Method and system for establishing a selection index system for a mars sampling area based on dust storm characteristics

Abstract

The application provides a Mars sampling area selection index system establishment method and system based on dust storm characteristics, belongs to the technical field of evaluating Mars sampling area preselected landing areas, and aims at the problem that dust storm classification and dust storm sequence characteristic analysis are ignored in the prior art. The selection index of the Mars sampling task landing area is constructed, including: a primary dust storm range, a dust storm free range and a dust storm warning time; a dangerous area is determined according to the primary dust storm range index, a safe area is determined according to the dust storm free range index, and a forecast area is determined according to the dust storm warning time index.

Description

Technical Field

[0001] This invention belongs to the technical field of evaluating Mars sampling areas for pre-selection of landing sites, specifically involving a method and system for establishing a Mars sampling area selection index system based on dust storm characteristics. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Mars has an atmospheric pressure 1% lower than Earth's, but its atmospheric activity is extremely high. Dust storms occur throughout the Martian season, impacting the accuracy and safety of landing and launch phases of Mars sampling missions. They can also cause dust deposits on solar panels, leading to insufficient power and instrument malfunctions. The proposed landing sites for future Mars sampling missions (such as Utopia and Cris Planitia) are major dust storm sources in the northern hemisphere of Mars, also affected by southward shifts in polar dust storms. Furthermore, the landing, sampling, and ascent / return phases all occur during periods of dust storm activity. Therefore, spatiotemporal analysis of Martian dust storms and selection of sampling areas are among the key technologies crucial to the success of future sample return missions.

[0004] Compared to topographical factors such as slope, rock abundance, and thermal inertia, which remain largely unchanged before and after landing, the dynamic atmospheric activity on Mars is actually more worthy of attention. In particular, dust storms that may be encountered throughout the Mars sampling mission directly impact its success or failure. Compared to Earth, Mars has lower data coverage, shorter observation time, and lacks real-time and on-site atmospheric data. Currently, only the medium- and high-resolution cameras carried by Tianwen-1 can observe Martian dust storms, making dust storm prediction and forecasting for future Mars sampling missions extremely difficult. There is currently no completely reliable (100% accurate) method for predicting dust storms. Therefore, establishing a safety index system for the Mars sampling mission based on dust storm classification and characteristic conditions, and selecting potential landing sites, is essential. If the selected landing site has a high probability of dust storms and cannot be effectively analyzed and predicted, the landing, sampling, and launch phases of the sampling mission will all be affected, potentially leading to mission failure.

[0005] The inventors discovered some shortcomings in the existing technology for establishing and selecting landing site selection criteria on the Martian surface: (1) Focus on static morphological factors and ignore dynamic dust storm phenomena. Existing technologies for the safety selection of Mars landing areas are mostly based on the evaluation and analysis of morphological factors, such as the average roughness, slope, thermal inertia and density distribution of rocks and impact craters of the landing area, etc., without establishing a sampling area selection index system for the safety evaluation of Martian dust storms. (2) Focusing on the spatiotemporal probability of dust storms while neglecting dust storm classification and dust storm sequence feature analysis. Existing technologies mainly select safe (lowest probability of dust storm occurrence) landing areas by extracting and analyzing the spatiotemporal probability of dust storms. However, Martian dust storms can be divided into primary and non-primitive dust storms according to their source regions, and dust storm sequences have characteristics such as life cycle, movement speed, and response time. These characteristics are not considered when establishing a safety indicator system and making selections. (3) The landing mission factor is adopted, ignoring the difference between landing and sampling missions. There is no precedent for Mars sampling missions, and sampling missions differ from Mars landing missions in content, objectives, and execution methods. Therefore, the engineering safety indicators of existing Mars landing missions cannot be copied, and there is currently no dust storm safety indicator system that can be used for Mars sample return missions. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for establishing a Martian sampling area selection index system based on dust storm characteristics. This system integrates dust storm classification, dust storm range, and response time to establish a dust storm safety index system for Martian sampling missions.

[0007] According to some embodiments, the present invention adopts the following technical solution: Firstly, a method for establishing a Martian sampling area selection index system based on dust storm characteristics is disclosed, including: Based on Mars color remote sensing images, all dust storm objects are identified in the identification area, and a dust storm dataset is generated. The dust storm dataset is divided into a native dust storm set and a non-native dust storm set. The union of all native dust storm polygons in the native dust storm set is used to generate a native dust storm polygon region, i.e., the native dust storm region. Then, the intersection of the native dust storm region and the study area is obtained, and the resulting polygon is the danger zone. The union of the polygons of all dust storms in the dust storm dataset of the identification area is used to generate a dust storm polygon, i.e., the dust storm region. The complement of the dust storm region and the study area is then used to obtain the polygon, i.e. the safe area. Apart from the native dust storm area and the safe zone, the remaining area in the study area is the area with dust storm sequence pathways, referred to as the forecast area; Obtain the dust storm warning time for each grid in the forecast area, then merge adjacent grids with the same dust storm warning time, divide the entire forecast area into regions with different dust storm warning times, and then obtain the set of all dust storm warning times for the regions after the forecast area is divided. The selection criteria for the landing area of ​​the Mars sampling mission include: the range of native dust storms, the range without dust storms, and the dust storm warning time. Danger zones are determined based on the primary dust storm range index, safe zones are determined based on the dust storm-free range index, and forecast zones are determined based on the dust storm warning time index.

[0008] As a further technical solution, a Martian dust storm sequence extraction step is also included, specifically: For the dust storm dataset, extract p During a Martian year, all dust storm sequences in the region are identified within the sampling mission period, ultimately generating a set of dust storm sequences in the identified region.

[0009] As a further technical solution, dust storm sequences are determined through visual interpretation. The rule is: after identifying a dust storm in a color image, look for dust storms near that location in the next Mars day remote sensing image, and combine physical proximity, morphological and textural similarity to determine, identify and track the performance of the dust storm in different images until the dust storm disappears in subsequent images. A dust storm sequence consists of the same dust storm object appearing in the first image and appearing in the last image before it disappears; The duration of the dust storm in the dust storm sequence must be greater than one Martian day, meaning it must appear continuously in at least two consecutive remote sensing images. As a further technical solution, each dust storm sequence contains multiple dust storm objects identified from different images. Assuming the dust storm sequence DS... i Among them, there are a total of n A dust storm, denoted as DS ij , where j=1, 2, …, n The dust storm sequence DS can also be obtained. i Duration DS i ( T )= n .

[0010] As a further technical solution, it also includes: calculating the dust storm response time and response range relative to the study area for the dust storm sequence set, including: Extract the extent and response time of each dust storm sequence when it reaches the study area from the dust storm sequence set, i.e., the Martian day from the generation of the dust storm sequence to its movement to the study area; the interval between consecutive Mars remote sensing images is one Martian day.

[0011] As a further technical solution, the extraction of the range and response time of each dust storm sequence in the dust storm sequence set when it arrives in the study area involves the following specific steps: (1) For a dust storm sequence DS i Its lifecycle is DS i ( T That is, the dust storm objects in this dust storm sequence are in continuous... T It appeared in Zhang Huoxing's remote sensing image; Let the first a Dust storm objects in Zhang Huoxing remote sensing images have reached the study area. a ∈[1, DSi ( T The dust storm in this image is DS. ia ; (2) DS ia By spatially intersecting the study area, the intersection polygon between the two is obtained, which is the dust storm response range S-DS. ia At the same time, the response time S-DS corresponding to the response range ia (T) is set as a -1 indicates that S-DS in the study area S ia Region, in dust storm sequence DS i After the source region is generated, it needs to be a It would take one Martian day to reach this area; (3) Continue to analyze the dust storm sequence DS i middle a +1 image of the dust storm object DS i(a+1) Continue to make judgments. If the dust storm object also has an intersection with the study area S, then record the dust storm response time and response range of the dust storm sequence in a+1 images respectively. (4) Repeat steps (1)-(3) until the dust storm sequence DS is generated. i Response range set S-DS ij and the corresponding response time set S-DS ij (T), where j= a , a +1, …, b , b For this dust storm sequence DS i The image number corresponding to the last time the dust storm object appeared in the study area; (5) When i=1, 2, ..., m For each dust storm sequence DS in the dust storm sequence set i Repeat steps (1)-(4) to obtain the dust storm sequence set DS relative to the study area S, the dust storm response range set S-DS, and the response time set S-DS(T).

[0012] As a further technical solution, the dust storm warning time for each grid in the forecast area is obtained through the following steps: (a) Divide the forecast area into regular grids, and let the set of grids after division be G, with a total of n 1 grid, where the first i The number of grids is G. i ,in i =1, 2, …, n 1; (b) Mesh G iEach dust storm response range polygon in the dust storm response range set S-DS ij Find the intersection; if there is an intersection, then calculate the corresponding dust storm response time S-DS. ij (T) Record it; Assume there is a total n Two dust storm response ranges and G i The intersection of these two sets of dust storm response times is denoted as G. i T j where j=1,2, …, n 2; (c) Take the dust storm response time set G i T j The minimum value is used as the grid G. i Dust storm warning time G i (T), i.e. G i (T)=min{G i T j j=1, 2, …, n 2}, if we want to forecast grid G i Whether a dust storm will occur depends on at least G. i Remote sensing images within (T) Martian days; (d) Repeat (a)-(c) to obtain the dust storm warning time for each grid in the forecast area.

[0013] Secondly, a system for establishing a Martian sampling area selection index based on dust storm characteristics was disclosed, including: The Mars dust storm identification module is configured to: identify all dust storm objects in the identification area based on Mars color remote sensing images, generate a dust storm dataset, and divide the dust storm dataset into a native dust storm set and a non-native dust storm set; The danger zone module is configured to: find the union of all native dust storm polygons in the native dust storm set to generate a native dust storm polygon region, i.e., the native dust storm region; then find the intersection of the native dust storm region and the study area, and the resulting polygon is the danger zone. The safe zone module is configured to: find the union of the polygons of all dust storms in the dust storm dataset of the area where the dust storm is identified, generate a dust storm polygon, i.e., the dust storm area, and find the complement of the dust storm area and the study area to obtain the safe zone polygon. The forecast area module is configured as follows: the area remaining in the study area, excluding the native dust storm area and the safe zone, is the area with dust storm sequence pathways, referred to as the forecast area; Obtain the dust storm warning time for each grid in the forecast area, then merge adjacent grids with the same dust storm warning time, divide the entire forecast area into regions with different dust storm warning times, and then obtain the set of all dust storm warning times for the regions after the forecast area is divided. The indicator construction module is configured to: construct selection indicators for the landing area of ​​the Mars sampling mission, including: native dust storm range, dust storm-free range, and dust storm warning time; Danger zones are determined based on the primary dust storm range index, safe zones are determined based on the dust storm-free range index, and forecast zones are determined based on the dust storm warning time index.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The dust storm safety index of this invention includes the range of native dust storms, dust storm-free areas, and dust storm warning time. The study area is divided into danger zones and safe zones by the ranges of native and non-native dust storms. Then, the dust storm warning time for different locations in the forecast area is determined based on the response time of the dust storm sequence. This addresses the problem in previous dust storm safety assessments that only considered the spatiotemporal probability of dust storms, neglecting dust storm classification and feature application.

[0015] This invention classifies dust storms and extracts their sequence features. Based on the relationship between the dust storm's origin and the landing area, dust storms can be divided into primary and non-primary dust storms. Primary and non-primary dust storms originate locally from the landing area and externally from it (generally referring to the Arctic source region), respectively. A dust storm sequence refers to the representation of a dust storm with a lifespan exceeding one Martian day in multiple consecutive remote sensing images. By classifying dust storms in the study area into primary and non-primary dust storms, tracking dust storm sequences, and extracting their features (lifespan and response time, etc.), safe sampling areas can be selected, addressing the problem of previous Mars sampling area selection methods that only considered the spatiotemporal probability distribution of dust storm objects.

[0016] This invention establishes and classifies a dust storm safety index system for sampling areas. By establishing this system, the impact of Martian dynamic atmospheric activity (dust storms) is incorporated into the selection process of Martian sampling areas. The study area undergoes classification and statistical analysis of native and non-native dust storms, and forecast areas are graded and warned based on the response time of dust storm sequences. A sampling mission safety index system is established based on the range of native dust storms, dust storm-free areas, and dust storm warning times. After excluding hazardous areas, the final preferred sampling areas include safe areas and forecast areas (dust storm warning times greater than or equal to 2 sols). This addresses the problem of previous Martian sampling area selection indices that considered morphological factors while neglecting dust storm safety.

[0017] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0020] Figure 1 A schematic diagram showing the study area, native dust storms, and danger zone delineation results for one or more implementation examples; Figure 2 A schematic diagram of dust storm objects identified in one or more instance sub-observation areas; Figure 3 A schematic diagram showing the results of dividing one or more sub-study areas of an embodiment into safe zones, danger zones, and forecast zones; Figure 4 This is a schematic diagram showing the results of dividing the forecast area into two-level warning zones (dust storm warning times correspond to 1 and 2 Martian days, respectively) for one or more implementation examples. Detailed implementation method: The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0023] Example 1: This embodiment discloses a method for establishing a Martian sampling area selection index system based on dust storm characteristics, including: First, Martian dust storms were identified as either native or non-native dust storms, and features of the dust storm sequences (lifecycle and response time, etc.) were extracted. Then, based on the distribution range of native and non-native dust storms, the pre-selected landing area was divided into danger zones, safe zones, and forecast zones. Based on features such as the response time of the dust storm sequences, dust storm warning times for the forecast zones were extracted. Finally, a dust storm safety index system for the Mars sampling mission was established by comprehensively considering dust storm classification, dust storm range, and response time.

[0024] The specific steps and content include: Step 1: Classification of dust storms in the Mars landing area: native dust storms and non-native dust storms.

[0025] A Martian Year MY The solar longitude (or longitude) is the time it takes for Mars to orbit the sun once. Ls ( ) is used to represent the angle between Mars and the Sun, and one Martian day Ls The change is 0.5°. Ls The vernal equinox in the Northern Hemisphere corresponds to 0°, while the summer solstice, autumnal equinox, and winter solstice correspond to 90°, 180°, and 270°, respectively. Therefore, the solar longitude can represent the seasonal changes of Mars, with values ​​of 1, 2, …, 360 (unit: °).

[0026] Based on their origin and relationship to the study area, dust storms can be divided into primary and non-primary dust storms, originating locally within the study area and externally, generally referring to the Arctic source region. Primary dust storms: These dust storms did not appear in the previous images, nor did they originate from another region and move there; rather, they appeared within the study area on that day. Assuming there are a total of... p A set of color remote sensing images of Mars for 1 Martian year, with one image corresponding to one Martian day (sol), and a time interval of 0.5 months between two consecutive images. Ls The entire process of the future Mars sampling mission (from landing and sampling to takeoff) will take place in [time period]. Ls 1, Ls 2).

[0027] Assume the latitudinal range of the rectangular study area S of the Mars sampling mission is... Lat 1 and Lat 2, and Lat 1< Lat 2. Generally speaking, in order to obtain sufficient sunlight and have good communication conditions, Lat 1, Lat 2∈[17°N, 30°N]. Most Martian dust storms originate in the Arctic region and then move south through the study area. Therefore, to identify and extract Martian dust storm sequences, the area for dust storm identification in this example is extended northward in latitude to 60°N, i.e., […]. Lat [1, 60°N], designated as identification region S'. Identification and extraction in Mars color remote sensing imagery. p Martian years, sampling mission time period [ Ls 1, Ls [2] Identify all dust storm objects in region S' and generate a dust storm dataset D. Then, determine whether each dust storm object is a native dust storm or a non-native dust storm, and divide the dust storm dataset D into a native dust storm set D-1 and a non-native dust storm set D-2.

[0028] Step 2: Martian dust storm sequence extraction and feature calculation.

[0029] Based on the dust storm dataset D identified earlier, extract... pThe sampling mission period during a Martian year [ Ls 1, Ls [2] Identify all dust storm sequences in region S'.

[0030] In this implementation example, dust storm sequences are determined through visual interpretation. The rules are as follows: after identifying a dust storm in a color image, search for dust storms near that location in the next Martian-day remote sensing image. Combining physical proximity (direction of movement and expansion), morphological and textural similarity, determine, identify, and track the dust storm's appearance in different images until it disappears in subsequent images. A dust storm sequence consists of the same dust storm object appearing in the first image and appearing in the last image before disappearing. The duration of the dust storm object in the sequence must be greater than one Martian day, meaning it must appear continuously in at least two consecutive remote sensing images.

[0031] In one implementation example, a dust storm sequence set DS is generated in the identification region S', containing a total of m There are 3 dust storm sequences, each represented as DS. i where i = 1, 2, ..., m Each dust storm sequence contains multiple dust storm objects identified from different images. Assuming the dust storm sequence DS... i Among them, there are a total of n A dust storm, denoted as DS ij , where j=1, 2, …, n The dust storm sequence DS can also be obtained. i Duration (Life Cycle) DS i ( T )= n .

[0032] In one or more implementation examples, the dust storm response time and response range relative to the study area S are calculated for the dust storm sequence set DS. The range and response time (Mars days from the generation of the dust storm sequence to its movement to the study area S) of each dust storm sequence in the dust storm sequence set DS are extracted. The interval between consecutive Mars remote sensing images is... Ls =0.5°, which is one Martian day.

[0033] In one implementation example, a dust storm sequence DS i For example, its lifecycle is DS i ( T That is, the dust storm objects in this dust storm sequence are in continuous... T It appeared in the Mars remote sensing image. Because the dust storm sequence does not necessarily originate in the study area S, it is assumed that its [number]th [dust storm sequence]... a The dust storm objects in the image reach the study area (any overlap is acceptable). a ∈[1, DSi ( T The dust storm in this image is DS. ia DS ia Spatial intersection with the study area S yields the intersection polygon, which is the dust storm response range S-DS. ia At the same time, the response time S-DS corresponding to the response range ia (T) is set as a -1. This means that S-DS in study area S ia Region, in dust storm sequence DS i After the source region is generated, it needs to be a It would take one Martian day to reach that region. Then, continue with the dust storm sequence DS. i middle a +1 image of the dust storm object DS i(a+1) Continue the assessment. If the dust storm object also overlaps with the study area S, record the dust storm response time and response range in the a+1 images. Repeat the above process until the dust storm sequence DS is generated. i Response range set S-DS ij and the corresponding response time set S-DS ij (T), where j= a , a +1, …, b , b For this dust storm sequence DS i The image number corresponding to the last appearance of the dust storm object in the study area S. If the dust storm sequence DS... i If a dust storm does not reach the study area S during its entire lifecycle, then none of the dust storm pairs in the dust storm sequence have a corresponding response time or range, meaning they will not affect the study area S.

[0034] In one implementation example, when i=1, 2, ..., m For each dust storm sequence DS in the dust storm sequence set DS i Repeat the above process to obtain the dust storm sequence set DS relative to the study area S, the dust storm response range set S-DS, and the response time set S-DS(T).

[0035] Step 3: Establishment and zoning of the dust storm safety index system for the study area.

[0036] (3-1) Hazard zone delineation The primary dust storms did not originate from elsewhere and then migrated there; rather, they appeared in the study area on the same day. Therefore, to predict or forecast primary dust storms, continuous 24-hour (Mars-like) observation of the study area is necessary, which is currently beyond the capabilities of Mars' remote sensing, in-situ observation methods, and data processing techniques. Given the spatiotemporal similarity of Martian atmospheric activity (i.e., the same weather phenomenon may recur at the same time and place), and to ensure that dust storm events are minimized during the Mars sampling mission, these in-situ primary dust storm regions (i.e., dust storm source areas) that are difficult to predict due to lack of buffer time analysis are classified as danger zones (requiring strict exclusion).

[0037] First, the union of all native dust storm polygons in the native dust storm set D-1 within the identification area S' is calculated to generate a native dust storm polygon DA (i.e., the native dust storm region). Then, the intersection of DA and the study area S is calculated, resulting in the polygon DAS, which represents the danger zone. This region (the source region of Martian dust storms) is unsuitable for use as a Mars sampling mission.

[0038] (3-2) Safe Zone Division If a location in study area S is p Martian years, sampling mission time period [ Ls 1, Ls Since no dust storm objects were found in [2], it can be assumed that dust storm activity is unlikely to occur at this location during future sampling missions, and these areas are defined as safe zones.

[0039] First, the polygons of all dust storms (native and non-native dust storms) in the dust storm set D within the identification area S' are joined to generate a dust storm polygon DB (i.e., the dust storm region). Then, the complement of DB and the study area S is obtained, resulting in a polygon DBS, which is the safe zone. This region is considered suitable for Mars sampling.

[0040] (3-3) Forecast area division Aside from the primary dust storm region and the safe zone, the remaining area in study region S is the region with dust storm sequence pathways (DC), also known as the forecast region. This forecast region does not generate dust storms; any dust storms that do occur originate from dust storms originating in other locations (such as the Arctic or surrounding areas) and then move towards it. Therefore, the time required for a dust storm sequence to travel from its source region to this region (response time) is crucial, directly affecting whether dust storms can be predicted and forecasted. Given current methods of acquiring Martian atmospheric data and their spatiotemporal resolution, real-time analysis and prediction of dust storms in the study region are not yet possible. Therefore, whether dust storms can be predicted during the "observation vacuum period" between the current remote sensing imagery of the study region and the next repeated imagery is critical.

[0041] In other words, assuming no primary dust storms originate in study area S1, and only dust storm sequences originating from region S2, and that dust storm sequences originating from region S2 reach region S1 after at least [a certain timeframe]... q There are c Martian days. Therefore, to predict the dust storm occurrence in region S1 on the c-th Martian day, we only need to analyze the events before c. q The image is taken within a Martian day. If no dust storm appears in region S2 in the image, then even if a dust storm occurs in region S2 during the subsequent "observation vacuum period," it will not reach region S1 on Martian day c. Therefore, region S1 is safe.

[0042] In one implementation example, the forecast area DC is divided into regular grids. Assume the resulting grid set is G, with a total of... n 1 grid, where the first i The number of grids is G. i ,in i =1, 2, …, n 1. Set the mesh G i Each dust storm response range polygon in the dust storm response range set S-DS ij Find the intersection; if there is an intersection, then calculate the corresponding dust storm response time S-DS. ij (T) Record it. Assume there are a total of n Two dust storm response ranges and G i The intersection of these two sets of dust storm response times is denoted as G. i T j where j=1,2, …, n 2. Then take the dust storm response time set G. i T j The minimum value is used as the grid G. i Dust storm warning time G i (T), i.e. G i (T)=min{G i T j j=1, 2, …, n 2}. This also means that if we want to predict grid G i Whether a dust storm will occur depends on at least obtaining G. i Remote sensing images within (T) Martian days. If G i If no dust storm was detected in the remote sensing images within (T) Martian days, then even if a dust storm subsequently appears in the identification area S', it will not move to grid G. i middle.

[0043] Repeat the above process to obtain the dust storm warning time for each grid in the forecast area. Then, merge adjacent grids with the same dust storm warning time, ultimately dividing the entire forecast area into regions with different dust storm warning times. Assume the set of all dust storm warning times for the regions after the forecast area is divided is T', totaling... n There are 3 dust storm warning times, where the k-th dust storm warning time is T' k , where k=1, 2, …, n 3. Therefore, the forecast area can be divided accordingly into... n The three types of warning zones are DC k The corresponding dust storm warning time is T' k .

[0044] Step 4: Establishment of indicator system and zoning results.

[0045] Accordingly, this example proposes three indicators for selecting the landing area of ​​the Mars sampling mission: the native dust storm range (DAS), the dust storm-free range (DBS), and the dust storm warning time (T'). The first two indicators are the spatial range of the study area, and the third indicator is a set of integers of a Martian day. The three indicators together constitute the dust storm safety evaluation index system.

[0046] Based on the above indicators, the study area can be divided into safe zones, danger zones, and forecast zones to guide the selection of Mars sampling areas. The forecast zone can be further divided into multiple warning zones based on dust storm warning times. Safe zones are areas where no dust storms have occurred in the observation history and can be used for Mars sampling. Danger zones are the source areas of Martian dust storms and need to be excluded. Forecast zones require forecasting and analyzing dust storms within the region based on Martian remote sensing imagery and warning times. Areas with longer dust storm warning times are generally considered safe sampling zones; typically, the warning time should be at least two Martian days. Of course, the longer the warning time, the better, as it provides sufficient buffer time for dust storm forecasting.

[0047] Based on the classification of Martian dust storms and the feature extraction results of dust storm sequences, this embodiment establishes a safety evaluation index system for Mars sampling missions, which includes three indicators: the range of native dust storms, dust storm-free areas, and dust storm warning time. The study area is divided into safe zones, dangerous zones, and forecast zones, providing a method for selecting safe sampling areas for future Mars exploration missions.

[0048] Research examples: 1. Scope and time period of the study: This example is based on my country's future Mars sampling mission. Considering the favorable conditions of good communication, ample sunlight, and flat terrain, the study area for this invention is located in Chryse Planitia on Mars. Figure 1The area indicated by the black box is defined by latitude [17°N, 30°N] and longitude [5°W, 75°W]. The gray line represents the boundary of the identified primary dust storms within the study area, and the dark gray area represents the primary dust storm region, which is designated as a sampling danger zone. Furthermore, based on the Mars mission window, the Mars sampling period can be inferred to be approximately between Ls = 0° and 40°, which will be used as the study time for this example. To better identify dust storms and extract dust storm sequences, the dust storm identification area was extended northward from the study area to 60°N, referred to as the observation area.

[0049] This example uses color imagery of MOC and MARCI taken by US satellite cameras, with a spatial resolution of 6 km / pixel and a temporal resolution of Ls=0.5°. This invention uses imagery from four Martian years (MY=24 to MY=28) to identify Martian dust storms in the Ls=0°–40° timeframe and extract Martian dust storm sequences. Figure 2 As shown, a total of 1,172 Martian dust storm targets were identified in the observation area.

[0050] 2. Delineation of hazardous and safe zones based on dust storm classification: The identified Martian dust storms were classified into native and non-native dust storms. It was found that most dust storms were non-native, with only 23 classified as native, such as... Figure 3 The gray line boundary is shown in the diagram. The intersection of the original dust storm polygon region and the study area is used to generate the danger zone, which is the area that needs to be excluded from the sampling task.

[0051] Then, all dust storm objects (including non-native and native dust storms) in the study area are merged into a single polygon object, and the complement of this polygon object is calculated with the study area to obtain the safe zone (the area where no dust storms appear), which is the preferred area for the sampling task. At this point, the remaining area of ​​the study area, excluding the safe zone and the danger zone, is the forecast area.

[0052] 3. Forecast zone division based on dust storm warning time: A total of 73 dust storm sequences were identified in the observation area, with lifecycles ranging from 2 to 6 sols. Among them, 35 dust storm sequences could move southward and reach the study area. The response time and response range of each dust storm in these 35 sequences were statistically analyzed. Then, dust storm warning times for each location in the forecast area were calculated, ultimately dividing the forecast area into two levels of warning zones, such as... Figure 4 As shown in the figure, areas with a warning period of one Martian day were excluded (due to the difficulty in effectively forecasting and issuing dust storm warnings), while areas with a warning period of two Martian days can be considered as future Martian sampling areas.

[0053] 4. Establishment of a dust storm safety index system for the study area: Based on the above work and analysis results, three indicators can be proposed for the selection of sampling task areas in this case study area: the primary dust storm range, the dust storm-free range, and the dust storm warning time. These three indicators together constitute the dust storm safety evaluation index system, dividing the study area into a safe zone, a danger zone, and a secondary warning zone. See Appendix for further details. Figure 4 As shown in the diagram, the safe zone and the forecast area with a warning period of two Martian days can be used as the area for the Mars sampling mission.

[0054] Example 2 The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described method.

[0055] Example 3 The purpose of this embodiment is to provide a computer-readable storage medium.

[0056] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the above method.

[0057] Example 4: Based on the method in Example 1, a system for establishing a Martian sampling area selection index system based on dust storm characteristics is disclosed, including: The Mars dust storm identification module is configured to: identify all dust storm objects in the identification area based on Mars color remote sensing images, generate a dust storm dataset, and divide the dust storm dataset into a native dust storm set and a non-native dust storm set; The danger zone module is configured to: find the union of all native dust storm polygons in the native dust storm set to generate a native dust storm polygon region, i.e., the native dust storm region; then find the intersection of the native dust storm region and the study area, and the resulting polygon is the danger zone. The safe zone module is configured to: find the union of the polygons of all dust storms in the dust storm dataset of the area where the dust storm is identified, generate a dust storm polygon, i.e., the dust storm area, and find the complement of the dust storm area and the study area to obtain the safe zone polygon. The forecast area module is configured as follows: the area remaining in the study area, excluding the native dust storm area and the safe zone, is the area with dust storm sequence pathways, referred to as the forecast area; Obtain the dust storm warning time for each grid in the forecast area, then merge adjacent grids with the same dust storm warning time, divide the entire forecast area into regions with different dust storm warning times, and then obtain the set of all dust storm warning times for the regions after the forecast area is divided. The indicator construction module is configured to: construct selection indicators for the landing area of ​​the Mars sampling mission, including: native dust storm range, dust storm-free range, and dust storm warning time; Danger zones are determined based on the primary dust storm range index, safe zones are determined based on the dust storm-free range index, and forecast zones are determined based on the dust storm warning time index.

[0058] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0059] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0060] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of one or more computer-usable storage media (including, but not limited to, disk storage, etc.) containing computer-usable program code. CD - ROM It takes the form of a computer program product implemented on (such as optical memory, etc.).

[0061] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0064] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for establishing a Martian sampling area selection index system based on dust storm characteristics, characterized by: include: Based on Mars color remote sensing images, all dust storm objects are identified in the identification area, and a dust storm dataset is generated. The dust storm dataset is divided into a native dust storm set and a non-native dust storm set. The union of all native dust storm polygons in the native dust storm set is used to generate a native dust storm polygon region, i.e., the native dust storm region. Then, the intersection of the native dust storm region and the study area is obtained, and the resulting polygon is the danger zone. The union of polygons of all dust storms in the dust storm dataset of the identified dust storm area is used to generate a dust storm polygon, i.e., the dust storm area. The complement of the dust storm area and the study area is then used to obtain the polygon, i.e., the safe area. Apart from the native dust storm area and the safe zone, the remaining area in the study area is the area with dust storm sequence pathways, referred to as the forecast area; Obtain the dust storm warning time for each grid in the forecast area, then merge adjacent grids with the same dust storm warning time, divide the entire forecast area into regions with different dust storm warning times, and then obtain the set of all dust storm warning times for the regions after the forecast area is divided. The selection criteria for the landing area of ​​the Mars sampling mission include: the range of native dust storms, the range without dust storms, and the dust storm warning time. Danger zones are determined based on the primary dust storm range index, safe zones are determined based on the dust storm-free range index, and forecast zones are determined based on the dust storm warning time index.

2. The method for establishing a Martian sampling area selection index system based on dust storm characteristics as described in claim 1, characterized in that, It also includes the Martian dust storm sequence extraction step, specifically: For the dust storm dataset, extract p During a Martian year, all dust storm sequences in the region are identified within the sampling mission period, ultimately generating a set of dust storm sequences in the identified region.

3. The method for establishing a Martian sampling area selection index system based on dust storm characteristics as described in claim 2, characterized in that, The dust storm sequence is determined by visual interpretation. The rule is: after identifying a dust storm in a color image, look for dust storms near that location in the next Mars day remote sensing image. Combine physical proximity, similarity in shape and texture to determine, identify and track the performance of the dust storm in different images until the dust storm disappears in subsequent images. A dust storm sequence consists of the same dust storm object appearing in the first image and appearing in the last image before it disappears; The duration of the dust storm in the dust storm sequence must be greater than one Martian day, meaning it must appear continuously in at least two consecutive remote sensing images.

4. The method for establishing a Martian sampling area selection index system based on dust storm characteristics as described in claim 2, characterized in that, Each dust storm sequence contains multiple dust storm objects identified from different images. Assuming the dust storm sequence DS... i Among them, there are a total of n A dust storm, denoted as DS ij , where j=1, 2, …, n The dust storm sequence DS can also be obtained. i Duration DS i ( T )= n .

5. The method for establishing a Martian sampling area selection index system based on dust storm characteristics as described in claim 2, characterized in that, it further... include: Calculate the dust storm response time and response range relative to the study area for the dust storm sequence set, including: Extract the extent and response time of each dust storm sequence when it reaches the study area from the dust storm sequence set, i.e., the Martian day from the generation of the dust storm sequence to its movement into the study area; The interval between consecutive Mars remote sensing images is one Martian day.

6. The method for establishing a Martian sampling area selection index system based on dust storm characteristics as described in claim 5, characterized in that, The extraction of the range and response time of each dust storm sequence in the dust storm sequence set when it arrives in the study area involves the following specific steps: (1) For a dust storm sequence DS i Its lifecycle is DS i ( T That is, the dust storm objects in this dust storm sequence are in continuous... T It appeared in Zhang Huoxing's remote sensing image; Let the first a Dust storm objects in Zhang Huoxing remote sensing images have reached the study area. a ∈[1, DS i ( T The dust storm in this image is DS. ia ; (2) DS ia By spatially intersecting the study area, the intersection polygon between the two is obtained, which is the dust storm response range S-DS. ia At the same time, the response time S-DS corresponding to the response range ia (T) is set as a -1 indicates that S-DS in the study area S ia Region, in dust storm sequence DS i After the source region is generated, it needs to be a It would take one Martian day to reach this area; (3) Continue to analyze the dust storm sequence DS i middle a +1 image of the dust storm object DS i(a+1) Continue to make judgments. If the dust storm object also has an intersection with the study area S, then record the dust storm response time and response range of the dust storm sequence in a+1 images respectively. (4) Repeat steps (1)-(3) until the dust storm sequence DS is generated. i Response range set S-DS ij and the corresponding response time set S-DS ij (T), where j= a , a +1, …, b , b For this dust storm sequence DS i The image number corresponding to the last time the dust storm object appeared in the study area; (5) When i=1, 2, ..., m For each dust storm sequence DS in the dust storm sequence set i Repeat steps (1)-(4) to obtain the dust storm sequence set DS relative to the study area S, the dust storm response range set S-DS, and the response time set S-DS(T).

7. The method for establishing a Martian sampling area selection index system based on dust storm characteristics as described in claim 1, characterized in that, To obtain the dust storm warning time for each grid in the forecast area, the specific steps are as follows: (a) Divide the forecast area into regular grids, and let the set of grids after division be G, with a total of n 1 grid, where the first i The number of grids is G. i ,in i =1, 2, …, n 1; (b) Mesh G i Each dust storm response range polygon in the dust storm response range set S-DS ij Find the intersection; if there is an intersection, then calculate the corresponding dust storm response time S-DS. ij (T) Record it; Assume there is a total n Two dust storm response ranges and G i The intersection of these two sets of dust storm response times is denoted as G. i T j , where j=1, 2, …, n 2; (c) Take the dust storm response time set G i T j The minimum value is used as the grid G. i Dust storm warning time G i (T), i.e., G i (T)=min{G i T j j=1, 2, …, n 2}, if we want to predict grid G i Whether a dust storm will occur depends on at least G. i Remote sensing images within (T) Martian days; (d) Repeat (a)-(c) to obtain the dust storm warning time for each grid in the forecast area.

8. A system for selecting Martian sampling areas based on dust storm characteristics is established, characterized by: include: The Mars dust storm identification module is configured to: identify all dust storm objects in the identification area based on Mars color remote sensing images, generate a dust storm dataset, and divide the dust storm dataset into a native dust storm set and a non-native dust storm set; The danger zone module is configured to: find the union of all native dust storm polygons in the native dust storm set to generate a native dust storm polygon region, i.e., the native dust storm region; then find the intersection of the native dust storm region and the study area, and the resulting polygon is the danger zone. The safe zone module is configured to: find the union of the polygons of all dust storms in the dust storm dataset of the area where the dust storm is identified, generate a dust storm polygon, i.e., the dust storm area, and find the complement of the dust storm area and the study area to obtain the safe zone polygon. The forecast area module is configured as follows: the area remaining in the study area, excluding the native dust storm area and the safe zone, is the area with dust storm sequence pathways, referred to as the forecast area; Obtain the dust storm warning time for each grid in the forecast area, then merge adjacent grids with the same dust storm warning time, divide the entire forecast area into regions with different dust storm warning times, and then obtain the set of all dust storm warning times for the regions after the forecast area is divided. The indicator construction module is configured to: construct selection indicators for the landing area of ​​the Mars sampling mission, including: native dust storm range, dust storm-free range, and dust storm warning time; Danger zones are determined based on the primary dust storm range index, safe zones are determined based on the dust storm-free range index, and forecast zones are determined based on the dust storm warning time index.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it performs the steps of the method described in any one of claims 1-7.

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