An agile satellite visibility analysis method based on along-track push-broom mode

Abstract

The present application relates to a kind of agile satellite visibility analysis method based on along meridian push scan mode, it is related to satellite mission planning and visibility analysis technical field, solve the technical problem that existing target visibility analysis method is difficult to accurately reflect the real visibility state in satellite continuous imaging process.The method comprises the following steps: obtaining imaging center point coordinate, imaging time length, satellite imaging parameter information, satellite orbit information, target shooting period;The visibility of imaging center point in shooting period is calculated, is divided according to orbit circle, and the visible information set of center point is obtained.The present application is suitable for agile optical remote sensing satellite, and the efficient visibility calculation of imaging scene along meridian is oriented, can accurately evaluate the visibility state of target in imaging process based on considering satellite attitude maneuvering characteristics and orbit constraint, to provide accurate support for task arrangement and resource scheduling.

Description

Technical Field

[0001] This invention relates to the field of satellite mission planning and visibility analysis technology, and in particular to an agile satellite visibility analysis method based on a pushbroom pattern along a meridian. Background Technology

[0002] With the continuous improvement of remote sensing technology and satellite platform capabilities, agile optical remote sensing satellites have been widely used in Earth observation missions. Compared with traditional optical remote sensing satellites, agile satellites have stronger attitude maneuverability and can complete large-angle attitude adjustments in a shorter time, thereby flexibly performing multi-target imaging tasks and improving observation efficiency and resource utilization.

[0003] In practical mission planning, to meet the imaging requirements of specific target areas, satellites often need to design imaging trajectories along specific directions (such as meridians, parallels, or oblique directions). Meridian imaging is a common and efficient observation method, particularly suitable for longitudinal strip coverage in mid- and low-latitude regions. However, unlike fixed-swath downward-looking imaging, meridian imaging requires the satellite to continuously maintain attitude changes over a certain period and ensure the target remains continuously visible within the observable range, placing higher demands on target visibility analysis. For example... Figure 1 As shown, point A is the imaging point at the start of imaging, point A′ is the satellite's nadir point at the start of imaging, point M is the imaging center point, point B is the imaging point at the end of imaging, and point B′ is the satellite's nadir point at the end of imaging.

[0004] Most commonly used target visibility analysis methods are based on pushbroom imaging modes along the orbit. These methods struggle to accurately reflect the true visibility state during continuous satellite imaging, especially when dealing with the rapid attitude changes of agile satellites. Particularly in meridian imaging scenarios, the relationship between the target and the satellite's line of sight is more complex, and traditional calculation methods are prone to bias, affecting the coverage effect of strip imaging. Summary of the Invention

[0005] This invention aims to address the technical problem that existing target visibility analysis methods cannot accurately reflect the true visibility state during continuous satellite imaging, and provides an agile satellite visibility analysis method based on a meridian pushbroom pattern.

[0006] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0007] An agile satellite visibility analysis method based on a meridian pushbroom pattern includes the following steps:

[0008] Step 1: Obtain the coordinates p of the imaging center point c =(lo c ,la c), imaging duration d, satellite imaging parameter information, satellite orbit information, target acquisition cycle;

[0009] Step 2: Calculate the visibility of the imaging center point within the shooting cycle, divide it according to the orbital revolution, and obtain the visible information set S of the target center point; if the visible information set S is empty, it means that the target center point has no visible window within the shooting cycle, and the process ends; otherwise, proceed to step 3;

[0010] Step 3: Filter out visible information that does not meet the requirements of side swing and solar altitude angle from the visible information set S, mark it as unusable, and delete it from the visible information set S. For each remaining element s in the visible information set S, execute step 4.

[0011] Step 4: Obtain the visible time t and lateral sway r of the imaging center point, and calculate the imaging start time t based on the imaging duration and the visible time of the center point. s and end time t e , that is, the visible time between the imaging start point and the imaging end point;

[0012] Step 5: Calculate the imaging start time t s Until the end time t e The satellite's trajectory during the period, and the t value obtained within the satellite's trajectory. s and t e The satellite position coordinates are p s =(lo s ,la s ) and p e =(lo e ,la e ), respectively for p s and p e Proceed to steps 6 and 7;

[0013] Step 6: Starting from imaging point p s Calculate the lateral sway r at the imaging starting point s ;

[0014] Step 7: Repeat step 6 to calculate the lateral sway r at the imaging endpoint at the end of imaging. e ;

[0015] Step 8: For each element s in the visible information set S, set the visible window information and determine the lateral sway r of the imaging start point at the beginning of imaging. s And the lateral sway r at the end of the imaging process e If the side-swing limit is not met, it is marked as not meeting the non-track imaging requirements and removed from the visible information set S;

[0016] Step 9: For each element s in the visible information set S, determine whether the cloud amount of the visible window meets the requirements. If it does not meet the requirements, mark it as having insufficient cloud amount and remove it from the visible information set S; otherwise, mark the window as available; the process ends.

[0017] In the above technical solution, step 6 specifically includes:

[0018] Step 6.1: Use the single approximation method to initially determine the lateral swing range of the imaging starting point;

[0019] Step 6.2: Use a segmented step-by-step iterative method to reduce the lateral swing range;

[0020] Step 6.3: Obtain the lateral sway r of the imaging starting point using the interval convergence search method. s .

[0021] In the above technical solution, step 6.1 specifically includes:

[0022] Step 6.1.1: Using the lateral swing r of the imaging center point as the initial value, calculate t. s The coordinates of the satellite's imaging point at that time are p0 = (lo0, la0);

[0023] Step 6.1.2: Given an initial step size of 0.01, calculate the imaging start time t. s The coordinates of the imaging point when the lateral swing is r+0.01 are p0'=(lo0′,la0′);

[0024] Step 6.1.3: In the meridian sweep mode, the longitudes of the imaging start point, imaging center point, and imaging end point are the same. Based on lo0 and lo0′ and the longitude lo of the imaging center point... c The relative distance determines the lateral swing range of the imaging starting point; if |lo0′-lo c |<|lo0-lo c The statement indicates that as the lateral sway increases, the longitude of the imaging point is closer to the longitude of the target. Therefore, the lateral sway r at the imaging starting point... s ∈(r,r max Otherwise, |lo0′-lo c |>|lo0-lo c The statement indicates that as the lateral sway increases, the longitude of the imaging point is farther from the longitude of the target point. Therefore, the lateral sway r at the imaging starting point... s ∈[r min ,r).

[0025] In the above technical solution, step 6.2 specifically includes:

[0026] Step 6.2.1: Using the lateral swing r of the imaging center point as the initial value, set the recursive step size according to the lateral swing range determined in Step 6.1. If r s ∈(r,rmax If the step size is Δr, set it to 1; otherwise, set it to -1.

[0027] Step 6.2.2: Starting from r, gradually adjust the lateral swing value by accumulating the step size to form a new lateral swing interval. Calculate the coordinates of the imaging point when the lateral swing occurs with the two endpoints of the interval as the imaging start point. If the longitude is greater than lo, c or both are less than lo c Then repeat the process until the object is tilted at both ends of a certain interval, lo c Between the calculated longitude coordinates of the two imaging points, the lateral sway of the imaging starting point belongs to this interval; assuming a lateral sway interval is [r+i*Δr, r+(i+1)*Δr], if r s =r+i*Δr or r s When the longitude of the imaging point lo′ is equal to r+(i+1)*Δr, the longitude lo′ is equal to lo. c Proceed directly to step 7; if r s When the longitude of the imaging point lo′ > lo is equal to r + i * Δr c And r s =r+(i+1)*Δr when lo′ <lo c , or r s =r+i*Δr lo′ <lo c And r s When = r + (i + 1) * Δr, lo′ > lo c Then r s ∈(r+i*Δr,r+(i+1)*Δr).

[0028] In the above technical solution, step 6.3 specifically includes:

[0029] Step 6.3.1: Perform a binary search iteration on the initial interval obtained in Step 6.2, setting the initial range to [r+i*Δr, r+(i+1)*Δr]. Initialize the left boundary L = r+i*Δr and the right boundary R = r+(i+1)*Δr, and calculate the midpoint mid:

[0030]

[0031] Step 6.3.2: Calculate t respectively s When r s =L, r s =mid,r s When =R, the longitude of the imaging point is lo L lo mid lo R ;

[0032] (1) If lo mid =lo c rs =mid, proceed to step 7;

[0033] (2) When lo L >lo c And lo R <lo c At that time, if lo mid >lo c Update the left boundary L = mid; if lo mid <lo c Update the right boundary R = mid;

[0034] (3) When lo L <lo c And lo R >lo c At that time, if lo mid >lo c Update the right boundary R = mid; if lo mid >lo c Update the left boundary L = mid;

[0035] Step 6.3.3: Repeat step 6.2.2 until |lo mid -lo c |<0.001, resulting in r s =mid.

[0036] In the above technical solution, the visibility information in the visible information set S in step 2 includes: imaging position coordinates, side sway, solar altitude angle, and visible time.

[0037] In the above technical solution, in step 8, for each element s in the visible information set S, the visible window information is set, including: imaging start time and side swing, imaging end time and side swing.

[0038] The present invention has the following beneficial effects:

[0039] The agile satellite visibility analysis method based on the meridian pushbroom mode of the present invention is applicable to agile optical remote sensing satellites and is designed for efficient visibility calculation in meridian imaging scenarios. It can accurately assess the visibility status of the target during the imaging process based on the satellite attitude maneuver characteristics and orbital constraints, thereby providing accurate support for mission orchestration and resource scheduling. Attached Figure Description

[0040] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0041] Figure 1 (a) is a schematic diagram of imaging along the track, and (b) is a schematic diagram of imaging along the meridian.

[0042] Figure 2 This is a flowchart of the agile satellite visibility analysis method based on the meridian pushbroom pattern of the present invention.

[0043] Figure 3 This is a simulation diagram of the push-broom imaging results along the track.

[0044] Figure 4 This is a simulation diagram of the push-broom imaging results along the meridian. Detailed Implementation

[0045] The inventive concept of this invention is as follows:

[0046] The key to the visibility calculation method of meridian push-broom imaging based on the latitude and longitude of the target center point and the imaging duration is to calculate the lateral tilt angle of the satellite at the start and end times of imaging. The method of this invention uses a combination of piecewise step iteration and interval convergence to calculate the lateral tilt at the start and end times of imaging, thereby obtaining the visible window of the satellite on the target within the imaging cycle.

[0047] The present invention will now be described in detail with reference to the accompanying drawings.

[0048] The agile satellite visibility analysis method based on meridian pushbroom pattern of the present invention, such as Figure 2 As shown, it includes the following steps:

[0049] Step 1: Obtain the coordinates p of the imaging center point c =(lo c ,la c ), imaging duration d, satellite imaging parameter information, satellite orbit information, and target acquisition cycle.

[0050] Step 2: Calculate the visibility of the imaging center point within the shooting cycle. Divide the data according to the orbital revolutions to obtain the visible information set S of the target center point. The visibility information mainly includes the imaging position coordinates, side sway, solar altitude angle, and visible time. If the visible information set S is empty, it means that the target center point has no visible window within the shooting cycle, and the process ends; otherwise, proceed to step 3.

[0051] Step 3: Filter out visible information that does not meet the requirements of side swing and solar altitude angle from the visible information set S, mark it as unavailable, and delete it from the visible information set S. For each remaining element s in the visible information set S, execute step 4.

[0052] Step 4: Obtain the visible time t and lateral sway r of the imaging center point, and calculate the imaging start time t based on the imaging duration and the visible time of the center point. s and end time t e This refers to the visible time between the imaging start point and the imaging end point.

[0053] Step 5: Calculate the imaging start time t s Until the end time t e The satellite's trajectory during the period, and the t value obtained within the satellite's trajectory. s and t e The satellite position coordinates are p s =(lo s ,la s ) and p e =(lo e ,la e ), respectively for p s and p e Proceed to steps 6 and 7.

[0054] Step 6: Starting from imaging point p s For example, calculate the lateral sway r at the imaging starting point. s The steps include:

[0055] Step 6.1: Use the single approximation method to initially determine the lateral swing range of the imaging starting point.

[0056] Step 6.1.1: Using the lateral swing r of the imaging center point as the initial value, calculate t. s The coordinates of the satellite's imaging point at that time are p0 = (lo0, la0).

[0057] Step 6.1.2: Given an initial step size of 0.01, calculate the imaging start time t. s The coordinates of the imaging point when the lateral swing is r+0.01 are p0'=(lo0′,la0′).

[0058] Step 6.1.3: In the meridian sweep mode, the longitudes of the imaging start point, imaging center point, and imaging end point are the same. Based on lo0 and lo0′ and the longitude lo of the imaging center point... c The relative distance is used to determine the lateral sway range of the imaging starting point. If |lo0′-lo c |<|lo0-lo c The statement indicates that as the lateral sway increases, the longitude of the imaging point is closer to the longitude of the target. Therefore, the lateral sway r at the imaging starting point... s ∈(r,r max Otherwise, |lo0′-lo c |>|lo0-lo c The statement indicates that as the lateral sway increases, the longitude of the imaging point is farther from the longitude of the target point. Therefore, the lateral sway r at the imaging starting point... s ∈[r min ,r).

[0059] Step 6.2: Use a segmented step-by-step iterative method to reduce the lateral swing range.

[0060] Step 6.2.1: Using the lateral swing r of the imaging center point as the initial value, set the recursive step size according to the lateral swing range determined in Step 6.1. If r s ∈(r,r max If the step size is Δr, set it to 1; otherwise, set it to -1.

[0061] Step 6.2.2: Starting from r, gradually adjust the lateral swing value by accumulating the step size to form a new lateral swing interval. Calculate the coordinates of the imaging point when lateral swinging with the two endpoints of the interval as the imaging start point. If the longitude is greater than lo, c or both are less than lo c Then repeat the process until the object is tilted at both ends of a certain interval, lo c Between the calculated longitude coordinates of the two imaging points, the lateral sway of the imaging starting point belongs to this interval. Assuming a lateral sway interval is [r+i*Δr, r+(i+1)*Δr], if r s =r+i*Δr or r s When the longitude of the imaging point lo′ is equal to r+(i+1)*Δr, the longitude lo′ is equal to lo. c Proceed directly to step 7. If r s When the longitude of the imaging point lo′ > lo is equal to r + i * Δr c And r s =r+(i+1)*Δr when lo′ <lo c , or r s =r+i*Δr lo′ <lo c And r s When = r + (i + 1) * Δr, lo′ > lo c Then r s ∈(r+i*Δr,r+(i+1)*Δr).

[0062] Step 6.3: Obtain the lateral swing using the interval convergence search method.

[0063] Step 6.3.1: Using the interval obtained in Step 6.2 as the initial interval, perform a binary search iteration, setting the initial range to [r+i*Δr, r+(i+1)*Δr]. Initialize the left boundary L = r+i*Δr and the right boundary R = r+(i+1)*Δr, and calculate the midpoint mid:

[0064]

[0065] Step 6.3.2: Calculate t respectively s When r s =L, r s =mid,r s When =R, the longitude of the imaging point is lo L lo mid lo R.

[0066] (1) If lo mid =lo c r s =mid, proceed to step 7.

[0067] (2) When lo L >lo c And lo R <lo c At that time, if lo mid >lo c Update the left boundary L = mid; if lo mid <lo c Update the right boundary R = mid.

[0068] (3) When lo L <lo c And lo R >lo c At that time, if lo mid >lo c Update the right boundary R = mid; if lo mid >lo c Update the left boundary L = mid.

[0069] Step 6.3.3: Repeat step 6.2.2 until |lo mid -lo c |<0.001, resulting in r s =mid.

[0070] Step 7: Repeat step 6 to calculate the lateral sway r at the imaging endpoint at the end of imaging. e .

[0071] Step 8: For each element s in the visible information set S, set the visible window information, including imaging start time and lateral tilt, imaging end time and lateral tilt, etc., and determine the lateral tilt r at the start of imaging. s And the side swing at the end of imaging e If the side-swing constraint is not met, it is marked as not meeting the non-track imaging requirement and removed from the visible information set S.

[0072] Step 9: For each element s in the visible information set S, determine whether the cloud amount of the visible window meets the requirements. If it does not meet the requirements, mark it as having insufficient cloud amount and remove it from the visible information set S; otherwise, mark the window as available. End of process.

[0073] Taking islands as an example, satellites were used to take pictures in both along-orbit pushbroom mode and along-meridian mode, and simulation calculations were performed. The orbital parameters of the simulation scenarios are shown in Table 1, and the scanning strip parameters are shown in Tables 2 and 3, respectively.

[0074] Table 1. Track parameters of the simulation scenario

[0075]

[0076] Table 2. Strip parameters of track-side sweeping

[0077]

[0078] Table 3. Strip parameters swept along the meridian

[0079]

[0080] The along-track sweeping mode and the along-meridian sweeping mode are respectively as follows: Figure 3 and Figure 4 As shown in the simulation results, imaging using the along-track pushbroom mode requires three transits and takes 14 days to complete; imaging using the meridian mode requires only one transit and can be completed within one day. Therefore, for targets extending along a meridian or partially extending along a meridian, imaging using the meridian-based imaging mode or a combination of along-track pushbroom and meridian-based imaging significantly improves observation efficiency.

[0081] The agile satellite visibility analysis method based on the meridian pushbroom mode of the present invention is applicable to agile optical remote sensing satellites and is designed for efficient visibility calculation in meridian imaging scenarios. It can accurately assess the visibility status of the target during the imaging process based on the satellite attitude maneuver characteristics and orbital constraints, thereby providing accurate support for mission orchestration and resource scheduling.

[0082] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. An agile satellite visibility analysis method based on a meridian pushbroom pattern, characterized in that, Includes the following steps: Step 1: Obtain the coordinates of the imaging center point Imaging duration Satellite imaging parameters, satellite orbit information, and target acquisition cycle; Step 2: Calculate the visibility of the imaging center point within the shooting cycle, divide it according to the orbital revolution, and obtain the visible information set S of the target center point; if the visible information set S is empty, it means that the target center point has no visible window within the shooting cycle, and the process ends; otherwise, proceed to step 3; Step 3: Filter out visible information that does not meet the requirements of side swing and solar altitude angle from the visible information set S, mark it as unusable, and delete it from the visible information set S. For each remaining element s in the visible information set S, execute step 4. Step 4: Obtain the visibility time of the imaging center point and side swing The imaging start time is calculated based on the imaging duration and the visible time of the center point. and end time , that is, the visible time between the imaging start point and the imaging end point; Step 5: Calculate the imaging start time End time The satellite's trajectory during the period, and the data obtained within the satellite's trajectory. and The satellite position coordinates are respectively and , respectively and Proceed to steps 6 and 7; Step 6: Starting from the imaging point For the target point, a single approximation method is used to determine the lateral swing range of the imaging starting point. Within this range, a piecewise step-by-step iterative method is used to narrow down the lateral swing range. Finally, within the narrowed lateral swing range, an interval convergence search method is used to obtain the lateral swing of the imaging starting point. ; Step 7: Using the imaging end point For the target point, calculate the lateral sway at the imaging end point according to the method described in step 6. ; Step 8: For each element s in the visible information set S, set the visible window information and determine the lateral sway of the imaging start point at the beginning of imaging. Lateral sway at the end of imaging and the end of imaging If the side-swing limit is not met, it is marked as not meeting the non-track imaging requirements and removed from the visible information set S; Step 9: For each element s in the visible information set S, determine whether the cloud amount in the visible window meets the requirements. If it does not meet the requirements, mark it as having insufficient cloud amount and remove it from the visible information set S. Otherwise, the marker window becomes available; the process ends.

2. The agile satellite visibility analysis method based on meridian pushbroom pattern according to claim 1, characterized in that, Step 6 specifically includes: Step 6.1: Use the single approximation method to initially determine the lateral swing range of the imaging starting point; Step 6.2: Use a segmented step-by-step iterative method to reduce the lateral swing range; Step 6.3: Obtain the lateral sway of the imaging starting point using the interval convergence search method. .

3. The agile satellite visibility analysis method based on meridian pushbroom pattern according to claim 2, characterized in that, Step 6.1 specifically includes: Step 6.1.1: Lateral swing around the imaging center point Calculate using the initial value. Coordinates of the imaging point of the satellite at any time ; Step 6.1.2: Given an initial step size of 0.01, calculate the imaging start time. In the side swing Image point coordinates at time ; Step 6.1.3: In the meridian sweep mode, the longitudes of the imaging start point, imaging center point, and imaging end point are the same. According to... and Longitude of the imaging center point The relative distance determines the lateral swing range of the imaging starting point; if This indicates that after the lateral sway increases, the longitude of the imaging point is closer to the longitude of the target, thus increasing the lateral sway at the imaging starting point. ;otherwise, This indicates that as the lateral sway increases, the longitude of the imaging point is farther from the longitude of the target point, thus increasing the lateral sway at the imaging starting point. .

4. The agile satellite visibility analysis method based on meridian pushbroom pattern according to claim 2, characterized in that, Step 6.2 specifically includes: Step 6.2.1: Lateral swing around the imaging center point As the initial value, the recursive step size is set according to the lateral swing range determined in step 6.

1. Set step size ;otherwise, ; Step 6.2.2: From Initially, the lateral swing value is gradually adjusted by accumulating step sizes to form a new lateral swing interval. The coordinates of the imaging point are calculated when the longitude is greater than the two endpoints of the interval. or both are less than Then repeat this process until the object is tilted at both ends of a certain interval. Between the calculated longitude coordinates of the two imaging points, the lateral sway of the imaging starting point belongs to this interval; assuming a lateral sway interval is... ,like Sometimes Longitude of imaging point Proceed directly to step 7; if Longitude of imaging point and hour ,or hour and hour ,but .

5. The agile satellite visibility analysis method based on meridian pushbroom pattern according to claim 4, characterized in that, Step 6.3 specifically includes: Step 6.3.1: Perform a binary search iteration using the initial interval obtained in Step 6.2, setting the initial range as... Initialize the left boundary right boundary Calculate the midpoint : Step 6.3.2: Calculate separately When , , At that time, the longitude of the imaging point , , ; (1) If , Proceed to step 7; (2) When and At that time, if Update the left boundary ;like Update the right boundary ; (3) When and At that time, if Update the right boundary ;like Update the left boundary ; Step 6.3.3: Repeat step 6.2.2 until... ,get .

6. The agile satellite visibility analysis method based on meridian pushbroom pattern according to claim 1, characterized in that, The visibility information in the visible information set S in step 2 includes: imaging position coordinates, side sway, solar altitude angle, and visible time.

7. The agile satellite visibility analysis method based on meridian pushbroom pattern according to claim 1, characterized in that, In step 8, for each element s in the visible information set S, the visible window information is set, including: imaging start time and side swing, imaging end time and side swing.

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