Agile satellite visibility analysis method based on along-longitude push-broom mode

Abstract

The invention relates to an agile satellite visibility analysis method based on an along-longitude push-broom mode, relates to the technical field of satellite task planning and visibility analysis, and solves the technical problem that an existing target visibility analysis method is difficult to accurately reflect a real visibility state in a satellite continuous imaging process. The method comprises the following steps: acquiring an imaging center point coordinate, an imaging duration, satellite imaging parameter information, satellite orbit information and a target shooting period; the visibility of the imaging center point in the shooting period is calculated, division is carried out according to the number of orbital circles, and a visible information set of the center point is obtained. The agile satellite visibility analysis method based on the along-longitude push-broom mode is suitable for efficient visibility calculation of an agile optical remote sensing satellite and oriented to an along-longitude imaging scene, the visibility state of a target in the imaging process can be accurately evaluated on the basis of considering satellite attitude maneuver characteristics and orbit constraints, and the accuracy of the visibility analysis is improved. Therefore, accurate support is provided for task arrangement and resource scheduling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite mission planning and visibility analysis, and particularly relates to an agile satellite visibility analysis method based on a meridian push-scan mode. BACKGROUND

[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 maneuvering capabilities and can complete large-angle attitude adjustment in a short time, thereby flexibly executing multi-target imaging tasks and improving observation efficiency and resource utilization.

[0003] In actual mission planning, in order to meet the imaging needs of a specific target area, the satellite often needs to be designed along a specific direction (such as a meridian, a latitude or an oblique direction) for imaging trajectory design. Among them, imaging along the meridian is a common and efficient observation method, which is particularly suitable for longitudinal strip coverage in low and middle latitude areas. However, unlike the positive downward imaging with a fixed swath width, imaging along the meridian direction requires the satellite to continuously change its attitude within a certain time and ensure that the target is continuously visible within the observable range, which puts higher requirements on the visibility analysis of the target. Figure 1 As shown in the figure, point A is the imaging point at the beginning of imaging, point A' is the subsatellite point of the satellite at the beginning 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 subsatellite point of the satellite at the end of imaging.

[0004] Most of the currently commonly used target visibility analysis methods are based on the imaging mode along the orbit push-scan. These methods are difficult to accurately reflect the real visibility state in the continuous imaging process of the satellite when facing the fast attitude change characteristics of the agile satellite. Especially in the scenario of imaging along the meridian, the relationship between the target and the satellite line of sight is more complex, and the traditional calculation method is easy to cause result deviation, which affects the strip shooting coverage effect. SUMMARY

[0005] The present application solves the technical problem that the existing target visibility analysis method is difficult to accurately reflect the real visibility state in the continuous imaging process of the satellite, and provides an agile satellite visibility analysis method based on a meridian push-scan mode.

[0006] In order to solve the above technical problems, the technical scheme of the present application is as follows:

[0007] An agile satellite visibility analysis method based on a meridian push-scan mode, comprising the following steps:

[0008] Step 1: obtaining the imaging center point coordinate p 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 this 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 as [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. Simulation Scenario Track Parameters

[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 p of the imaging center point c =(lo c ,la c ), imaging duration d, satellite imaging parameter information, satellite orbit information, 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 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; 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; Step 6: Starting from imaging point p s Calculate the lateral sway r at the imaging starting point s ; Step 7: Repeat step 6 to calculate the lateral sway r at the imaging endpoint at the end of imaging. e ; 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; 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 r of the imaging starting point using the interval convergence search method. s .

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: 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); 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′); 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).

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: 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. 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).

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 on the initial interval obtained in Step 6.2, setting the initial range as [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: 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 ; (1) If lo mid =lo c r s =mid, proceed to step 7; (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; (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; Step 6.3.3: Repeat step 6.2.2 until |lo mid -lo c |<0.001, resulting in r s =mid.

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.

Images