (Grant No. 42192582). REFERENCESWang, Q.,
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