Satellite telemetry data analysis method, system and program product
By performing real-time analysis, time series similarity calculation, and difference processing on satellite telemetry data, confidence intervals are constructed, solving the problems of low accuracy and poor dynamic adaptability in traditional methods, and realizing dynamic anomaly detection of satellite telemetry data.
Patent Information
- Application Number
- CN202511011367.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-22
- Publication Date
- 2025-11-07
Smart Images
Figure CN120910745A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of satellite telemetry, and particularly relates to a satellite telemetry data analysis method, system and program product. BACKGROUND
[0002] Satellite telemetry data is satellite state parameters, environmental parameters, engineering parameters and other data collected in real time by sensors carried by satellites. After these data are transmitted to a ground receiving station through a telemetry system, the data are decoded, spliced and operated by professional equipment, and finally can be used for satellite state monitoring, orbit correction and other engineering applications, and can also be used as a basis for scientific research analysis. Through telemetry data, satellite operation state and system parameters can be obtained in real time, and equipment abnormalities or environmental changes can be found in a timely manner. Therefore, abnormal analysis and detection of satellite telemetry data are crucial.
[0003] Traditional satellite telemetry data abnormality analysis methods mostly use a static threshold method, that is, according to the properties and functional requirements of each item of telemetry data, a corresponding alarm threshold is set, and once the corresponding telemetry data value exceeds the alarm threshold, the data is determined to be abnormal and an alarm is given. Such an abnormality analysis method has low analysis and detection accuracy and poor dynamic adaptability, and also cannot detect abnormal data that dynamically changes within the threshold range (for example, data changes caused by some abnormal conditions may only fluctuate within the threshold range, but do not exceed the static threshold range, and will not trigger an alarm, which will cause abnormality to be missed). SUMMARY
[0004] The application aims to provide a satellite telemetry data analysis method, system and program product to solve the above problems in the prior art.
[0005] To achieve the above-mentioned purpose, the application adopts the following technical solutions:
[0006] In a first aspect, a satellite telemetry data analysis method is provided, comprising:
[0007] receiving a telemetry data packet sent by a satellite telemetry system in real time, and analyzing the telemetry data packet to obtain satellite telemetry data;
[0008] extracting satellite state parameters at a current telemetry time point from the satellite telemetry data, and adding the satellite state parameters at the current telemetry time point to a satellite state parameter sequence of a current telemetry time period to obtain a telemetry state time sequence of the current telemetry time period;
[0009] calling a reference state time sequence of the current telemetry time period, and calculating a time sequence similarity between the telemetry state time sequence of the current telemetry time period and the reference state time sequence;
[0010] When the time series similarity reaches a set condition, the satellite state parameter sequence of the current telemetry time period is subjected to difference processing to obtain a state change parameter sequence of the current telemetry time period;
[0011] A state change parameter confidence interval is determined based on the state change parameter sequence of the current telemetry time period;
[0012] The satellite state parameter of the previous telemetry time point is extracted from the satellite state parameter sequence of the current telemetry time period, and the satellite state change parameter of the current telemetry time point is calculated using the satellite state parameter of the current telemetry time point and the satellite state parameter of the previous telemetry time point;
[0013] It is determined whether the satellite state parameter of the current telemetry time point is abnormal according to the satellite state change parameter of the current telemetry time point and the state change parameter confidence interval, and satellite telemetry abnormality early warning information is output when it is determined that the satellite state parameter of the current telemetry time point is abnormal.
[0014] In one possible design, the telemetry data packet is parsed to obtain satellite telemetry data, including:
[0015] The decryption key is called from the key library, and the telemetry data packet is decrypted using the SM4 block cipher algorithm based on the decryption key to obtain the to-be-verified telemetry data and the hash check code;
[0016] The to-be-verified telemetry data is subjected to hash calculation to obtain the hash value of the to-be-verified telemetry data;
[0017] The hash value of the to-be-verified telemetry data is compared with the hash check code, and when the two are consistent, the to-be-verified telemetry data is taken as the satellite telemetry data.
[0018] In one possible design, the satellite state parameter of the current telemetry time point is extracted from the satellite telemetry data, including:
[0019] The state parameter split identifier in the satellite telemetry data is searched for, and the state parameter group is split from the satellite state parameter according to the searched state parameter split identifier;
[0020] The current telemetry time, the linear transformation parameter, and the initial state parameter are sequentially extracted from the state parameter group, and the current telemetry time is subjected to time verification;
[0021] After the time verification passes, the initial state parameter is subjected to linear transformation processing using the linear transformation parameter to obtain the transformed state parameter, and the transformed state parameter is subjected to radix conversion processing to obtain the satellite state parameter of the current telemetry time point.
[0022] In a possible design, the calculating the time series similarity between the telemetry state time series of the current telemetry period and the reference state time series comprises the following steps.
[0023] The DTW distance between the telemetry state time series of the current telemetry period and the reference state time series is calculated by using the DTW algorithm.
[0024] The DTW distance between the telemetry state time series and the reference state time series is normalized to obtain a normalized distance d.
[0025] The time series similarity S between the telemetry state time series of the current telemetry period and the reference state time series is calculated by using the normalized distance d, S = 1 / d.
[0026] In a possible design, the differentiating the satellite state parameter sequence of the current telemetry period to obtain the state change parameter sequence of the current telemetry period comprises the following steps.
[0027] The satellite state parameter sequence X of the current telemetry period is determined, X = {x(t), x(t-T), x(t-2T),..., x(t-nT)}, where t represents a previous telemetry time, x(t) represents a satellite state parameter at the previous telemetry time point, T represents a telemetry time interval, and n is a quantity parameter.
[0028] The satellite state parameter sequence X of the current telemetry period is substituted into the difference formula to perform difference calculation, the difference formula being
[0029]
[0030] where N is the number of difference items, N = n, y N represents the Nth difference item.
[0031] Each difference item obtained by the difference calculation is taken as a corresponding state change parameter, and the state change parameter sequence Y of the current telemetry period is constructed by using the state change parameters, Y = {y1, y2,..., yn}. N
[0032] In a possible design, the determining the state change parameter confidence interval based on the state change parameter sequence of the current telemetry period comprises the following steps.
[0033] The maximum value A of the state change parameter in the state change parameter sequence of the current telemetry period and the minimum value B of the state change parameter are determined.
[0034] An initial lower limit value M1 is calculated using the maximum value A of the state change parameter and the minimum value B of the state change parameter, M1 = B + [(A-B) x e], e being a set interval division coefficient and e < 0.5, and an initial upper limit value M2 is calculated using the maximum value A of the state change parameter and the minimum value B of the state change parameter, M2 = A - [(A-B) x e];
[0035] An interval lower limit value Q1 is calculated using the initial lower limit value M1 and the initial upper limit value M2, Q1 = M1 - 1.5 x (M1-M2), and an interval upper limit value Q2 is calculated using the initial lower limit value M1 and the initial upper limit value M2, Q2 = M2 + 1.5 x (M1-M2);
[0036] The state change parameter confidence interval [Q1, Q2] is constructed using the interval lower limit value Q1 and the interval upper limit value Q2.
[0037] In one possible design, the judging whether the satellite state parameter at the current telemetry time point is abnormal according to the satellite state change parameter at the current telemetry time point and the state change parameter confidence interval comprises:
[0038] The satellite state change parameter at the current telemetry time point is compared with the state change parameter confidence interval to judge whether the satellite state change parameter at the current telemetry time point is within the state change parameter confidence interval;
[0039] If the satellite state change parameter at the current telemetry time point is not within the state change parameter confidence interval, it is determined that the satellite state parameter at the current telemetry time point is abnormal, otherwise, it is determined that the satellite state parameter at the current telemetry time point is normal.
[0040] In a second aspect, a satellite telemetry data analysis system is provided, comprising a data receiving unit, a data analysis unit, a time sequence matching unit, a difference processing unit, an interval judging unit, a parameter calculation unit and an abnormality detecting unit, wherein:
[0041] The data receiving unit is configured to receive a telemetry data packet sent by a satellite telemetry system in real time, analyze the telemetry data packet, and obtain satellite telemetry data;
[0042] The data analysis unit is configured to extract a satellite state parameter at a current telemetry time point from the satellite telemetry data, add the satellite state parameter at the current telemetry time point to a satellite state parameter sequence of a current telemetry period, and obtain a telemetry state time sequence of the current telemetry period;
[0043] The time sequence matching unit is configured to call a reference state time sequence of the current telemetry period, and calculate a time sequence similarity between the telemetry state time sequence of the current telemetry period and the reference state time sequence;
[0044] a differential processing unit configured to perform differential processing on the satellite state parameter sequence of the current telemetry time period to obtain a state change parameter sequence of the current telemetry time period when the time sequence similarity reaches a set condition;
[0045] an interval determination unit configured to determine a state change parameter confidence interval based on the state change parameter sequence of the current telemetry time period;
[0046] a parameter calculation unit configured to extract the satellite state parameter of a previous telemetry time point from the satellite state parameter sequence of the current telemetry time period, and calculate the satellite state change parameter of the current telemetry time point by using the satellite state parameter of the current telemetry time point and the satellite state parameter of the previous telemetry time point;
[0047] an anomaly detection unit configured to determine whether the satellite state parameter of the current telemetry time point is abnormal according to the satellite state change parameter of the current telemetry time point and the state change parameter confidence interval, and output satellite telemetry anomaly early warning information when it is determined that the satellite state parameter of the current telemetry time point is abnormal.
[0048] In a third aspect, a satellite telemetry data analysis system is provided, comprising:
[0049] a memory configured to store instructions;
[0050] a processor configured to read the instructions stored in the memory and execute the satellite telemetry data analysis method of any one of the first aspect according to the instructions.
[0051] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores instructions thereon, when the instructions are executed on a computer, the computer is caused to execute the satellite telemetry data analysis method of any one of the first aspect. Meanwhile, a computer program product is also provided, and when the computer program product is executed on a computer, the satellite telemetry data analysis method of any one of the first aspect is executed.
[0052] Beneficial effects: The satellite telemetry data received is analyzed to obtain real-time satellite state parameters, a telemetry state time sequence is constructed, the telemetry state time sequence is matched and verified with reference time sequence, differential processing and confidence interval calculation are performed on the telemetry state time sequence, a dynamic confidence interval is determined, and finally the state change parameter between the real-time satellite state parameter and the satellite state parameter at the previous time is detected for anomaly by using the confidence interval, and if an anomaly is detected, an anomaly early warning is performed, so as to realize efficient and accurate satellite telemetry data analysis. The present application can effectively solve the problems of poor analysis accuracy and poor dynamic adaptability of the traditional static threshold determination method, can completely adapt to the dynamic change characteristics of satellite telemetry data, realize dynamic analysis and detection of satellite telemetry data, and accurately determine the abnormal situation of satellite telemetry data. Attached Figure Description
[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0054] Figure 1 This is a flowchart illustrating the method in Embodiment 1 of the present invention;
[0055] Figure 2 This is a schematic diagram of the system configuration in Embodiment 2 of the present invention;
[0056] Figure 3 This is a schematic diagram of the system configuration in Embodiment 3 of the present invention. Detailed Implementation
[0057] It should be noted that the descriptions of these embodiments are intended to aid in understanding the invention and do not constitute a limitation thereof. The specific structural and functional details disclosed herein are merely for describing exemplary embodiments of the invention. However, the invention may be embodied in many alternative forms and should not be construed as being limited to the embodiments described herein.
[0058] It should be understood that, unless otherwise explicitly specified and limited, the corresponding terms should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments according to the specific circumstances.
[0059] Specific details are provided in the following description to provide a complete understanding of the exemplary embodiments. However, those skilled in the art will understand that the exemplary embodiments can be implemented without these specific details. For example, apparatus may be shown in block diagrams to avoid obscuring the examples with unnecessary details. In other embodiments, well-known processes, structures, and techniques may be omitted with non-essential details to avoid obscuring the embodiments.
[0060] Example 1:
[0061] This embodiment provides a satellite telemetry data analysis method, which can be applied to corresponding ground monitoring systems, such as... Figure 1 As shown, the method includes the following steps:
[0062] S1. Real-time receive the telemetry data packet sent by the satellite telemetry system, and parse the telemetry data packet to obtain satellite telemetry data.
[0063] In specific implementation, the satellite telemetry system collects relevant parameters of the satellite according to a fixed sampling frequency, and then marks the corresponding telemetry time and transmits the telemetry data packet to the ground monitoring system. The ground monitoring system receives the telemetry data packet sent by the satellite telemetry system in real time, then retrieves the decryption key from the key library, and decrypts the telemetry data packet based on the decryption key using the SM4 block cipher algorithm to obtain the to-be-verified telemetry data and the hash check code; then, the hash value of the to-be-verified telemetry data is obtained by performing hash calculation on the to-be-verified telemetry data; and finally, the hash value of the to-be-verified telemetry data is compared with the hash check code, and when the two are consistent, the to-be-verified telemetry data is taken as the satellite telemetry data.
[0064] S2. Extract the satellite state parameter at the current telemetry time point from the satellite telemetry data, and add the satellite state parameter at the current telemetry time point to the satellite state parameter sequence of the current telemetry period to obtain the telemetry state time sequence of the current telemetry period.
[0065] In specific implementation, the satellite telemetry data contains satellite state parameters such as combustion chamber pressure, propellant level, and turbine pump speed, which are related to the safety and stability of satellite operation. After obtaining the satellite telemetry data, the ground monitoring system can traverse and find the state parameter segmentation identifier in the satellite telemetry data, and segment the state parameter group from the satellite state parameter according to the found state parameter segmentation identifier; then, the current telemetry time, the linear transformation parameter and the initial state parameter are extracted from the state parameter group in turn, and the current telemetry time is time-verified (the current telemetry time is compared with the system time, and if the time difference between the two is not more than a threshold value, the time verification is passed); after the time verification is passed, the initial state parameter is linearly transformed using the linear transformation parameter to obtain the transformed state parameter, and the transformed state parameter is processed by radix conversion to obtain the satellite state parameter at the current telemetry time point.
[0066] Then, the ground monitoring system adds the satellite state parameter at the current telemetry time point to the satellite state parameter sequence of the current telemetry period (the satellite state parameter sequence of the current telemetry period contains satellite state parameters corresponding to a plurality of historical telemetry time points in the current telemetry period) to obtain the telemetry state time sequence of the current telemetry period.
[0067] S3. Retrieve the reference state time sequence of the current telemetry period, and calculate the time sequence similarity between the telemetry state time sequence of the current telemetry period and the reference state time sequence.
[0068] In implementation, the ground monitoring system calls the pre-stored reference state time sequence of the current telemetry period, which can be obtained by simulating and predicting the satellite operation state parameters by the ground monitoring system in advance. After calling the reference state time sequence of the current telemetry period, the system can calculate the DTW distance between the telemetry state time sequence and the reference state time sequence of the current telemetry period by using the DTW algorithm; then, the DTW distance between the telemetry state time sequence and the reference state time sequence is normalized to obtain the normalized distance d; then, the time sequence similarity S between the telemetry state time sequence and the reference state time sequence of the current telemetry period is calculated by using the normalized distance d, S = 1 / d. If the time sequence similarity S meets the set condition, the system can output the corresponding abnormal prompt information.
[0069] S4. When the time sequence similarity meets the set condition, the satellite state parameter sequence of the current telemetry period is subjected to difference processing to obtain the state change parameter sequence of the current telemetry period.
[0070] In implementation, when the time sequence similarity meets the set condition, the ground monitoring system determines the satellite state parameter sequence X of the current telemetry period, X = {x(t), x(t-T), x(t-2T),..., x(t-nT)}, where t represents the last telemetry time, x(t) represents the satellite state parameter at the last telemetry time point, T represents the telemetry time interval, and n is a quantity parameter; then, the satellite state parameter sequence X of the current telemetry period is substituted into the difference formula for difference calculation, the difference formula being
[0071]
[0072] where N is the number of difference items, N = n, y N represents the Nth difference item; each difference item obtained by difference calculation is taken as a corresponding state change parameter, and the state change parameter sequence Y of the current telemetry period is constructed by using each state change parameter, Y = {y1, y2,..., y N
[0073] S5. The state change parameter confidence interval is determined based on the state change parameter sequence of the current telemetry period.
[0074] In specific implementation, the ground monitoring system determines a maximum state change parameter A and a minimum state change parameter B in the state change parameter sequence of the current telemetry period; then calculates an initial lower limit value M1 using the maximum state change parameter A and the minimum state change parameter B, M1 = B + [(A-B) x ε], where ε is a set interval division coefficient and ε < 0.5, calculates an initial upper limit value M2 using the maximum state change parameter A and the minimum state change parameter B, M2 = A - [(A-B) x ε]; then calculates an interval lower limit value Q1 using the initial lower limit value M1 and the initial upper limit value M2, Q1 = M1 - 1.5 x (M1-M2), calculates an interval upper limit value Q2 using the initial lower limit value M1 and the initial upper limit value M2, Q2 = M2 + 1.5 x (M1-M2); and finally constructs a state change parameter confidence interval [Q1, Q2] using the interval lower limit value Q1 and the interval upper limit value Q2.
[0075] S6. Extracting a satellite state parameter at a previous telemetry time point from the satellite state parameter sequence of the current telemetry period, and calculating a satellite state change parameter at the current telemetry time point using the satellite state parameter at the current telemetry time point and the satellite state parameter at the previous telemetry time point.
[0076] In specific implementation, the ground monitoring system extracts a satellite state parameter at a previous telemetry time point from the satellite state parameter sequence of the current telemetry period, and then calculates a satellite state change parameter at the current telemetry time point by subtracting the satellite state parameter at the previous telemetry time point from the satellite state parameter at the current telemetry time point.
[0077] S7. Judging whether the satellite state parameter at the current telemetry time point is abnormal according to the satellite state change parameter at the current telemetry time point and the state change parameter confidence interval, and outputting satellite telemetry abnormality early warning information when it is judged that the satellite state parameter at the current telemetry time point is abnormal.
[0078] In specific implementation, the ground monitoring system compares the satellite state change parameter at the current telemetry time point with the state change parameter confidence interval to judge whether the satellite state change parameter at the current telemetry time point is within the state change parameter confidence interval. If the satellite state change parameter at the current telemetry time point is not within the state change parameter confidence interval, it is judged that the satellite state parameter at the current telemetry time point is abnormal, otherwise, it is judged that the satellite state parameter at the current telemetry time point is normal. When it is judged that the satellite state parameter at the current telemetry time point is abnormal, the system outputs satellite telemetry abnormality early warning information.
[0079] The method can effectively solve the problems of poor analysis accuracy and poor dynamic adaptability existing in the traditional static threshold judgment method, can fully adapt to the dynamic change characteristics of satellite telemetry data, and can realize dynamic analysis and detection of satellite telemetry data and accurately judge abnormal conditions of satellite telemetry data.
[0080] Embodiment 2:
[0081] The embodiment provides a satellite telemetry data analysis system, as shown in Figure 2 The satellite telemetry data analysis system comprises a data receiving unit, a data analysis unit, a time sequence matching unit, a differential processing unit, an interval determination unit, a parameter calculation unit and an anomaly detection unit, wherein:
[0082] The data receiving unit is configured to receive a telemetry data packet transmitted by a satellite telemetry system in real time, analyze the telemetry data packet, and obtain satellite telemetry data.
[0083] The data analysis unit is configured to extract a satellite state parameter at a current telemetry time point from the satellite telemetry data, add the satellite state parameter at the current telemetry time point to a satellite state parameter sequence of a current telemetry time period, and obtain a telemetry state time sequence of the current telemetry time period.
[0084] The time sequence matching unit is configured to call a reference state time sequence of the current telemetry time period, and calculate a time sequence similarity between the telemetry state time sequence of the current telemetry time period and the reference state time sequence.
[0085] The differential processing unit is configured to perform differential processing on the satellite state parameter sequence of the current telemetry time period when the time sequence similarity reaches a set condition, and obtain a state change parameter sequence of the current telemetry time period.
[0086] The interval determination unit is configured to determine a state change parameter confidence interval based on the state change parameter sequence of the current telemetry time period.
[0087] The parameter calculation unit is configured to extract a satellite state parameter at a previous telemetry time point from the satellite state parameter sequence of the current telemetry time period, and calculate a satellite state change parameter at the current telemetry time point by using the satellite state parameter at the current telemetry time point and the satellite state parameter at the previous telemetry time point.
[0088] The anomaly detection unit is configured to determine whether the satellite state parameter at the current telemetry time point is abnormal according to the satellite state change parameter at the current telemetry time point and the state change parameter confidence interval, and output satellite telemetry anomaly early warning information when it is determined that the satellite state parameter at the current telemetry time point is abnormal.
[0089] Embodiment 3:
[0090] The embodiment provides a satellite telemetry data analysis system, as shown in Figure 3 At a hardware level, the satellite telemetry data analysis system comprises:
[0091] The data interface is configured to establish data connection between the processor and an external data terminal.
[0092] The memory is configured to store instructions.
[0093] a processor configured to read instructions stored in the memory and perform the satellite telemetry data analysis method in embodiment 1 according to the instructions.
[0094] Optionally, the system further comprises an internal bus through which the processor, the memory and the data interface are connected to each other, the internal bus can be a PCIe (Peripheral Component Interconnect Express) bus, and the bus can be divided into an address bus, a data bus, a control bus, etc. The memory can include, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a flash memory, a first-in first-out memory (FIFO) and / or a first-in last-out memory (FILO), etc. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.
[0095] Embodiment 4:
[0096] The embodiment provides a computer-readable storage medium, and instructions are stored on the computer-readable storage medium. When the instructions are run on a computer, the computer is caused to perform the satellite telemetry data analysis method in embodiment 1. The computer-readable storage medium is a carrier for storing data, and can include, but is not limited to, a floppy disk, an optical disc, a hard disk, a flash memory, a USB flash disk and / or a memory stick, etc. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices.
[0097] The embodiment further provides a computer program product, and when the computer program product is run on a computer, the satellite telemetry data analysis method in embodiment 1 is performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices.
[0098] It should be pointed out finally that the above description is only for preferred embodiments of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims
1. A method of satellite telemetry data analysis, characterized in that, The method comprises the following steps: real-time receiving of a telemetry data packet sent by a satellite telemetry system, and analysis of the telemetry data packet to obtain satellite telemetry data; extraction of satellite state parameters at a current telemetry time point from the satellite telemetry data, and addition of the satellite state parameters at the current telemetry time point to a satellite state parameter sequence of a current telemetry time period to obtain a telemetry state time sequence of the current telemetry time period; calling of a reference state time sequence of the current telemetry time period, and calculation of a time sequence similarity between the telemetry state time sequence of the current telemetry time period and the reference state time sequence; when the time sequence similarity reaches a set condition, differential processing of the satellite state parameter sequence of the current telemetry time period to obtain a state change parameter sequence of the current telemetry time period; determination of a state change parameter confidence interval based on the state change parameter sequence of the current telemetry time period; extraction of satellite state parameters at a previous telemetry time point from the satellite state parameter sequence of the current telemetry time period, and calculation of satellite state change parameters at the current telemetry time point using the satellite state parameters at the current telemetry time point and the satellite state parameters at the previous telemetry time point; determination of whether the satellite state parameters at the current telemetry time point are abnormal based on the satellite state change parameters at the current telemetry time point and the state change parameter confidence interval, and output of satellite telemetry abnormality early warning information when it is determined that the satellite state parameters at the current telemetry time point are abnormal.
2. The method of claim 1, wherein, The analysis of the telemetry data packet to obtain satellite telemetry data comprises the following steps: calling of a decryption key from a key library, decryption processing of the telemetry data packet based on the decryption key using an SM4 block cipher algorithm to obtain to-be-verified telemetry data and a hash check code; hash calculation of the to-be-verified telemetry data to obtain a hash value of the to-be-verified telemetry data; comparison of the hash value of the to-be-verified telemetry data with the hash check code, and taking the to-be-verified telemetry data as the satellite telemetry data when the two are consistent.
3. The method of claim 1, wherein, The extraction of satellite state parameters at a current telemetry time point from the satellite telemetry data comprises the following steps: iterative search for a state parameter segmentation identifier in the satellite telemetry data, and segmentation of state parameters from the satellite state parameters according to the searched state parameter segmentation identifier; iterative extraction of a current telemetry time, linear transformation parameters and initial state parameters from the state parameter group, and time verification of the current telemetry time; after the time verification passes, linear transformation processing of the initial state parameters using the linear transformation parameters to obtain transformed state parameters, and decimal conversion processing of the transformed state parameters to obtain the satellite state parameters at the current telemetry time point.
4. The method of claim 1, wherein, The calculation of the time sequence similarity between the telemetry state time sequence of the current telemetry time period and the reference state time sequence comprises the following steps: calculation of a DTW distance between the telemetry state time sequence of the current telemetry time period and the reference state time sequence using a DTW algorithm; normalization processing of the DTW distance between the telemetry state time sequence and the reference state time sequence to obtain a normalized distance d; calculation of the time sequence similarity S between the telemetry state time sequence of the current telemetry time period and the reference state time sequence using the normalized distance d, S = 1 / d.
5. The method of claim 1, wherein, The satellite state parameter sequence of the current telemetry time period is differentially processed to obtain a state change parameter sequence of the current telemetry time period, including: determining the satellite state parameter sequence X of the current telemetry time period, X={x(t), x(t-T), x(t-2T),..., x(t-nT)}, where t represents the last telemetry time, x(t) represents the satellite state parameter at the last telemetry time point, T represents the telemetry time interval, and n is a quantity parameter; the satellite state parameter sequence X of the current telemetry time period is substituted into a differential formula for differential calculation, and the differential formula is where N is the number of difference terms, N = n, y N characterize the Nth difference term; The difference terms obtained from the difference calculation are used as the corresponding state change parameters, and the state change parameter sequence Y for the current telemetry period is constructed using these state change parameters, Y = {y1, y2, ..., y...}. N } 6. The method of claim 1, wherein, The state change parameter confidence interval is determined based on the state change parameter sequence of the current telemetry time period, including: determining the maximum state change parameter A and the minimum state change parameter B in the state change parameter sequence of the current telemetry time period; an initial lower limit value M1 is calculated using the maximum state change parameter A and the minimum state change parameter B, M1=B+[(A-B)×ε], where ε is a set interval division coefficient and ε<0.5, and an initial upper limit value M2 is calculated using the maximum state change parameter A and the minimum state change parameter B, M2=A-[(A-B)×ε]; an interval lower limit value Q1 is calculated using the initial lower limit value M1 and the initial upper limit value M2, Q1=M1-1.5×(M1-M2), and an interval upper limit value Q2 is calculated using the initial lower limit value M1 and the initial upper limit value M2, Q2=M2+1.5×(M1-M2); the state change parameter confidence interval [Q1, Q2] is constructed using the interval lower limit value Q1 and the interval upper limit value Q2.
7. The method of claim 1, wherein, The satellite state parameter of the current telemetry time point is determined to be abnormal or normal according to the satellite state change parameter of the current telemetry time point and the state change parameter confidence interval, including: the satellite state change parameter of the current telemetry time point is compared with the state change parameter confidence interval to determine whether the satellite state change parameter of the current telemetry time point is within the state change parameter confidence interval; if the satellite state change parameter of the current telemetry time point is not within the state change parameter confidence interval, it is determined that the satellite state parameter of the current telemetry time point is abnormal, otherwise, it is determined that the satellite state parameter of the current telemetry time point is normal.
8. A satellite telemetry data analysis system characterized by, The system comprises a data receiving unit, a data analysis unit, a time sequence matching unit, a differential processing unit, an interval determination unit, a parameter calculation unit, and an abnormality detection unit, wherein: The data receiving unit is configured to receive telemetry data packets sent by a satellite telemetry system in real time, analyze the telemetry data packets, and obtain satellite telemetry data. The data analysis unit is configured to extract the satellite state parameter of the current telemetry time point from the satellite telemetry data, add the satellite state parameter of the current telemetry time point to the satellite state parameter sequence of the current telemetry time period, and obtain a telemetry state time sequence of the current telemetry time period. The time sequence matching unit is configured to call a reference state time sequence of the current telemetry time period, and calculate the time sequence similarity between the telemetry state time sequence of the current telemetry time period and the reference state time sequence. a difference processing unit configured to perform difference processing on the satellite state parameter sequence of the current telemetry time period to obtain a state change parameter sequence of the current telemetry time period when the time sequence similarity reaches a set condition; an interval determination unit configured to determine a state change parameter confidence interval based on the state change parameter sequence of the current telemetry time period; a parameter calculation unit configured to extract a satellite state parameter at a previous telemetry time point from the satellite state parameter sequence of the current telemetry time period, and calculate a satellite state change parameter at the current telemetry time point using the satellite state parameter at the current telemetry time point and the satellite state parameter at the previous telemetry time point; an anomaly detection unit configured to determine whether the satellite state parameter at the current telemetry time point is abnormal according to the satellite state change parameter at the current telemetry time point and the state change parameter confidence interval, and output satellite telemetry anomaly early warning information when it is determined that the satellite state parameter at the current telemetry time point is abnormal.
9. A satellite telemetry data analysis system characterized by, comprising: a memory configured to store instructions; a processor configured to read the instructions stored in the memory, and execute the satellite telemetry data analysis method according to any one of claims 1-7 according to the instructions.
10. A computer program product, characterised in that, when the computer program product is run on a computer, the satellite telemetry data analysis method according to any one of claims 1-7 is executed.