A method and system for transmitting audio composite data stream over FD-CAN bus

Abstract

The application relates to the field of audio transmission technology and discloses an FD-CAN bus audio composite data stream transmission method and system. Three types of real-time multi-modal parameters, including audio content features, bus physical features and service quality constraints, are acquired, an audio dynamic complexity coefficient is calculated according to audio instantaneous energy and spectral flatness, a bus transmission quality coefficient is calculated according to bus instantaneous load rate and signal-to-noise ratio, the maximum transmission delay allowed is obtained according to service quality and signal-to-noise ratio, a dynamic scheduling priority coefficient is acquired in combination with the bus transmission quality coefficient, a time-frequency-space multi-modal coupling matrix is constructed based on the three types of coefficients, a principal coupling feature vector is extracted through principal component analysis and a dynamic transmission strategy index value is calculated, a frame format, a modulation mode and error correction coding parameters are adaptively selected according to the index value, and the audio is sent after being packaged into an FD-CAN frame. The application solves the problems of bandwidth waste and transmission jitter caused by traditional static scheduling through multi-dimensional parameter coupling and dynamic strategy adaptation.

Description

Technical Field

[0001] This invention relates to the field of audio transmission technology, and in particular to a method and system for transmitting audio composite data streams via FD-CAN bus. Background Technology

[0002] Flexible Data Rate Controller Area Network (FD-CAN), as an upgrade and evolution of the traditional CAN bus, has been widely used in complex data stream transmission scenarios such as in-vehicle audio transmission, industrial field voice communication, and robot auditory interaction due to its high bandwidth, high reliability, and real-time performance. The FD-CAN bus significantly improves the bandwidth bottleneck problem of the traditional CAN bus when transmitting large amounts of data such as audio by increasing the maximum effective payload of the data field (up to 64 bytes) and using a variable bit rate mode.

[0003] Currently, existing technologies for transmitting audio composite data streams on the FD-CAN bus mainly focus on static priority scheduling or fixed time slot allocation strategies. For example, different audio channels are pre-assigned fixed identifiers (IDs), and their competition order in bus arbitration is determined by the priority bits in the IDs; or audio pulse code modulation (PCM) data is packetized according to a fixed length and injected into the FD-CAN transmit queue at a constant rate. However, existing methods fail to effectively couple the dynamic characteristics of the audio signal in the time and frequency domain. The complexity of audio content (such as silence segments, speech segments, and music segments) changes drastically over time, and its importance to human auditory perception is not constant. Existing methods employ a uniform encoding bitrate and packetization strategy, resulting in wasted bus bandwidth when audio complexity is low, while bus congestion and transmission jitter occur due to a surge in data volume when audio complexity is high. Therefore, an FD-CAN bus audio composite data stream transmission method is needed to solve the above problems. Summary of the Invention

[0004] The main objective of this invention is to provide a method and system for transmitting audio composite data streams via FD-CAN bus, aiming to solve the technical problems mentioned in the background section.

[0005] This invention proposes a method for transmitting audio composite data streams on an FD-CAN bus based on multimodal parameter coupling, comprising: The real-time multimodal parameters of the FD-CAN bus audio composite data stream are obtained, wherein the real-time multimodal parameters include audio content feature parameters, bus physical feature parameters, and quality of service constraint parameters. The audio instantaneous energy parameter and audio spectral flatness parameter are obtained based on the audio content feature parameters, and the audio dynamic complexity coefficient is obtained based on the audio instantaneous energy parameter and the audio spectral flatness parameter. The bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter are obtained based on the bus physical characteristic parameters, and the bus transmission quality coefficient is obtained based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter. The maximum allowable transmission delay parameter is obtained based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and the dynamic scheduling priority coefficient is obtained based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient. A time-frequency-space multimodal coupling matrix is ​​constructed based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient. Principal component analysis is performed on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector. The dynamic transmission strategy index value is calculated based on the main coupling feature vector. The transmission method is obtained according to the dynamic transmission strategy index value, and the audio composite data stream is encapsulated into FD-CAN frames and sent through the FD-CAN bus according to the transmission method.

[0006] Preferably, the step of obtaining the audio instantaneous energy parameter and the audio spectral flatness parameter based on the audio content feature parameters, and obtaining the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectral flatness parameter, includes: Based on the audio content feature parameters, obtain an audio signal sample sequence within a preset time window; The audio instantaneous energy parameter is calculated based on the audio signal sample sequence, and the audio spectral flatness parameter is calculated based on the frequency domain representation of the audio signal sample sequence. Obtain the average instantaneous energy parameter and average spectral flatness parameter of historical normal audio signals; The first energy change rate is obtained based on the instantaneous audio energy parameter and the average instantaneous energy parameter, and the spectral offset is obtained based on the audio spectral flatness parameter and the average spectral flatness parameter. The audio dynamic range fluctuation coefficient is obtained based on the first energy change rate and the spectral offset. Obtain the signal category weight factor from the audio content feature parameters, and correct the audio dynamic range fluctuation coefficient according to the signal category weight factor to obtain the audio dynamic complexity coefficient.

[0007] Preferably, the step of obtaining the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and obtaining the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter, includes: The bus occupancy time and total bus time within the current sampling period are obtained based on the bus physical characteristic parameters, and the bus instantaneous load rate parameter is calculated based on the bus occupancy time and total bus time. Obtain the signal power and noise power of the bus physical characteristic parameters in the current sampling period, and calculate the bus signal-to-noise ratio parameter based on the signal power and the noise power; Obtain the baseline load rate parameter and baseline signal-to-noise ratio parameter of the bus under historical normal transmission conditions; The load deviation is obtained based on the bus instantaneous load rate parameter and the reference load rate parameter, and the signal-to-noise ratio gain is obtained based on the bus signal-to-noise ratio parameter and the reference signal-to-noise ratio parameter. The comprehensive evaluation value of the channel state is obtained based on the load deviation and the signal-to-noise ratio gain. Obtain the channel coherence bandwidth parameter from the bus physical characteristic parameters, and normalize the channel state comprehensive evaluation value based on the channel coherence bandwidth parameter to obtain the bus transmission quality coefficient.

[0008] Preferably, the step of obtaining the maximum allowable transmission delay parameter based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and obtaining the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient, includes: Obtain the maximum permissible end-to-end latency and maximum permissible jitter of the audio data stream from the aforementioned quality of service constraint parameters; Based on the bus signal-to-noise ratio parameters and the preset signal-to-noise ratio-delay tolerance mapping relationship, obtain the delay tolerance correction factor under the current signal-to-noise ratio condition; The maximum allowable transmission delay parameter is calculated based on the maximum allowable end-to-end delay, the maximum allowable jitter, and the delay tolerance correction factor. Obtain the estimated transmission time of the current data frame, and obtain the initial transmission urgency based on the maximum allowable transmission delay parameter and the estimated transmission time; The initial transmission urgency is corrected based on the bus transmission quality coefficient to obtain a standardized transmission urgency. The importance weight of the audio data stream is obtained from the quality of service constraint parameters, and the standardized transmission urgency is calculated based on the importance weight to obtain the dynamic scheduling priority coefficient.

[0009] Preferably, the steps of constructing a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient, performing principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector, and calculating the dynamic transmission strategy index value based on the main coupling feature vector include: The audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient are used as core feature dimensions, and extended feature parameters related to each core feature dimension in the time domain, frequency domain, and spatial domain are obtained. Based on the core feature dimensions and the extended feature parameters, a time-frequency-space multimodal coupling matrix is ​​constructed, with rows corresponding to different sampling times and columns corresponding to different feature dimensions. Principal component analysis is performed on the time-frequency-space multimodal coupling matrix to extract the top K principal components whose cumulative contribution rate exceeds a preset threshold, and the feature vectors of these K principal components are used as the principal coupling feature vectors. Obtain the feature value corresponding to each of the principal coupling feature vectors, and calculate the contribution rate weight of each principal component based on the feature value; The weighted contribution rate is calculated based on the projection value of the main coupling feature vector at the current sampling time and its corresponding contribution rate weight; Obtain the historical weighted contribution rate sum corresponding to the historical best transmission strategy, obtain the strategy deviation degree based on the current weighted contribution rate sum and the historical weighted contribution rate sum, and calculate the dynamic transmission strategy index value in combination with the preset strategy mapping table.

[0010] Preferably, the step of obtaining the transmission mode according to the dynamic transmission strategy index value, encapsulating the audio composite data stream into an FD-CAN frame according to the transmission mode, and transmitting it through the FD-CAN bus includes: The predefined strategy-parameter mapping table is queried according to the dynamic transmission strategy index value to obtain the corresponding target frame format parameters, target modulation mode parameters and forward error correction coding parameters. Based on the target frame format parameters, determine the data field length, frame type, and padding rules of the FD-CAN frame; Based on the target modulation parameters and the forward error correction coding parameters, channel coding and signal modulation are performed on the audio composite data stream to be transmitted to generate a baseband data stream; Based on the filling rules and the baseband data stream, a data link layer frame structure conforming to the FD-CAN protocol is constructed, and the FD-CAN frame is encapsulated to obtain an encapsulated FD-CAN frame. The encapsulated FD-CAN frame is converted into a physical signal according to the target modulation parameters, and the physical signal is transmitted through the FD-CAN bus.

[0011] This application also provides an FD-CAN bus audio composite data stream transmission system based on multimodal parameter coupling, including: The multimodal parameter acquisition module is used to acquire real-time multimodal parameters of the FD-CAN bus audio composite data stream, wherein the real-time multimodal parameters include audio content feature parameters, bus physical feature parameters, and service quality constraint parameters. The audio dynamic complexity analysis module is used to obtain the audio instantaneous energy parameter and the audio spectrum flatness parameter based on the audio content feature parameters, and to obtain the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectrum flatness parameter. The bus transmission quality assessment module is used to obtain the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and to obtain the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter. The dynamic scheduling priority calculation module is used to obtain the maximum allowable transmission delay parameter based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and to obtain the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient. The strategy index generation module is used to construct a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient, and to perform principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector, and to calculate the dynamic transmission strategy index value based on the main coupling feature vector; The transmission module is used to obtain the transmission mode according to the dynamic transmission strategy index value, encapsulate the audio composite data stream into FD-CAN frames according to the transmission mode, and send them through the FD-CAN bus.

[0012] Preferably, the audio dynamic complexity analysis module includes: An audio sample extraction unit is used to obtain an audio signal sample sequence within a preset time window based on the audio content feature parameters. The first calculation unit is used to calculate the audio instantaneous energy parameter based on the audio signal sample sequence, and to calculate the audio spectral flatness parameter based on the frequency domain representation of the audio signal sample sequence. The second acquisition unit is used to acquire the average instantaneous energy parameter and average spectral flatness parameter of historical normal audio signals; The historical reference parameter acquisition unit is used to obtain a first energy change rate based on the audio instantaneous energy parameter and the average instantaneous energy parameter, and to obtain a spectral offset based on the audio spectral flatness parameter and the average spectral flatness parameter. A fluctuation coefficient generation unit is used to obtain the audio dynamic range fluctuation coefficient based on the first energy change rate and the spectral offset. The correction unit is used to obtain the signal category weight factor in the audio content feature parameters, and correct the audio dynamic range fluctuation coefficient according to the signal category weight factor to obtain the audio dynamic complexity coefficient.

[0013] This application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0014] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0015] The beneficial effects of this application are as follows: This invention constructs a complete perception system from audio dynamic analysis and channel state assessment to transmission urgency calculation by acquiring three types of real-time multimodal parameters: audio content features, bus physical features, and service quality constraints. Specifically, by calculating the instantaneous audio energy and spectral flatness, and introducing a signal category weighting factor for correction, the dynamic complexity of the audio content is accurately quantified, avoiding wasted bandwidth in silent or simple audio segments, while prioritizing transmission resources in complex audio segments. By calculating the instantaneous bus load rate and signal-to-noise ratio, and combining them with channel coherence bandwidth for normalization, the bus transmission quality is accurately evaluated, providing a reliable physical layer basis for dynamic adjustment strategies. Furthermore, by fusing the maximum allowable transmission delay and bus transmission quality, a dynamic scheduling priority coefficient is generated, realizing the priority scheduling of high-urgency data streams. Finally, by constructing a time-frequency-space multimodal coupling matrix and performing principal component analysis, multidimensional features are efficiently fused into dynamic transmission strategy index values, adaptively selecting the optimal frame format, modulation scheme, and error correction coding parameters. This method effectively solves the problems of low bandwidth utilization, congestion, and jitter caused by static scheduling in traditional FD-CAN audio transmission. It achieves deep coupling and dynamic adaptation of audio content, channel state, and quality of service requirements, and significantly improves the bandwidth efficiency, real-time performance, and robustness of the FD-CAN bus when transmitting audio composite data streams. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a method flow according to an embodiment of this application.

[0017] Figure 2This is a schematic diagram of the system structure according to an embodiment of this application.

[0018] 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

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] like Figure 1 As shown, this application provides a method for transmitting audio composite data streams via an FD-CAN bus, applied to shipboard broadcasting equipment, including: S1. Obtain the real-time multimodal parameters of the FD-CAN bus audio composite data stream, wherein the real-time multimodal parameters include audio content feature parameters, bus physical feature parameters, and service quality constraint parameters; S2. Obtain the audio instantaneous energy parameter and audio spectrum flatness parameter based on the audio content feature parameters, and obtain the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectrum flatness parameter; S3. Obtain the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and obtain the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter; S4. Obtain the maximum allowable transmission delay parameter based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and obtain the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient; S5. Construct a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient; perform principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector; and calculate the dynamic transmission strategy index value based on the main coupling feature vector. S6. Obtain the transmission mode according to the dynamic transmission strategy index value, encapsulate the audio composite data stream into an FD-CAN frame according to the transmission mode, and send it through the FD-CAN bus.

[0021] As described in steps S1-S6 above, existing FD-CAN audio transmission methods fail to effectively couple the dynamic characteristics of the audio signal in the time and frequency domain, resulting in wasted bus bandwidth when audio complexity is low, and bus congestion and transmission jitter caused by a surge in data volume when audio complexity is high. This invention first obtains real-time multimodal parameters of the FD-CAN bus audio composite data stream. These parameters comprehensively characterize the current transmission environment and requirements from three dimensions: audio content, bus physical state, and service quality, providing a data foundation for subsequent dynamic decision-making.

[0022] Then, based on the audio content feature parameters, the instantaneous audio energy parameter and the audio spectral flatness parameter are obtained, and the audio dynamic complexity coefficient is obtained based on these two parameters. Instantaneous energy reflects the intensity change of the audio signal (such as the abrupt change from silence to speech), while spectral flatness characterizes whether the audio is noise-like (flat spectrum) or pitch-like (with peaks). By coupling the two, silence segments, unvoiced segments, voiced segments, or musical climaxes can be accurately distinguished, and the complexity of their encoding and transmission can be quantified.

[0023] Next, the instantaneous bus load rate parameter and bus signal-to-noise ratio parameter are obtained based on the bus physical characteristic parameters, and then the bus transmission quality coefficient is obtained. The load rate reflects the bus's busy level, and the signal-to-noise ratio reflects the reliability of the physical channel. Combining the two, it is possible to accurately determine whether the current bus is idle, normal, or congested / interference-affected, providing a basis for whether to degrade transmission quality or add error correction codes.

[0024] Secondly, the maximum allowable transmission delay parameter is obtained based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and a dynamic scheduling priority coefficient is obtained by combining it with the bus transmission quality coefficient. This coefficient dynamically adjusts the urgency of the current audio data frame in the transmission queue. For example, when the bus signal-to-noise ratio is low, the allowable transmission delay is relaxed, and the priority is relatively lower; while when the audio dynamic complexity is high and the transmission quality is good, the priority is increased to ensure that critical audio data is sent in a timely manner.

[0025] Next, a time-frequency-space multimodal coupling matrix is ​​constructed based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient. This matrix uniformly organizes the three core features and their extended parameters in time (different sampling times), frequency (different frequency band features), and space (different bus nodes or channels). Through principal component analysis (PCA), the main coupling feature vectors with the largest contribution rate are extracted from the high-dimensional matrix. These vectors represent the most important combinations of transmission influencing factors in the current environment. Based on these vectors, the dynamic transmission strategy index value is calculated, realizing an intelligent mapping from complex multi-parameters to a single decision index.

[0026] Finally, based on the dynamic transmission strategy index value, the optimal transmission method (such as frame format, modulation method, and error correction coding strength) is obtained, and the audio composite data stream is encapsulated into FD-CAN frames and sent. In this way, the system can adaptively adjust the transmission strategy of each frame based on the importance of the audio content, the current bus load, and channel quality. This maximizes bus bandwidth utilization and minimizes transmission jitter and congestion risks while ensuring audio quality, significantly improving the overall performance of FD-CAN bus audio transmission.

[0027] In one embodiment, step S2, which involves obtaining the audio instantaneous energy parameter and the audio spectral flatness parameter based on the audio content feature parameters, and obtaining the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectral flatness parameter, includes: S201. Obtain an audio signal sample sequence within a preset time window based on the audio content feature parameters; S202. Calculate the audio instantaneous energy parameter based on the audio signal sample sequence, and calculate the audio spectral flatness parameter based on the frequency domain representation of the audio signal sample sequence; S203. Obtain the average instantaneous energy parameter and average spectral flatness parameter of historical normal audio signals; S204. Obtain the first energy change rate based on the audio instantaneous energy parameter and the average instantaneous energy parameter, and obtain the spectral offset based on the audio spectral flatness parameter and the average spectral flatness parameter; S205. Obtain the audio dynamic range fluctuation coefficient based on the first energy change rate and the spectral offset; S206. Obtain the signal category weight factor in the audio content feature parameters, and correct the audio dynamic range fluctuation coefficient according to the signal category weight factor to obtain the audio dynamic complexity coefficient.

[0028] As described in steps S201-S206 above, the present invention first extracts an audio signal sample sequence within a preset time window (e.g., 20ms, corresponding to the human auditory integration time) from the audio content feature parameters. This sequence is the smallest unit of analysis for time-frequency analysis.

[0029] Next, the instantaneous energy (e.g., summing the squares of the amplitudes at each sampling point) and spectral flatness (e.g., the ratio of the geometric mean to the arithmetic mean of the signal spectrum) of the audio signal within the window are calculated. Instantaneous energy distinguishes speech / music segments from silent segments, while spectral flatness distinguishes voiced sounds (spectral peaks, low flatness) from unvoiced sounds / noise (flat spectrum, high flatness).

[0030] Then, the average instantaneous energy and average spectral flatness of the audio channel under historical normal transmission conditions (no congestion, no faults) are obtained as a benchmark. By comparing the instantaneous energy of the current window with the historical average, the first energy change rate is obtained, which can keenly capture sudden increases (such as drum beats, plosive sounds) or decreases (such as pauses between sentences) in energy. Simultaneously, by comparing the current spectral flatness with the historical average, a spectral offset is obtained, which can detect significant changes in the audio spectral structure (such as switching from speech to music). Combining the first energy change rate with the spectral offset, for example through weighted summation or multiplication, yields an audio dynamic range fluctuation coefficient. This coefficient comprehensively reflects the drastic dynamic changes in the audio's energy and spectral structure. Finally, a signal category weighting factor (e.g., 0.8 for speech signals, 1.0 for music signals, and 1.5 for emergency alarm tones) is introduced to correct the dynamic range fluctuation coefficient.

[0031] For example, for the same drastic energy fluctuations, the complexity coefficient of an emergency alarm tone would be further increased to ensure it receives higher transmission priority. In this way, the final audio dynamic complexity coefficient accurately reflects the importance of the current audio content, its coding complexity, and its contribution to human auditory perception.

[0032] In one embodiment, step S3, which involves obtaining the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and obtaining the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter, includes: S301. Obtain the bus occupancy time and total bus time within the current sampling period based on the bus physical characteristic parameters, and calculate the bus instantaneous load rate parameter based on the bus occupancy time and total bus time; S302. Obtain the signal power and noise power of the bus physical characteristic parameters in the current sampling period, and calculate the bus signal-to-noise ratio parameter based on the signal power and the noise power; S303. Obtain the reference load rate parameter and reference signal-to-noise ratio parameter of the bus under historical normal transmission conditions; S304. Obtain the load deviation based on the bus instantaneous load rate parameter and the reference load rate parameter, and obtain the signal-to-noise ratio gain based on the bus signal-to-noise ratio parameter and the reference signal-to-noise ratio parameter; S305. Obtain a comprehensive evaluation value of the channel state based on the load deviation and the signal-to-noise ratio gain; S306. Obtain the channel coherence bandwidth parameter from the bus physical characteristic parameters, and normalize the channel state comprehensive evaluation value according to the channel coherence bandwidth parameter to obtain the bus transmission quality coefficient.

[0033] As described in steps S301-S306 above, this invention first monitors the FD-CAN bus and calculates the ratio of the actual time used for data transmission on the bus (bus occupancy time) to the total duration of the period within a sampling cycle (e.g., 100ms), thus obtaining the instantaneous bus load rate. A high load rate means that the bus is close to saturation, and new data frames may require a longer arbitration waiting time.

[0034] Simultaneously, the signal power and background noise power on the bus are measured to calculate the real-time signal-to-noise ratio (SNR). A high SNR indicates good channel quality, a low data transmission error rate, and the ability to use higher-order modulation or fewer error correction codes.

[0035] Then, obtain the baseline load rate (e.g., 20%) and baseline signal-to-noise ratio (e.g., 30dB) of the system under historical normal, light-load conditions. By comparing the current load rate with the baseline value, the load deviation is obtained (e.g., if the current load rate is 80%, the deviation is +60%); by comparing the current signal-to-noise ratio with the baseline value, the signal-to-noise ratio gain is obtained (e.g., if the current signal-to-noise ratio is 25dB, the gain is -5dB). The load deviation reflects the bus congestion pressure, and the signal-to-noise ratio gain reflects the relative change in channel quality. Combining the two, for example, using the formula Channel State Comprehensive Evaluation Value = (1 - Load Deviation Normalized Value) * Signal-to-Noise Ratio Gain Normalized Value, a comprehensive index that simultaneously reflects the "busyness of data transmission on the bus" and the "quality of the channel" is obtained.

[0036] Finally, considering that the physical layer characteristics of different FD-CAN networks (such as cable length, terminating resistance, and number of nodes) affect their frequency selective fading, a channel coherence bandwidth parameter is introduced. This parameter describes the frequency range within which two frequency components of the channel can correlate. The overall channel state evaluation value is normalized based on the coherence bandwidth. For example, for channels with narrow coherence bandwidth (severe frequency selective fading), the overall evaluation value is appropriately reduced to encourage the adoption of more robust transmission strategies. The resulting bus transmission quality coefficient is a standardized value between 0 and 1, calibrated for physical layer characteristics, which can be fairly used for dynamic decision-making across different bus systems.

[0037] In one embodiment, step S4, which involves obtaining the maximum allowable transmission delay parameter based on the quality of service constraint parameter and the bus signal-to-noise ratio parameter, and obtaining the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient, includes: S401. Obtain the maximum permissible end-to-end latency and maximum permissible jitter of the audio data stream from the quality of service constraint parameters; S402. Based on the bus signal-to-noise ratio parameters and the preset signal-to-noise ratio-delay tolerance mapping relationship, obtain the delay tolerance correction factor under the current signal-to-noise ratio condition; S403. Calculate the maximum allowable transmission delay parameter based on the maximum allowable end-to-end delay, the maximum allowable jitter, and the delay tolerance correction factor. S404. Obtain the estimated transmission time of the current data frame, and obtain the initial transmission urgency based on the maximum allowed transmission delay parameter and the estimated transmission time. S405. Correct the initial transmission urgency based on the bus transmission quality coefficient to obtain a standardized transmission urgency; S406. Obtain the importance weight of the audio data stream from the quality of service constraint parameters, calculate the standardized transmission urgency based on the importance weight, and obtain the dynamic scheduling priority coefficient.

[0038] As described in steps S401-S406 above, the present invention first extracts the maximum permissible end-to-end latency (e.g., 10ms) and maximum permissible jitter (e.g., 1ms) of the audio stream from pre-set Quality of Service (QoS) parameters. These are hard indicators to ensure audio experience. Next, based on the currently measured signal-to-noise ratio (SNR), a pre-set mapping table or function is queried to obtain the latency tolerance correction factor.

[0039] This mapping reflects the impact of the physical layer on latency: a high signal-to-noise ratio (SNR) ensures reliable transmission and allows for more stringent latency requirements (correction factor close to 1); a low SNR increases the risk of errors and retransmissions, necessitating a more relaxed latency tolerance (correction factor greater than 1). Then, using the formula Maximum Allowable Transmission Latency = (Maximum Allowable End-to-End Latency - Maximum Allowable Jitter) / Latency Tolerance Correction Factor, the maximum allowable time for this frame of data to be successfully transmitted from entering the transmission queue is calculated under the current channel conditions.

[0040] To determine the initial transmission urgency, obtain the estimated transmission time of the current data frame (considering frame length, data field size, and current baud rate). Then, the initial transmission urgency is calculated as: Estimated transmission time / Maximum allowable transmission delay. The closer this ratio is to or greater than 1, the more urgent the frame is, and it must be sent as soon as possible. Subsequently, the initial transmission urgency is adjusted using a bus transmission quality coefficient.

[0041] If the bus transmission quality is good (coefficient close to 1), maintain or slightly increase the urgency; if the quality is poor (coefficient low), appropriately reduce the urgency, because even if priority is given in this case, the risk of error is high, and it may be better to wait for the channel to improve or adopt a more robust strategy. This results in a standardized transmission urgency.

[0042] Finally, the importance weight of the audio stream is obtained from the QoS parameters (e.g., navigation voice weight 0.9, entertainment music weight 0.5, and call voice weight 0.7). The dynamic scheduling priority coefficient = standardized transmission urgency * importance weight. This coefficient combines "urgency" and "importance," providing the upper-layer scheduler with a precise and dynamic priority value.

[0043] In one embodiment, step S5, which involves constructing a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient, performing principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector, and calculating the dynamic transmission strategy index value based on the main coupling feature vector, includes: S501. Using the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient as core feature dimensions, and obtaining extended feature parameters related to each core feature dimension in the time domain, frequency domain, and spatial domain. S502. Based on the core feature dimension and the extended feature parameters, construct the time-frequency-space multimodal coupling matrix with rows corresponding to different sampling times and columns corresponding to different feature dimensions; S503. Perform principal component analysis on the time-frequency-space multimodal coupling matrix, extract the top K principal components whose cumulative contribution rate exceeds a preset threshold, and use the feature vectors of the K principal components as the principal coupling feature vectors. S504. Obtain the feature value corresponding to each of the principal coupling feature vectors, and calculate the contribution rate weight of each principal component based on the feature value; S505. Calculate the weighted contribution rate sum based on the projection value of the main coupling feature vector at the current sampling time and its corresponding contribution rate weight; S506. Obtain the historical weighted contribution rate corresponding to the historical best transmission strategy, obtain the strategy deviation based on the current weighted contribution rate and the historical weighted contribution rate, and calculate the dynamic transmission strategy index value in conjunction with the preset strategy mapping table.

[0044] As described in steps S501-S506 above, the present invention first takes the audio dynamic complexity coefficient (A), bus transmission quality coefficient (B), and dynamic scheduling priority coefficient (C) as core features.

[0045] Meanwhile, to describe the system state more comprehensively and obtain their extended features, for example: in the time domain, take the change rate or moving window average of A, B, and C; in the frequency domain, A can be decomposed into sub - coefficients in different frequency bands; in the spatial domain, consider the values of A, B, and C of different bus nodes or audio channels. Then, construct a matrix with N rows and M columns, where N is the number of historical sampling moments (such as the past 50 time points), and M is the total number of all core and extended features (such as 15). This matrix is the time - frequency - space multi - modal coupling matrix.

[0046] Next, perform principal component analysis (PCA) on this matrix. PCA can transform the original M correlated features into K (K << M) uncorrelated principal components, which are arranged according to the magnitude of their ability to explain the data variance (i.e., the amount of information). Extract the first K principal components whose cumulative contribution rate exceeds a preset threshold (such as 95%), and the corresponding eigenvectors are the main coupling eigenvectors. They represent the combination of several core factors that affect the bus transmission performance (for example, the first principal component may mainly reflect the combination of "high audio activity + high bus load").

[0047] The magnitude of the eigenvalue of each principal component reflects its contribution rate, based on which the contribution rate weight of each principal component can be calculated. For the current sampling moment, project its eigenvalue onto these K main coupling eigenvectors to obtain a set of projection values, and then perform weighted summation with the contribution rate weights of each principal component to obtain a weighted contribution rate sum. This value reflects the position relationship between the current system state and the historical optimal state in the space spanned by the principal components.

[0048] Obtain the historical weighted contribution rate sum corresponding to the historical optimal transmission strategy (for example, the moment determined by offline experiments or online learning that makes the comprehensive performance optimal). Calculate the deviation degree (such as difference or ratio) between the current weighted contribution rate and the historical optimal value. The smaller the deviation degree, the closer the current state is to the optimal. Finally, combine a preset strategy mapping table (which maps different ranges of weighted contribution rate sums or deviation degrees to specific transmission strategy indices) to calculate the dynamic transmission strategy index value. For example, when the deviation degree is between 0 - 0.1, it is mapped to index 1 (optimal strategy); when the deviation degree is between 0.1 - 0.3, it is mapped to index 2 (sub - optimal strategy), and so on.

[0049] In one embodiment, step S6 of obtaining the transmission mode according to the dynamic transmission strategy index value and encapsulating the audio composite data stream into FD - CAN frames and sending them through the FD - CAN bus includes: S601. Query the predefined strategy - parameter mapping table according to the dynamic transmission strategy index value to obtain the corresponding target frame format parameters, target modulation mode parameters, and forward error correction coding parameters; S602. Determine the data field length, frame type, and padding rules of the FD-CAN frame according to the target frame format parameters; S603. Based on the target modulation parameters and the forward error correction coding parameters, perform channel coding and signal modulation on the audio composite data stream to be transmitted to generate a baseband data stream; S604. Based on the filling rules and the baseband data stream, construct a data link layer frame structure conforming to the FD-CAN protocol, and complete the encapsulation of the FD-CAN frame to obtain an encapsulated FD-CAN frame. S605. Convert the encapsulated FD-CAN frame into a physical signal according to the target modulation parameters, and send the physical signal through the FD-CAN bus.

[0050] As described in steps S601-S605 above, the present invention first uses the dynamic transmission strategy index value calculated in the previous step to query a predefined, optimized strategy-parameter mapping table. This table contains the specific parameters that FD-CAN transmission should use under different strategy indices.

[0051] For example, index 0 (low complexity, high quality channel) is mapped as follows: data field length 64 bytes, modulation method is high-speed NRZ (non-return-to-zero code), and forward error correction (FEC) coding rate is 4 / 5; while index 5 (high complexity, low quality channel) is mapped as follows: data field length 16 bytes, modulation method is robust PWM (pulse width modulation), and FEC coding rate is 1 / 2.

[0052] Then, based on the target frame format parameters obtained from the lookup table, determine the data field payload length (e.g., 8, 16, 32 or 64 bytes), frame type (e.g., standard frame or extended frame), and bit stuffing rules (e.g., inserting an inverted phase after every 5 consecutive identical bits) of the current FD-CAN frame.

[0053] Next, the original audio PCM data is processed using the target modulation method and FEC parameters: first, FEC encoding is performed to add redundancy check information; then, channel modulation is performed to map the digital bit stream into a physical symbol sequence suitable for bus transmission, generating a baseband data stream.

[0054] Then, according to the FD-CAN protocol specification, the frame header (including ID, control bits, etc.), baseband data stream, and cyclic redundancy check (CRC) code are assembled into a complete data link layer frame according to the padding rules.

[0055] Finally, the physical layer transceiver of the FD-CAN controller converts the encapsulated FD-CAN frame into a differential voltage signal according to the target modulation method, and drives the bus to transmit.

[0056] In this way, the system can select the most suitable combination of physical layer and data link layer parameters in real time during each transmission cycle, based on the current dynamically changing audio content, bus status, and service requirements, thus achieving truly adaptive and intelligent audio composite data stream transmission.

[0057] like Figure 2 As shown, this application also provides an FD-CAN bus audio composite data stream transmission system based on multimodal parameter coupling, used to perform the above method. The system includes: The multimodal parameter acquisition module is used to acquire real-time multimodal parameters of the FD-CAN bus audio composite data stream, wherein the real-time multimodal parameters include audio content feature parameters, bus physical feature parameters, and service quality constraint parameters. The audio dynamic complexity analysis module is used to obtain the audio instantaneous energy parameter and the audio spectrum flatness parameter based on the audio content feature parameters, and to obtain the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectrum flatness parameter. The bus transmission quality assessment module is used to obtain the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and to obtain the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter. The dynamic scheduling priority calculation module is used to obtain the maximum allowable transmission delay parameter based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and to obtain the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient. The strategy index generation module is used to construct a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient, and to perform principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector, and to calculate the dynamic transmission strategy index value based on the main coupling feature vector; The transmission module is used to obtain the transmission mode according to the dynamic transmission strategy index value, encapsulate the audio composite data stream into FD-CAN frames according to the transmission mode, and send them through the FD-CAN bus.

[0058] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of an FD-CAN bus audio composite data stream transmission method.

[0059] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of an FD-CAN bus audio composite data stream transmission method.

[0060] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0061] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for transmitting audio composite data streams via FD-CAN bus, characterized in that, include: The real-time multimodal parameters of the FD-CAN bus audio composite data stream are obtained, wherein the real-time multimodal parameters include audio content feature parameters, bus physical feature parameters, and quality of service constraint parameters. The audio instantaneous energy parameter and audio spectral flatness parameter are obtained based on the audio content feature parameters, and the audio dynamic complexity coefficient is obtained based on the audio instantaneous energy parameter and the audio spectral flatness parameter. The bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter are obtained based on the bus physical characteristic parameters, and the bus transmission quality coefficient is obtained based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter. The maximum allowable transmission delay parameter is obtained based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and the dynamic scheduling priority coefficient is obtained based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient. A time-frequency-space multimodal coupling matrix is ​​constructed based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient. Principal component analysis is performed on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector. The dynamic transmission strategy index value is calculated based on the main coupling feature vector. The transmission method is obtained according to the dynamic transmission strategy index value, and the audio composite data stream is encapsulated into FD-CAN frames and sent through the FD-CAN bus according to the transmission method.

2. The FD-CAN bus audio composite data stream transmission method according to claim 1, characterized in that, The steps of obtaining the audio instantaneous energy parameter and the audio spectral flatness parameter based on the audio content feature parameters, and obtaining the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectral flatness parameter, include: Based on the audio content feature parameters, obtain an audio signal sample sequence within a preset time window; The audio instantaneous energy parameter is calculated based on the audio signal sample sequence, and the audio spectral flatness parameter is calculated based on the frequency domain representation of the audio signal sample sequence. Obtain the average instantaneous energy parameter and average spectral flatness parameter of historical normal audio signals; The first energy change rate is obtained based on the instantaneous audio energy parameter and the average instantaneous energy parameter, and the spectral offset is obtained based on the audio spectral flatness parameter and the average spectral flatness parameter. The audio dynamic range fluctuation coefficient is obtained based on the first energy change rate and the spectral offset. Obtain the signal category weight factor from the audio content feature parameters, and correct the audio dynamic range fluctuation coefficient according to the signal category weight factor to obtain the audio dynamic complexity coefficient.

3. The FD-CAN bus audio composite data stream transmission method according to claim 1, characterized in that, The steps of obtaining the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and obtaining the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter, include: The bus occupancy time and total bus time within the current sampling period are obtained based on the bus physical characteristic parameters, and the bus instantaneous load rate parameter is calculated based on the bus occupancy time and total bus time. Obtain the signal power and noise power of the bus physical characteristic parameters in the current sampling period, and calculate the bus signal-to-noise ratio parameter based on the signal power and the noise power; Obtain the baseline load rate parameter and baseline signal-to-noise ratio parameter of the bus under historical normal transmission conditions; The load deviation is obtained based on the bus instantaneous load rate parameter and the reference load rate parameter, and the signal-to-noise ratio gain is obtained based on the bus signal-to-noise ratio parameter and the reference signal-to-noise ratio parameter. The comprehensive evaluation value of the channel state is obtained based on the load deviation and the signal-to-noise ratio gain. Obtain the channel coherence bandwidth parameter from the bus physical characteristic parameters, and normalize the channel state comprehensive evaluation value based on the channel coherence bandwidth parameter to obtain the bus transmission quality coefficient.

4. The FD-CAN bus audio composite data stream transmission method according to claim 1, characterized in that, The steps of obtaining the maximum allowable transmission delay parameter based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and obtaining the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient, include: Obtain the maximum permissible end-to-end latency and maximum permissible jitter of the audio data stream from the aforementioned quality of service constraint parameters; Based on the bus signal-to-noise ratio parameters and the preset signal-to-noise ratio-delay tolerance mapping relationship, obtain the delay tolerance correction factor under the current signal-to-noise ratio condition; The maximum allowable transmission delay parameter is calculated based on the maximum allowable end-to-end delay, the maximum allowable jitter, and the delay tolerance correction factor. Obtain the estimated transmission time of the current data frame, and obtain the initial transmission urgency based on the maximum allowable transmission delay parameter and the estimated transmission time; The initial transmission urgency is corrected based on the bus transmission quality coefficient to obtain a standardized transmission urgency. The importance weight of the audio data stream is obtained from the quality of service constraint parameters, and the standardized transmission urgency is calculated based on the importance weight to obtain the dynamic scheduling priority coefficient.

5. The FD-CAN bus audio composite data stream transmission method according to claim 1, characterized in that, The steps of constructing a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient, performing principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector, and calculating the dynamic transmission strategy index value based on the main coupling feature vector include: The audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient are used as core feature dimensions, and extended feature parameters related to each core feature dimension in the time domain, frequency domain, and spatial domain are obtained. Based on the core feature dimensions and the extended feature parameters, a time-frequency-space multimodal coupling matrix is ​​constructed, with rows corresponding to different sampling times and columns corresponding to different feature dimensions. Principal component analysis is performed on the time-frequency-space multimodal coupling matrix to extract the top K principal components whose cumulative contribution rate exceeds a preset threshold, and the feature vectors of these K principal components are used as the principal coupling feature vectors. Obtain the feature value corresponding to each of the principal coupling feature vectors, and calculate the contribution rate weight of each principal component based on the feature value; The weighted contribution rate is calculated based on the projection value of the main coupling feature vector at the current sampling time and its corresponding contribution rate weight; Obtain the historical weighted contribution rate sum corresponding to the historical best transmission strategy, obtain the strategy deviation degree based on the current weighted contribution rate sum and the historical weighted contribution rate sum, and calculate the dynamic transmission strategy index value in combination with the preset strategy mapping table.

6. The FD-CAN bus audio composite data stream transmission method according to claim 1, characterized in that, The steps of obtaining the transmission mode according to the dynamic transmission strategy index value, encapsulating the audio composite data stream into an FD-CAN frame according to the transmission mode, and transmitting it through the FD-CAN bus include: The target frame format parameters, target modulation method parameters, and forward error correction coding parameters are obtained by querying the predefined strategy-parameter mapping table based on the dynamic transmission strategy index value. Based on the target frame format parameters, determine the data field length, frame type, and padding rules of the FD-CAN frame; Based on the target modulation parameters and the forward error correction coding parameters, channel coding and signal modulation are performed on the audio composite data stream to be transmitted to generate a baseband data stream; Based on the filling rules and the baseband data stream, a data link layer frame structure conforming to the FD-CAN protocol is constructed, and the FD-CAN frame is encapsulated to obtain an encapsulated FD-CAN frame. The encapsulated FD-CAN frame is converted into a physical signal according to the target modulation parameters, and the physical signal is transmitted through the FD-CAN bus.

7. An FD-CAN bus audio composite data stream transmission system, characterized in that, include: The multimodal parameter acquisition module is used to acquire real-time multimodal parameters of the FD-CAN bus audio composite data stream, wherein the real-time multimodal parameters include audio content feature parameters, bus physical feature parameters, and service quality constraint parameters. The audio dynamic complexity analysis module is used to obtain the audio instantaneous energy parameter and the audio spectrum flatness parameter based on the audio content feature parameters, and to obtain the audio dynamic complexity coefficient based on the audio instantaneous energy parameter and the audio spectrum flatness parameter. The bus transmission quality assessment module is used to obtain the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter based on the bus physical characteristic parameters, and to obtain the bus transmission quality coefficient based on the bus instantaneous load rate parameter and the bus signal-to-noise ratio parameter. The dynamic scheduling priority calculation module is used to obtain the maximum allowable transmission delay parameter based on the service quality constraint parameter and the bus signal-to-noise ratio parameter, and to obtain the dynamic scheduling priority coefficient based on the maximum allowable transmission delay parameter and the bus transmission quality coefficient. The strategy index generation module is used to construct a time-frequency-space multimodal coupling matrix based on the audio dynamic complexity coefficient, the bus transmission quality coefficient, and the dynamic scheduling priority coefficient, and to perform principal component analysis on the time-frequency-space multimodal coupling matrix to extract the main coupling feature vector, and to calculate the dynamic transmission strategy index value based on the main coupling feature vector; The transmission module is used to obtain the transmission mode according to the dynamic transmission strategy index value, encapsulate the audio composite data stream into FD-CAN frames according to the transmission mode, and send them through the FD-CAN bus.

8. The FD-CAN bus audio composite data stream transmission system according to claim 7, characterized in that, The audio dynamic complexity analysis module includes: An audio sample extraction unit is used to obtain an audio signal sample sequence within a preset time window based on the audio content feature parameters. The first calculation unit is used to calculate the audio instantaneous energy parameter based on the audio signal sample sequence, and to calculate the audio spectral flatness parameter based on the frequency domain representation of the audio signal sample sequence. The second acquisition unit is used to acquire the average instantaneous energy parameter and average spectral flatness parameter of historical normal audio signals; The historical reference parameter acquisition unit is used to obtain a first energy change rate based on the audio instantaneous energy parameter and the average instantaneous energy parameter, and to obtain a spectral offset based on the audio spectral flatness parameter and the average spectral flatness parameter. A fluctuation coefficient generation unit is used to obtain the audio dynamic range fluctuation coefficient based on the first energy change rate and the spectral offset. The correction unit is used to obtain the signal category weight factor in the audio content feature parameters, and correct the audio dynamic range fluctuation coefficient according to the signal category weight factor to obtain the audio dynamic complexity coefficient.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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