Automatic testing method and system for spaceflight measurement and control software

Abstract

The invention relates to the technical field of software automatic testing, and particularly discloses an automatic testing method and system for spaceflight measurement and control software, and the method comprises the steps: simulating a space complex electromagnetic environment through constructing an all-fiber measurement and control system architecture, and generating a multi-band composite electromagnetic interference signal; injecting the multi-band composite electromagnetic interference signal into a main signal link of an all-fiber measurement and control system through an optical fiber coupler, and collecting response data of spaceflight measurement and control software in real time; carrying out anti-interference capability comprehensive evaluation according to the response data, and generating an anti-interference performance comprehensive score; and optimizing a logic control algorithm of spaceflight measurement and control software based on the anti-interference performance comprehensive score, and carrying out iterative testing through the all-fiber measurement and control system architecture until a preset anti-interference threshold is met, so that the reliability and adaptability of the spaceflight measurement and control system can be comprehensively improved, the task risk caused by electromagnetic interference is reduced, and the service life of the spaceflight measurement and control software is prolonged. And meanwhile, the accuracy and precision of a test result can be ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of software automated testing, and relates to an automated testing method and system for aerospace TT&C software. Background Art

[0002] As the core control system for spacecraft in-orbit operation, the anti-interference ability of aerospace TT&C software directly affects the mission success and the survival ability of the spacecraft in a complex electromagnetic environment. Due to the presence of multi-source, time-varying, and non-steady electromagnetic interferences in the space environment, such as low-frequency noise caused by solar wind plasma, transient harmonic distortion caused by inter-satellite link switching, and multipath reflection superposition of ground TT&C signals, these interferences have characteristics such as wide-band coverage, dynamic power fluctuation, and spatial heterogeneity. If the TT&C software fails to pass the high-fidelity electromagnetic interference simulation test, it will lead to catastrophic consequences such as the failure of critical command transmission, telemetry data packet loss, and even system deadlock in the real in-orbit scenario.

[0003] However, there are still significant deficiencies in the current technical system for the anti-interference test of aerospace TT&C software: Existing test systems mostly rely on fixed-frequency interference sources and are difficult to dynamically generate time-varying electromagnetic interference signals that match the real space environment. For example, traditional radio frequency modules only support a single interference mode in a preset frequency band and cannot simulate the multi-band signal coupling effect in the space environment, resulting in incomplete test coverage. Summary of the Invention

[0004] In view of the above problems existing in the prior art, the present invention provides an automated testing method and system for aerospace TT&C software to solve the above technical problems.

[0005] To achieve the above and other purposes, the technical solution adopted by the present invention is as follows: On the one hand, the present invention provides an automated testing method for aerospace TT&C software, and the method includes the following steps: Step S1: Construct a full-fiber TT&C system architecture, and the full-fiber TT&C system architecture includes a full-fiber signal transmission module, a radio frequency direct sampling module, and a digital demodulation module; Step S2: Simulate the complex electromagnetic environment in space and generate multi-band composite electromagnetic interference signals; Step S3: Inject the multi-band composite electromagnetic interference signals into the main signal link of the full-fiber TT&C system through an optical fiber coupler, and collect the response data of the aerospace TT&C software in real time; Step S4: Conduct a comprehensive evaluation of the anti-interference ability based on the response data and generate a comprehensive anti-interference performance score; specifically including: calculating the dynamic weight of the response data of the aerospace TT&C software and generating a comprehensive anti-interference performance score in combination with the preset priority of the aerospace TT&C mission scenario; Step S5: Optimize the logic control algorithm of the space TT&C software based on the comprehensive anti-interference performance score, and perform iterative testing through the all-fiber TT&C system architecture until the preset anti-interference threshold is met.

[0006] Exemplarily, convert the control instruction of the space TT&C software into an optical signal through the all-fiber signal transmission module, and transmit it to the simulated spacecraft under test via the optical fiber link; directly sample the optical signal through the RF direct sampling module to generate a digital signal; demodulate the digital signal through the digital demodulation module to obtain the interaction data between the space TT&C software and the simulated spacecraft under test.

[0007] Exemplarily, Step S11: Receive the control instruction of the space TT&C software, and perform CRC check and protocol compliance verification on the instruction format; modulate the verified control instruction into an optical signal with a wavelength of 1550 nm through an electro-optic converter, and the modulation method is intensity modulation; transmit the optical signal to the simulated spacecraft under test through a single-mode optical fiber link at a rate not lower than the set threshold; Step S12: Receive the optical signal transmitted by the optical fiber link, and convert the optical signal into an analog RF signal through a photodetector; perform band-pass filtering on the analog RF signal to retain the effective signals in the L band to the Ka band; directly sample the filtered signal through an ultra-wideband ADC to generate a digital signal; Step S13: Perform adaptive equalization processing on the digital signal to eliminate chromatic dispersion and nonlinear distortion in optical fiber transmission; demodulate the equalized signal using the QPSK demodulation algorithm to generate baseband I / Q data; perform frame synchronization and decoding on the I / Q data based on the spacecraft communication protocol, and extract the instruction response parameters and spacecraft status telemetry parameters in the interaction data.

[0008] Exemplarily, the generation of the multi-band composite electromagnetic interference signal in Step S2 specifically includes: Step S21: Based on the historical in-orbit electromagnetic interference data of spacecraft, extract multi-dimensional electromagnetic interference characteristic parameters, and the characteristic parameters include the spectral distribution of solar wind disturbances, the transient harmonic phase jump characteristics of inter-satellite links, and the ground multipath interference time delay attenuation gradient; Step S22: Use the quantum optimization algorithm to perform parameter collaborative configuration on multi-band interference sources to generate baseband interference signals covering the C band, X band, and Ku band; Step S23: Generate multi-band carrier components of the baseband interference signal through a direct digital frequency synthesizer, and use radio-over-fiber modulation technology to modulate each band signal onto different wavelength optical carriers respectively, and then perform spectral synthesis through a wavelength division multiplexer to generate a multi-band composite electromagnetic interference signal containing at least three independent interference bands.

[0009] Exemplarily, in step S3, the multi-band composite electromagnetic interference signal is injected into the main signal link of the all-fiber measurement and control system through an optical fiber coupler. During the injection process, the polarization state of the optical signal needs to be dynamically adjusted according to the polarization sensitivity of the optical fiber link. The specific adjustment steps are as follows: Deploy a high-precision polarization analyzer at the receiving end of the main signal link to measure the Stokes parameters of the optical signal in the main link in real time, and construct a polarization sensitivity prediction model based on the fiber type and link length; then transmit the multi-band composite electromagnetic interference signal to be injected through a polarization-maintaining fiber to a polarization beam splitter prism, which is decomposed into X / Y orthogonal polarization components, and an online polarization ellipse rate χ and azimuth angle θ of the interference signal are analyzed using a dual-channel optical power meter; calculate the polarization angle deviation Δθ and the ellipse rate deviation Δχ based on the above parameters, and generate a polarization matching degree evaluation function F in combination with a preset dynamic weight coefficient; during this process, perform a proportional-integral closed-loop adjustment on Δθ, apply a driving voltage V_θ linearly related to the angle deviation, and simultaneously perform an optical path difference compensation on Δχ to converge the ellipse rate deviation to within a threshold range; after the adjustment is completed, determine whether the injection requirement of F_actual≥0.9 is satisfied by periodically measuring the actual matching degree F_actual. If the measurement is qualified for 3 consecutive times, the polarization matching is completed, otherwise, trigger an adaptive iteration mechanism to recalculate the difference parameters.

[0010] Exemplarily, the response data of the space measurement and control software is collected in real time. The response data includes instruction transmission delay, signal error rate, and fault tolerance recovery time.

[0011] Exemplarily, a comprehensive anti-interference performance score is generated. The specific generation process is as follows: Define scenario priority parameters according to the type of space measurement and control tasks, including task criticality level K, real-time constraint coefficient T, and data integrity weight D; among them, the task criticality level divides the priority coefficient according to manned spaceflight, deep space exploration, and satellite navigation. The real-time constraint coefficient is set according to the maximum allowable delay of instruction transmission, and the data integrity weight is classified according to the error rate tolerance; Thus, comprehensively calculate the weight factor α of the instruction transmission delay = (K×T) / (K×T + D) and the weight factor β of the signal error rate = (D) / (K×T + D); finally, calculate the weight factor γ of the fault tolerance recovery time = 1 - (α + β); when γ is less than 0, force γ to zero; Furthermore, perform a non-linear normalization process on the measured instruction transmission delay, signal error rate, and fault tolerance recovery time: the normalized value of the instruction transmission delay is calculated by the ratio of the difference between the measured delay and the maximum allowable delay; the signal error rate uses a logarithmic function with base 10 to compress its magnitude difference; the fault tolerance recovery time is mapped through an exponential decay function; Multiply the normalized instruction transmission delay, signal error rate, and fault tolerance recovery time by the dynamic weight factors and sum them to generate a comprehensive anti-interference performance score.

[0012] Exemplarily, according to the real-time value of the comprehensive anti-interference performance score, the system automatically determines to enter the optimization state: when the score is higher than or equal to 60 points, the normal mode is triggered, and no optimization operation is performed on the space TT&C software; conversely, when the score is lower than 60 points, the emergency optimization mode is triggered. The operation logic of the emergency optimization mode is as follows: according to the comparison between the normalized values of each index in the comprehensive score and the preset threshold, the core type of performance defects is located. If the delay normalized value is lower than the threshold, it is determined as a communication protocol defect; if the bit error rate normalized value is insufficient, it is determined as a bit error rate defect; if the recovery time score is too low, it is determined as a recovery time defect; For communication protocol defects, time-sensitive network technology is used to optimize the communication protocol and deploy a lightweight protocol stack; for bit error rate defects, low-density parity-check codes and adaptive equalization algorithms are used to reduce the bit error rate; for recovery time defects, the dual-active hot standby mechanism and machine learning fault prediction model are used to shorten the recovery time; The same electromagnetic interference signal is reproduced to compare the performance data before and after optimization, the extreme interference parameters are loaded to test the algorithm robustness, and the multi-spacecraft concurrent scenario is simulated to evaluate the system stability; at the same time, the passing threshold is dynamically adjusted according to the mission type; Finally, when the score fluctuation is less than the set threshold in three consecutive iterative tests, it is determined that the convergence is achieved. If the standard is not met after more than ten times, manual intervention is triggered.

[0013] On the other hand, the present invention provides an automated test system for space TT&C software, which includes an interference signal generation module, a response data acquisition module, an interference score calculation module, and an interference iterative test module. The above-mentioned modules are connected by wired and / or wireless connection methods to realize data transmission between modules; Interference signal generation module: Construct a full-fiber TT&C system architecture, which includes a full-fiber signal transmission module, a radio frequency direct sampling module, and a digital demodulation module; simulate the complex electromagnetic environment in space and generate multi-band composite electromagnetic interference signals; Response data acquisition module: Inject the multi-band composite electromagnetic interference signal into the main signal link of the full-fiber TT&C system through an optical fiber coupler and collect the response data of the space TT&C software in real time; Interference score calculation module: Conduct a comprehensive evaluation of the anti-interference ability according to the response data and generate a comprehensive anti-interference performance score; Interference iterative test module: Optimize the logic control algorithm of the space TT&C software based on the comprehensive anti-interference performance score and conduct iterative tests through the full-fiber TT&C system architecture until the preset anti-interference threshold is met.

[0014] As described above, the automated test method and system for space TT&C software provided by the present invention have at least the following beneficial effects: In the embodiments of the present invention, by constructing an all-fiber measurement and control system architecture and utilizing the high-performance characteristics of the all-fiber signal transmission module, radio frequency direct sampling module, and digital demodulation module, a complex space electromagnetic environment is simulated and a multi-band composite electromagnetic interference signal is generated, which is injected into the main signal link of the all-fiber measurement and control system. The response data of the space measurement and control software is collected in real time, and then the anti-interference ability of the system is comprehensively evaluated and a comprehensive anti-interference performance score is generated. The advantages and necessity of this process are reflected in the following aspects: First, there are complex electromagnetic interferences in the space environment, such as solar wind, ground signal interference, and electromagnetic radiation from other spacecrafts. These interferences may seriously affect the signal transmission and command execution of the space measurement and control system. By simulating the multi-band composite electromagnetic interference signal, the weaknesses of the measurement and control system in the interference environment can be discovered in advance during the ground test stage, thus avoiding mission failures or system crashes caused by insufficient anti-interference ability in real space missions; Through the comprehensive anti-interference performance score, the performance of the measurement and control system in different interference scenarios can be comprehensively evaluated, and a clear improvement direction can be provided for subsequent optimization. Optimizing the logic control algorithm of the space measurement and control software based on the scoring results can significantly improve the anti-interference ability and operation stability of the system. In addition, using the all-fiber measurement and control system architecture for iterative testing can reproduce the same interference environment multiple times after optimization, verify the effectiveness of the improvement measures, and further test the robustness of the system by loading extreme interference parameters to ensure that the optimized system can operate stably in a more complex and severe environment; thus comprehensively improving the reliability and adaptability of the space measurement and control system, reducing the mission risks caused by electromagnetic interference, and at the same time ensuring the accuracy and repeatability of the test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a schematic connection diagram of each step of the method of the present invention.

[0017] Figure 2 It is a schematic connection diagram of each module of the system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will combine the embodiments of the present invention. The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications, supplements, or use similar methods to replace the described specific embodiments, as long as they do not deviate from the concept of the invention or exceed the scope defined by this claim book, they should all fall within the protection scope of the present invention.

[0019] Embodiment 1 Please refer to Figure 1 As shown, an automated testing method for aerospace TT&C software, the method includes the following steps: Step S1: Construct a full-fiber TT&C system architecture, the full-fiber TT&C system architecture includes a full-fiber signal transmission module, a radio frequency direct sampling module, and a digital demodulation module; wherein the full-fiber signal transmission module converts the control instructions of the aerospace TT&C software into optical signals and transmits them to the simulated spacecraft under test via an optical fiber link; directly sample the optical signals through the radio frequency direct sampling module to generate digital signals; demodulate the digital signals through the digital demodulation module to obtain the interaction data between the aerospace TT&C software and the simulated spacecraft under test; wherein the interaction data includes instruction response parameters and spacecraft status telemetry parameters; Step S11: Receive the control instructions of the aerospace TT&C software, and perform CRC check and protocol compliance verification on the instruction format; modulate the verified control instructions into optical signals with a wavelength of 1550 nm through an electro-optical converter, and the modulation method is intensity modulation; transmit the optical signals to the simulated spacecraft under test through a single-mode optical fiber link at a rate not lower than the set threshold; Step S12: Receive the optical signals transmitted by the optical fiber link, and convert the optical signals into analog radio frequency signals through a photodetector; perform band-pass filtering on the analog radio frequency signals to retain the effective signals in the L band to the Ka band; directly sample the filtered signals through an ultra-wideband ADC to generate digital signals; Step S13: Perform adaptive equalization processing on the digital signals to eliminate dispersion and nonlinear distortion in optical fiber transmission; demodulate the equalized signals using a QPSK demodulation algorithm to generate baseband I / Q data; perform frame synchronization and decoding on the I / Q data based on the spacecraft communication protocol, and extract the instruction response parameters and spacecraft status telemetry parameters in the interaction data; Among them, the instruction response parameters include the control instruction execution status code, timestamp synchronization deviation data, and multi-threaded instruction conflict flag; the control instruction execution status code includes an instruction reception success flag (ACK / NACK) and the checksum matching result at the spacecraft end; the timestamp synchronization deviation data is the difference between the instruction transmission timestamp generated according to the Beidou time system and the response arrival timestamp; the multi-threaded instruction conflict flag is characterized as when resource competition occurs in the parallel instruction queue, marking the conflict instruction ID and priority weight; Spacecraft status telemetry parameters include attitude dynamics parameters, propulsion system status, and energy management data; attitude dynamics parameters include, but are not limited to, three-dimensional Euler angles (roll angle / pitch angle / yaw angle), angular velocity (X / Y / Z axes); propulsion system status includes, but is not limited to, remaining fuel quantity, thrust chamber pressure, valve opening / closing degree; energy management data includes, but is not limited to, output power of solar panels, SOC of lithium battery packs, and distribution bus voltage.

[0020] Step S2: Simulate the complex space electromagnetic environment to generate multi-band composite electromagnetic interference signals; The generation of multi-band composite electromagnetic interference signals in Step S2 specifically includes: Step S21: Based on historical in-orbit electromagnetic interference data of spacecraft, extract multi-dimensional electromagnetic interference characteristic parameters, where the characteristic parameters include solar wind perturbation spectrum distribution, inter-satellite link transient harmonic phase jump characteristics, and ground multipath interference time delay attenuation gradient; Step S22: Use a quantum optimization algorithm to perform parameter collaborative configuration on multi-band interference sources to generate baseband interference signals covering the C-band, X-band, and Ku-band; Step S23: Generate multi-band carrier components of the baseband interference signals through a direct digital frequency synthesizer, modulate each band signal onto different wavelength optical carriers using radio-over-fiber modulation technology, and then perform spectral synthesis through a wavelength division multiplexer to generate multi-band composite electromagnetic interference signals containing at least three independent interference bands.

[0021] In the embodiments of the present invention, the specific implementation method for simulating the complex space electromagnetic environment and generating multi-band composite electromagnetic interference signals is as follows: First, multi-dimensional characteristic parameters are extracted based on historical in-orbit electromagnetic interference data of spacecraft. Among them, the spectral distribution of solar wind disturbances is obtained by collecting in-orbit telemetry data during the peak of solar activity, generating a time-frequency spectrum matrix using short-time Fourier transform, and combining Gaussian mixture model clustering analysis to obtain the peak frequency drift rate, harmonic energy ratio, and frequency band broadening factor, which are used to characterize the dynamic spectral characteristics of solar wind low-frequency noise; the transient harmonic phase jump characteristics of the inter-satellite link are obtained by extracting the instantaneous phase curves of I / Q signals within a 500-ms window before and after link switching using Hilbert transform, detecting the phase mutation amplitude and stable recovery time, and establishing an association model between the harmonic order and the jump variable using non-linear regression; the ground multipath interference delay attenuation gradient is obtained by simulating the terrain reflection path around the TT&C station using the ray tracing method, calculating the delay spread slope and frequency selectivity index, and using the least squares method to fit the delay-power distribution curve to quantify the attenuation gradient; after the characteristic parameters are extracted, a quantum optimization algorithm is used to configure multi-band interference sources: the frequency points, bandwidths, and modulation depths of the C band (4-8 GHz), X band (8-12 GHz), and Ku band (12-18 GHz) are encoded into sequences of 4 qubits / parameter, and are iteratively optimized through the Grover quantum search algorithm (the objective function is to minimize the KL divergence) to generate pseudo-random phase-coded signals in the C band, linear frequency modulation signals in the X band, and Gaussian pulse sequences in the Ku band respectively; subsequently, baseband signals of each band are generated through a direct digital frequency synthesizer, and the baseband signals are modulated onto optical carriers of 1550.12 nm (C band), 1549.32 nm (X band), and 1548.52 nm (Ku band) by a modulator, and spectral synthesis is performed using a wavelength division multiplexer to finally generate multi-band composite electromagnetic interference signals containing three independent frequency bands.

[0022] Step S3: Inject the multi-band composite electromagnetic interference signal into the main signal link of the all-fiber TT&C system through an optical fiber coupler, and collect the response data of the space TT&C software in real time; In step S3, the multi-band composite electromagnetic interference signal is injected into the main signal link of the all-fiber TT&C system through an optical fiber coupler. During the injection process, the polarization state of the optical signal needs to be dynamically adjusted according to the polarization sensitivity of the optical fiber link. The specific adjustment steps are as follows: Deploy a high-precision polarization analyzer at the receiving end of the main signal link to measure the Stokes parameters of the optical signal in the main link in real time, and construct a polarization sensitivity prediction model based on the fiber type and link length. Subsequently, the multi-band composite electromagnetic interference signal to be injected is transmitted through a polarization-maintaining fiber to a polarization beam splitter prism. After being decomposed into X / Y orthogonal polarization components, a dual-channel optical power meter is used to online analyze the polarization ellipticity χ and azimuth angle θ of the interference signal. Based on the above parameters, calculate the polarization angle deviation Δθ and ellipticity deviation Δχ, and generate a polarization matching degree evaluation function F in combination with a preset dynamic weight coefficient. During this process, perform proportional-integral closed-loop regulation on Δθ, apply a driving voltage V_θ that is linearly related to the angle deviation, and simultaneously perform optical path difference compensation on Δχ to converge the ellipticity deviation to within the threshold range. After the adjustment is completed, determine whether the injection requirement of F_actual≥0.9 is met by periodically measuring the actual matching degree F_actual. If the measurement is qualified for 3 consecutive times, the polarization matching is completed; otherwise, trigger the adaptive iteration mechanism to recalculate the difference parameters.

[0023] Collect the response data of the space TT&C software in real time. The response data includes instruction transmission delay, signal error rate, and fault tolerance recovery time. After injecting the multi-band composite electromagnetic interference signal into the main signal link of the all-fiber TT&C system through an optical fiber coupler, in order to comprehensively collect the response data of the space TT&C software under interference conditions, the following specific operations need to be carried out: First, set the parameters of the real-time acquisition system, including sampling frequency, sampling accuracy, and data storage format, to ensure that the acquisition system can efficiently capture the impact of the interference signal on the TT&C system. Second, send standardized instruction signals to the TT&C system through a pre-designed test instruction set to simulate the instruction transmission process of the spacecraft during actual operation. While injecting the interference signal, monitor the instruction transmission delay of the TT&C system in real time and record the time interval from the instruction being sent to receiving the confirmation feedback. At the same time, collect the signal error rate data, and count the number of error codes and the change trend of the error rate in signal transmission by comparing the differences between the sent signal and the received signal. In addition, for the abnormal situations that may occur in the system under interference conditions, record the fault tolerance recovery time, that is, the time required for the TT&C system to recover from the fault state to the normal operation state.

[0024] Step S4: Perform a comprehensive evaluation of the anti-interference ability based on the response data to generate a comprehensive anti-interference performance score; specifically including: perform dynamic weight calculation on the response data of the space TT&C software, and generate a comprehensive anti-interference performance score in combination with the preset priority of the space TT&C mission scenario; Generate a comprehensive anti-interference performance score, and the specific generation process is as follows: Define the scenario priority parameters according to the types of space TT&C missions, including the mission criticality level K, the real-time constraint coefficient T, and the data integrity weight D. Among them, the mission criticality level divides the priority coefficient according to manned spaceflight, deep space exploration, and satellite navigation. The real-time constraint coefficient is set according to the maximum allowable delay for command transmission. The data integrity weight is classified according to the error rate tolerance. Mission criticality level K: Classified by mission nature as manned spaceflight (K = 1.0), deep space exploration (K = 0.8), and satellite navigation (K = 0.6). Real-time constraint coefficient T: Set according to the maximum allowable delay for command transmission, where the rendezvous and docking mission T = 0.9, and the orbit maintenance mission T = 0.7. Data integrity weight D: Classified according to the error rate tolerance, with D = 0.8 for telemetry command transmission and D = 0.5 for payload data transmission. Thus, comprehensively calculate the weight factor α of the command transmission delay = (K × T) / (K × T + D) and the weight factor β of the signal error rate = (D) / (K × T + D). Finally, calculate the weight factor γ of the fault tolerance recovery time = 1 - (α + β). When γ is less than 0, force γ to zero. When α + β ≤ 1: γ is positive (e.g., if α = 0.4, β = 0.5, then γ = 0.1), indicating that the fault tolerance recovery time has a positive impact on the score. When α + β > 1: The calculated result of γ is negative (e.g., if α = 0.7, β = 0.6, then γ = 1 - 1.3 = -0.3). At this time, force γ to be set to 0.

[0025] The physical meaning of the weight factors (α, β, γ) is the proportion of the importance of each index, and their sum should be 1 (i.e., 100%). If α + β exceeds 1, a negative γ will result in: The sum of the weights exceeds 1 (e.g., α = 0.7, β = 0.6, γ = -0.3, and the sum is 1.0), but negative weights are meaningless. Negative weights will cause the score calculation to be distorted (e.g., the shorter the recovery time, the lower the score).

[0026] In high-priority missions (such as manned spaceflight), α and β may be significantly amplified due to the excessive product of the mission criticality (K) and the real-time constraint (T), resulting in α + β > 1. At this time: Force γ = 0, and only retain the weights of the delay and the error rate (α + β = 1), reflecting that the mission has a very high tolerance for the recovery time (e.g., in the rendezvous and docking mission, the delay and the error rate are the primary indicators).

[0027] Furthermore, perform non-linear normalization processing on the measured command transmission delay, signal error rate, and fault tolerance recovery time: The normalized value of the command transmission delay is calculated by the ratio of the difference between the measured delay and the maximum allowable delay. The signal error rate uses a logarithmic function with base 10 to compress its magnitude difference. The fault tolerance recovery time is mapped through an exponential decay function. Multiply the normalized instruction transmission delay, signal error rate, and fault tolerance recovery time by the dynamic weight factor and sum them to generate a comprehensive anti-interference performance score.

[0028] Step S5: Optimize the logical control algorithm of the space TT&C software based on the comprehensive anti-interference performance score, and perform iterative testing through the all-fiber TT&C system architecture until the preset anti-interference threshold is met.

[0029] Based on the real-time value of the comprehensive anti-interference performance score, the system automatically determines whether to enter the optimization state: when the score is higher than or equal to 60 points, the normal mode is triggered, and no optimization operation is performed on the space TT&C software; conversely, when the score is lower than 60 points, the emergency optimization mode is triggered. The operation logic of the emergency optimization mode is as follows: according to the comparison between the normalized values of each index in the comprehensive score and the preset threshold, locate the core type of performance defects: if the normalized delay value is lower than the threshold, it is determined as a communication protocol defect; if the normalized error rate value is insufficient, it is determined as an error rate defect; if the recovery time score is too low, it is determined as a recovery time defect. Optimize the communication protocol using time-sensitive network technology for communication protocol defects and deploy a lightweight protocol stack; use low-density parity-check codes and adaptive equalization algorithms to reduce the error rate for error rate defects; and shorten the recovery time for recovery time defects through dual-active hot standby mechanisms and machine learning fault prediction models. Replicate the same electromagnetic interference signal to compare the performance data before and after optimization, and load extreme interference parameters to test the algorithm robustness; at the same time, dynamically adjust the compliance threshold according to the task type. Finally, when the score fluctuation is less than the set threshold in three consecutive iterative tests, it is determined that the convergence is achieved. If it fails to meet the standard after more than ten times, manual intervention is triggered.

[0030] In the embodiment of the present invention, based on the real-time value of the comprehensive anti-interference performance score, the system automatically triggers the optimization process: when the comprehensive score ≥ 60 points, the normal mode is maintained and optimization is not started; when the score < 60 points, the emergency optimization mode is immediately entered. Its specific implementation logic is as follows: through the anti-interference performance index analysis unit, compare the normalized values of the instruction transmission delay, signal error rate, and fault tolerance recovery time with the preset thresholds (delay threshold 0.6, error rate threshold 0.7, recovery time threshold 0.5) to determine the core defect type: if the normalized delay value < 0.6, it is determined as a communication protocol defect, and the protocol reconstruction unit is triggered; if the normalized error rate value < 0.7, it is determined as an error rate defect, and the coding enhancement unit is triggered; if the normalized recovery time value < 0.5, it is determined as a recovery time defect, and the redundancy optimization unit is triggered. For communication protocol defects, the time-sensitive network technology is adopted to reconstruct the instruction scheduling strategy, a lightweight protocol stack is deployed, and the protocol parsing delay is reduced by more than 40%; for bit error rate defects, the coding scheme is upgraded to a low-density parity-check code and an adaptive equalization algorithm (such as a least mean square error equalizer) is embedded, and the signal phase distortion is compensated in real time through the radio frequency direct sampling module in the all-optical measurement and control system; for recovery time defects, the dual-active hot standby mechanism is adopted to optimize the redundant switching logic, and a fault prediction model based on LSTM is deployed. The model is trained using the historical fault data set to achieve early warning switching before the occurrence of a fault; the same electromagnetic interference signal is reproduced through the multi-band interference source of the all-optical measurement and control system, and the instruction delay, bit error rate, and recovery time data before and after optimization are compared; the limit interference parameters are loaded, and a vector signal transceiver is used to collect the signal integrity index to verify the robustness of the algorithm.

[0031] Embodiment 2 As Figure 2 shown, an automated test system for aerospace measurement and control software includes an interference signal generation module, a response data acquisition module, an interference score calculation module, and an interference iterative test module. The above-mentioned modules are connected by wired and / or wireless connection methods to realize data transmission between the modules; Interference signal generation module: Construct an all-optical measurement and control system architecture, which includes an all-optical signal transmission module, a radio frequency direct sampling module, and a digital demodulation module; simulate the complex electromagnetic environment in space to generate multi-band composite electromagnetic interference signals; Response data acquisition module: Inject the multi-band composite electromagnetic interference signal into the main signal link of the all-optical measurement and control system through an optical fiber coupler, and collect the response data of the aerospace measurement and control software in real time; Interference score calculation module: Perform a comprehensive evaluation of the anti-interference ability based on the response data, and generate a comprehensive anti-interference performance score; Interference iterative test module: Optimize the logic control algorithm of the aerospace measurement and control software based on the comprehensive anti-interference performance score, and perform iterative tests through the all-optical measurement and control system architecture until the preset anti-interference threshold is met.

[0032] It should be understood that in various embodiments of the present application, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0033] It should be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0034] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the said claims.

[0035] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An automated testing method for aerospace measurement and control software, characterized in that: include: Step S1: constructing an all-fiber measurement and control system architecture, wherein the all-fiber measurement and control system architecture includes an all-fiber signal transmission module, a radio frequency direct sampling module, and a digital demodulation module; Step S2: simulating the complex electromagnetic environment in space to generate a multi-band composite electromagnetic interference signal; Step S3: injecting the multi-band composite electromagnetic interference signal into the main signal link of the all-fiber measurement and control system through the fiber coupler, and collecting the response data of the aerospace measurement and control software in real time; Step S4: performing a comprehensive evaluation of anti-interference capability based on the response data to generate a comprehensive score of anti-interference performance; Step S5: Optimizing the logic control algorithm of the aerospace measurement and control software based on the comprehensive anti-interference performance score, and performing iterative testing through the all-fiber measurement and control system architecture until a preset anti-interference threshold is met.

2. The automated testing method for aerospace measurement and control software according to claim 1, characterized in that: The control instructions of the aerospace measurement and control software are converted into optical signals through the all-optical fiber signal transmission module, and transmitted to the simulated spacecraft under test via the optical fiber link; the optical signal is directly sampled by the radio frequency direct sampling module to generate a digital signal; the digital signal is demodulated by the digital demodulation module to obtain the interaction data between the aerospace measurement and control software and the simulated spacecraft under test.

3. The automated testing method for aerospace measurement and control software according to claim 2, characterized in that: Step S11: receiving control instructions from aerospace measurement and control software, and performing CRC check and protocol compliance verification on the instruction format; modulating the verified control instructions into an optical signal with a wavelength of 1550nm through an electro-optical converter, and the modulation mode is intensity modulation; transmitting the optical signal to the simulated spacecraft under test through a single-mode optical fiber link at a rate not less than a set threshold; Step S12: receiving an optical signal transmitted by the optical fiber link, and converting the optical signal into an analog radio frequency signal through a photodetector; performing bandpass filtering on the analog radio frequency signal to retain valid signals from the L band to the Ka band; and directly sampling the filtered signal through an ultra-wideband ADC to generate a digital signal; Step S13: Perform adaptive equalization processing on the digital signal to eliminate dispersion and nonlinear distortion in optical fiber transmission; use the QPSK demodulation algorithm to demodulate the equalized signal to generate baseband I / Q data; perform frame synchronization and decoding on the I / Q data based on the spacecraft communication protocol, and extract the command response parameters and spacecraft status telemetry parameters in the interactive data.

4. The automated testing method for aerospace measurement and control software according to claim 1, characterized in that: Generating a multi-band composite electromagnetic interference signal in step S2 specifically includes: Step S21: extracting multi-dimensional electromagnetic interference characteristic parameters based on historical spacecraft on-orbit electromagnetic interference data, wherein the characteristic parameters include solar wind disturbance spectrum distribution, intersatellite link transient harmonic phase jump characteristics, and ground multipath interference delay attenuation gradient; Step S22: using a quantum optimization algorithm to perform parameter collaborative configuration on multi-band interference sources to generate baseband interference signals covering C-band, X-band and Ku-band; Step S23: Generate a multi-band carrier component of the baseband interference signal through a direct digital frequency synthesizer, and use optical wireless modulation technology to modulate each frequency band signal onto an optical carrier of different wavelengths, and then perform spectral synthesis through a wavelength division multiplexer to generate a multi-band composite electromagnetic interference signal containing at least three independent interference frequency bands.

5. The automated testing method for aerospace measurement and control software according to claim 1, characterized in that: In step S3, the multi-band composite electromagnetic interference signal is injected into the main signal link of the all-fiber measurement and control system through the fiber coupler. During the injection process, the polarization state of the optical signal is dynamically adjusted according to the polarization sensitivity of the fiber link. The specific adjustment steps are as follows: A high-precision polarization analyzer is deployed at the receiving end of the main signal link to measure the Stokes parameters of the main link optical signal in real time, and a polarization sensitivity prediction model is constructed based on the fiber type and link length. Subsequently, the multi-band composite electromagnetic interference signal to be injected is transmitted to the polarization beam splitter through a polarization-maintaining fiber, decomposed into X / Y orthogonal polarization components, and then a dual-channel optical power meter is used to analyze the polarization ellipticity χ and azimuth θ of the interference signal online. Based on the above parameters, the polarization angle deviation Δθ and the ellipticity deviation Δχ are calculated, and the polarization matching evaluation function F is generated in combination with the preset dynamic weight coefficient. In this process, Δθ is adjusted in a proportional-integral closed-loop manner, a driving voltage V_θ that is linearly related to the angle deviation is applied, and Δχ is compensated for the optical path difference synchronously, so that the ellipticity deviation converges to the threshold range. After the adjustment is completed, the actual matching degree F_actual is periodically measured to determine whether it meets the injection requirement of F_actual≥0.

9. If the measurement meets the standard for three consecutive times, the polarization matching is completed, otherwise the adaptive iteration mechanism is triggered to recalculate the difference parameters.

6. The automated testing method for aerospace measurement and control software according to claim 1, characterized in that: The response data of the aerospace measurement and control software is collected in real time, and the response data includes instruction transmission delay, signal bit error rate and fault tolerance recovery time.

7. The automated testing method for aerospace measurement and control software according to claim 6, characterized in that: Generate a comprehensive score for anti-interference performance. The specific generation process is as follows: The scenario priority parameters are defined according to the type of aerospace measurement and control mission, including mission criticality level K, real-time constraint coefficient T and data integrity weight D; among which, the mission criticality level is divided into priority coefficients according to manned spaceflight, deep space exploration and satellite navigation, the real-time constraint coefficient is set according to the maximum delay allowed for command transmission, and the data integrity weight is graded according to the bit error rate tolerance; Thus, the weight factor α=(K×T) / (K×T+D) of the instruction transmission delay and the weight factor β=(D) / (K×T+D) of the signal bit error rate are calculated comprehensively; finally, the weight factor γ=1-(α+β) of the fault tolerance recovery time is calculated; when γ is less than 0, γ is forced to return to zero; Then, the measured command transmission delay, signal bit error rate and fault-tolerant recovery time are subjected to nonlinear normalization: the normalized value of the command transmission delay is calculated by the difference ratio between the measured delay and the maximum allowable delay; the signal bit error rate is compressed by a logarithmic function with a base of 10; the fault-tolerant recovery time is mapped by an exponential decay function; The normalized command transmission delay, signal bit error rate and fault tolerance recovery time are multiplied and summed with the dynamic weight factor to generate a comprehensive score for anti-interference performance.

8. The automated testing method for aerospace measurement and control software according to claim 1, characterized in that: The operation logic of step S5 is: According to the real-time value of the comprehensive score of anti-interference performance, the system automatically determines to enter the optimization state: when the score is higher than or equal to 60 points, the normal mode is triggered, and the aerospace measurement and control software is not optimized; conversely, when the score is lower than 60 points, the emergency optimization mode is triggered. The operation logic of the emergency optimization mode is: according to the comparison between the normalized value of each indicator in the comprehensive score and the preset threshold, the core type of performance defects is located: if the delay normalized value is lower than the threshold, it is judged as a communication protocol defect; if the bit error rate normalized value is insufficient, it is judged as a bit error rate defect; if the recovery time score is too low, it is judged as a recovery time defect; To address the defects in communication protocols, time-sensitive network technology is used to optimize the communication protocols and deploy lightweight protocol stacks; For bit error rate defects, low-density parity check code and adaptive equalization algorithm are used to reduce the bit error rate; for recovery time defects, active-active hot standby mechanism and machine learning fault prediction model are used to shorten the recovery time; Reproduce the same electromagnetic interference signal to compare the performance data before and after optimization, load extreme interference parameters to test the robustness of the algorithm, and simulate multi-spacecraft concurrent scenarios to evaluate system stability; at the same time, dynamically adjust the threshold according to the mission type; Finally, when the score fluctuation in three consecutive iterative tests is less than the set threshold, it is judged that convergence has been achieved. If it fails to meet the standard for more than ten times, manual intervention is triggered.

9. An automated test system for aerospace measurement and control software, characterized in that: The method is implemented based on an automated testing method of aerospace measurement and control software according to any one of claims 1 to 8, comprising: Interference signal generation module: construct an all-fiber measurement and control system architecture, which includes an all-fiber signal transmission module, a radio frequency direct sampling module, and a digital demodulation module; simulate the complex electromagnetic environment of space to generate a multi-band composite electromagnetic interference signal; Response data acquisition module: injects the multi-band composite electromagnetic interference signal into the main signal link of the all-fiber measurement and control system through the fiber coupler, and collects the response data of the aerospace measurement and control software in real time; Interference score calculation module: performs a comprehensive evaluation of anti-interference capability based on the response data to generate a comprehensive score of anti-interference performance; Interference iteration test module: optimizes the logic control algorithm of the aerospace measurement and control software based on the comprehensive score of the anti-interference performance, and performs iterative testing through the all-fiber measurement and control system architecture until the preset anti-interference threshold is met.

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