Satellite payload performance evaluation method, device and equipment and readable storage medium

Abstract

The present disclosure relates to the technical field of spacecraft load, in particular to a satellite load efficiency evaluation method, device, equipment and readable storage medium, the method comprises: calculating the signal-to-clutter ratio of a target in each frame of a sequence image of a target life cycle under different cloud parameters, counting the proportion of the signal-to-clutter ratio of the target in the target life cycle exceeding a threshold value as target detection availability, analyzing the analytical relationship between the target detection availability and different cloud parameters, establishing an availability model, and evaluating satellite load efficiency by using the availability model, which can effectively shorten the efficiency evaluation time of typical satellite loads in the field of remote sensing.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of spacecraft load, in particular to a satellite load efficiency evaluation method, device, equipment and readable storage medium. BACKGROUND

[0002] The satellite detection load can realize real-time detection of targets in a wide area background, and has the characteristics of high detection accuracy, strong anti-interference ability, wide coverage and strong timeliness. The existing satellite load performance parameters are designed according to whether the specific background radiation characteristics and target radiation characteristics can be detected by the load. In the actual work of the satellite load, the detection background is complex and diverse according to the different underlying surface and time phase. In addition to the fixed background, there may also be a moving interference background, which will seriously affect the actual use efficiency of the satellite load.

[0003] The current satellite load efficiency evaluation method mainly adopts optical model simulation based on background and target, which can evaluate the load efficiency under different detection spectral bands, detection geometry, illumination conditions, target parameters and background types. Each time the satellite load efficiency evaluation is performed, simulation needs to be run, and a large amount of finite element analysis needs to be performed, which consumes a lot of time. SUMMARY

[0004] In order to solve the problems in the related art, the embodiments of the present disclosure provide a satellite load efficiency evaluation method, device, equipment and readable storage medium.

[0005] In a first aspect, the embodiments of the present disclosure provide a satellite load efficiency evaluation method, comprising:

[0006] calculating a signal-to-clutter ratio of a target in each frame of a sequence image of a target life cycle under different cloud parameters;

[0007] statistically calculating a proportion of the target in the target life cycle whose signal-to-clutter ratio exceeds a threshold value as a target detection availability;

[0008] analyzing an analytical relationship between the target detection availability and different cloud parameters, and establishing an availability model;

[0009] evaluating satellite load efficiency by using the availability model.

[0010] According to the embodiments of the present disclosure, the cloud parameters include the position, number, speed, area and radiation intensity of the cloud.

[0011] According to the embodiments of the present disclosure, the calculation of the signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters comprises:

[0012] determining the maximum radiation intensity of the target under different cloud parameters;

[0013] A neighborhood sliding window with a side length of n x n and m x m is set as a target, and a background radiation intensity mean value of the m x m neighborhood minus the n x n neighborhood is a neighborhood background average radiation intensity, and a standard deviation of the radiation intensity of the m x m neighborhood minus the n x n neighborhood is a neighborhood background spatial clutter; wherein n is less than m, and both are natural numbers;

[0014] According to the maximum radiation intensity of the target, the neighborhood background average radiation intensity, and the neighborhood background spatial clutter, a signal-to-clutter ratio of the target is calculated.

[0015] According to an embodiment of the present disclosure, the target detection availability is analyzed, and an analytical relationship between different cloud parameters is established to build an availability model, including:

[0016] An independent analytical model between the signal-to-clutter ratio of the target and different cloud parameters is established;

[0017] The availability model is constructed according to the independent analytical model;

[0018] A model coefficient of the availability model is determined by a regression analysis method.

[0019] According to an embodiment of the present disclosure, the availability model is in a form of one of a polynomial, an exponential function, a logarithmic function, a hyperbolic curve, a trigonometric function, a Gaussian function, a Lorentz function, and a Poisson distribution function.

[0020] In a second aspect, a satellite payload performance evaluation device is provided in an embodiment of the present disclosure, and includes:

[0021] A calculation module is configured to calculate a signal-to-clutter ratio of a target in each frame of a sequence image of a target life cycle under different cloud parameters;

[0022] A statistical module is configured to statistically calculate a proportion of the signal-to-clutter ratio of the target exceeding a threshold value in the target life cycle as a target detection availability;

[0023] An establishment module is configured to analyze the target detection availability and an analytical relationship between different cloud parameters to build an availability model;

[0024] An evaluation module is configured to evaluate satellite payload performance by using the availability model.

[0025] According to an embodiment of the present disclosure, the cloud parameters include a position, a number, a speed, an area, and a radiation intensity of a cloud.

[0026] According to an embodiment of the present disclosure, the calculation module includes:

[0027] A first determination sub-module is configured to determine a maximum radiation intensity of a target under different cloud parameters;

[0028] The first calculation sub-module is configured to set a neighborhood sliding window with a side length of n x n and m x m centered on the target, and subtract the mean value of the background radiation intensity of the n x n neighborhood from the m x m neighborhood to obtain the neighborhood background average radiation intensity, and subtract the standard deviation of the radiation intensity of the m x m neighborhood from the n x n neighborhood to obtain the neighborhood background spatial clutter, where n is less than m, and both n and m are natural numbers.

[0029] The second calculation sub-module is configured to calculate the signal-to-clutter ratio of the target according to the maximum radiation intensity of the target, the neighborhood background average radiation intensity, and the neighborhood background spatial clutter.

[0030] In a third aspect, an electronic device is provided, including a memory and a processor, wherein the memory is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the method of any one of the first aspect.

[0031] In a fourth aspect, a computer readable storage medium is provided, which stores computer instructions, and the computer instructions are executed by a processor to implement the method of any one of the first aspect.

[0032] According to the technical scheme provided by the embodiments of the present disclosure, a satellite payload performance evaluation method based on an analytical formula is provided. The signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters is calculated, the proportion of the signal-to-clutter ratio of the target in the target life cycle that exceeds the threshold value is counted as the target detection availability, the analytical relationship between the target detection availability and different cloud parameters is analyzed, the availability model is established, and the satellite payload performance is evaluated by using the availability model. The performance evaluation time of typical satellite payloads in the field of remote sensing and the like can be effectively shortened.

[0033] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0034] Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of the non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:

[0035] Figure 1 A flowchart of a satellite payload performance evaluation method according to an embodiment of the present disclosure is shown.

[0036] Figure 2 A structural block diagram of a satellite payload performance evaluation device according to an embodiment of the present disclosure is shown.

[0037] Figure 3 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0038] Figure 4 A structural diagram of a computer system suitable for implementing the method according to the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0039] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so as to be easily implemented by those skilled in the art. Also, parts irrelevant to the description of the exemplary embodiments are omitted in the accompanying drawings for the sake of clarity.

[0040] In the present disclosure, it should be understood that terms such as "include" or "have" are intended to indicate that there are features, numbers, steps, actions, parts, or combinations thereof disclosed in the specification, and do not exclude the possibility that one or more other features, numbers, steps, actions, parts, or combinations thereof exist or are added.

[0041] It is further noted that the embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0042] In the present disclosure, if the operation of acquiring user information or user data or the operation of showing user information or user data to others is involved, the operation is an operation authorized, confirmed by the user, or actively selected by the user.

[0043] The current satellite payload performance evaluation method mainly adopts optical model simulation based on background and target, which can evaluate the payload performance under different detection spectral bands, detection geometries, illumination conditions, target parameters, and background types. Each time the satellite payload performance is evaluated, simulation needs to be run, and a large amount of finite element analysis needs to be performed, which consumes a lot of time.

[0044] Figure 1 A flowchart of a satellite payload performance evaluation method according to an embodiment of the present disclosure is shown. As shown in Figure 1 The satellite payload performance evaluation method includes the following steps S101-S104:

[0045] In step S101, the signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters is calculated.

[0046] Specifically, step S101 calculates the signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters, including: determining the maximum radiation intensity of the target under different cloud parameters; setting a neighborhood sliding window with a side length of n*n and m*m centered on the target, using the background radiation intensity mean of the m*m neighborhood minus the n*n neighborhood as the neighborhood background average radiation intensity, and the radiation intensity standard deviation of the m*m neighborhood minus the n*n neighborhood as the neighborhood background spatial clutter; wherein n is less than m, and both are natural numbers; calculating the signal-to-clutter ratio of the target according to the maximum radiation intensity of the target, the neighborhood background average radiation intensity, and the neighborhood background spatial clutter.

[0047] Wherein, considering that the spatial resolution of satellite payload (such as space-based infrared detection system) is much larger than the size of the target, the target can be approximated as a point target at this time, the target involved in the present disclosure includes but is not limited to aircraft, spacecraft, airship, carrier, etc., and the fixed background where the target is located can be plain, mountainous area, desert, lake, ocean, deep space, etc. The interference background can be non-target aircraft, smoke, cloud, etc.

[0048] The prerequisite for detecting a point target in a single frame image is that there is a certain difference between the target and its neighborhood background. When detecting, a sliding window with a side length of L N is set centered on the target, the neighborhood background radiation intensity mean μ B is the background average radiation intensity of the part of the sliding window except the target, and the neighborhood background spatial clutter σ B is the background radiation intensity standard deviation of the part of the sliding window except the target. The signal-to-clutter ratio (SCR) is defined as the ratio of the absolute value of the difference between the maximum radiation intensity of the target and the neighborhood background average radiation intensity to the neighborhood background spatial clutter, and the formula is as follows:

[0049]

[0050] In the present disclosure, in order to fully evaluate the influence of different cloud parameters on the effectiveness of satellite payload in actual scenes, target and different cloud parameter (cloud position, number, area, speed, radiation intensity) simulation scene data are generated, then the maximum radiation intensity of the target in the scene is determined, and then a sliding window with a side length of 5*5 and 11*11 is set centered on the target, the background radiation intensity mean of the part of the 11*11 neighborhood minus the 5*5 neighborhood is used as the neighborhood background average radiation intensity, and the radiation intensity standard deviation is used as the neighborhood background spatial clutter, and then the signal-to-clutter ratio of the target is calculated. Wherein, the simulation image data uses an actual infrared image obtained on orbit as the background, and superimposes a Gaussian dispersed infrared dim target and a cloud with adjustable cloud parameters.

[0051] In step S102, the proportion of the signal-to-clutter ratio of the target in the target life cycle exceeding the threshold value is counted as the target detection availability.

[0052] Wherein, the target detection availability η0 is defined as the proportion of time (t0) in the target life cycle that the system detects the target with a signal-to-clutter ratio greater than a certain threshold (SCR0), and the formula is as follows:

[0053]

[0054] In step S103, the target detection availability is analyzed, and the analytical relationship between different cloud parameters is established to build an availability model.

[0055] Specifically, step S103 analyzes the target detection availability and the analytical relationship between different cloud parameters to build an availability model, including: building an independent analytical model between the signal-to-clutter ratio of the target and different cloud parameters; constructing an availability model according to the independent analytical model; and determining the model coefficients of the availability model by using a regression analysis method.

[0056] For example, the influence of different cloud parameters on the signal-to-clutter ratio of target detection is investigated. With cloud parameters (same initial position, speed of 0, area of 1, and radiation intensity of 100%) as the benchmark, different numbers of clouds (1 to 3), areas (25%, 50%, and 75%), speeds (0.1 pixel / s, 0.3 pixel / s, 0.5 pixel / s), and radiation intensities (20%, 40%, 60%) are set in the simulation scene on the target trajectory.

[0057] The proportion of the number of frames in which the signal-to-clutter ratio exceeds the threshold value in the target life cycle is counted as the target detection availability, and the corresponding target detection availability is obtained under the condition of 0 to 3 clouds, which is 100%, 75%, 59%, and 45%, respectively. Under the condition of cloud area scaling ratios of 25%, 50%, 75%, and 100%, the corresponding target detection availability is 84%, 80%, 77%, and 75%, respectively. Under the condition of cloud speeds of 0 pixel / s, 0.1 pixel / s, 0.3 pixel / s, and 0.5 pixel / s, the corresponding target detection availability is 75%, 73%, 70%, and 67%, respectively. Under the condition of cloud radiation intensity scaling ratios of 20%, 40%, 60%, and 100%, the corresponding target detection availability is 86%, 83%, 79%, and 75%, respectively.

[0058] According to the simulation data described above, the analytical relationship between the number of image frames (F) in which the signal-to-clutter ratio is lower than the threshold value and the cloud parameters (number N, area S, speed v c , and radiation intensity I) is regression analyzed to build an independent analytical model, as shown below:

[0059] F=a1+b1N,F=a2+b2S,F=a3+b3v cF = a4 + b4I

[0060] According to the above independent analysis model, combined with the physical meaning of each parameter, the availability model is established, and the model coefficients of the availability model are determined by regression analysis using the above simulation data, that is, the availability model is obtained as follows:

[0061]

[0062] To verify the practicability of the above availability model, scenarios with a large difference from the original cloud parameters need to be generated. By comparing the availability simulation value with the model prediction value, the accuracy and robustness of the model are verified. Among them, the simulation parameters of verification scenarios one and two are set to have one cloud, but the cloud position, area, speed, and radiation intensity are different from the original cloud parameters, so as to investigate whether the model established based on the simulation results of single variable change can adapt to the case of multiple variable changes. In addition, since the simulation previously changed the number of clouds without changing other parameters, verification scenarios three and four are set to have two clouds, and the position, area, speed, and radiation intensity of the clouds are changed. Finally, in verification scenario five, there are three clouds overlapping with the target trajectory, and in verification scenario six, an additional cloud is added away from the target, and the position, area, speed, and radiation intensity of each cloud are changed.

[0063] The simulation and prediction value results of the availability in the six verification scenarios are as follows:

[0064]

[0065]

[0066] In these six scenarios, the prediction value of the availability model can be well matched with the simulation value, with a maximum error of about 0.56%, and it can be considered that the model can accurately and quickly predict the availability when the cloud parameters change.

[0067] It should be noted that the availability model constructed above can be used for point target detection in a fixed cloud scenario. It can be understood that, considering the shape, speed, and position of the target, or when performing target detection in a complex cloud scenario, an availability model can be constructed in the manner of the present disclosure, and the form of the availability model can be one of a polynomial, an exponential function, a logarithmic function, a hyperbolic curve, a trigonometric function, a Gaussian function, a Lorentz function, and a Poisson distribution function, which will not be described here.

[0068] In step S104, the satellite payload performance is evaluated using the availability model.

[0069] Specifically, the cloud parameters, including the position, number, speed, area, and radiation intensity of the cloud, can be input, and the target detection availability is calculated using the availability model as an index for evaluating the satellite payload performance.

[0070] The technical scheme provided by the embodiments of the present disclosure provides a satellite payload performance evaluation method based on an analytical formula. The signal-to-clutter ratio of a target in each frame of a sequence image of a target life cycle under different cloud parameters is calculated, the proportion of the signal-to-clutter ratio of the target in the target life cycle exceeding a threshold value is counted as a target detection availability, the analytical relationship between the target detection availability and different cloud parameters is analyzed, an availability model is established, and the satellite payload performance is evaluated by using the availability model, which can effectively shorten the performance evaluation time of typical satellite payloads in the field of remote sensing.

[0071] Figure 2 A structural block diagram of a satellite payload performance evaluation device according to an embodiment of the present disclosure is shown. The device can be realized as part or all of an electronic device by software, hardware or a combination of the two.

[0072] As shown in Figure 2 The satellite payload performance evaluation device 200 includes a calculation module 210, a statistics module 220, an establishment module 230 and an evaluation module 240.

[0073] The calculation module 210 is configured to calculate the signal-to-clutter ratio of a target in each frame of a sequence image of a target life cycle under different cloud parameters.

[0074] The statistics module 220 is configured to count the proportion of the signal-to-clutter ratio of the target in the target life cycle exceeding a threshold value as a target detection availability.

[0075] The establishment module 230 is configured to analyze the analytical relationship between the target detection availability and different cloud parameters, and establish an availability model.

[0076] The evaluation module 240 is configured to evaluate the satellite payload performance by using the availability model.

[0077] The technical scheme provided by the embodiments of the present disclosure provides a satellite payload performance evaluation device based on an analytical formula. The signal-to-clutter ratio of a target in each frame of a sequence image of a target life cycle under different cloud parameters is calculated, the proportion of the signal-to-clutter ratio of the target in the target life cycle exceeding a threshold value is counted as a target detection availability, the analytical relationship between the target detection availability and different cloud parameters is analyzed, an availability model is established, and the satellite payload performance is evaluated by using the availability model, which can effectively shorten the performance evaluation time of typical satellite payloads in the field of remote sensing.

[0078] According to an embodiment of the present disclosure, the cloud parameters include the position, number, speed, area and radiation intensity of the cloud.

[0079] According to an embodiment of the present disclosure, the calculation module 210 includes:

[0080] The first determining sub-module is configured to determine the maximum radiation intensity of the target under different cloud parameters.

[0081] The first calculating sub-module is configured to set a neighborhood sliding window with a side length of n×n and m×m centered on the target, subtract the background radiation intensity mean value of the n×n neighborhood from the m×m neighborhood to obtain the neighborhood background average radiation intensity, and subtract the radiation intensity standard deviation of the n×n neighborhood from the m×m neighborhood to obtain the neighborhood background spatial clutter, where n is less than m, and both n and m are natural numbers.

[0082] The second calculating sub-module is configured to calculate the signal-to-clutter ratio of the target according to the maximum radiation intensity of the target, the neighborhood background average radiation intensity, and the neighborhood background spatial clutter.

[0083] According to an embodiment of the present disclosure, the establishing module 230 comprises:

[0084] The establishing sub-module is configured to establish the signal-to-clutter ratio of the target and an independent analytical model between different cloud parameters.

[0085] The constructing sub-module is configured to construct an availability model according to the independent analytical model.

[0086] The second determining sub-module is configured to determine the model coefficients of the availability model by using a regression analysis method.

[0087] According to an embodiment of the present disclosure, the availability model is in the form of one of a polynomial, an exponential function, a logarithmic function, a hyperbolic curve, a trigonometric function, a Gaussian function, a Lorentz function, and a Poisson distribution function.

[0088] The present disclosure also discloses an electronic device, Figure 3 The structure block diagram of the electronic device according to an embodiment of the present disclosure is shown.

[0089] As Figure 3 shown, the electronic device comprises a memory and a processor, wherein the memory is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the method according to an embodiment of the present disclosure:

[0090] The signal-to-clutter ratio of the target in each frame in the sequence image of the target life cycle under different cloud parameters is calculated.

[0091] The proportion of the signal-to-clutter ratio of the target in the target life cycle that exceeds a threshold value is counted as the target detection availability.

[0092] The analytical relationship between the target detection availability and different cloud parameters is analyzed, and an availability model is established.

[0093] The satellite payload performance is evaluated by using the availability model.

[0094] According to embodiments of this disclosure, the cloud parameters include the cloud's location, quantity, velocity, area, and radiation intensity.

[0095] According to embodiments of this disclosure, calculating the signal-to-clutter ratio (SCR) of the target in each frame of a sequence of images representing the target's lifecycle under different cloud parameters includes:

[0096] Determine the maximum radiation intensity of the target under different cloud parameters;

[0097] A neighborhood sliding window with side lengths n×n and m×m is set with the target as the center. The mean background radiation intensity of the neighborhood is obtained by subtracting the mean background radiation intensity of the n×n neighborhood from the mean background radiation intensity of the m×m neighborhood. The standard deviation of the radiation intensity of the neighborhood is obtained by subtracting the mean background radiation intensity of the n×n neighborhood from the mean background radiation intensity of the m×m neighborhood. Here, n is less than m and both are natural numbers.

[0098] The signal-to-clutter ratio of the target is calculated based on the target's maximum radiation intensity, the average radiation intensity of the surrounding background, and the spatial clutter in the surrounding background.

[0099] According to embodiments of this disclosure, the step of analyzing the target detection availability and the analytical relationship between different cloud parameters to establish an availability model includes:

[0100] Establish independent analytical models for the signal-to-noise ratio and different cloud parameters of the target;

[0101] Construct an availability model based on the independent analytical model;

[0102] The model coefficients of the availability model were determined using regression analysis.

[0103] According to embodiments of this disclosure, the availability model is in the form of a polynomial, exponential function, logarithmic function, hyperbola, trigonometric function, Gaussian function, Lorentz function, or Poisson distribution function.

[0104] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the method according to embodiments of the present disclosure is shown.

[0105] like Figure 4 As shown, the computer system includes a processing unit that can execute various methods described above based on a program stored in a read-only memory (ROM) or a program loaded from a storage portion into a random access memory (RAM). The RAM also stores various programs and data required for the operation of the computer system. The processing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0106] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN card, a modem, etc. The communication part performs a communication process via a network such as the Internet. A drive is also connected to the I / O interface as necessary. A removable medium such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is mounted on the drive as necessary, so that a computer program read out therefrom is installed in the storage part as necessary. Among them, the processing unit can be implemented as a CPU, a GPU, a TPU, a FPGA, a NPU, etc.

[0107] In particular, the method described above can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program containing program code for executing the methods described above. In such embodiments, the computer program can be downloaded and installed from a network via the communication part, and / or installed from a removable medium.

[0108] The flow and block diagrams in the drawings show possible architectural, functional, and operational scenarios of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flow and block diagrams can represent a module, a segment, or a portion of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks noted in succession can in fact be executed substantially concurrently or in the opposite order, depending on the functionality involved. It will also be noted that each block in the block and / or flow diagrams and combinations of blocks in the block and / or flow diagrams can be implemented by special-purpose hardware-based systems, which perform the specified functions or operations, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0109] The units or modules involved in the embodiments of the present disclosure can be implemented by software or by programmable hardware. The described units or modules can also be arranged in a processor, and the names of these units or modules do not constitute a limitation on the units or modules themselves in some cases.

[0110] As another aspect, the disclosure also provides a computer readable storage medium, which can be the computer readable storage medium contained in the electronic device or the computer system in the above embodiments; or can be a computer readable storage medium existing separately and not assembled into a device. The computer readable storage medium stores one or more programs used by one or more processors to execute the method described in the disclosure.

[0111] The above description is merely the preferred embodiments of the disclosure and the explanation of the principles of the applied technology. It should be understood by those skilled in the art that the inventive scope of the disclosure is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by the combinations of the above technical features or equivalent features without departing from the inventive concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features disclosed in the disclosure (but not limited to) having similar functions.

Claims

1. A method of satellite payload performance assessment, characterized in that, The method comprises the following steps: calculating the signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters; counting the proportion of the signal-to-clutter ratio of the target exceeding a threshold value in the target life cycle as the target detection availability; analyzing the analytical relationship between the target detection availability and different cloud parameters to establish an availability model; evaluating the satellite payload performance by using the availability model.

2. The method of claim 1, wherein, The cloud parameters comprise the position, number, speed, area and radiation intensity of the cloud.

3. The method of claim 1 or 2, wherein, The calculation of the signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters comprises the following steps: determining the maximum radiation intensity of the target under different cloud parameters; setting a neighborhood sliding window with side length n*n and m*m centered on the target, using the mean value of the background radiation intensity of the m*m neighborhood minus the n*n neighborhood as the neighborhood background average radiation intensity, and using the standard deviation of the radiation intensity of the m*m neighborhood minus the n*n neighborhood as the neighborhood background spatial clutter; wherein n is less than m, and both are natural numbers; calculating the signal-to-clutter ratio of the target according to the maximum radiation intensity of the target, the neighborhood background average radiation intensity and the neighborhood background spatial clutter.

4. The method of claim 1 or 2, wherein, The analysis of the analytical relationship between the target detection availability and different cloud parameters to establish an availability model comprises the following steps: establishing an independent analytical model between the signal-to-clutter ratio of the target and different cloud parameters; constructing an availability model according to the independent analytical model; determining the model coefficients of the availability model by using a regression analysis method.

5. The method of claim 4, wherein, The availability model is in the form of one of a polynomial, an exponential function, a logarithmic function, a hyperbolic curve, a trigonometric function, a Gaussian function, a Lorentz function and a Poisson distribution function.

6. A satellite payload performance evaluation apparatus, characterized by, The method comprises the following steps: a calculation module configured to calculate the signal-to-clutter ratio of the target in each frame of the sequence image of the target life cycle under different cloud parameters; a statistics module configured to count the proportion of the signal-to-clutter ratio of the target exceeding a threshold value in the target life cycle as the target detection availability; an establishment module configured to analyze the analytical relationship between the target detection availability and different cloud parameters to establish an availability model; an evaluation module configured to evaluate the satellite payload performance by using the availability model.

7. The apparatus for evaluating the effectiveness of a satellite payload according to claim 6, wherein The cloud parameters comprise the position, number, speed, area and radiation intensity of the cloud.

8. The satellite payload performance evaluation apparatus according to claim 6 or 7, characterized in that, The calculation module comprises the following steps: a first determination sub-module configured to determine the maximum radiation intensity of the target under different cloud parameters; a first calculation sub-module configured to set a neighborhood sliding window with side length n*n and m*m centered on the target, use the mean value of the background radiation intensity of the m*m neighborhood minus the n*n neighborhood as the neighborhood background average radiation intensity, and use the standard deviation of the radiation intensity of the m*m neighborhood minus the n*n neighborhood as the neighborhood background spatial clutter; wherein n is less than m, and both are natural numbers; a second calculation sub-module configured to calculate the signal-to-clutter ratio of the target according to the maximum radiation intensity of the target, the neighborhood background average radiation intensity and the neighborhood background spatial clutter.

9. An electronic device, comprising: The method comprises the following steps: a memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method in any one of claims 1-5.

10. A computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions, when executed by the processor, implement the method of any one of claims 1-5.

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