A Wireless Testing Method for Satellite Telemetry and Control Systems Based on Dynamic Decoding

Abstract

This invention discloses a wireless testing method for a satellite telemetry, tracking, and command (TT&C) system based on dynamic decoding, targeting a pre-defined satellite TT&C system. The method includes: establishing a communication link between a platform module's ground-to-ground TT&C antenna and ground testing equipment; transmitting uplink remote control data via the ground testing equipment, which is received and processed by the platform module's ground-to-ground TT&C antenna and a USB transponder to achieve platform module remote control testing; transmitting on-satellite telemetry data downlink via the platform module's ground-to-ground TT&C antenna, which is received and processed by the ground testing equipment to achieve platform module telemetry testing; transmitting uplink remote control data via the ground testing equipment, which is received and processed by the platform module's ground-to-ground TT&C antenna and a USB transponder, and then transmitted to the payload module to achieve payload module remote control testing; and transmitting payload module telemetry information to the platform module, where the platform module's ground-to-ground TT&C antenna transmits payload module telemetry data downlink, which is received and processed by the ground testing equipment to achieve payload module telemetry testing. This invention improves the overall design of microsatellites, adapts to dynamic communication environments, enables real-time data interaction, and improves information transmission efficiency.

Description

Technical Field

[0001] This invention belongs to the field of satellite telemetry, tracking and command (TT&C), and specifically relates to a wireless testing method for satellite TT&C systems based on dynamic decoding. Background Technology

[0002] Because separable microsatellites employ a configuration where the payload compartment and platform compartment can be separated, they are capable of undertaking more diverse on-orbit missions, and have thus become a focus of attention in related fields in recent years.

[0003] However, solving the problems of communication between the two modules and communication with the ground when the two modules of a separable satellite are separated, as well as testing issues, especially how to improve the overall design of microsatellites, and how to adapt to dynamic communication environments, achieve real-time data interaction, and improve information transmission efficiency during testing, are still some key issues that plague the industry. Summary of the Invention

[0004] To address the aforementioned problems in the existing technology, this invention provides a wireless testing method for satellite telemetry and control systems based on dynamic decoding. The technical problem to be solved by this invention is achieved through the following technical solution: A wireless testing method for a satellite telemetry, tracking, and command (TT&C) system based on dynamic decoding, targeting a pre-defined satellite TT&C system. The pre-defined satellite TT&C system includes a separate payload compartment and a platform compartment. The payload compartment includes payload data processing equipment, payload wireless communication equipment, and a payload wireless communication antenna. The platform compartment includes platform data processing equipment, platform wireless communication equipment, a platform wireless communication antenna, a USB transponder, a multi-port network, and a platform-to-ground TT&C antenna. The method includes: A communication link is established between the platform cabin's ground-based telemetry and control antenna and the ground-based testing equipment. The platform cabin wireless test is completed by sending uplink remote control data through the ground test equipment, and receiving and processing the data with the platform cabin's ground telemetry and control antenna and the USB transponder to realize the platform cabin remote control test; and by transmitting satellite telemetry data downlink through the platform cabin's ground telemetry and control antenna, and receiving and processing the data with the ground test equipment to realize the platform cabin telemetry test. The payload compartment wireless testing process includes: sending uplink remote control data via the ground testing equipment; receiving and processing this data via the platform compartment's ground telemetry antenna and the USB transponder; and transmitting the data to the payload compartment via a two-compartment communication link to achieve remote control testing of the payload compartment. It also includes transmitting payload compartment telemetry information to the platform compartment via the two-compartment communication link; the platform compartment's ground telemetry antenna then transmits payload compartment telemetry data downlink; and the ground testing equipment receives and processes this data to achieve payload compartment telemetry testing. The two-compartment communication link is constructed based on the wireless communication equipment and antennas of both compartments. The USB transponder is a fully digital USB transponder, and the decoding of the received data employs a dynamic decoding method based on dynamic adjustment of normalized parameters.

[0005] In one embodiment of the present invention, the USB transponder is used to perform telemetry and control of the ground via the platform compartment's ground telemetry and control antenna, including platform compartment uplink remote control, platform compartment downlink telemetry, payload compartment uplink remote control, and payload compartment downlink telemetry.

[0006] In one embodiment of the present invention, the USB transponder includes: Radio frequency receiver module, baseband module, remote control FPGA module, management module, power supply module, and radio frequency transmitter module; The radio frequency (RF) receiving module is configured to: receive and process uplink RF signals, and output uplink intermediate frequency (IF) signals to the baseband module; the baseband module is configured to: generate its own telemetry information for the management module, and demodulate remote control baseband information and ranging tone information from the uplink IF signals and provide them to the remote control FPGA module and the RF transmitting module respectively, and also receive on-board telemetry data and transmit it to the RF transmitting module; the remote control FPGA module is configured to: generate its own FPGA telemetry information and process the remote control baseband information to obtain remote control data and remote control commands, transmit the remote control data to the preset management system, and transmit the FPGA's own telemetry information and the remote control commands... The data is transmitted to the management module and also used to receive on-board telemetry data transmitted by the preset management system and output it to the baseband module; the management module is used to: generate its own telemetry information and receive its own telemetry information and remote control commands output by the remote control FPGA module and the baseband module, and transmit all telemetry information to the preset management system for processing, and transmit the remote control commands to at least the baseband module and the remote control FPGA module as control commands; the power supply module is used to provide different voltage values ​​required by each module; the radio frequency transmission module is used to receive the ranging tone information and the on-board telemetry data output by the baseband module, process them, generate downlink radio frequency signals, and transmit them to the ground.

[0007] In one embodiment of the present invention, the baseband module is implemented based on an ASIC chip and includes a PROM configuration chip, wherein the configuration information in the PROM configuration chip is set according to task requirements.

[0008] In one embodiment of the present invention, the radio frequency receiving module adopts a double frequency conversion, wherein the local oscillator adopts a phase-locked loop frequency multiplication method, and the second local oscillator is generated by the provided high-stability clock signal after passing through a frequency divider and a phase-locked loop frequency multiplication.

[0009] In one embodiment of the present invention, the radio frequency transmitting module adopts a double frequency conversion, wherein the first local oscillator is generated by the split signal output of the crystal oscillator, and the second local oscillator is a phase-locked loop frequency multiplier signal.

[0010] In one embodiment of the present invention, the dynamic decoding method includes: After performing data preprocessing on the information to be decoded, the weight parameter group, cutoff parameter and adjustment parameter corresponding to the information to be decoded are determined. Each weight parameter group contains the weight parameters corresponding to each iteration number after the first iteration. Based on the relationship between the iteration number and the cutoff parameter, determine the normalization parameter corresponding to the iteration number; Based on the normalization parameter corresponding to the iteration number and the information of the variable nodes obtained from previous iterations, the information of the verification nodes and variable nodes is updated, the information of the decision nodes is calculated, and the decoding is completed to obtain the decoded data. If the decoding termination condition is met, the decoded data is taken as the decoding result; otherwise, the process returns to the step of determining the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter, and continues iterating.

[0011] In one embodiment of the present invention, determining the weight parameter group, cutoff parameter, and adjustment parameter corresponding to the information to be decoded includes: The signal-to-noise ratio of the information to be decoded is obtained by using the calculated noise variance of the information to be decoded; Based on a predetermined correspondence between signal-to-noise ratio and weight parameter set, cutoff parameter and adjustment parameter, determine the weight parameter set, cutoff parameter and adjustment parameter corresponding to the signal-to-noise ratio of the information to be decoded.

[0012] In one embodiment of the present invention, the process of determining the parameter correspondence includes: For each of a pre-set plurality of signal-to-noise ratios, multiple sample decoding information is obtained for that signal-to-noise ratio; wherein, the step size of adjacent signal-to-noise ratios among the plurality of signal-to-noise ratios is equal; For each sample of information to be decoded at this signal-to-noise ratio, the original mean and estimated mean of information in the information matrix of the verification node at each iteration number are calculated using the BP decoding algorithm and the MS decoding algorithm respectively. The weight parameter of the sample of information to be decoded corresponding to the iteration number is obtained using the original mean and estimated mean of information at each iteration number. The average of the weight parameters corresponding to the same iteration number among the weight parameters of all samples to be decoded for this signal-to-noise ratio is obtained to get the weight parameter group corresponding to this signal-to-noise ratio. The iteration number corresponding to the smallest weight parameter in the weight parameter group corresponding to the signal-to-noise ratio is used as the cutoff parameter corresponding to the signal-to-noise ratio. Based on the weight parameter group, cutoff parameter, and the original mean and estimated mean of information corresponding to the cutoff parameter, the adjustment parameter corresponding to the signal-to-noise ratio is determined using the adjustment parameter determination formula. The parameter correspondence is constituted by each signal-to-noise ratio and its corresponding weight parameter group, cutoff parameter, and adjustment parameter.

[0013] In one embodiment of the present invention, determining the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter includes: When the iteration number is one, the normalization parameter is a predetermined value; When the iteration number is greater than one and less than or equal to the cutoff parameter, the normalization parameter is the sum of the weight parameter corresponding to the iteration number and the normalization parameter corresponding to the previous iteration number in the weight parameter group; When the iteration number is greater than the cutoff parameter, the normalization parameter is the product of the normalization parameter when the iteration number is equal to the cutoff parameter and the adjustment parameter.

[0014] Compared with existing technologies, in the pre-set satellite telemetry and control system of this invention, the satellite's payload compartment and platform compartment can share a single telemetry and control antenna (i.e., the platform compartment's ground-to-ground telemetry and control antenna) to receive uplink remote control information from ground test equipment. This eliminates the need for a separate telemetry and control antenna for the payload compartment, effectively reducing satellite weight and benefiting the overall design of microsatellites. Furthermore, the wireless testing method for satellite telemetry and control systems based on dynamic decoding provided in this invention can receive telemetry data from the payload compartment in real time, process it, and then wirelessly relay it to the ground test equipment via the platform compartment's radio frequency to achieve satellite-to-ground data transmission. It can also utilize the wireless inter-satellite communication channel between the payload compartment and the platform compartment to achieve real-time data interaction between them, thus improving information transmission efficiency and solving communication problems between the two compartments, ground-to-ground communication problems, and testing problems. Additionally, the USB transponder in the platform compartment of this invention is a fully digital USB transponder, resulting in high integration, reduced size and weight, making it more suitable for microsatellites, and offering simple debugging, strong versatility, and high flexibility. Meanwhile, the USB transponder in this embodiment of the invention employs a dynamic decoding method based on dynamic adjustment of normalized parameters during decoding processing. This method can dynamically adjust the normalized parameters to better adapt to dynamic communication environments, reduce bit error rate, and improve decoding efficiency. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating a wireless testing method for a satellite telemetry and control system based on dynamic decoding, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the preset satellite telemetry and control system provided in the embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a USB transponder according to an embodiment of the present invention; Figure 4 This is a flowchart illustrating the dynamic decoding method provided in an embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] like Figure 1 As shown, the present invention provides a wireless testing method for a satellite telemetry and control system based on dynamic decoding, targeting a preset satellite telemetry and control system, such as... Figure 2As shown, the preset satellite telemetry and control system includes a separate payload compartment and a platform compartment. The payload compartment includes payload data processing equipment, payload wireless communication equipment, and payload wireless communication antenna. The platform compartment includes platform data processing equipment, platform wireless communication equipment, platform wireless communication antenna, USB transponder, multi-port network, and platform-to-ground telemetry and control antenna. The wireless testing method for the satellite telemetry and control system based on dynamic decoding may include the following steps: S1, establish a communication link with ground test equipment through the ground telemetry and control antenna of the platform cabin; S2, complete the platform cabin wireless test, including sending uplink remote control through the ground test equipment, and receiving and processing the platform cabin's ground telemetry and control antenna and the USB transponder to realize the platform cabin remote control test; and transmitting satellite telemetry data downlink through the platform cabin's ground telemetry and control antenna, and receiving and processing the data through the ground test equipment to realize the platform cabin telemetry test. S3, complete the payload compartment wireless test, including sending uplink remote control through the ground test equipment, receiving and processing the data via the platform compartment's ground telemetry antenna and the USB transponder, and then transmitting it to the payload compartment via the two-compartment communication link to achieve payload compartment remote control testing; and transmitting payload compartment telemetry information to the platform compartment via the two-compartment communication link, whereby the platform compartment's ground telemetry antenna transmits payload compartment telemetry data downlink, and the ground test equipment receives and processes it to achieve payload compartment telemetry testing; wherein, the two-compartment communication link is constructed based on the wireless communication equipment and wireless communication antenna of the two compartments; the USB transponder is a fully digital USB transponder, and the decoding processing of the received data adopts a dynamic decoding method based on dynamic adjustment of normalized parameters.

[0018] This pre-set satellite telemetry and control system is a satellite telemetry and control system designed for discrete microsatellites. To facilitate understanding of the embodiments of this invention, the following is combined with... Figure 2 The preset satellite telemetry and control system shown herein provides a detailed explanation of the wireless testing method for a satellite telemetry and control system based on dynamic decoding, as described in this embodiment of the invention.

[0019] The satellite in this embodiment of the invention is divided into two separate parts: a platform module and a payload module. The specific wireless testing is divided into two parts: platform module wireless testing and payload module wireless testing. Before conducting the test, a communication link needs to be established between the satellite and the ground test equipment. In S1, this communication link is specifically achieved through communication between the platform module's ground-to-ground telemetry and control antenna and the ground-to-ground telemetry and control antenna of the ground test equipment; wherein, the platform module's ground-to-ground telemetry and control antenna may include a ground-to-ground telemetry and control antenna and a sky-to-ground telemetry and control antenna.

[0020] The communication link between the two modules is used for ground tracking and control from the payload module. Specifically, after the payload module transmits data to the platform module's data processing equipment via the two-module communication link, ground tracking and control is then achieved through a USB transponder and the platform module's ground tracking and control antenna.

[0021] The USB transponder is used for ground telemetry and control via the platform module's ground telemetry and control antenna, including platform module uplink remote control, platform module downlink telemetry, payload module uplink remote control, and payload module downlink telemetry.

[0022] For S2, this includes platform cabin uplink remote control and platform cabin downlink telemetry.

[0023] The process of remote control testing of the platform cabin involves the ground test equipment sending uplink remote control signals through the ground telemetry and control antenna. After receiving the uplink remote control command, the satellite's ground telemetry and control antenna, i.e. the platform cabin's ground telemetry and control antenna, transmits it through a multi-port network to the USB transponder for processing. The processing result is then transmitted to the platform cabin's data processing equipment for calculation, and finally the calculation result is transmitted to each individual machine in the platform cabin. Specifically, this part is the platform cabin uplink remote control. The platform cabin's ground-to-ground telemetry and control antenna receives the remote control signals from the ground test equipment and transmits them to the USB transponder. The USB transponder mainly demodulates and decodes the remote control signals, forming PCM data, which is then transmitted to the platform cabin's data processing equipment. The platform cabin's data processing equipment then enables remote control operation of each individual machine in the platform cabin.

[0024] The telemetry test process in the platform cabin involves each individual machine in the platform cabin sending data to the platform cabin data processing equipment for calculation. The calculation results are then transmitted to the USB transponder for processing. The processed on-board telemetry data is then transmitted to the platform cabin's ground telemetry and control antenna via a multi-port network for outward transmission. The ground telemetry and control antenna receives the data and transmits it to the ground test equipment.

[0025] Specifically, this part is the downlink telemetry of the platform cabin. The platform cabin data processing equipment collects the telemetry data from each individual machine in the platform cabin, formats and scrambles it, and then transmits it to the USB transponder for encoding, modulation, and up-conversion processing before sending it to the ground test equipment through the platform cabin's ground telemetry and control antenna.

[0026] After completing S2, the telemetry and remote control links of the platform cabin are connected, and then step S3 can be executed.

[0027] For S3, this includes uplink remote control of the payload compartment and downlink telemetry of the payload compartment.

[0028] The payload compartment remote control test process involves the ground test equipment sending uplink remote control signals through the ground telemetry and control antenna. After receiving the uplink remote control command, the platform compartment's ground telemetry and control antenna transmits it to the USB transponder via a multi-port network for processing. The processing result is then transmitted to the platform compartment's data processing equipment for calculation. Finally, the calculation result is transmitted to the payload compartment's data processing equipment for calculation via a two-compartment communication link consisting of the platform compartment's wireless communication equipment, the platform compartment's wireless communication antenna, the payload compartment's wireless communication antenna, and the payload compartment's wireless communication equipment. Finally, the calculation result is transmitted to each individual machine within the payload compartment. Specifically, this part is the payload compartment's uplink remote control. First, the platform compartment's ground-to-ground telemetry and control antenna and USB transponder receive remote control information from the ground test equipment. The USB transponder demodulates and decodes the information to form PCM data, which is then sent to the platform compartment's data processing equipment for processing. After being modulated by the platform compartment's wireless communication equipment, the data is transmitted to the payload compartment via the platform compartment's wireless communication antenna. The payload compartment's wireless communication antenna receives the remote control signals from the platform compartment and transmits them to the payload compartment's wireless communication equipment for demodulation. Finally, the payload compartment's data processing equipment enables remote control operation of each individual machine in the payload compartment.

[0029] The process of telemetry testing in the payload compartment involves each individual machine in the payload compartment sending data to the payload compartment data processing equipment for calculation. The calculated payload compartment telemetry information is then transmitted to the platform compartment data processing equipment via a two-compartment communication link consisting of the payload compartment wireless communication equipment, the payload compartment wireless communication antenna, the platform compartment wireless communication antenna, and the platform compartment wireless communication equipment. The calculation results are then transmitted to the USB transponder for processing. The processed payload compartment telemetry data is then transmitted to the platform compartment ground control antenna via a multi-port network for outward transmission. The ground control antenna receives the data and transmits it to the ground test equipment.

[0030] Specifically, this part is the downlink telemetry of the payload compartment. The payload compartment data processing equipment collects telemetry data from each individual machine in the payload compartment, formats and scrambles it, then modulates it through the payload compartment wireless communication equipment and transmits it to the platform compartment wireless communication equipment through the payload compartment wireless communication antenna. The platform compartment wireless communication equipment demodulates the data to form PCM data and transmits it to the platform compartment data processing equipment. The platform compartment data processing equipment then processes the data and transmits it to the USB transponder for encoding, modulation, and up-conversion processing. Finally, it is transmitted to the ground test equipment through the platform compartment ground telemetry and control antenna.

[0031] The USB transponder in the embodiments of the present invention will be briefly described below.

[0032] Please see Figure 3 In one optional implementation, the USB transponder includes: The system comprises an RF receiver module, a baseband module, a remote control FPGA module, a management module, a power supply module, and an RF transmitter module; among which: ①The radio frequency receiving module is used to: receive uplink radio frequency signals, process them, and output uplink intermediate frequency signals to the baseband module.

[0033] Specifically, the RF receiving module receives uplink RF signals, including remote control signals and ranging tone signals, performs filtering, low-noise amplification, and AD conversion processing, and then outputs uplink intermediate frequency signals.

[0034] The RF receiving module employs a double-conversion scheme to achieve uplink RF signal downconversion and automatic gain control. Specifically, the RF receiving module uses a double-conversion scheme, where one local oscillator uses a phase-locked loop (PLL) frequency multiplier, i.e., a PLL multiplied signal; the second local oscillator is generated from a provided high-stability clock signal through a frequency divider and PLL multiplication, with the high-stability clock signal provided by the baseband module.

[0035] ② The baseband module is used to: generate its own telemetry information for the management module, demodulate the remote control baseband information and ranging tone information from the uplink intermediate frequency signal and provide them to the remote control FPGA module and the radio frequency transmission module respectively, and also to receive on-board telemetry data and transmit it to the radio frequency transmission module.

[0036] Specifically, the baseband module receives the uplink intermediate frequency signal data stream to capture and track the remote control signal and ranging tone signal, demodulates the remote control baseband information and ranging tone information, and sends the remote control baseband information to the remote control FPGA module and the ranging tone information to the RF transmission module. Furthermore, it collects its own telemetry information, performs PM modulation, and sends it to the RF transmission module. The baseband module also receives on-board telemetry data forwarded by the remote control FPGA module and outputs it to the RF transmission module.

[0037] The baseband module is implemented based on an ASIC chip and includes a PROM configuration chip. Configuration information in the PROM configuration chip is set according to mission requirements. This configuration information includes the initial word for frequency control of the frequency-locked loop (LLL), the modulation index of the ranging tone signal, the modulation index of the on-board telemetry data, the lock-in decision threshold, the bit synchronization rate, and the clock frequencies for the AD and DA conversions. The LLL frequency is the local intermediate frequency carrier frequency generated by the baseband module; the lock-in decision threshold is the threshold used by the baseband module to determine whether the LLL and PLL are locked; the bit synchronization rate is the code rate of the remote control baseband information and the on-board telemetry data; and the clock frequencies for the AD and DA conversions are the clock frequencies of the AD and DA converters on the RF receiving module and RF transmitting module, respectively.

[0038] ③ The remote control FPGA module is used to: generate FPGA telemetry information and process the remote control baseband information to obtain remote control data and remote control commands, transmit the remote control data to the preset management system, transmit the FPGA telemetry information and the remote control commands to the management module, and also to receive on-board telemetry data transmitted by the preset management system and output it to the baseband module.

[0039] The remote control FPGA module processes the remote control baseband information demodulated by the baseband module, and outputs it to the preset management system, such as the satellite management system, after completing the remote control command decoding, descrambling of the uploaded data and CRC verification. At the same time, it outputs its own telemetry information and remote control commands to the management module.

[0040] ④ The management module is used to: generate its own telemetry information and receive its own telemetry information and remote control commands output by the remote control FPGA module and the baseband module, and transmit all telemetry information to the preset management system for processing, and transmit the remote control commands to at least the baseband module and the remote control FPGA module as control commands.

[0041] Specifically, the management module completes the processing of direct remote control commands, transponder and self-telemetry data acquisition, receiving indirect commands from satellite crews, and on-orbit autonomous management functions; it integrates interfaces such as AD, 8051 microcontroller, serial port, CAN bus, and OC driver.

[0042] ⑤ The power supply module is used to provide different voltage values ​​required by each module.

[0043] The power module manages primary and secondary power supplies and provides surge protection. It can generate +12V, -12V, and +5.2V secondary power supplies, which are then filtered before being supplied to other modules of the USB transponder.

[0044] ⑥ The radio frequency transmission module is used to receive the ranging tone information and the on-board telemetry data output by the baseband module, process them to generate a downlink radio frequency signal and send it to the ground.

[0045] Specifically, the RF transmitter module performs DA conversion, filtering, amplification, and power amplifier processing on the on-board telemetry data output from the baseband module to generate a downlink RF signal.

[0046] Specifically, the RF transmission module uses a double-conversion scheme to achieve up-conversion of the downlink intermediate frequency signal; the baseband ASIC module completes functions such as capturing and demodulating the uplink intermediate frequency remote control signal, modulating and transmitting the telemetry signal, and tracking and forwarding the ranging tone signal, and outputs the downlink modulated intermediate frequency signal.

[0047] The radio frequency transmitting module employs a double frequency conversion, where the primary oscillator is generated by the branch signal output from the crystal oscillator, and the secondary oscillator is a phase-locked loop frequency multiplier signal.

[0048] The fully digital USB transponder used in this invention has a simple structure, high integration, and high adaptability to small satellites. Specifically, it uses an ASIC chip to implement fully digital baseband signal processing, offering advantages such as simple debugging, strong versatility, and high flexibility. Furthermore, the baseband module parameters are configurable, making parameter changes simple, debugging convenient, and engineering implementation easy. In addition, the remote control FPGA module's remote control and telemetry interfaces adopt a digital format, and the management module integrates various interfaces, facilitating integration, simplifying debugging, reducing size, and lowering weight.

[0049] The following describes the dynamic decoding method based on dynamic adjustment of normalized parameters used in the embodiments of the present invention.

[0050] The LDPC decoding algorithm is commonly used in USB transponder decoding methods. Among them, the NMS algorithm is a decoding method that has been widely used in recent years. However, it uses a fixed normalization factor, which cannot better match the dynamically changing decoding system. Therefore, it will affect the decoding performance, resulting in a higher bit error rate and lower decoding efficiency.

[0051] To address the high demands on decoding performance in satellite telemetry and control, this invention proposes a dynamic decoding method based on dynamic adjustment of normalized parameters, hereinafter referred to as the dynamic decoding method. See also... Figure 4 The dynamic decoding method includes the following steps.

[0052] A1. After preprocessing the information to be decoded, determine the weight parameter group, cutoff parameter and adjustment parameter corresponding to the information to be decoded. Each weight parameter group contains the weight parameters corresponding to each iteration number after the first iteration. As will be understood by those skilled in the art, LDPC codes, as a type of linear block code, have their transmitted codewords obtained by multiplying the information codeword by the generator matrix. The generator matrix can be derived from the parity check matrix. The result is obtained through transformation, assuming the verification matrix is... The dimension is In the decoding stage, the parity check matrix used for encoding can be obtained in advance. It assists in completing the decoding process.

[0053] The information to be decoded is a sequence of encoded codewords transmitted through a channel with added noise contamination, which can be represented as follows: , in sequence The numerical range of is [-1, 1], and the sequence length is n, where m and n are both natural numbers.

[0054] Data preprocessing of the information to be decoded can be accomplished using the BP algorithm initialization method. The purpose is to preprocess each bit of the information to be decoded. Calculate the corresponding decoded data. The probability of being initially 0 The probability of starting with 1 Then, take the logarithmic solution of the ratio of the two probabilities to obtain the initialization sequence. ,in Represents the first in the initialization sequence One. Then utilize Initialize the variable nodes at the corresponding positions.

[0055] (1) The calculation method can specifically include the following steps: 1) Calculate the noise variance of the information to be decoded.

[0056] noise variance It utilizes the information to be decoded It is obtained by calculating the numerical variance.

[0057] 2) Using the ratio of each data in the information to be decoded to the noise variance, the initial information of the variable nodes at the corresponding positions is obtained respectively.

[0058] The information to be decoded Each data point is compared with the noise variance. Find the ratio and get and take it as the first Initial information for each variable node.

[0059] As will be understood by those skilled in the art, the verification matrix Each row corresponds to a check node, and each column corresponds to a variable node. Therefore, the number of check nodes is m, and the number of variable nodes is the same as the length n of the information to be decoded. For ease of understanding, it is usually based on the check matrix. The information of the verification nodes is represented by a verification node information matrix, and the information of the variable nodes is represented by a variable node information matrix. The verification node information matrix and the variable node information matrix are then compared with the verification matrix. The dimensions are the same, and decoding is iterated by continuously updating the element values ​​in the verification node information matrix and the variable node information matrix.

[0060] Therefore, after obtaining the initial information of n variable nodes, the information of each variable node can be sequentially filled into the verification matrix. In the corresponding column, specifically, it is... All values ​​of 1 in the i-th column are replaced with ,in This is to obtain the initial variable node information matrix.

[0061] The weight parameter group, cutoff parameter, and adjustment parameter corresponding to the information to be decoded are determined; Each weight parameter group contains weight parameters corresponding to each iteration number after the first iteration.

[0062] In one optional implementation, determining the weight parameter group, cutoff parameter, and adjustment parameter corresponding to the information to be decoded includes the following steps: (1) Using the noise variance of the information to be decoded obtained by calculation, the signal-to-noise ratio of the information to be decoded is obtained; The noise variance of the information to be decoded can be... This was obtained during the calculation process.

[0063] Noise variance can characterize the signal-to-noise ratio (SNR), and the two have a certain functional relationship. The SNR of the information to be decoded can be obtained from the noise variance using an existing functional relationship. For example, in one existing functional relationship, the SNR and noise variance are related... The relationship is: (2) in, For channel coding rate, for Number system modulation.

[0064] (2) In the predetermined correspondence between signal-to-noise ratio and weight parameter set, cutoff parameter and adjustment parameter, determine the weight parameter set, cutoff parameter and adjustment parameter corresponding to the signal-to-noise ratio of the information to be decoded.

[0065] In the parameter correspondence, each signal-to-noise ratio corresponds to a weight parameter group, a cutoff parameter, and an adjustment parameter. Furthermore, each weight parameter group contains the weight parameters corresponding to each iteration number after the first iteration.

[0066] Determining the weight parameter set, cutoff parameter, and adjustment parameter corresponding to the information to be decoded involves finding the signal-to-noise ratio (SNR) that is closest to the SNR of the information to be decoded in the parameter correspondence, and then finding the corresponding weight parameter set, cutoff parameter, and adjustment parameter.

[0067] The process of determining the correspondence between the parameters includes: ① For each of the multiple preset signal-to-noise ratios, obtain multiple sample decoding information for that signal-to-noise ratio; wherein, the step size of adjacent signal-to-noise ratios among the multiple signal-to-noise ratios is equal; Since the signal-to-noise ratio (SNR) represents the ratio of signal to noise, it can effectively measure the information status of the information to be decoded. Therefore, in this embodiment of the invention, multiple SNRs can be set in advance with a certain SNR step size. For example, the SNR step size can be 0.5, 1, etc., which can be determined according to the decoding requirements.

[0068] When acquiring multiple sample decoding information with the same signal-to-noise ratio, these sample decoding information are all different. To simplify the acquisition of sample decoding information, different sample decoding information can be obtained by adding different noise to the channel, changing the magnitude of the channel input signal, or changing the modulation method, using a small number of input signal transformations.

[0069] ② For each sample of information to be decoded at this signal-to-noise ratio, the original mean and estimated mean of information in the information matrix of the verification node at each iteration number are calculated using the BP decoding algorithm and the MS decoding algorithm respectively. The weight parameter of the sample of information to be decoded corresponding to the iteration number is obtained using the original mean and estimated mean of information at each iteration number. This step may include the following steps: a1, for iteration number... At that time, the BP decoding algorithm is used to calculate the original values ​​of the information in the check node information matrix: (3) in, , Indicates the preset maximum iteration number; and These represent the first verifier node in the information matrix. Column and number OK, , ; Indicates the iteration number is The first node in the time verification node information matrix Liede The elements of the row are the original values ​​of the information; Indicates the iteration number is The first node in the time verification node information matrix Liede The elements of the row are information estimates; Represents the hyperbolic tangent function; Indicates the multiplication symbol; Represents a symbolic function; This indicates finding the minimum value; This indicates calculating the average. Indicates the multiplication sign; Indicates the iteration number is The first node in the time variable node information matrix Liede Row elements; Indicates calculation hour, The iteration numbers are selected sequentially as follows: In the time variable node information matrix, besides the first The remaining columns besides the column number. It is understandable that the sequence number is... That is to say, the first The next iteration.

[0070] The BP decoding algorithm is used because of its very high accuracy, and the result is closest to the original data. This step actually uses the BP decoding algorithm to complete the decoding iteration, extracting the elements in the verification node information matrix at each iteration as the original information value.

[0071] a2, using the MS decoding algorithm to calculate the estimated information value in the check node information matrix: (4) The MS decoding algorithm simplifies the numerous and complex function multiplication operations of the BP algorithm into symbolic function operations and a single minimum value multiplication operation. While reducing the complexity of the algorithm, some accuracy is sacrificed. Therefore, in this embodiment of the invention, the result is used as the information estimate.

[0072] in, Indicates the first During the next iteration, the node information matrix is ​​verified in the [number]th [item]. Liede The elements in the row represent information estimates; Represents a symbolic function; This indicates that the minimum value is being sought.

[0073] This step actually uses the MS code algorithm to complete the decoding iteration, extracting the elements in the verification node information matrix at each iteration as the information estimate.

[0074] a3, Calculate the original mean of the information matrix of the verification nodes: (5) For each iteration, using the original information values ​​in the verification node information matrix obtained from a1, an original average information value can be obtained according to formula (5). .in, This indicates that the average value is being calculated.

[0075] a4, Calculate the mean information estimate of the verification node information matrix: (6) Similarly, for each iteration, using the information estimate value in the verification node information matrix obtained from a2, an information estimate mean can be obtained according to formula (6). .

[0076] a5, the weight parameters are calculated as follows: (7) Understandably, this applies to the number of iterations. This allows us to obtain a numerical set consisting of multiple weight parameters corresponding to the information to be decoded in the sample. .

[0077] ③ Take the average of the weight parameters corresponding to the same iteration number among the weight parameters of all samples to be decoded for the signal-to-noise ratio, and obtain the weight parameter group corresponding to the signal-to-noise ratio. For this signal-to-noise ratio, a set of values ​​can be obtained for each sample of information to be decoded. Therefore, we can identify the same iteration number from multiple sets of values. multiple Calculate the mean to obtain a final value. Therefore, a set of values ​​can be obtained in the end. This serves as the weight parameter group corresponding to the signal-to-noise ratio.

[0078] The following table illustrates the example of the numerical data obtained from two samples of information to be decoded. The first row... The subscript 1 indicates the first group, and the second row. The subscript 2 indicates the second group.

[0079] Table 1

[0080] Then for the same data in both sets The average value of each weight parameter is calculated to obtain the weight parameter set corresponding to this signal-to-noise ratio. .

[0081] ④ Use the iteration number corresponding to the smallest weight parameter in the weight parameter group corresponding to the signal-to-noise ratio as the cutoff parameter corresponding to the signal-to-noise ratio; We can set the final set of weight parameters as follows: Find the smallest weight parameter and use its index, which represents the iteration number, as the cutoff parameter corresponding to that signal-to-noise ratio. For example, the smallest weight parameter in the weight parameter group is ,but .

[0082] ⑤ Based on the weight parameter group, cutoff parameter, and the original mean and estimated mean of information corresponding to the cutoff parameter, the adjustment parameter corresponding to the signal-to-noise ratio is determined using the adjustment parameter determination formula; The formula for determining the adjustment parameters includes: (8) in, The adjustment parameters are defined; the part after the cutoff parameter in the weight parameter group corresponding to this signal-to-noise ratio is... ; The cutoff parameter is... express The mean of each weight parameter in the formula. and Please refer to formulas (5) and (6) for the calculation method. It can be understood that under this signal-to-noise ratio, the weight parameter group, the cutoff parameter, and the adjustment parameter are corresponding.

[0083] ⑥ The parameter correspondence is constituted by each signal-to-noise ratio and its corresponding weight parameter group, cutoff parameter and adjustment parameter.

[0084] Specifically, the parameter correspondence can be in the form of a table or similar format.

[0085] A2. Determine the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter. In existing technologies, the decoding process can be simply divided into several stages: initialization, check node update, variable node update, and trial decision. When a decision fails, the process iterates again, completing the check node update-variable node update-trial decision process. Therefore, this check node update-variable node update-trial decision process can be considered an iterative cycle. In this embodiment of the invention, the main difference from existing NMS algorithms lies in the dynamic adjustment of the normalization parameter used for check node updates during the iteration process. In this embodiment, for each iteration, the normalization parameter for that iteration is first determined before subsequent steps such as check node updates are performed.

[0086] Specifically, A2 can include: ① When the iteration number is one, the normalization parameter is a predetermined value; Specifically, regarding the iteration number Normalized parameters This is a predetermined value. This predetermined value can be randomly selected, such as 0.5, or it can use the normalization parameter value of other decoding algorithms as the predetermined value, such as the fixed normalization parameter in the NMS algorithm, etc.

[0087] In another optional implementation, the normalization parameter This can be a fixed value obtained through density evolution theory. For details on the acquisition process, please refer to the relevant technical explanations; it will not be elaborated upon here.

[0088] ② When the iteration number is greater than one and less than or equal to the cutoff parameter, the normalization parameter is the sum of the weight parameter corresponding to the iteration number and the normalization parameter corresponding to the previous iteration number in the weight parameter group; Specifically, regarding the number of iterations Normalized parameters for: (9) The weight parameters corresponding to the iteration number in the defined weight parameter group; This is the normalized parameter for the previous iteration number.

[0089] ③ When the iteration number is greater than the cutoff parameter, the normalization parameter is the product of the normalization parameter when the iteration number is equal to the cutoff parameter and the adjustment parameter.

[0090] Specifically, regarding the number of iterations Normalized parameters for: (10) in, For the determined adjustment parameters, The normalized parameter is the one used when the iteration number equals the cutoff parameter.

[0091] A3. Based on the normalization parameter corresponding to the iteration number and the information of the variable nodes obtained in the previous iteration, update the information of the verification node and the variable node, calculate the information of the decision node and complete the decoding to obtain the decoded data. First, based on the normalization parameters corresponding to the iteration number and the information of the variable nodes obtained from previous iterations, the information of the verification nodes is updated. Specifically: No. During the iteration, the elements of each node in the verification node information matrix are determined according to the... During each iteration, the elements in the variable node information matrix and the normalization parameter for that iteration are updated. Specifically, the NMS check node update formula is modified using the dynamic normalization parameter of this embodiment of the invention to obtain the... In the next iteration, the elements in the node information matrix are verified: (11) For the specific update process of the NMS verification node update formula, please refer to the relevant existing technologies. The parameters in the formula can be found in the previous explanations, and will not be repeated here.

[0092] Secondly, the information of the variable nodes is updated based on the information of the verification nodes. Specifically: No. In the second iteration, the variable node information is based on the first iteration. The verification node information matrix is ​​updated during each iteration.

[0093] (12) in, Indicates the first During the nth iteration Information about each variable node; Indicates the first In the nth iteration, the nth vertex in the information matrix of the verification node is obtained. Except for the first in the column The sum of all elements other than the first element, i.e. express The value is Except j All values ​​other than those listed above.

[0094] For details on the process of updating variable nodes, please refer to the relevant existing technologies. For the parameters in the formula, please refer to the relevant explanations above, which will not be repeated here.

[0095] Next, the information of the decision node is calculated based on the information of the verification node.

[0096] Specifically, there are n decision nodes in total, the first... Information of each judgment node It indicates. In the first In each iteration, the information of each decision node is obtained from the information of all verification nodes in that iteration. Wherein: (13) in, Indicates the first During the nth iteration Information about each judgment node; Represents the process of obtaining the information matrix of the verification nodes. i List of CCP j The sum of the elements.

[0097] For details on the generation process of the information for the decision node, please refer to the relevant existing technologies, which will not be elaborated here.

[0098] Then, the decoding is completed based on the information from the decision node to obtain the decoded data.

[0099] Specifically, the information of each decision node is decoded and decided using a preset decision threshold value, where the decision threshold value can be a value such as 0.

[0100] At the time of judgment, if If the value is greater than the decision threshold, then the first [value] in the decoded data... i If the bit is 1, If the value is less than or equal to the decision threshold, then the first element in the decoded data... i The bit is 0, therefore the decoded data for this iteration can be obtained. The decoded data is n bits.

[0101] A4. If the decoding termination condition is met, the decoded data is taken as the decoding result; otherwise, return to the step of determining the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter, and continue iterating.

[0102] This step uses the decoded data and a pre-acquired parity check matrix to determine whether the decoding termination condition is met. Specifically, it checks whether the condition exists or whether the current iteration number has reached the maximum iteration number, where represents the transpose of the matrix. If yes, the decoding termination condition is met, and the decoded data is used as the decoding result. If no, i.e., the current iteration count has not reached the maximum iteration count, the decoding termination condition is not met, and the process returns to A2 to continue iterating.

[0103] It should be noted that the specific updates to the verification node information matrix and the variable node information matrix can be found in the relevant existing technologies, and will not be elaborated here.

[0104] Compared to existing NMS algorithms that use a fixed normalization factor, the dynamic decoding method provided in this invention determines the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter during the decoding iteration process, thereby dynamically adjusting the normalization parameter. The adjusted normalization parameter is then used to dynamically update the information of the check node, making the updated check node information closer to the original information. Therefore, this invention can adapt to the dynamic changes in the message exchange between variable nodes and check nodes during the iteration process, better matching the decoding system and reducing the bit error rate. Furthermore, when the iteration number is greater than the cutoff parameter, the normalization parameter is adjusted to a fixed value, which is the product of the normalization parameter when the iteration number equals the cutoff parameter and the adjusted parameter. Therefore, for code blocks with low confidence that fail to converge after repeated iterations, convergence can be accelerated, and the estimated value deviating from the original data can be corrected to be closer to the original data, thus improving decoding performance.

[0105] In summary, compared with existing technologies, in the pre-set satellite telemetry and control system of this invention, the satellite's payload compartment and platform compartment can share a single telemetry and control antenna (i.e., the platform compartment's ground-to-ground telemetry and control antenna) to receive uplink remote control information from the ground test equipment. This eliminates the need for a separate telemetry and control antenna for the payload compartment, effectively reducing satellite weight and benefiting the overall design of microsatellites. Furthermore, the wireless testing method for satellite telemetry and control systems based on dynamic decoding provided in this invention can receive telemetry data from the payload compartment in real time, process it, and then wirelessly relay it to the ground test equipment via the platform compartment's radio frequency to achieve satellite-to-ground data transmission. It can also utilize the wireless inter-satellite communication channel between the payload compartment and the platform compartment to achieve real-time data interaction between them, thus improving information transmission efficiency and solving communication problems between the two compartments, ground-to-ground communication problems, and testing problems. Additionally, the USB transponder in the platform compartment of this invention is a fully digital USB transponder, resulting in high integration, reduced size and weight, making it more suitable for microsatellites, and offering simple debugging, strong versatility, and high flexibility. Meanwhile, the USB transponder in this embodiment of the invention employs a dynamic decoding method based on dynamic adjustment of normalized parameters during decoding processing. This method can dynamically adjust the normalized parameters to better adapt to dynamic communication environments, reduce bit error rate, and improve decoding efficiency.

[0106] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A wireless testing method for a satellite telemetry, tracking, and command system based on dynamic decoding, characterized in that, For a pre-defined satellite telemetry and control system; the pre-defined satellite telemetry and control system includes a separate payload compartment and a platform compartment; the payload compartment includes payload compartment data processing equipment, payload compartment wireless communication equipment, and payload compartment wireless communication antenna; the platform compartment includes platform compartment data processing equipment, platform compartment wireless communication equipment, platform compartment wireless communication antenna, USB transponder, multi-port network, and platform compartment ground-to-ground telemetry and control antenna; the method includes: A communication link is established between the platform cabin's ground-based telemetry and control antenna and the ground-based testing equipment. The platform cabin wireless test is completed by sending uplink remote control data through the ground test equipment, and receiving and processing the data with the platform cabin's ground telemetry and control antenna and the USB transponder to realize the platform cabin remote control test; and by transmitting satellite telemetry data downlink through the platform cabin's ground telemetry and control antenna, and receiving and processing the data with the ground test equipment to realize the platform cabin telemetry test. The payload compartment wireless testing process includes: sending uplink remote control data via the ground testing equipment; receiving and processing this data via the platform compartment's ground-to-ground telemetry antenna and the USB transponder; and transmitting the data to the payload compartment via a two-compartment communication link to achieve remote control testing of the payload compartment. It also includes transmitting payload compartment telemetry information to the platform compartment via the two-compartment communication link; the platform compartment's ground-to-ground telemetry antenna then transmits payload compartment telemetry data downlink; and the ground testing equipment receives and processes this data to achieve payload compartment telemetry testing. The two-compartment communication link is constructed based on the wireless communication equipment and antennas of both compartments. The USB transponder is a fully digital USB transponder, and the decoding of the received data employs a dynamic decoding method based on dynamic adjustment of normalized parameters. The dynamic decoding method includes: After preprocessing the information to be decoded, the signal-to-noise ratio (SNR) of the information to be decoded is obtained by using the calculated noise variance of the information to be decoded. In the pre-determined correspondence between the SNR and the weight parameter group, cutoff parameter and adjustment parameter, the weight parameter group, cutoff parameter and adjustment parameter corresponding to the SNR of the information to be decoded are determined. Each weight parameter group contains the weight parameters corresponding to each iteration number after the first iteration. Based on the relationship between the iteration number and the cutoff parameter, determine the normalization parameter corresponding to the iteration number; Based on the normalization parameter corresponding to the iteration number and the information of the variable nodes obtained from previous iterations, the information of the verification nodes and variable nodes is updated, the information of the decision nodes is calculated, and the decoding is completed to obtain the decoded data. If the decoding termination condition is met, the decoded data is taken as the decoding result; otherwise, the process returns to the step of determining the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter, and continues iterating. The process of determining the correspondence between the parameters includes: For each of a pre-set plurality of signal-to-noise ratios, multiple sample decoding information is obtained for that signal-to-noise ratio; wherein, the step size of adjacent signal-to-noise ratios among the plurality of signal-to-noise ratios is equal; For each sample of information to be decoded at this signal-to-noise ratio, the original mean and estimated mean of information in the information matrix of the verification node at each iteration number are calculated using the BP decoding algorithm and the MS decoding algorithm respectively. The weight parameters of the sample of information to be decoded corresponding to the iteration number are obtained using the original mean and estimated mean of information at each iteration number. This step includes steps a1 to a5. The average of the weight parameters corresponding to the same iteration number among the weight parameters of all samples to be decoded for this signal-to-noise ratio is obtained to get the weight parameter group corresponding to this signal-to-noise ratio. The iteration number corresponding to the smallest weight parameter in the weight parameter group corresponding to the signal-to-noise ratio is used as the cutoff parameter corresponding to the signal-to-noise ratio. Based on the weight parameter group, cutoff parameter, and the original mean and estimated mean of information corresponding to the cutoff parameter, the adjustment parameter corresponding to the signal-to-noise ratio is determined using the adjustment parameter determination formula. The parameter correspondence is constituted by each signal-to-noise ratio and its corresponding weight parameter group, cutoff parameter, and adjustment parameter. Steps a1 to a5 are as follows: a1, for iteration number... At that time, the BP decoding algorithm is used to calculate the original values ​​of the information in the check node information matrix: ； a2, using the MS decoding algorithm to calculate the estimated information value in the check node information matrix: ； a3, Calculate the original mean of the information matrix of the verification nodes: ； a4, Calculate the mean information estimate of the verification node information matrix: ； a5, the weight parameters are calculated as follows: ； in, , Indicates the preset maximum iteration number; and These represent the first verifier node in the information matrix. Column and number OK, , , and All are natural numbers; Indicates the iteration number is The first node in the time verification node information matrix Liede The elements of the row are the original values ​​of the information; Indicates the iteration number is The first node in the time verification node information matrix Liede The elements of the row are information estimates; Represents the hyperbolic tangent function; Indicates the multiplication symbol; Represents a symbolic function; This indicates finding the minimum value; This indicates calculating the average. Indicates the multiplication sign; Indicates the iteration number is The first node in the time variable node information matrix Liede Row elements; Indicates calculation hour, The iteration numbers are selected sequentially as follows: In the time variable node information matrix, besides the first The remaining columns besides the main column.

2. The wireless testing method for a satellite telemetry and control system based on dynamic decoding according to claim 1, characterized in that, The USB transponder is used for ground telemetry and control via the platform module's ground telemetry and control antenna, including platform module uplink remote control, platform module downlink telemetry, payload module uplink remote control, and payload module downlink telemetry.

3. The wireless testing method for a satellite telemetry and control system based on dynamic decoding according to claim 1 or 2, characterized in that, The USB transponder includes: Radio frequency receiver module, baseband module, remote control FPGA module, management module, power supply module, and radio frequency transmitter module; The radio frequency (RF) receiving module is configured to: receive and process uplink RF signals, and output uplink intermediate frequency (IF) signals to the baseband module; the baseband module is configured to: generate its own telemetry information for the management module, and demodulate remote control baseband information and ranging tone information from the uplink IF signals and provide them to the remote control FPGA module and the RF transmitting module respectively, and also receive on-board telemetry data and transmit it to the RF transmitting module; the remote control FPGA module is configured to: generate its own FPGA telemetry information and process the remote control baseband information to obtain remote control data and remote control commands, transmit the remote control data to the preset management system, and transmit the FPGA's own telemetry information and the remote control commands... The data is transmitted to the management module and also used to receive on-board telemetry data transmitted by the preset management system and output it to the baseband module; the management module is used to: generate its own telemetry information and receive its own telemetry information and remote control commands output by the remote control FPGA module and the baseband module, and transmit all telemetry information to the preset management system for processing, and transmit the remote control commands to at least the baseband module and the remote control FPGA module as control commands; the power supply module is used to provide different voltage values ​​required by each module; the radio frequency transmission module is used to receive the ranging tone information and the on-board telemetry data output by the baseband module, process them, generate downlink radio frequency signals, and transmit them to the ground.

4. The wireless testing method for a satellite telemetry and control system based on dynamic decoding according to claim 3, characterized in that, The baseband module is implemented based on an ASIC chip and includes a PROM configuration chip. The configuration information in the PROM configuration chip is set according to the task requirements.

5. The wireless testing method for a satellite telemetry and control system based on dynamic decoding according to claim 4, characterized in that, The radio frequency receiving module adopts a double frequency conversion, in which the local oscillator adopts a phase-locked loop frequency multiplication method, and the second local oscillator is generated by the provided high-stability clock signal after passing through a frequency divider and phase-locked loop frequency multiplication.

6. The wireless testing method for a satellite telemetry and control system based on dynamic decoding according to claim 5, characterized in that, The radio frequency transmitting module adopts a double frequency conversion, in which the first local oscillator is generated by the branch signal output of the crystal oscillator, and the second local oscillator is a phase-locked loop frequency multiplier signal.

7. The method according to claim 1, characterized in that, The step of determining the normalization parameter corresponding to the iteration number based on the relationship between the iteration number and the cutoff parameter includes: When the iteration number is one, the normalization parameter is a predetermined value; When the iteration number is greater than one and less than or equal to the cutoff parameter, the normalization parameter is the sum of the weight parameter corresponding to the iteration number and the normalization parameter corresponding to the previous iteration number in the weight parameter group; When the iteration number is greater than the cutoff parameter, the normalization parameter is the product of the normalization parameter when the iteration number is equal to the cutoff parameter and the adjustment parameter.

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