Method, medium and device for determining size of space debris using distributed laser ranging and photon counting data

Abstract

The application provides a method, medium and equipment for solving the size of space debris by using distributed laser ranging and photon number data, and belongs to the technical field of space debris characteristic research.The application is based on the layout of a station for emitting laser signals, a second station for receiving ranging data, and a third station for receiving photon number data, and inversely solves the size of space debris by combining the data of the three stations.Compared with the layout of a single station for emitting and receiving ranging data, the application improves the solving accuracy and stability of the size of space debris.The application firstly pre-processes echo data, obtains distance and photon number residuals by high-order polynomial fitting and removing low-frequency trend items, then calculates the difference between adjacent peak values and valley values of the processed residual data to obtain oscillation amplitude values and amplitude uncertainty, and finally solves the target size by matching simulation results with observation data.The application can effectively improve the accuracy and stability of the solving of the size of space debris.

Description

Technical Field

[0001] This invention belongs to the field of space debris characteristics research technology, specifically involving a method, medium, and device for calculating the size of space debris using distributed laser ranging and photon number data. Background Technology

[0002] High-precision inversion of the geometric parameters of space debris is a crucial prerequisite for collision risk assessment and target identification. Laser ranging and photon counting technologies, with their high precision and all-weather capabilities, have become important tools for space debris detection. However, current target inversion research still has significant shortcomings. Single-source observation data has inherent limitations; relying solely on laser ranging data cannot decouple the relationship between length and radius; and relying solely on photon counting data is susceptible to the coupling effect of surface reflectivity and geometric dimensions, easily leading to non-unique solutions. Summary of the Invention

[0003] This invention addresses the shortcomings of existing technologies by providing a method, medium, and device for calculating the size of space debris using distributed laser ranging and photon count data. This invention acquires laser ranging and photon count data under multiple observation geometries in a single emission. The pre-processed ranging residual sequence characterizes the distance deviation between the reflection point and the centroid of the space debris under different rotational attitudes. The photon count residual sequence reflects the dynamic changes in the combined albedo under the coupling effect of the debris's reflective area and surface reflectivity. The amplitude fluctuations of both types of observation sequences are directly physically related to the debris's geometric size and surface reflectivity. By simulating and matching the consistency between echo data and observation data under different size parameters, the optimal simulated size is identified as the target size for calculation.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] In a first aspect, the present invention provides a method for calculating the size of space debris using distributed laser ranging and photon number data, comprising: Step 1: The transmitting station emits a laser signal, which is reflected back to the ground by the space debris target. The receiving station receives the returned signal and obtains observation data, including laser ranging data and photon count data. The observation data is preprocessed by fitting with a high-order polynomial and removing low-frequency trend terms to obtain distance residual data and photon count residual data. Step 2: Calculate the oscillation amplitude and amplitude uncertainty based on the distance residual data and photon number residual data; Step 3: Obtain simulation data for different target sizes and reflectivities through numerical simulation. The simulation data includes laser ranging data and photon number data. Process the simulation data to obtain the simulation signal amplitude, and then substitute it together with the oscillation amplitude value and amplitude uncertainty calculated in Step 2 into the goodness-of-fit function to evaluate the consistency between the simulation data and the observation data, and match the optimal simulation target size as the target size to be solved.

[0006] Optionally, in step 1, there are three receiving stations. The first receiving station is the same as the transmitting station. The first and second receiving stations obtain laser ranging data by analyzing the time difference between the returned signal and the transmitted signal. The third receiving station detects the number of photons in the returned signal to obtain photon count data.

[0007] Optionally, in step 1, the calculation process for the distance residual data is as follows: A third-order polynomial is used to fit the sum of the distances from the target reflection point to the transmitting and receiving stations. The distance residual data is obtained by subtracting the fitting result from the laser ranging data in the observation data.

[0008] Optionally, in step 1, the calculation process of the photon number residual data is as follows: The photon counts of the 21 pulses in the returned signal are combined, and the photon count residual data is obtained by subtracting the fitting result from the combined photon count data.

[0009] Optionally, in step 2, the calculation process for the oscillation amplitude value and amplitude uncertainty is as follows: Data fitting was performed on the distance residual data and the photon number residual data to extract the values ​​of peak points and valley points. The value of each peak and valley point was denoted as... , i The index of the peak and trough points is taken as one standard deviation of the 10 pulses near the peak and trough points. The uncertainty at the peak and valley points The difference between two adjacent peak and trough values ​​is the oscillation amplitude. , The geometric mean of the uncertainties of two adjacent peak and trough points is the amplitude uncertainty. , .

[0010] Optionally, in step 3, the goodness-of-fit function for: ; In the formula, Indicates the corresponding height h ,radius r and reflectivity Under the conditions value, For height h ,radius r and reflectivity The amplitude of the simulated signal under the given conditions.

[0011] Optionally, in step 3, the optimal simulation target size is The simulated target size corresponding to the minimum value is used as the target size calculated under the corresponding reflectivity.

[0012] In a second aspect, the present invention provides a computer-readable storage medium storing a computer program that causes a computer to perform the method described in the first aspect for calculating the size of space debris using distributed laser ranging and photon number data.

[0013] Thirdly, the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for calculating the size of space debris using distributed laser ranging and photon number data as described in the first aspect.

[0014] The beneficial effects of this invention are as follows: Compared with traditional single ranging data for calculating target size, this invention introduces multi-dimensional target information through distributed multi-station and multi-type observations; the pre-processed ranging residual sequence can characterize the distance deviation variation law of the optical reflection point relative to the centroid under different rotational attitudes of space debris; the photon counting residual sequence can reflect the dynamic change characteristics of the comprehensive albedo under the coupling effect of debris reflective area and surface reflectivity; the amplitude fluctuations of both types of observation sequences are directly physically related to the geometric size and surface reflectivity of the debris, which can significantly reduce the coupling of size parameters encountered in calculating target size from single ranging data, and significantly improve the accuracy and stability of the target size parameter calculation results. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for calculating the size of space debris using distributed laser ranging and photon number data.

[0016] Figure 2 It contains raw ranging data (a) and photon number data (b) that include orbital information.

[0017] Figure 3 The data are: distance residual data after eliminating the low-frequency trend term (a), photon number data after combining 21 pulses and low-frequency fitting term (b), and photon number residual data obtained by eliminating the low-frequency trend term from the photon number of 21 pulses (c).

[0018] Figure 4This is the result of processing measured data from multiple stations. (a) to (c) correspond to the residual sequences after preprocessing at three observation stations, respectively. (a) and (b) are laser ranging data, and (c) is photon number data. The scatter points in the figure are the measured data, the curves are the data fitting mean, the black triangles mark the peak and valley positions extracted from the sequence, and the black error bars are the measurement uncertainties corresponding to the peak and valley values. (d) to (f) correspond to the oscillation amplitude and amplitude uncertainty calculated at the three observation stations, respectively. The solid black circles are the signal amplitudes at each time point obtained by calculating the difference between adjacent extreme values, and the hollow circles are the amplitude uncertainties obtained by calculating the geometric mean of the uncertainties of two adjacent peak and valley points.

[0019] Figure 5 It refers to the target size and data accuracy calculated by a single ranging station.

[0020] Figure 6 The target size is calculated using data from different observation stations. (a) is the target size calculated using data from three observation stations, (b) and (c) are the target sizes calculated using distance measurement data from the first and second observation stations, respectively, and (d) is the target size calculated using photon number data.

[0021] Figure 7 This is a comparison of the dimensional calculation results and accuracy of single-station and three-station combined measurements within the total reflectivity range. (a)~(d) correspond to the comparison of radius, radius accuracy, height, and height accuracy, respectively. In the figure, solid dots represent the calculation results of single-station ranging data, and hollow circles represent the calculation results of combined measurements from three observation stations (including ranging data and photon number data). Detailed Implementation

[0022] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0023] In one embodiment, the present invention proposes a method for calculating the size of space debris using distributed laser ranging and photon count data. In this embodiment, a laser signal is emitted from a transmitting station. The laser is reflected back to Earth by space debris, and three receiving stations on the ground receive the returned signal. The first laser signal receiving station is identical to the transmitting station. The first and second receiving stations obtain distance information by analyzing the time difference between the returned and transmitted signals. The third receiving station detects the photon count information in the returned signal. Since the laser signal is emitted in pulses at regular time intervals, the received laser ranging and photon count data are also pulsed at regular time intervals.

[0024] This invention preprocesses echo data by fitting it with a high-order polynomial and removing low-frequency trend terms to obtain distance and photon number residual data. The difference between adjacent peaks and valleys is calculated from the processed residual data to obtain the oscillation amplitude and amplitude uncertainty. Numerical simulation is used to obtain data under different target sizes and reflectivities. A goodness-of-fit function is used to evaluate the consistency between the simulation data and observed data with different parameters; the simulation size with the smallest goodness-of-fit is the calculated target size.

[0025] like Figure 1 As shown, the specific process of calculating the size of space debris using distributed laser ranging and photon number data is as follows: Step 1: Preprocess the echo data (return signal) by fitting it with a high-order polynomial and removing the low-frequency trend term to obtain the distance residual data and photon number residual data.

[0026] The first and second measuring stations receive distance data from the laser reflected from the target, while the third station receives photon count data from the reflected laser. Since this data includes target trajectory information, such as... Figure 2 As shown, it is crucial to eliminate the impact of orbital changes on the overall data trend. A third-order polynomial is used to fit the sum of the distances between the target reflection point and the transmitting and receiving stations, and the original distance information is subtracted from the fitted result. After subtracting the ranging data, the equivalent reflection point distance difference on different sides caused only by the target's rotation attitude is obtained, as shown in the figure. Figure 3 As shown in (a). Due to the small number of photons, the local periodicity of the observed photon number data is not obvious. Therefore, it is necessary to combine photon numbers to enhance the periodicity feature. If the number of combined pulses is too low, the periodicity will be difficult to reflect due to the small number of photons and low resolution. If the number of combined pulses is too high, the periodic information will be masked by the smoothing effect over a long period of time. Tests have shown that combining photon numbers of 21 pulses can show the periodicity with high quality. Therefore, combining photon numbers of 21 pulses, as shown in (a). Figure 3 As shown in (b), the photon number residual obtained by subtracting the third-order polynomial fitting result from the merged photon number data is then obtained, as shown in (b). Figure 3 As shown in (c), the photon number residual data exhibits a periodic variation in the reflection intensity of the reflecting surface.

[0027] Step 2: Calculate the difference between adjacent peaks and valleys in the processed residual data to obtain the oscillation amplitude and amplitude uncertainty.

[0028] The processed distance residual data and photon number residual data are fitted together to extract the values ​​of peak and valley points, as shown below. Figure 4 As shown by the black triangles in (a), (b), and (c), the values ​​of each peak and valley point are denoted as... , i The index of the peak and trough points is represented by a standard deviation of the 10 pulse echo data points near the peak and trough points. The uncertainty of the peak and valley points , Standard deviation, such as Figure 4 As shown by the black lines in (a), (b), and (c), the difference between two adjacent peak and trough values ​​represents the signal amplitude in the goodness-of-fit function. , ,like Figure 4 The black solid circles in (d), (e), and (f) represent the uncertainty of the amplitude. The geometric mean of the uncertainties of two adjacent peak and trough points is taken as the uncertainty of the amplitude. ,like Figure 4 The hollow circles in (d), (e), and (f) are shown.

[0029] Step 3: Numerical simulation is used to obtain data under different target sizes and reflectivities, and the resulting oscillation amplitude values ​​under different simulation parameters are processed. The goodness-of-fit function is used to evaluate the consistency between the simulation data and the observed data for different parameters; the simulation size with the smallest goodness-of-fit is the calculated target size.

[0030] Numerical simulations were used to obtain laser ranging and photon count data for different target sizes and reflectivities. The processing of the grid traversal parameter results was the same as the processing of the observation data, yielding the data corresponding to the set height. h ,radius r Reflectivity Simulated signal amplitude under certain conditions However, , Substitute these values ​​into the goodness-of-fit function to calculate the goodness-of-fit. Use the goodness-of-fit function... The consistency between simulation data and observation data with different parameters is evaluated, and the optimal simulation size is the target size for solution.

[0031] For single-station ranging data passing through different target sizes at a certain reflectivity The minimum value determines the target size calculated at this reflectivity. The range corresponding to 10% of the values ​​is used as the precision of the solution, such as... Figure 5 As shown. Whether it's range measurement or photon count data, different target sizes at a given reflectivity... Distributed in h r The parameters are approximately distributed along a straight line in the plane, such as Figure 6As shown. The distribution lines of the two ranging stations are relatively close, and the distribution line of the photometric substation intersects the distribution lines of the ranging stations at two points. The average value of these two intersection points is used as the final calculated target size, and the range of the two intersection points is used as the calculation accuracy. The results calculated by a single ranging station and a distributed ranging photometric substation are compared under different reflectivities, as shown. Figure 7 As shown. For a rocket body 8 meters high, 2 meters in radius, and with a reflectivity of 0.16, the optimal accuracy calculation scheme for single-station ranging data corresponds to the position with the highest reflectivity. ρ =0.10, compared to the true value of reflectivity ρ =0.16 shows a significant deviation; the calculated size at this optimal position is r =2.14m h =8.250m, with a relative error of 7.0% for the radius and 3.1% for the length, indicating a significant deviation in the optimal solution itself. Extending to the total reflectivity scanning range further highlights the limitations of single-station solutions; the size estimates fluctuate significantly with reflectivity changes, resulting in low overall solution accuracy, particularly for the radius. r The relative deviation from the true value varies by approximately 7% to -6%, and the height... h The relative deviation from the true value varies by approximately 3% to -3%. Under the three-station joint calculation scheme, the position with optimal accuracy appears at the true reflectance value. ρ At =0.16, the corresponding solution dimension is r =2.009m h =8.026m, with parameter errors of only ±0.00007m and ±0.00006m, the optimal estimate perfectly matches the target true value. Within the total reflectivity scanning range, even when deviating from the position of optimal accuracy, the entire scheme still maintains excellent solution accuracy, and the overall deviation of the size estimate from the true value can be controlled within 1%, demonstrating strong stability. The above comparative experiments show that the multi-station fusion solution scheme has comprehensive advantages in terms of target size, reflectivity calculation accuracy, and stability.

[0032] In another embodiment, the present invention provides a computer-readable storage medium storing a computer program that causes a computer to execute the method of calculating space debris size using distributed laser ranging and photon number data from the foregoing embodiments.

[0033] In another embodiment, the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method of calculating the size of space debris using distributed laser ranging and photon number data as described in the foregoing embodiment.

[0034] In the embodiments disclosed in this application, a computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CDROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0035] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0036] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for calculating the size of space debris using distributed laser ranging and photon number data, characterized in that, include: Step 1: The transmitting station emits a laser signal, which is reflected back to the ground by the space debris target. The receiving station receives the returned signal and obtains observation data, including laser ranging data and photon count data. The observation data is preprocessed by fitting with a high-order polynomial and removing low-frequency trend terms to obtain distance residual data and photon count residual data. Step 2: Calculate the oscillation amplitude and amplitude uncertainty based on the distance residual data and photon number residual data; the calculation process for the oscillation amplitude and amplitude uncertainty is as follows: Data fitting was performed on the distance residual data and the photon number residual data to extract the values ​​of peak points and valley points. The value of each peak and valley point was denoted as... , i The index of the peak and trough points is taken as one standard deviation of the 10 pulses near the peak and trough points. The uncertainty at the peak and valley points The difference between two adjacent peak and trough values ​​is the oscillation amplitude. , The geometric mean of the uncertainties of two adjacent peak and trough points is the amplitude uncertainty. , ; Step 3: Obtain simulation data for different target sizes and reflectivities through numerical simulation. The simulation data includes laser ranging data and photon number data. Process the simulation data to obtain the simulation signal amplitude, and then substitute it together with the oscillation amplitude value and amplitude uncertainty calculated in Step 2 into the goodness-of-fit function to evaluate the consistency between the simulation data and the observation data, and match the optimal simulation target size as the target size to be solved.

2. The method for calculating space debris size using distributed laser ranging and photon number data as described in claim 1, characterized in that: In step 1, there are three receiving stations. The first receiving station is the same as the transmitting station. The first and second receiving stations obtain laser ranging data by analyzing the time difference between the returned signal and the transmitted signal. The third receiving station detects the number of photons in the returned signal to obtain photon count data.

3. The method for calculating space debris size using distributed laser ranging and photon number data as described in claim 1, characterized in that: In step 1, the calculation process for the distance residual data is as follows: A third-order polynomial is used to fit the sum of the distances from the target reflection point to the transmitting and receiving stations. The distance residual data is obtained by subtracting the fitting result from the laser ranging data in the observation data.

4. The method for calculating space debris size using distributed laser ranging and photon number data as described in claim 3, characterized in that: In step 1, the calculation process for the photon number residual data is as follows: The photon counts of the 21 pulses in the returned signal are combined, and the photon count residual data is obtained by subtracting the fitting result from the combined photon count data.

5. The method for calculating space debris size using distributed laser ranging and photon number data as described in claim 1, characterized in that: In step 3, the goodness-of-fit function for: ； In the formula, Indicates the corresponding height h ,radius r and reflectivity Under the conditions value, For height h ,radius r and reflectivity The amplitude of the simulated signal under the given conditions.

6. The method for calculating space debris size using distributed laser ranging and photon number data as described in claim 5, characterized in that: In step 3, the optimal simulation target size is The simulated target size corresponding to the minimum value is used as the target size calculated under the corresponding reflectivity.

7. A computer-readable storage medium storing a computer program, characterized in that, The computer program causes the computer to perform the method for calculating the size of space debris using distributed laser ranging and photon number data as described in any one of claims 1-6.

8. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for calculating the size of space debris using distributed laser ranging and photon number data as described in any one of claims 1-6.

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