Method for selecting landing site based on comprehensive evaluation of small celestial body features

Abstract

The small celestial body appearance feature comprehensive evaluation landing point selection method disclosed by the application belongs to the field of deep space exploration. The method of the application is as follows: in a digital elevation map of the surface appearance of a small celestial body, the ups and downs of the surface appearance of the small celestial body are described by slope, the dispersion degree of the elevation values in a sub-region is described by local variance, the slope and the local variance of a pixel point are used as indexes, a safety landing area and autonomous navigation observation effect comprehensive evaluation model is established, the navigation requirement is integrated into the landing point selection process, the optimal landing point capable of meeting the autonomous navigation requirement of the probe is obtained by comprehensively screening the landing area, the quantitative evaluation and selection of the landing point of the probe attached to the surface of the small celestial body are realized, the landing point coordinate information is provided for subsequent real-time planning and guidance control of the attached trajectory, the autonomous navigation precision of the probe is improved under the premise of ensuring the safety of the probe attachment, and safe and accurate attachment to the surface of the small celestial body is realized.

Description

[0001] Technical Field

[0002] This invention relates to a method for selecting landing sites based on a comprehensive evaluation of the topographic features of small celestial bodies, belonging to the field of deep space exploration. Background Technology

[0003] The surface topography of small celestial bodies is complex and uncertain, containing numerous rocks, steep slopes, and impact craters, posing a threat to the safety of the probe. To achieve successful attachment and exploration of small celestial bodies, the probe needs the ability to identify and assess obstacles in the surface topography, enabling rapid and accurate searching of safe landing areas. Furthermore, due to the vast distance between the small celestial bodies and Earth, and the limited prior information, there is a significant communication delay between the probe and the ground near the small celestial body. Therefore, the probe needs high-precision autonomous navigation capabilities during attachment, using its onboard measurement and computing devices to determine its own motion state and navigation parameters in real time without relying on ground equipment, providing necessary status information to the guidance and control system. The choice of landing point affects the observation of navigation features during landing, thus impacting the performance of autonomous navigation. Currently, scholars both domestically and internationally have conducted some research on landing point selection algorithms based on the three-dimensional topography of small celestial bodies. Most of these methods primarily consider attachment safety and establish different evaluation criteria, but lack consideration for the autonomous navigation observation requirements during attachment. Summary of the Invention

[0004] The purpose of this invention is to provide a method for selecting landing points by comprehensively evaluating the topographic features of small celestial bodies. This method is used to select landing points for small celestial body attachment missions. By establishing a comprehensive evaluation model of safe landing areas and autonomous navigation observation effects, navigation requirements are integrated into the landing point selection process. By comprehensively screening the landing areas, the optimal landing point that can meet the autonomous navigation requirements of the detector is obtained. This enables quantitative evaluation and selection of landing points for detector attachment on the surface of small celestial bodies, providing landing point coordinate information for subsequent real-time planning and guidance control of the attachment trajectory. Under the premise of ensuring the safety of detector attachment, this method improves the autonomous navigation accuracy of the detector and achieves safe and accurate attachment to the surface of small celestial bodies.

[0005] The present invention is achieved through the following technical solution.

[0006] The method for selecting landing sites based on comprehensive evaluation of the morphological features of small celestial bodies disclosed in this invention includes the following steps:

[0007] Step 1: In the digital elevation map of the surface topography of the small celestial body, the slope is used to describe the undulation of the surface topography, and the local variance is used to describe the dispersion of elevation values ​​in a certain sub-region. The slope and local variance of the pixels are used as indicators to evaluate the surface topography of the small celestial body. The relationship between the slope and local variance data of the pixels and a given threshold is compared. Navigation features are obtained through navigation feature evaluation, and safe landing areas are obtained through safe landing area evaluation. The evaluated navigation features and safe landing areas are used as necessary conditions for subsequent accurate selection of landing points.

[0008] In digital elevation mapping (DEM), slope represents the maximum rate of change of elevation near a pixel, describing the undulating changes in the surface topography of small celestial bodies. Elevation information in a 3D image is denoted as... The first-order partial derivatives of elevation with respect to the X and Y matrices are defined as follows:

[0009]

[0010]

[0011] in, and Each pixel is located at Coordinates in the matrix and They are respectively with This matrix contains the one-dimensional coordinate information of all pixels. The slope value of each pixel is defined using its first-order partial derivatives.

[0012]

[0013] Local variance represents the dispersion of elevation values ​​within a sub-region and reflects the detailed information of an image. For each pixel, a sub-region with side length l is defined centered on that pixel, and the variance of the elevation values ​​within this sub-region is defined as the local variance of that pixel. The mean elevation value of the selected sub-region is then calculated.

[0014]

[0015] Define the local variance of the center point of this region as

[0016]

[0017] The slope and local variance of pixels are used as indicators to evaluate the surface morphology of small celestial bodies. The relationship between the slope and local variance data of pixels and a given threshold is compared. Navigation features are obtained through navigation feature evaluation, and safe landing areas are obtained through safe landing area evaluation. The evaluated navigation features and safe landing areas are used as necessary conditions for subsequent accurate selection of landing points.

[0018] Navigation features are obtained through navigation feature evaluation. The method is as follows:

[0019] To improve 3D topographic feature matching during landing navigation, pixels with significant surface undulations in the digital elevation map are used as navigation features, representing the locations of the most dramatic changes in surface topography within a local area. Given the slope and local variance, normalization is performed, and a weighted evaluation matrix is ​​defined.

[0020]

[0021] in, Weight allocation , It should be determined based on the specific requirements of the task. and These are the normalized matrices for local variance and slope, respectively. For the weighted evaluation matrix, given an evaluation threshold... When the weighted value is greater than a given threshold, the pixel is determined to be a location with relatively obvious shape features within the range. Define the navigation feature evaluation matrix. To exclude regions with low weights in the normalized matrix, i.e., regions with relatively gentle surface topography, areas in the normalized slope matrix below a threshold are excluded. The elements of the navigation feature evaluation matrix The corresponding element in is set to 0, that is,

[0022]

[0023] To avoid a large number of densely extracted features appearing in the same frame of digital elevation maps, which could affect the matching results, a minimum spacing between given topographic features is required. Constraints are imposed on feature selection. For each pixel, minimum spacing is applied. Search for the radius to determine if the pixel is itself. Within range The pixel with the largest value is considered a desired feature if it meets the requirements; otherwise, it is excluded. The remaining pixels after the search are complete constitute the set of navigation features required.

[0024] The safe landing area is determined through a safe landing area assessment. The method is as follows:

[0025] The smaller the slope and local variance at a pixel, the gentler the terrain around that pixel, and the safer the landing. Thresholds are given for the slope and local variance of each pixel. , When both metrics are below a threshold limit, the pixel is considered safe. , It can be adjusted according to the specific attachment detection requirements and related influencing factors in different detection missions.

[0026] Define the surface morphology evaluation matrix For pixels with a slope or local variance exceeding a given threshold, the corresponding element in the surface topography evaluation matrix is ​​set to 1, indicating that pixels with a corresponding element of 1 are considered dangerous points. For pixels with both slope and local variance below the given threshold, the corresponding element in the surface topography evaluation matrix is ​​set to 0, indicating that pixels with a corresponding element of 0 are considered safe points.

[0027]

[0028] The set of all safe pixels is defined as the safe region, and the set of remaining pixels is defined as the danger region. Based on this, and taking into account the detector's attachment navigation error, the navigation error radius around the danger region is determined. Pixels within the specified range are also unsuitable for landing. Define the error radius evaluation parameters. For each pixel within the safe area Choose any danger point from the danger zone. The following judgment is made:

[0029]

[0030] During the judgment process, the error radius assessment parameter is used at any dangerous point. An output of 1 indicates that the safe landing point does not meet the safe landing requirements under navigation error constraints. Considering the above limiting factors, the final safe landing area selection results are obtained.

[0031] Step 2: Starting from the autonomous navigation observation requirements of the detector attachment, and based on the given initial state information of the detector, any pixel within the safe landing area is taken as the final position of the attachment process. The attachment trajectory is obtained by calculating the given guidance law, and the observation field sequence of the attachment process is calculated based on the attachment trajectory. The guidance law includes polynomial guidance, energy-optimal guidance, and convex optimization guidance. Based on the relationship between the observation field sequence and the navigation feature position obtained in Step 1, a quantitative evaluation index for the observation effect of the navigation features is established.

[0032] Based on the given initial state information of the detector, any pixel within the safe landing area is taken as the end position of the attachment process. The attachment trajectory is obtained by calculating a given guidance law, and the observation field sequence of the attachment process is calculated based on the attachment trajectory. The guidance law includes polynomial guidance, energy-optimal guidance, and convex optimization guidance. The field of view is determined based on the field angle. By calculating the current flight altitude h, the field of view of the lidar at the current moment can be obtained, and the observation field of view sequence with the target landing point as the pixel can be obtained. The side length of the field of view is expressed as...

[0033]

[0034] Based on the observation field sequence and the positional relationship of the navigation features obtained in step one, the observation results of each frame during the detector attachment process are statistically analyzed to obtain all feature observation data during the attachment process. An index for quantitatively evaluating the overall observation effect of the features is constructed by combining the feature observation data. The quantitative evaluation index includes the proportion of frames with features in the total number of frames during the attachment process, the mean of the number of features observed during the attachment process, and the variance of the number of features observed during the attachment process.

[0035] Indicator ①: The percentage of frames with distinctive features in the total number of frames during the attachment process.

[0036]

[0037] Where N is the total number of frames during the attachment process. The number of frames in which features can be observed.

[0038] Indicator ②: The mean number of features observed during the attachment process.

[0039]

[0040] in, The number of features observed in each frame.

[0041] Indicator ③: Variance of the number of observed features during the attachment process.

[0042]

[0043] The three indicators describe whether features can be observed during the attachment process, the number of visible features, and the fluctuation of the number. These three indicators enable a quantitative evaluation of the navigation feature observation effect.

[0044] Step 3: Based on the quantitative evaluation index of navigation feature observation effect established in Step 2, define the observation effectiveness evaluation factor. In the safe landing area obtained in Step 1, select the pixel with the largest observation effectiveness evaluation factor as the landing point. This achieves the simultaneous consideration of attachment safety and navigation feature observation effect, obtaining the optimal landing point that meets the autonomous navigation requirements of the detector, and correspondingly obtaining the coordinates of the optimal landing point on the digital elevation map.

[0045] Based on the quantitative evaluation index of navigation feature observation effect established in step two, the observation effectiveness evaluation factor is defined as follows: As shown

[0046]

[0047] A higher observation effectiveness evaluation factor for a pixel indicates better feature observation performance at that pixel, meaning the pixel is more suitable as a landing point. Conversely, a lower factor indicates the pixel is unsuitable as a final landing point. Therefore, in the safe landing area obtained in step one, the pixel with the highest observation effectiveness evaluation factor ensures both landing safety and stable observation of a large number of navigation features with minimal fluctuations during the attachment process. Selecting the pixel with the highest observation effectiveness evaluation factor as the landing point represents the final comprehensive evaluation result. Should meet

[0048]

[0049] in, This is a matrix containing the observation performance evaluation factors for all pixels. The selection result considers both attachment safety and navigation feature observation effects, thus obtaining the optimal landing point that meets the autonomous navigation requirements of the detector, and correspondingly, the coordinates of the optimal landing point on the digital elevation map.

[0050] Step 4: Based on the coordinates of the optimal landing point selected in Step 3, determine the final state of the small celestial body attachment. Substitute the final state of the attachment into the guidance law given in Step 2, and combine it with the initial state of the detector to realize real-time trajectory planning and guidance control of the attachment process. This improves the autonomous navigation accuracy of the detector while ensuring the safety of the detector attachment, and achieves safe and accurate attachment to the surface of the small celestial body.

[0051] Beneficial effects

[0052] This invention discloses a method for selecting landing points by comprehensively evaluating the topographic features of small celestial bodies. In a digital elevation map of the surface topography of a small celestial body, slope describes the undulation of the surface topography, and local variance describes the dispersion of elevation values ​​within a sub-region. The slope and local variance of pixels are used as indicators to evaluate the surface topography. By comparing the slope and local variance data of pixels with a given threshold, navigation features are obtained through navigation feature evaluation, and safe landing areas are obtained through safe landing area evaluation. The evaluated navigation features and safe landing areas are used as necessary conditions for accurate landing point selection. This invention uses slope and local variance as indicators to simultaneously quantify and evaluate the surface topography and navigation features, thus both selecting landing areas that meet attachment safety requirements and obtaining features suitable for autonomous navigation.

[0053] 2. To address the issue that the selection of different landing points during the attachment process can affect the observation effect of navigation features, this invention discloses a method for comprehensively evaluating the landing point selection based on the morphological features of small celestial bodies. This method constructs three indicators to describe whether features can be observed during the attachment process, the number of visible features, and the fluctuation of that number. Based on these indicators, an observation performance evaluation factor is defined. Within the safe landing area, the pixel with the largest observation performance evaluation factor is selected as the landing point. This achieves a balance between attachment safety and navigation feature observation effect, resulting in the optimal landing point that meets the autonomous navigation requirements of the detector. This provides an intuitive and quantitative evaluation of the navigation feature observation effect during the attachment process.

[0054] 3. This invention discloses a method for selecting landing points based on a comprehensive evaluation of the topographic features of small celestial bodies. It achieves the division of safe and dangerous areas based on the surface topography information of the small celestial body through a safe landing area assessment, ensuring the safety of the landing point obtained from the comprehensive evaluation. Based on this, the navigation feature observation effect of different pixels within the safe landing area is evaluated. Landing point selection is made by comprehensively considering both surface topography and navigation features, providing landing point coordinate information for subsequent real-time planning of the attachment trajectory and guidance control. This improves the autonomous navigation accuracy of the detector while ensuring the safety of the detector's attachment, achieving safe and accurate attachment to the surface of small celestial bodies. Attached Figure Description

[0055] Figure 1 This is a flowchart of the landing site selection method for comprehensive evaluation of the morphological features of small celestial bodies disclosed in this invention;

[0056] Figure 2 shows the simulated digital elevation map of the surface of the small celestial body used in the simulation, where (a) is a three-dimensional elevation map and (b) is a top-down elevation map;

[0057] Figure 3 Results of safe landing area and navigation feature extraction;

[0058] Figure 4 shows the calculation results of the quantitative evaluation index of the navigation feature observation effect of all pixels in the safe landing area, where (a) is The calculation result, (b) is The calculation result, (c) is The calculation results;

[0059] Figure 5 The results of the observation performance evaluation factor calculation for all pixels within the safe landing area;

[0060] Figure 6 The results of a comprehensive assessment of the landing site;

[0061] Figure 7 To comprehensively evaluate the attachment trajectory under the constraints of the obtained attachment end state. Detailed Implementation

[0062] To better illustrate the purpose and advantages of the present invention, the invention will be further described below in conjunction with the accompanying drawings and examples.

[0063] This embodiment establishes a simulated digital elevation map of the surface of a small celestial body based on existing data. From the existing data, a range is selected... For a region of size m, with a step size of 0.1m, an interpolation method is used to obtain a set of... The elevation information, in which the x and y coordinates of each coordinate point are known, is used as the surface topography data of the small celestial body for subsequent simulation, as shown in Figure 2.

[0064] Under the fixed connection at the attachment point, the initial position of the detector is set as follows: initial velocity The end position is adjustable, and the engine pulse... The duration is 225s. During the simulation, the nominal trajectory of the detector can be generated using an energy-optimal guidance law. This law establishes an optimal control problem with energy optimization as the performance metric, and the control acceleration is obtained by solving the optimization problem. The analytical form of this guidance law is:

[0065]

[0066] in, For the control input of the detector, , These represent the differences between the probe's current position / velocity vector and its position / velocity vector at the target landing point, respectively. The gravitational acceleration at the probe's current position. This represents the remaining flight time.

[0067] like Figure 1As shown in the figure, this embodiment discloses a method for selecting landing sites based on a comprehensive evaluation of the topographic features of small celestial bodies. The specific implementation steps are as follows:

[0068] Step 1: In the digital elevation map of the surface topography of the small celestial body, the slope is used to describe the undulation of the surface topography, and the local variance is used to describe the dispersion of elevation values ​​in a certain sub-region. The slope and local variance of the pixels are used as indicators to evaluate the surface topography of the small celestial body. The relationship between the slope and local variance data of the pixels and a given threshold is compared. Navigation features are obtained through navigation feature evaluation, and safe landing areas are obtained through safe landing area evaluation. The evaluated navigation features and safe landing areas are used as necessary conditions for subsequent accurate selection of landing points.

[0069] A comprehensive evaluation method for surface topography based on slope and local variance is designed. Navigation features and safe landing areas are extracted based on the digital elevation map information used in the simulation. In this embodiment, slopes greater than 0.15 and local variances greater than 0.09 are considered. Areas designated as dangerous zones are defined as such. , With navigation error radius Determine the safe landing area and define the radius of all danger points. Safety points within the area are also unsuitable as landing sites. Simultaneously, a threshold for evaluating the normalized matrix is ​​specified. Minimum spacing of features Based on this, navigation features are extracted. The safe landing area and feature extraction results are as follows: Figure 3 As shown.

[0070] Step 2: Starting from the autonomous navigation observation requirements of the detector attachment, and based on the given initial state information of the detector, any pixel within the safe landing area is taken as the final position of the attachment process. The attachment trajectory is obtained by calculating the given guidance law, and the observation field sequence of the attachment process is calculated based on the attachment trajectory. The guidance law includes polynomial guidance, energy-optimal guidance, and convex optimization guidance. Based on the relationship between the observation field sequence and the navigation feature position obtained in Step 1, a quantitative evaluation index for the observation effect of the navigation features is established.

[0071] For a given pixel, an attached nominal trajectory is generated using the energy-optimal guidance law, and the imaging interval of the lidar camera is defined as follows: LiDAR field of view For each pixel, the observation field sequence of the attachment process can be calculated. Combined with the navigation feature selection results from step one, navigation feature observation data for each frame can be obtained, and the quantitative evaluation index for that pixel can be calculated based on the navigation feature observation results and the observation field sequence. , , Figure 4 shows the calculation results of the quantitative evaluation index for all pixels in the safe landing area.

[0072] Step 3: Based on the quantitative evaluation index of navigation feature observation effect established in Step 2, define the observation effectiveness evaluation factor. In the safe landing area obtained in Step 1, select the pixel with the largest observation effectiveness evaluation factor as the landing point. This achieves the simultaneous consideration of attachment safety and navigation feature observation effect, obtaining the optimal landing point that meets the autonomous navigation requirements of the detector, and correspondingly obtaining the coordinates of the optimal landing point on the digital elevation map.

[0073] Because different attachment detection missions have different detection objectives and target landing area surface morphologies, which vary significantly, it is necessary to weight the evaluation indicators according to specific mission requirements to obtain a specific expression for the observation effectiveness evaluation factor. In this embodiment, the observation effectiveness evaluation factor is defined.

[0074]

[0075] in, , All weights are adjustable. In this embodiment, we tend to select pixels where features can be continuously observed as landing points, therefore... Set it to a large value. Because... This represents the percentage of frames with distinctive features during the attachment process out of the total number of frames in the attachment process; its value range is... The interval, when the features cannot be observed throughout the attachment process of the selected pixels. To become a very small number, and vice versa. This value will remain at 1, thereby distinguishing between two types of pixels whose features can be observed throughout the entire process. This embodiment defines... , The weighted evaluation results are as follows: Figure 5 .

[0076] During the attachment process, A larger value indicates that more features can be observed during the attachment process, while A smaller value indicates a more stable number of features observed during the attachment process. When a large number of features can be observed during attachment to a pixel, and the number of features remains stable, then that pixel is determined to be a landing point that meets the landing navigation observation requirements. Considering the above constraints, an observation effectiveness evaluation factor is selected. The largest pixel is used as the target landing point. In this example, due to the spacing between adjacent pixels in the digital elevation map... Because the accuracy is high, the observation performance evaluation factors of adjacent pixels may be similar or the same. Therefore, the screening results may include a region of adjacent pixels. To address this, the pixel at the center of this region is selected as the optimal landing point. The mean x and y coordinates of the screening results are calculated, and the pixel closest to this value is found. This pixel is the target landing point. The final comprehensive evaluation and selection result of the landing point is as follows: Figure 6 As shown.

[0077] Step 4: Based on the coordinates of the optimal landing point selected in Step 3, determine the final state of the small celestial body attachment. Substitute the final state of the attachment into the guidance law given in Step 2, and combine it with the initial state of the detector to realize real-time trajectory planning and guidance control of the attachment process. This improves the autonomous navigation accuracy of the detector while ensuring the safety of the detector attachment, and achieves safe and accurate attachment to the surface of the small celestial body.

[0078] like Figure 7 Combining the given initial state information, the attachment end state obtained in step three is substituted into the formula. The attachment trajectory of the detector is calculated based on the energy-optimal guidance law.

[0079] The above detailed description further illustrates the purpose, technical solution, and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for selecting landing sites based on comprehensive evaluation of the morphological characteristics of small celestial bodies, characterized by: Includes the following steps, Step 1: In the digital elevation map of the surface topography of the small celestial body, the slope is used to describe the undulation of the surface topography, and the local variance is used to describe the dispersion of the elevation values ​​in a certain sub-region. The slope and local variance of the pixel points are used as indicators to evaluate the surface topography of the small celestial body. The relationship between the slope and local variance data of the pixel points and the given threshold is compared. Navigation features are obtained through navigation feature evaluation, and safe landing areas are obtained through safe landing area evaluation. The evaluated navigation features and safe landing areas are used as necessary conditions for subsequent accurate selection of landing points. Step 2: Starting from the autonomous navigation observation requirements of the detector attachment, based on the given initial state information of the detector, any pixel point within the safe landing area is taken as the end position of the attachment process. The attachment trajectory is obtained by calculating the given guidance law, and the observation field sequence of the attachment process is calculated based on the attachment trajectory. The guidance law includes polynomial guidance, energy optimal guidance, and convex optimization guidance. Based on the relationship between the observation field sequence and the navigation feature position obtained in Step 1, a quantitative evaluation index for the observation effect of the navigation features is established. Step 3: Based on the quantitative evaluation index of navigation feature observation effect established in Step 2, define the observation effectiveness evaluation factor; in the safe landing area obtained in Step 1, select the pixel with the largest observation effectiveness evaluation factor as the landing point, that is, simultaneously consider the attachment safety and navigation feature observation effect, and obtain the optimal landing point that can meet the autonomous navigation requirements of the detector, and obtain the coordinates of the optimal landing point in the digital elevation map. Step 4: Based on the coordinates of the optimal landing point selected in Step 3, determine the final state of the small celestial body attachment. Substitute the final state of the attachment into the guidance law given in Step 2, and combine it with the initial state of the detector to realize real-time trajectory planning and guidance control of the attachment process. This improves the autonomous navigation accuracy of the detector while ensuring the safety of the detector attachment, and achieves safe and accurate attachment to the surface of the small celestial body.

2. The method for selecting landing sites based on comprehensive evaluation of small celestial body morphology features as described in claim 1, characterized in that: The implementation method for step one is as follows: In digital elevation mapping (DEM), slope represents the maximum rate of elevation change near a pixel, describing the undulating changes in the surface topography of small celestial bodies; elevation information in a 3D image is denoted as... The first-order partial derivatives of elevation with respect to the X and Y matrices are defined as follows: in, and Each pixel is located at Coordinates in the matrix and They are respectively with The matrix corresponds to the one-dimensional coordinate information matrix of all pixels; the slope value of each pixel is defined using the first-order partial derivative. Local variance represents the dispersion of elevation values ​​within a sub-region and reflects the detailed information of an image. For each pixel, a sub-region with a side length of l is defined centered on that pixel, and the variance of the elevation values ​​in this sub-region is defined as the local variance of that pixel. The mean elevation value of the selected sub-region is then calculated. Define the local variance of the center point of this sub-region as The slope and local variance of pixels are used as indicators to evaluate the surface morphology of small celestial bodies. The relationship between the slope and local variance data of pixels and a given threshold is compared. Navigation features are obtained through navigation feature evaluation, and safe landing areas are obtained through safe landing area evaluation. The evaluated navigation features and safe landing areas are used as necessary conditions for subsequent accurate selection of landing points. Navigation features are obtained through navigation feature evaluation. The method is as follows: Pixels with significant surface undulations in the digital elevation map are used as navigation features, representing the locations with the most dramatic changes in surface topography within a local area. Given a slope and local variance, normalization is performed, and a weighted evaluation matrix is ​​defined. in, Weight allocation , It should be determined based on the specific requirements of the task. and These are the normalized matrices for local variance and slope, respectively; for the weighted evaluation matrix, a given evaluation threshold is applied. When the weighted value is greater than a given threshold, the pixel is determined to be a location with relatively obvious shape features within the range; define a navigation feature evaluation matrix. To exclude regions with low weights in the normalized matrix, i.e., regions with relatively gentle surface topography, areas in the normalized slope matrix below a threshold are excluded. The elements of the navigation feature evaluation matrix The corresponding element in is set to 0, that is, Minimum spacing between given morphological features Constrain the selection of features; for each pixel, use the minimum spacing Search for the radius to determine if the pixel is itself. Within range If the pixel with the largest value meets the requirements, it is determined to be the desired feature; otherwise, it is excluded. After the search is completed, the remaining pixels are the set of the required navigation features. The safe landing area is determined through a safe landing area assessment. The method is as follows: The smaller the slope and local variance at a pixel, the gentler the terrain around that pixel, and the safer the landing. Thresholds are given for the slope and local variance of each pixel. , When both metrics are below a threshold limit, the pixel is considered safe. , It can be adjusted according to the specific attachment detection requirements and related influencing factors in different detection missions; Define the surface morphology evaluation matrix For pixels with a slope or local variance exceeding a given threshold, the corresponding element in the surface topography evaluation matrix is ​​set to 1, indicating that pixels with a corresponding element of 1 are considered dangerous points. For pixels with both slope and local variance below the given threshold, the corresponding element in the surface topography evaluation matrix is ​​set to 0, indicating that pixels with a corresponding element of 0 are considered safe points. The set of all safe pixels is defined as the safe region, and the set of remaining pixels is defined as the danger region. Based on this, and taking into account the detector's attachment navigation error, the navigation error radius around the danger region is determined. Pixels within the range are also unsuitable for landing; define error radius evaluation parameters. For each pixel within the safe area Choose any danger point from the danger zone. The following judgment is made: During the judgment process, the error radius assessment parameter is used at any dangerous point. The output result is 1, which means that the safe point does not meet the safe landing requirements under the navigation error constraint; based on formula (8) and formula (9), the final safe landing area screening result is obtained.

3. The method for selecting landing sites based on comprehensive evaluation of small celestial body morphology features as described in claim 2, characterized in that: The second step is implemented as follows: Based on the given initial state information of the detector, any pixel within the safe landing area is taken as the end position of the attachment process. The attachment trajectory is obtained by calculating the given guidance law, and the observation field sequence of the attachment process is calculated based on the attachment trajectory. The guidance law includes polynomial guidance, energy-optimal guidance, and convex optimization guidance. Based on the field angle... By calculating the current field of view of the lidar at the current flight altitude h, the observation field of view sequence with that point as the target landing point can be obtained. The side length of the field of view is expressed as... Based on the relationship between the observation field sequence and the navigation feature position obtained in step one, the observation results of each frame during the detector attachment process are statistically analyzed to obtain all feature observation data during the attachment process. A quantitative evaluation index for assessing the overall observation effect of features is constructed by combining feature observation data. The quantitative evaluation index includes the proportion of frames with features in the total number of frames in the attachment process, the mean of the number of features observed in the attachment process, and the variance of the number of features observed in the attachment process. Indicator ①: The percentage of frames with distinctive features in the total number of frames during the attachment process; Where N is the total number of frames during the attachment process. The number of frames in which features can be observed; Indicator ②: The mean number of features observed during the attachment process; in, The number of features observed in each frame; Indicator ③: Variance of the number of observed features during the attachment process; The three indicators describe whether features can be observed during the attachment process, the number of visible features, and the fluctuation of the number. These three indicators enable a quantitative evaluation of the navigation feature observation effect.

4. The method for selecting landing sites based on comprehensive evaluation of small celestial body morphology features as described in claim 3, characterized in that: The method for implementing step three is as follows: Based on the quantitative evaluation index of navigation feature observation effect established in step two, the observation effectiveness evaluation factor is defined as follows: As shown The larger the observation performance evaluation factor corresponding to a pixel, the better the feature observation effect of attaching at that pixel, that is, the more suitable the pixel is as a landing point. Conversely, it indicates that the pixel is not suitable as the final landing point. Therefore, in the safe landing area obtained in step one, the pixel with the largest observation performance evaluation factor can not only ensure the safety of landing, but also ensure that a large number of navigation features with small fluctuations can be observed stably during the attachment process. The pixel with the highest observation effectiveness evaluation factor is selected as the landing point, which is the final comprehensive evaluation result. Should meet in, This is a matrix containing the observation performance evaluation factors of all pixels; the screening result takes into account both the attachment safety and the observation effect of navigation features, that is, it obtains the optimal landing point that can meet the autonomous navigation requirements of the detector, and the corresponding coordinates of the optimal landing point in the digital elevation map are obtained.

Images