A method and system for processing multi-channel data synchronously in a TR chip

Abstract

The application relates to the technical field of data transmission, and discloses a TR chip multi-channel data synchronization processing method and system.The method comprises the following steps: performing blind starting and framing on multi-channel baseband data streams of a chip to obtain multi-channel protocol data frames of the chip; performing cross-correlation evaluation on the multi-channel protocol data frames to obtain relative time delay parameters and phase offsets of the multi-channel protocol data frames; performing phase-coherent collection on the multi-channel protocol data frames based on the relative time delay parameters and the phase offsets to obtain in-phase data blocks of the chip; performing soft decision Viterbi decoding on the in-phase data blocks to obtain decision metric sequences of the chip; performing probability soft demodulation reconstruction on the decision metric sequences to obtain regenerated reference waveforms of the chip; and performing iterative Bayes correction on the multi-channel baseband data streams based on the regenerated reference waveforms to obtain stable state synchronization data streams of the chip.The application can improve the synchronization processing efficiency of multi-channel data of a TR chip.

Description

Technical Field

[0001] This invention relates to the field of data transmission technology, and in particular to a method and system for multi-channel data synchronization processing of a TR chip. Background Technology

[0002] In multi-channel communication systems, accurate synchronization of the baseband data streams across channels is crucial for correct demodulation and maximizing performance gains. This process involves steps such as frame localization, delay estimation, and phase difference compensation. Existing technologies typically achieve channel alignment based on known frame structures, utilizing training sequences or pilots. However, in blind scenarios such as spectrum monitoring and non-cooperative reception, the receiver lacks prior information such as signal frame format and timing, posing a challenge to accurate multi-channel synchronization. Traditional methods often process single channels independently or simply combine multiple channels, making it difficult to robustly achieve high-precision time and phase synchronization under blind conditions, thus limiting the performance of subsequent advanced signal processing such as soft-decision decoding.

[0003] Existing multi-channel baseband data stream processing technologies still have problems when facing high-precision and high-reliability application scenarios. In particular, during the blind start framing process of multi-channel baseband data streams, the determination of the frame start boundary often relies on the energy characteristics or fixed threshold of a single channel, without establishing a correlation verification mechanism for the energy peaks of multiple channels. This results in the consistency and accuracy of the frame boundary being greatly affected by the fluctuations of the signal in a single channel, making it difficult to adapt to the technical requirements of multi-channel collaborative processing. Furthermore, the synchronization calibration and signal reconstruction stages of multi-channel data are independent of each other, and the delay compensation and phase calibration are mostly open-loop processing modes, without iterative optimization based on the decoded and reconstructed reference waveform. This makes it impossible to effectively correct the residual deviations generated during the synchronization process, which restricts the further improvement of the synchronization accuracy of multi-channel data streams. Therefore, improving the synchronization processing efficiency of multi-channel data in TR chips has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for multi-channel data synchronization processing of TR chips to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a multi-channel data synchronization processing method for a TR chip, comprising: S1. Perform blind frame division on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip; S2. Perform cross-correlation evaluation on the multi-channel protocol data frame to obtain the relative delay parameter and phase offset of the multi-channel protocol data frame; S3. Based on the relative delay parameter and the phase offset, perform phase coherence aggregation on the multi-channel protocol data frames to obtain the in-phase data block of the chip; S4. Perform soft-decision Viterbi decoding on the in-phase data block to obtain the decision metric sequence of the chip; S5. Perform probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip; S6. Based on the regenerated reference waveform, perform iterative Bayesian correction on the multi-channel baseband data stream to obtain the steady-state synchronous data stream of the chip.

[0006] In a preferred embodiment, blind-start framing is performed on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip, including: Time-domain energy profiling is performed on the multi-channel baseband data stream of the chip to obtain the chip's energy pulses; Based on the energy pulse, peak correlation boundary determination is performed on the multi-channel baseband data stream to obtain the frame start boundary of the chip; Based on the frame start boundary of the chip, the multi-channel baseband data stream is subjected to protocol window interception to obtain the original fields of the chip; The original fields are co-framed to obtain the chip's multi-channel protocol data frame.

[0007] In a preferred embodiment, cross-correlation evaluation is performed on the multi-channel protocol data frames to obtain the relative delay parameters and phase offset of the multi-channel protocol data frames, including: The reference channel data frame of the chip is obtained by anchoring the reference channel of the multi-channel protocol data frame. Using the reference channel data frame as a reference, a similarity comparison is performed on the non-reference channel data in the protocol data frame to obtain the relevant results of the chip; The relevant results of the chip are analyzed by characteristic peak analysis to obtain the peak position information and peak phase characteristics of the chip; Based on the peak position information, a delay difference analysis is performed on the non-reference channel data and the reference channel data to obtain the relative delay parameters of the multi-channel protocol data frame; Based on the peak phase characteristics, the non-reference channel data and the reference channel data are anchored relative to each other to obtain the phase offset of the multi-channel protocol data frame.

[0008] In a preferred embodiment, based on the relative delay parameter and the phase offset, the multi-channel protocol data frames are coherently aggregated to obtain the in-phase data block of the chip, including: Based on the relative delay parameters, delay compensation and alignment are performed on the multi-channel protocol data frames to obtain the delay alignment data of the chip; Based on the phase offset, the delay alignment data is subjected to phase rotation calibration to obtain the initial phase calibration data of the chip; Error components are identified in the initial phase calibration data to obtain the phase error of the chip; Based on the phase error, phase compensation is performed on the initial phase calibration data to obtain the phase fine calibration data of the chip; The phase calibration data is then subjected to collaborative phase consolidation to obtain the in-phase data block of the chip.

[0009] In a preferred embodiment, the formula for calculating the phase calibration data is as follows: ; In the formula, For the first The phase calibration data for each channel, For the first The initial phase calibration data for each channel, For the first The relative delay parameters of each channel, For the first The phase shift of each channel For the first Each channel at time The phase error, is a complex number rotation factor.

[0010] In a preferred embodiment, soft-decision Viterbi decoding is performed on the in-phase data block to obtain the decision metric sequence of the chip, including: The in-phase data blocks are topologically constructed to obtain the decoding grid of the chip; Based on the state transition relationship and associated codewords of the decoding grid, Euclidean distance quantization is performed on the in-phase data block to obtain the branch metric sequence of the chip; Based on the branch metric sequence, the cumulative metric is recursively applied to the decoding grid to obtain the optimal path of the chip; The optimal path is backtracked using reliability metrics to obtain the soft decision likelihood ratio sequence of the chip; The soft decision likelihood ratio sequence is normalized to a bit-level metric to obtain the decision metric sequence of the chip.

[0011] In a preferred embodiment, the soft decision likelihood ratio sequence is subjected to bit-level metric normalization to obtain the decision metric sequence of the chip, including: The likelihood ratio sequence of the soft decision is normalized to obtain the normalized soft information of the chip; The confidence level of the normalized soft information is enhanced to obtain the enhanced soft information of the chip. The enhanced soft information is quantized in a fixed format to obtain the decision metric sequence of the chip.

[0012] In a preferred embodiment, the step of performing probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip includes: The soft information distribution of the chip is obtained by performing soft information distribution analysis on the decision metric sequence; The soft bit probability distribution is subjected to probability-driven symbol decision to obtain the complex symbols of the chip; The complex symbols are orthogonally frequency-division multiplexed and framed to obtain the multi-carrier symbol stream of the chip; In a preferred embodiment, the step of performing iterative Bayesian correction on the multi-channel baseband data stream based on the regenerated reference waveform to obtain the steady-state synchronous data stream of the chip includes: Based on the regenerated reference waveform, a multidimensional difference analysis is performed on the multi-channel baseband data stream to obtain the synchronization error characteristics of the chip; Based on the synchronization error characteristics, dynamic deviation compensation calibration is performed on the multi-channel baseband data stream to obtain the correction intermediate data of the multi-channel baseband data stream; Based on the correction intermediate data, synchronous residual detection is performed on the multi-channel baseband data stream to obtain the residual deviation of the chip; Based on the residual deviation, the multi-channel baseband data stream is synchronously closed-loop calibrated to obtain the steady-state synchronous data stream of the chip.

[0013] To address the aforementioned problems, the present invention also provides a TR chip multi-channel data synchronization processing system, the system comprising: The blind-start framing module is used to perform blind-start framing on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip. The cross-correlation evaluation module is used to perform cross-correlation evaluation on the multi-channel protocol data frame to obtain the relative delay parameters and phase offset of the multi-channel protocol data frame; The phase coherence aggregation module is used to perform phase coherence aggregation on the multi-channel protocol data frames based on the relative delay parameter and the phase offset to obtain the in-phase data blocks of the chip. A soft Viterbi decoding module is used to perform soft decision Viterbi decoding on the in-phase data block to obtain the decision metric sequence of the chip; The probabilistic soft demodulation and reconstruction module is used to perform probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip; The iterative Bayesian correction module is used to perform iterative Bayesian correction on the multi-channel baseband data stream based on the regenerated reference waveform to obtain the steady-state synchronous data stream of the chip.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention extracts energy pulses by performing time-domain energy profiling on multi-channel baseband data streams, establishes a multi-channel energy peak correlation verification mechanism, and determines the frame start boundary by combining the time axis synchronization of peak points of each channel. This replaces the energy feature or fixed threshold judgment of a single channel, avoids the influence of single-channel signal fluctuations, adapts to the needs of multi-channel collaborative processing, and standardizes the original field format to form a standardized protocol data frame, thereby improving the consistency and accuracy of frame start boundary determination.

[0015] 2. This invention links the synchronization calibration and signal reconstruction stages, generates a regenerated reference waveform through soft-decision Viterbi decoding and probabilistic soft demodulation reconstruction, and performs multidimensional difference analysis, dynamic compensation and closed-loop calibration based on this reference. It constructs an iterative Bayesian correction process to replace the open-loop processing mode, effectively corrects the synchronization residual deviation, significantly improves the synchronization accuracy and stability of multi-channel data, realizes closed-loop iterative optimization of synchronization calibration, and eliminates residual deviation. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a multi-channel data synchronization processing method for a TR chip according to an embodiment of the present invention. Figure 2 This is a functional block diagram of a TR chip multi-channel data synchronization processing system provided in an embodiment of the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0018] This application provides a method for multi-channel data synchronization processing of a TR chip. The execution subject of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for multi-channel data synchronization processing of a TR chip can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0019] Reference Figure 1 The diagram shown is a flowchart illustrating a multi-channel data synchronization processing method for a TR chip according to an embodiment of the present invention. In this embodiment, the multi-channel data synchronization processing method for a TR chip includes: S1. Perform blind frame division on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip; In this embodiment of the invention, blind-start framing is performed on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip, including: Time-domain energy profiling is performed on the multi-channel baseband data stream of the chip to obtain the chip's energy pulses; Based on the energy pulse, peak correlation boundary determination is performed on the multi-channel baseband data stream to obtain the frame start boundary of the chip; Based on the frame start boundary of the chip, the multi-channel baseband data stream is subjected to protocol window interception to obtain the original fields of the chip; The original fields are co-framed to obtain the chip's multi-channel protocol data frame.

[0020] Temporal energy profiling is performed on the multi-channel baseband data stream of a chip. The multi-channel baseband data stream is the unmodulated raw digital signal stream from multiple channels of the chip, containing the core data information required for transmission. Temporal energy profiling involves continuously detecting the energy of the baseband data stream of each channel over time. The energy value of the data stream at each time interval is extracted, and these energy values ​​are compared with a preset energy threshold. Energy segments exceeding the threshold are selected. These continuous segments that meet the energy requirements are called energy pulses. Energy pulses are signal segments in the multi-channel baseband data stream with concentrated energy that conform to preset standards, and they can reflect the potential location information of the data frame.

[0021] Peak correlation boundary determination is performed on multi-channel baseband data streams based on energy pulses. First, the position corresponding to the maximum energy value of each energy pulse is extracted as the peak point. Then, the peak points of energy pulses from different channels are correlated. By judging the synchronicity of the peak points of each channel on the time axis, the position that is commonly recognized by all channels and can be used as the start marker of the data frame is determined. This position is the frame start boundary. The frame start boundary is the precise time node for the start of the data frame in the multi-channel baseband data stream, providing an accurate starting reference for subsequent data interception.

[0022] Based on the chip's frame start boundary, protocol windowing is performed on the multi-channel baseband data stream. The protocol window is a fixed time window determined according to the data frame length specified by the preset communication protocol. Starting from the frame start boundary, the corresponding signal segment is extracted from the baseband data stream of each channel according to the fixed length of the protocol window. These extracted signal segments that have not undergone further processing are the original fields. The original fields are the initial signal segments that conform to the length specified by the protocol and contain the core content of the data frame, thus preserving the original characteristics of the data.

[0023] The original fields are co-framed, and the original fields of all channels are organized and combined according to the format specified by the preset communication protocol to ensure that the original fields of each channel are in the corresponding preset position in the data frame. At the same time, the necessary structural information such as frame header and frame trailer required by the protocol is supplemented to form a multi-channel protocol data frame with complete structure and conforming to the protocol standard. The multi-channel protocol data frame is a standardized data unit with a standard structure that can be used for subsequent cross-correlation evaluation, and integrates the effective data of all channels.

[0024] The beneficial effects are as follows: accurately locating the potential location range of data frames, providing a reliable basis for determining the frame start boundary, improving the accuracy of frame start boundary identification, utilizing the multi-channel data synchronization characteristics to ensure that the frame start boundary is a precise time node commonly recognized by all channels, avoiding the judgment deviation of a single channel, improving the consistency and reliability of the frame start boundary, intercepting original fields in accordance with the communication protocol, ensuring that the signal segment length is compliant, preserving the original characteristics of the data, providing standardized basic data for collaborative framing, improving the standardization of original fields, integrating the original fields of each channel according to the protocol format and supplementing structural information to form a complete multi-channel protocol data frame, integrating effective data, meeting the needs of subsequent cross-correlation evaluation, and improving data availability and standardization.

[0025] S2. Perform cross-correlation evaluation on the multi-channel protocol data frame to obtain the relative delay parameter and phase offset of the multi-channel protocol data frame; In this embodiment of the invention, cross-correlation evaluation is performed on the multi-channel protocol data frame to obtain the relative delay parameters and phase offset of the multi-channel protocol data frame, including: The reference channel data frame of the chip is obtained by anchoring the reference channel of the multi-channel protocol data frame. Using the reference channel data frame as a reference, a similarity comparison is performed on the non-reference channel data in the protocol data frame to obtain the relevant results of the chip; The relevant results of the chip are analyzed by characteristic peak analysis to obtain the peak position information and peak phase characteristics of the chip; Based on the peak position information, a delay difference analysis is performed on the non-reference channel data and the reference channel data to obtain the relative delay parameters of the multi-channel protocol data frame; Based on the peak phase characteristics, the non-reference channel data and the reference channel data are anchored relative to each other to obtain the phase offset of the multi-channel protocol data frame.

[0026] From multi-channel protocol data frames, selection is based on three fixed criteria: data transmission stability, signal strength uniformity, and data integrity. Data transmission stability is judged by the longest duration of transmission without packet loss or errors; signal strength uniformity is judged by the smallest fluctuation range of signal amplitude across different time periods; and data integrity is judged by the absence of missing fields and format abnormalities in the data frame. Channels that simultaneously meet all three criteria are selected as baseline channels, and the complete data frames corresponding to these baseline channels are the reference channel data frames.

[0027] Using the reference channel data frame as a fixed reference object, the non-reference channel data is compared byte by byte with the reference channel data frame. During the comparison, the proportion of identical data at corresponding positions is counted out of the total data volume, and the proportion of the duration of the same rising, falling, or stable phases in the signal change trends of both is also counted out of the total duration. These two proportions are combined and calculated according to a pre-set fixed weight, and the resulting value is the correlation result, which directly reflects the similarity between the non-reference channel data and the reference channel data.

[0028] A comprehensive signal analysis is performed on the obtained results, iterating through the signal amplitudes corresponding to all data points in the results. The signal amplitude of each data point is compared with the signal amplitudes of its neighboring data points, and signal points with significantly higher amplitudes than their neighbors are selected as characteristic peaks. The specific location of each characteristic peak in the entire data sequence is recorded, and this location information is integrated to form peak location information. Simultaneously, the direction and amplitude of the signal phase change corresponding to each characteristic peak are extracted, and this phase-related information is integrated to form peak phase features.

[0029] Based on the acquired peak location information, the occurrence time of the characteristic peak of the reference channel data is used as a fixed reference point. The specific occurrence time of each characteristic peak of the non-reference channel data on the time axis is determined, and the time length by which the occurrence time of the characteristic peak of each non-reference channel data lags behind or precedes the reference point is calculated. This time length is the delay difference between the non-reference channel and the reference channel data. All delay differences between the non-reference channel and the reference channel are collected, and these delay differences together constitute the relative delay parameter of the multi-channel protocol data frame.

[0030] Based on the extracted peak phase features, the peak phase state of each characteristic feature of the non-reference channel data is compared one by one with the corresponding peak phase state of the reference channel data. Using the peak phase of the reference channel data as the standard phase, the differences between the peak phase of the non-reference channel data and the standard phase in terms of direction and magnitude of change are identified. Based on this difference, the phase value that needs to be adjusted in the non-reference channel data is determined; this value is the phase offset of the non-reference channel data relative to the reference channel data. The phase offsets corresponding to all non-reference channels are collected, and these phase offsets together constitute the phase offset of the multi-channel protocol data frame.

[0031] The beneficial effects are as follows: ensuring the reliability and representativeness of the reference channel data frames, laying a stable and accurate foundation for subsequent evaluation, improving the accuracy of the overall evaluation results, accurately capturing data similarity features, providing high-precision support for feature peak extraction, improving the accuracy of similarity comparison, ensuring the completeness and accuracy of peak position information and phase features, providing effective data basis for subsequent calculations, enhancing the comprehensiveness and reliability of feature analysis, accurately reflecting the time differences of each channel, providing accurate data support for delay compensation, ensuring the accuracy of delay compensation, accurately reflecting the phase differences of each channel, providing accurate basis for phase calibration, ensuring the effectiveness of phase calibration, and improving the overall effect of multi-channel data synchronous processing.

[0032] S3. Based on the relative delay parameter and the phase offset, perform phase coherence aggregation on the multi-channel protocol data frames to obtain the in-phase data block of the chip; In this embodiment of the invention, based on the relative delay parameter and the phase offset, phase coherence aggregation is performed on the multi-channel protocol data frames to obtain the in-phase data block of the chip, including: Based on the relative delay parameters, delay compensation and alignment are performed on the multi-channel protocol data frames to obtain the delay alignment data of the chip; Based on the phase offset, the delay alignment data is subjected to phase rotation calibration to obtain the initial phase calibration data of the chip; Error components are identified in the initial phase calibration data to obtain the phase error of the chip; Based on the phase error, phase compensation is performed on the initial phase calibration data to obtain the phase fine calibration data of the chip; The phase calibration data is then subjected to collaborative phase consolidation to obtain the in-phase data block of the chip.

[0033] The specific formula for calculating the phase calibration data is as follows: ; In the formula, For the first The phase calibration data for each channel, For the first The initial phase calibration data for each channel, For the first The relative delay parameters of each channel, For the first The phase shift of each channel For the first Each channel at time The phase error, is a complex number rotation factor.

[0034] The relative delay parameter is the time delay difference information between each non-reference channel and the reference channel obtained after cross-correlation evaluation of the multi-channel protocol data frames. The multi-channel protocol data frame is a multi-channel data unit that conforms to the preset communication protocol standard after blind framing. For each channel's multi-channel protocol data frame, the delay duration indicated by its corresponding relative delay parameter is determined. For channels with positive delay durations, the start time of the data frame of that channel is shifted backward by the corresponding duration; for channels with negative delay durations, the start time of the data frame of that channel is adjusted forward by the corresponding duration. Through this time adjustment operation, the starting position of the multi-channel protocol data frames of all channels is made completely consistent with the reference channel on the time axis. The data obtained after this time adjustment process is the delay alignment data, which is the set of protocol data frames that are synchronized across channels in the time dimension.

[0035] Phase offset refers to the phase difference information between each channel and the reference channel obtained from the previous cross-correlation evaluation. Delay alignment data refers to the time-synchronized data of each channel. For the delay alignment data of each channel, the phase of each signal point in the data is adjusted one by one according to the phase offset of the corresponding channel. The direction and magnitude of the adjustment are strictly determined according to the phase offset to ensure that the phase of each signal point rotates in the same direction as the phase of the reference channel data. After this comprehensive phase rotation adjustment, the data obtained is the initial phase calibration data. The initial phase calibration data is the synchronized data of each channel with the main phase offset eliminated and the phase tending to be uniform.

[0036] The initial phase calibration data consists of the synchronized data of each channel after preliminary phase rotation calibration. The standard data of the reference channel is the data corresponding to the previously anchored reference channel, serving as the phase comparison benchmark. The initial phase calibration data of each channel is compared point-by-point with the standard data of the reference channel, calculating the phase difference between each corresponding data point. A fixed allowable range for phase deviation is preset. The calculated phase difference is compared with this allowable range, and all phase difference values ​​exceeding the allowable range are filtered out. These phase difference values ​​exceeding the allowable range are the error components. All error components are systematically processed to form comprehensive information that fully reflects the phase deviation between the initial phase calibration data and the standard data of each channel; this is the phase error.

[0037] Phase error is a comprehensive information on phase deviations exceeding the allowable range in the previously identified initial phase calibration data for each channel. The initial phase calibration data consists of data that has undergone preliminary phase calibration but still contains some phase deviations. For each data point in the initial phase calibration data for each channel, based on the corresponding phase error information, the required phase adjustment amount is determined for each data point. The magnitude and direction of the adjustment amount are strictly determined according to the phase deviation value corresponding to that data point. Then, the phase of each data point is precisely corrected according to the determined adjustment amount, ensuring that the phase of each data point perfectly matches the phase of the reference channel's standard data. The data obtained after this precise correction is the phase fine calibration data.

[0038] Phase calibration data consists of synchronized data from each channel, precisely phase-compensated and highly consistent with the standard data from the reference channel. A predefined channel order rule and data arrangement format are established. Phase calibration data for each channel is extracted sequentially according to this rule. The extracted data is then integrated and arranged according to the predefined format. During integration, the transitions between different channel data are smoothed to ensure a continuous and unbroken data stream. Simultaneously, the identification information of each channel is preserved to ensure data traceability. The resulting unified data set with a consistent structure and continuous data flow is called the in-phase data block.

[0039] In the calculation formula of the phase calibration data, For the first The phase calibration data of the first channel is the final accurate synchronization data after phase error compensation, used for subsequent collaborative phase aggregation to form in-phase data blocks. It is the data used for the first channel's phase calibration. The product is obtained by performing phase compensation on the initial phase calibration data of each channel, which matches the requirement of complete phase synchronization of multi-channel data. For the first The initial phase calibration data for each channel is the result of phase rotation calibration of the time delay aligned data based on phase offset. It serves as the foundation for fine-tuning the phase, preserving the characteristics of the time delay aligned data while eliminating only the main phase offset. For the first The relative delay parameter of the first channel is derived from the cross-correlation evaluation of multi-channel protocol data frames. Specifically, it is obtained through analytical analysis of the delay difference between non-reference channel data and reference channel data, and is used to characterize the first channel. The time delay difference between each channel and the reference channel is the core parameter for achieving delay compensation alignment. The complex rotation factor is a mathematical tool specifically used for signal phase adjustment. It rotates and corrects residual phase deviations in the initial phase calibration data to ensure the correct phase alignment. The phase of each channel's data is completely consistent with the phase of the reference channel's data. For the first The phase shift of the channel, derived from the relative phase shift anchoring results in the cross-correlation assessment, is obtained by analyzing the peak phase characteristics of the correlation results and comparing the phase difference between the non-reference channel data and the reference channel data. It is the primary correction target in the initial phase calibration stage. For the first Each channel at time The phase error originates from the identification of error components in the initial phase calibration data, which is to... After comparing the initial phase calibration data of each channel with the standard data of the reference channel point by point, the phase deviations that exceed the preset allowable range are selected as key data for achieving accurate phase compensation and are used to correct the slight phase deviations remaining after the initial phase calibration.

[0040] The overall formula is based on the first Based on the initial phase calibration data of each channel, first through The time delay between this channel and the reference channel is compensated, and then a complex rotation factor is used, combined with the phase shift of this channel. and real-time phase error The data phase is precisely rotated and corrected to obtain the final result. All channels are completely phase synchronized. This ensures that the data in each channel is highly consistent in the phase dimension.

[0041] The beneficial effects include eliminating time delay differences between channels, achieving time synchronization, improving the accuracy and consistency of subsequent data processing, quickly eliminating major phase deviations, reducing the difficulty of precise calibration, improving the efficiency of the overall phase calibration process, accurately locating phase deviations exceeding the allowable range, providing a clear basis for phase compensation, improving calibration accuracy, finely correcting phase deviations, ensuring that the phase of each channel is highly consistent with the standard data, improving phase synchronization accuracy, integrating into a unified and continuous in-phase data block, improving the efficiency and accuracy of subsequent decoding processing, and comprehensively optimizing the multi-channel data synchronization processing performance of the TR chip.

[0042] S4. Perform soft-decision Viterbi decoding on the in-phase data block to obtain the decision metric sequence of the chip; In this embodiment of the invention, soft-decision Viterbi decoding is performed on the in-phase data block to obtain the decision metric sequence of the chip, including: The in-phase data blocks are topologically constructed to obtain the decoding grid of the chip; Based on the state transition relationship and associated codewords of the decoding grid, Euclidean distance quantization is performed on the in-phase data block to obtain the branch metric sequence of the chip; Based on the branch metric sequence, the cumulative metric is recursively applied to the decoding grid to obtain the optimal path of the chip; The optimal path is backtracked using reliability metrics to obtain the soft decision likelihood ratio sequence of the chip; The soft decision likelihood ratio sequence is normalized to a bit-level metric to obtain the decision metric sequence of the chip.

[0043] The soft decision likelihood ratio sequence is subjected to bit-level metric normalization to obtain the decision metric sequence of the chip, including: The likelihood ratio sequence of the soft decision is normalized to obtain the normalized soft information of the chip; The confidence level of the normalized soft information is enhanced to obtain the enhanced soft information of the chip. The enhanced soft information is quantized in a fixed format to obtain the decision metric sequence of the chip.

[0044] When constructing the topology for in-phase data blocks, first clarify the encoding rules used in the data transmission process, determine all possible encoding states according to the encoding rules, treat each encoding state as an independent node, and then determine the possible transformation relationships between each node according to the state transition logic specified in the encoding rules. Connect the nodes with transformation relationships with line segments to form a mesh structure containing all state nodes and state transition edges. This structure fully presents all possible state transition paths in the encoding process.

[0045] When performing Euclidean distance quantization based on the state transition relationships and associated codewords in the decoding grid, the specific path corresponding to each state transition in the decoding grid and the encoded data (i.e., the associated codeword) corresponding to each state transition path are first defined. Next, each received data point is extracted from the in-phase data block, and the Euclidean distance between each received data point and the associated codeword corresponding to each state transition is calculated one by one. The calculation method involves obtaining the numerical difference between the corresponding positions of the received data and the associated codeword, squaring each difference value, summing the results, and then taking the square root of the sum. The resulting value is the Euclidean distance. Then, the Euclidean distances corresponding to each state transition are arranged sequentially according to the order of the state transitions, forming the branch metric sequence.

[0046] When performing cumulative metric recursion on the decoding grid based on the branch metric sequence, the process starts from the initial state of the decoding grid and proceeds step by step according to the order of state transitions. For each state, the cumulative metric value of the previous state is added to the branch metric value corresponding to the current state transition to obtain the cumulative metric value of the current state. During the recursion, for each state, only the transition path with the smallest cumulative metric value is retained, because the smaller the cumulative metric value, the higher the matching degree between the path and the received data. When the recursion reaches the final state of the decoding grid, the path with the smallest cumulative metric value is the optimal path.

[0047] When performing reliability measurement backtracking on the optimal path, the process starts from the termination state of the decoding grid and traces back along the optimal path to the starting state. During the tracing process, for each bit, the probabilities of that bit being 0 and 1 in all state transitions along the optimal path are statistically analyzed. Combined with the matching degree between the received data and the associated codeword, the probability of that bit being 0 and 1 is determined. Then, the probability of the bit being 1 is divided by the probability of the bit being 0 to obtain the likelihood ratio of that bit. Arranging the likelihood ratios of all bits according to the transmission order of the bits forms the soft-decision likelihood ratio sequence.

[0048] When performing likelihood ratio normalization on a soft-decision likelihood ratio sequence, a fixed numerical range is first set based on the performance indicators of the decoding system and the requirements of subsequent processing. The maximum and minimum values ​​of this range are determined by the system's processing capacity and error tolerance range, ensuring that most likelihood ratio values ​​fall within this range. Then, each likelihood ratio value in the soft-decision likelihood ratio sequence is checked one by one. If the value is greater than the maximum value of the set range, it is adjusted to that maximum value; if the value is less than the minimum value of the set range, it is adjusted to that minimum value; if the value is within the set range, the original value remains unchanged. The adjusted information is the normalized soft information.

[0049] When enhancing the confidence of regularized soft information, a fixed amplification ratio is first determined through extensive experimental data verification. This ratio can effectively improve the confidence of the information without changing its original characteristics. The value of the regularized soft information is already within a preset fixed range. The median value of this range is used as the evaluation benchmark. Regularized soft information values ​​above and below the benchmark are both multiplied by this fixed amplification ratio. This further increases the confidence of regularized soft information above the benchmark and correspondingly enhances the confidence of regularized soft information below the benchmark. The information after amplification is the enhanced soft information.

[0050] When performing fixed-format quantization on enhanced soft information, the number of bits for quantization is first determined based on the system's storage capacity, transmission bandwidth, and other requirements. Then, the numerical range of the enhanced soft information is divided into several equal parts according to the number of quantization bits; the length of each part is the quantization interval. Next, each value in the enhanced soft information is compared with each quantization interval to find the corresponding interval. The original value is replaced with the fixed quantization value corresponding to that interval. All the replaced quantization values ​​are arranged in the order of the original values ​​in the enhanced soft information, forming a sequence called the decision metric sequence.

[0051] The beneficial effects include: presenting the logic of encoded state transitions, providing structural support, improving the logicality and accuracy of decoding, quantifying the matching degree between state transition paths and received data, providing reliable numerical basis, improving the accuracy of path selection, ensuring the highest matching degree between the selected path and received data, reducing the probability of decoding errors, improving the reliability of decoding results, reflecting the reliability of bit values, providing rich reliability information, enhancing the effectiveness of soft decisions, standardizing the range of likelihood ratio values, avoiding abnormal interference, improving the stability and consistency of information processing, improving the credibility of bit values, enhancing the distinguishability of quantization processing, improving the reliability of decision measurement sequences, forming standardized data that is compatible with the system, facilitating subsequent demodulation and reconstruction, and improving the practicality and adaptability of the overall decoding process.

[0052] S5. Perform probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip; In this embodiment of the invention, probabilistic soft demodulation and reconstruction are performed on the decision metric sequence to obtain the regenerated reference waveform of the chip, including: The soft information distribution of the chip is obtained by performing soft information distribution analysis on the decision metric sequence; The soft bit probability distribution is subjected to probability-driven symbol decision to obtain the complex symbols of the chip; The complex symbols are orthogonally frequency-division multiplexed and framed to obtain the multi-carrier symbol stream of the chip; The multi-carrier symbol stream is subjected to inverse discrete Fourier transform to obtain the regenerated reference waveform of the chip.

[0053] The decision metric sequence is a sequence containing reliability metric information for each bit, obtained after bit-level metric normalization. When performing soft information distribution analysis on it, it is necessary to traverse each metric value in the decision metric sequence one by one, count the number of times the bit corresponding to each metric value appears in different numerical intervals, calculate the proportion of bit occurrence in each interval, and analyze these proportions to clarify the probability values ​​corresponding to each bit taking the 0 state and the 1 state. The final soft bit probability distribution is the result of quantifying the probability of each bit in the two possible states, clearly showing the specific probability of each bit being in the 0 state and the 1 state.

[0054] The soft bit probability distribution clearly defines the probability of each bit taking 0 and 1. In the probability-driven symbol decision process, for each bit, the probability values ​​of taking 0 and 1 are directly compared, and the state with the larger probability value is determined as the final state of that bit. Then, according to the preset fixed symbol mapping rules, the final states of multiple consecutive bits are combined and transformed into the corresponding complex form. This complex form carrier transformed from bit combination is the complex symbol, and each complex symbol uniquely corresponds to a specific set of bit combinations.

[0055] Complex symbols are complex forms of carriers that carry bit combination information. When framing in orthogonal frequency division multiplexing (OFDM), multiple complex symbols are allocated to different preset subcarriers according to the fixed specifications of OFDM technology, ensuring that each subcarrier corresponds to only one complex symbol. Then, according to the preset frame structure requirements, a synchronization sequence for synchronization and a pilot symbol for channel estimation are added to the front end of the complex symbol sequence allocated to the subcarriers, and a guard interval is added to the back end of the sequence, so that these complex symbols carrying data form a continuous symbol sequence with a complete structure that meets the OFDM transmission standard. This sequence is the multi-carrier symbol stream.

[0056] A multicarrier symbol stream is a continuous sequence of symbols that conforms to the orthogonal frequency division multiplexing frame structure. During the inverse discrete Fourier transform, the complex symbols on each subcarrier in the multicarrier symbol stream are sequentially subjected to inverse transform operations. This integrates the symbol information that is scattered across different subcarriers in the frequency domain and transforms it into a continuous signal waveform in the time domain. The continuous signal waveform in the time domain obtained after the inverse transform is the regenerated reference waveform. This waveform can completely preserve the characteristics of the original data and provide a standard reference for subsequent iterative Bayesian correction.

[0057] The beneficial effects include improving the accuracy, consistency, and reliability of frame start boundary identification; enhancing the standardization of original fields; increasing data availability and standardization; meeting the needs of subsequent cross-correlation evaluation; ensuring the reliability and representativeness of reference channel data frames; improving the accuracy of similarity comparison and the comprehensiveness of feature analysis; providing accurate basis for delay compensation and phase calibration; ensuring the effectiveness of both; improving the overall effect of multi-channel data synchronization processing; improving the accuracy of symbol decision and the reliability of complex symbols; enhancing the orthogonality and transmission adaptability of multi-carrier symbol streams; ensuring the quality of regenerated reference waveforms; providing a high-quality reference for subsequent correction; and improving the overall effect of data synchronization processing.

[0058] S6. Based on the regenerated reference waveform, perform iterative Bayesian correction on the multi-channel baseband data stream to obtain the steady-state synchronous data stream of the chip; In this embodiment of the invention, the step of performing iterative Bayesian correction on the multi-channel baseband data stream based on the regenerated reference waveform to obtain the steady-state synchronous data stream of the chip includes: Based on the regenerated reference waveform, a multidimensional difference analysis is performed on the multi-channel baseband data stream to obtain the synchronization error characteristics of the chip; Based on the synchronization error characteristics, dynamic deviation compensation calibration is performed on the multi-channel baseband data stream to obtain the correction intermediate data of the multi-channel baseband data stream; Based on the correction intermediate data, synchronous residual detection is performed on the multi-channel baseband data stream to obtain the residual deviation of the chip; Based on the residual deviation, the multi-channel baseband data stream is synchronously closed-loop calibrated to obtain the steady-state synchronous data stream of the chip.

[0059] The regenerated reference waveform is a standard reference waveform obtained through probabilistic soft demodulation reconstruction, while the multi-channel baseband data stream is the raw, unprocessed baseband signal stream from multiple channels of the chip. Difference analysis is conducted along three fixed dimensions: time, amplitude, and phase. In the time dimension, the signal occurrence time of each channel's baseband data stream is compared with that of the regenerated reference waveform at the same time point. Using the signal occurrence time of the regenerated reference waveform as the standard, the difference between the signal occurrence time of each channel and the standard time is recorded. In the amplitude dimension, at each corresponding time point, the signal amplitude of each channel's baseband data stream and the signal amplitude of the regenerated reference waveform are extracted, and the difference is calculated. A positive difference indicates that the channel's signal amplitude is greater than the reference, while a negative difference indicates that it is less than the reference. In the phase dimension, the signal phase state of each channel's baseband data stream and the regenerated reference waveform at the corresponding time point is observed to determine the direction and degree of phase deviation. Integrating the difference information from these three dimensions forms a comprehensive set of information reflecting the deviation between the multi-channel baseband data stream and the regenerated reference waveform in each key dimension; this is the synchronization error characteristic.

[0060] Synchronization error characteristics include deviations between the multi-channel baseband data stream and the regenerated reference waveform in three dimensions: time, amplitude, and phase. For time dimension compensation, the baseband data stream of each channel is shifted over time according to the time difference value in the synchronization error characteristics. A positive difference indicates a lagging channel signal, and the data stream is shifted backward by the corresponding time. A negative difference indicates a leading channel signal, and the data stream is shifted forward by the corresponding time, ensuring that each channel signal is aligned with the regenerated reference waveform in time. For amplitude dimension compensation, the signal amplitude of each channel data stream is adjusted based on the amplitude difference value in the synchronization error characteristics. A positive amplitude difference decreases the corresponding signal amplitude by the magnitude of the difference, while a negative difference increases the corresponding signal amplitude by the absolute value of the difference, ensuring that the signal amplitude of each channel matches the amplitude of the regenerated reference waveform. For phase dimension compensation, the signal phase of each channel data stream is rotated according to the direction and degree of phase deviation in the synchronization error characteristics, rotating by the corresponding angle in the opposite direction of the deviation to eliminate the phase deviation. The multi-channel baseband data stream obtained after these three dimensions of compensation and calibration is the intermediate correction data.

[0061] The intermediate calibration data is a multi-channel baseband data stream calibrated with dynamic deviation compensation. To detect incompletely eliminated deviations, the intermediate calibration data for each channel is compared point-by-point with the regenerated reference waveform in three dimensions: time, amplitude, and phase. In the time dimension, it is checked whether the signal occurrence time at each time point is completely consistent with the regenerated reference waveform; if not, a new time difference is recorded. In the amplitude dimension, the signal amplitude at each time point is compared, and a new amplitude difference is calculated. In the phase dimension, the phase state is observed, and new phase deviations are recorded. A fixed allowable deviation threshold is set based on the accuracy requirements of data synchronization. The newly obtained time, amplitude, and phase differences are compared with the corresponding allowable thresholds, and all differences exceeding the thresholds are filtered out. These differences exceeding the thresholds are the incompletely eliminated residual deviations. These residual deviations are classified and organized by channel and dimension, and the resulting comprehensive residual deviation information is the residual deviation amount.

[0062] The residual deviation is the incompletely eliminated residual deviation information obtained after synchronous residual detection. For the residual deviation of each channel, precise adjustments are made again in three dimensions: time, amplitude, and phase. In the time dimension, based on the residual time difference, the intermediate correction data of that channel is shifted twice, with the shift duration strictly determined according to the residual time difference to ensure perfect time matching. In the amplitude dimension, based on the residual amplitude difference, the signal amplitude is finely adjusted, with the adjustment amplitude based on the residual amplitude difference to make the amplitude perfectly match the regenerated reference waveform. In the phase dimension, according to the residual phase deviation, a second phase rotation is performed, with the rotation angle precisely corresponding to the residual phase deviation to completely eliminate the phase deviation. After completing the second adjustment, the adjusted data stream is compared with the regenerated reference waveform in all dimensions to confirm that all deviations are within the allowable threshold range. The resulting multi-channel baseband data stream is the steady-state synchronous data stream, which maintains a high degree of consistency with the regenerated reference waveform in terms of time, amplitude, and phase, and the deviation is stable within the allowable range.

[0063] The beneficial effects are as follows: It accurately locates the potential position of data frames, improving the accuracy, consistency, and reliability of frame start boundary identification; it standardizes the original field format, integrates effective data to form standardized protocol data frames, improves data availability to meet subsequent processing needs, ensures the reliability and representativeness of reference channel data frames, and improves the accuracy and comprehensiveness of evaluation results, similarity comparison, and feature analysis; it accurately obtains time delay parameters and phase offset, providing a valid basis for subsequent compensation calibration, improving the effect of multi-channel data synchronization processing, achieving time synchronization of each channel, efficiently eliminating major phase deviations, accurately correcting minor phase errors, and improving phase synchronization accuracy; and it integrates to form a structure. Unified, continuous in-phase data blocks optimize the efficiency and accuracy of subsequent decoding processing, construct a complete decoding grid, and improve the accuracy of branch measurement and path selection; enhance the confidence of soft information, generate standardized decision measurement sequences, provide reliable data support for subsequent demodulation and reconstruction, accurately analyze the distribution of soft information and generate complex symbols, forming a standard multi-carrier symbol stream; obtain a high-quality regenerated reference waveform through inverse transformation, provide a high-precision reference for iterative correction, comprehensively capture data deviations, dynamically compensate to reduce initial deviations, accurately detect and completely eliminate residual deviations; improve the accuracy and stability of multi-channel data synchronization, and ensure high-quality output of steady-state synchronized data streams.

[0064] like Figure 2 The diagram shown is a functional block diagram of a TR chip multi-channel data synchronization processing system provided in an embodiment of the present invention.

[0065] The TR chip multi-channel data synchronization processing system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the TR chip multi-channel data synchronization processing system 100 may include a blind-start framing module 101, a cross-correlation evaluation module 102, a phase coherence aggregation module 103, a soft Viterbi decoding module 104, a probabilistic soft demodulation and reconstruction module 105, and an iterative Bayesian correction module 106. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0066] In this embodiment, the functions of each module / unit are as follows: The blind-start framing module 101 is used to perform blind-start framing on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip. The cross-correlation evaluation module 102 is used to perform cross-correlation evaluation on the multi-channel protocol data frame to obtain the relative delay parameters and phase offset of the multi-channel protocol data frame. The phase coherence aggregation module 103 is used to perform phase coherence aggregation on the multi-channel protocol data frames based on the relative delay parameter and the phase offset to obtain the in-phase data blocks of the chip. The soft Viterbi decoding module 104 is used to perform soft decision Viterbi decoding on the in-phase data block to obtain the decision metric sequence of the chip; The probabilistic soft demodulation and reconstruction module 105 is used to perform probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip. The iterative Bayesian correction module 106 is used to perform iterative Bayesian correction on the multi-channel baseband data stream based on the regenerated reference waveform to obtain the steady-state synchronization data stream of the chip. In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0067] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0068] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0069] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0070] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for multi-channel data synchronization processing of a TR chip, characterized in that, The method includes: S1. Perform blind frame division on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip; S2. Perform cross-correlation evaluation on the multi-channel protocol data frame to obtain the relative delay parameter and phase offset of the multi-channel protocol data frame; S3. Based on the relative delay parameter and the phase offset, perform phase coherence aggregation on the multi-channel protocol data frames to obtain the in-phase data block of the chip; S4. Perform soft-decision Viterbi decoding on the in-phase data block to obtain the decision metric sequence of the chip; S5. Perform probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip; S6. Based on the regenerated reference waveform, perform iterative Bayesian correction on the multi-channel baseband data stream to obtain the steady-state synchronous data stream of the chip.

2. The method for multi-channel data synchronization processing of a TR chip as described in claim 1, characterized in that, Blind-start framing is performed on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip, including: Time-domain energy profiling is performed on the multi-channel baseband data stream of the chip to obtain the chip's energy pulses; Based on the energy pulse, peak correlation boundary determination is performed on the multi-channel baseband data stream to obtain the frame start boundary of the chip; Based on the frame start boundary of the chip, the multi-channel baseband data stream is subjected to protocol window interception to obtain the original fields of the chip; The original fields are co-framed to obtain the chip's multi-channel protocol data frame.

3. The method for multi-channel data synchronization processing of a TR chip as described in claim 1, characterized in that, The cross-correlation of the multi-channel protocol data frames is evaluated to obtain the relative delay parameters and phase offset of the multi-channel protocol data frames, including: The reference channel data frame of the chip is obtained by anchoring the reference channel of the multi-channel protocol data frame. Using the reference channel data frame as a reference, a similarity comparison is performed on the non-reference channel data in the protocol data frame to obtain the relevant results of the chip; The relevant results of the chip are analyzed by characteristic peak analysis to obtain the peak position information and peak phase characteristics of the chip; Based on the peak position information, a delay difference analysis is performed on the non-reference channel data and the reference channel data to obtain the relative delay parameters of the multi-channel protocol data frame; Based on the peak phase characteristics, the non-reference channel data and the reference channel data are anchored relative to each other to obtain the phase offset of the multi-channel protocol data frame.

4. The method for multi-channel data synchronization processing of a TR chip as described in claim 1, characterized in that, Based on the relative delay parameter and the phase offset, the multi-channel protocol data frames are coherently aggregated to obtain the in-phase data block of the chip, including: Based on the relative delay parameters, delay compensation and alignment are performed on the multi-channel protocol data frames to obtain the delay alignment data of the chip; Based on the phase offset, the delay alignment data is subjected to phase rotation calibration to obtain the initial phase calibration data of the chip; Error components are identified in the initial phase calibration data to obtain the phase error of the chip; Based on the phase error, phase compensation is performed on the initial phase calibration data to obtain the phase fine calibration data of the chip; The phase calibration data is then subjected to collaborative phase consolidation to obtain the in-phase data block of the chip.

5. The method for multi-channel data synchronization processing of a TR chip as described in claim 4, characterized in that, The specific formula for calculating the phase calibration data is as follows: ； In the formula, For the first The phase calibration data for each channel, For the first The initial phase calibration data for each channel, For the first The relative delay parameters of each channel, For the first The phase shift of each channel For the first Each channel at time The phase error, is a complex number rotation factor.

6. The method for multi-channel data synchronization processing of a TR chip as described in claim 1, characterized in that, Soft-decision Viterbi decoding is performed on the in-phase data block to obtain the decision metric sequence of the chip, including: The in-phase data blocks are topologically constructed to obtain the decoding grid of the chip; Based on the state transition relationship and associated codewords of the decoding grid, Euclidean distance quantization is performed on the in-phase data block to obtain the branch metric sequence of the chip; Based on the branch metric sequence, the cumulative metric is recursively applied to the decoding grid to obtain the optimal path of the chip; The optimal path is backtracked using reliability metrics to obtain the soft decision likelihood ratio sequence of the chip; The soft decision likelihood ratio sequence is normalized to a bit-level metric to obtain the decision metric sequence of the chip.

7. The method for multi-channel data synchronization processing of a TR chip as described in claim 6, characterized in that, The soft decision likelihood ratio sequence is subjected to bit-level metric normalization to obtain the decision metric sequence of the chip, including: The likelihood ratio sequence of the soft decision is normalized to obtain the normalized soft information of the chip; The confidence level of the normalized soft information is enhanced to obtain the enhanced soft information of the chip. The enhanced soft information is quantized in a fixed format to obtain the decision metric sequence of the chip.

8. The method for multi-channel data synchronization processing of a TR chip as described in claim 1, characterized in that, The decision metric sequence is reconstructed using probabilistic soft demodulation to obtain the regenerated reference waveform of the chip, including: The soft information distribution of the chip is obtained by performing soft information distribution analysis on the decision metric sequence; The soft bit probability distribution is subjected to probability-driven symbol decision to obtain the complex symbols of the chip; The complex symbols are orthogonally frequency-division multiplexed and framed to obtain the multi-carrier symbol stream of the chip; The multi-carrier symbol stream is subjected to inverse discrete Fourier transform to obtain the regenerated reference waveform of the chip.

9. The method for multi-channel data synchronization processing of a TR chip as described in claim 1, characterized in that, The step of performing iterative Bayesian correction on the multi-channel baseband data stream based on the regenerated reference waveform to obtain the steady-state synchronous data stream of the chip includes: Based on the regenerated reference waveform, a multidimensional difference analysis is performed on the multi-channel baseband data stream to obtain the synchronization error characteristics of the chip; Based on the synchronization error characteristics, dynamic deviation compensation calibration is performed on the multi-channel baseband data stream to obtain the correction intermediate data of the multi-channel baseband data stream; Based on the correction intermediate data, synchronous residual detection is performed on the multi-channel baseband data stream to obtain the residual deviation of the chip; Based on the residual deviation, the multi-channel baseband data stream is synchronously closed-loop calibrated to obtain the steady-state synchronous data stream of the chip.

10. A TR chip multi-channel data synchronization processing system, characterized in that, The system for implementing the TR chip multi-channel data synchronization processing method according to claim 1 includes: The blind-start framing module is used to perform blind-start framing on the multi-channel baseband data stream of the chip to obtain the multi-channel protocol data frame of the chip. The cross-correlation evaluation module is used to perform cross-correlation evaluation on the multi-channel protocol data frame to obtain the relative delay parameters and phase offset of the multi-channel protocol data frame; The phase coherence aggregation module is used to perform phase coherence aggregation on the multi-channel protocol data frames based on the relative delay parameter and the phase offset to obtain the in-phase data blocks of the chip. A soft Viterbi decoding module is used to perform soft decision Viterbi decoding on the in-phase data block to obtain the decision metric sequence of the chip; The probabilistic soft demodulation and reconstruction module is used to perform probabilistic soft demodulation and reconstruction on the decision metric sequence to obtain the regenerated reference waveform of the chip; The iterative Bayesian correction module is used to perform iterative Bayesian correction on the multi-channel baseband data stream based on the regenerated reference waveform to obtain the steady-state synchronous data stream of the chip.

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