A method for correcting AM demodulated waveforms

Abstract

This invention discloses an AM demodulation waveform correction algorithm, relating to the field of signal processing technology. The algorithm performs envelope detection processing on the subcarrier received by the antenna; low-pass filtering on the detected signal; inputting the low-pass filtered signal into a comparator circuit for binary encoding conversion; in the case of signal distortion, acquiring signal data through AD sampling to obtain AD sampling data, which includes several AD sampling values ​​for several level time periods; and performing data analysis on the AD sampling data to obtain level thresholds and enhanced level representation values ​​for each level time period. By calculating the enhanced level representation values ​​and determining thresholds for the distorted waveform, this invention effectively reduces the impact of noise and interference, ensuring accurate signal recovery even under poor signal quality conditions, and improving the stability and reliability of the system in complex environments.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, specifically to a method for correcting AM demodulated waveforms. Background Technology

[0002] AM signals are very common in daily life. Common applications such as NFC and high-frequency RFID use AM demodulation technology. AM demodulation is the process of restoring the modulated AM signal to the original baseband signal. The recovered signal is Manchester encoded. Manchester encoding is a commonly used encoding method in digital signal processing. It is a self-synchronizing encoding method proposed by the University of Manchester. It uses the transition edges of the signal to represent the logical value of the data. Manchester encoding has error detection capabilities and does not require clock synchronization, so it is widely used in Ethernet, wireless transmission and other fields.

[0003] Manchester encoding has a simple encoding rule: each symbol is represented by two level signals with different phases, which is a square wave of one cycle. However, the phases of the 0 and 1 symbols are exactly opposite. The 0 and 1 symbols can be defined as a 0->1 transition or a 1->0 transition. The detection device can detect the transition edge as a clock signal, so Manchester encoding does not require a separate clock signal.

[0004] The communication between the high-frequency RFID tag and the reader uses Manchester encoding. According to the ISO15693 standard, the carrier frequency fc between the VICC and VCD is 13.56MHz. The VICC transmits data to the VCD through load modulation, and the load wave is generated by the VICC switching the load. The amplitude of the load modulation is at least greater than 10mV. The first bit of the VCD communication message selects whether to use one or two subcarriers. The VICC supports two modes. When using one subcarrier, the subcarrier load modulation frequency fs1 is fc / 32 (423.75KHz). When using two subcarriers, the frequencies fs1 is fc / 32 (423.75KHz) and fs2 is fc / 28 (428.28KHz).

[0005] The load wave modulation used by VICC generates a very weak load wave signal. Generally, it requires detection, amplification, filtering, and comparison circuits to reconstruct the Manchester-coded waveform carrying VICC data. In practical applications, the distortion of the Manchester-coded waveform is related to many factors, such as the distance between the tag and the antenna, the surrounding environment of the antenna, and various parameters of the hardware circuit. These factors can not only cause waveform distortion, but may even cause the waveform to be submerged in noise, making it impossible to identify the Manchester-coded information. When multiple tags collide or the distance between the tag and the antenna changes, the amplitude of the demodulated waveform will also change. Therefore, to parse the Manchester-coded information, it is necessary to reconstruct the Manchester waveform without distortion and then use a processor to demodulate the waveform. Using traditional hardware circuits for demodulation is not only complex and difficult to debug parameters, but also makes it difficult to ensure the consistency of circuit parameters during mass production. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a method for correcting AM demodulation waveforms, which solves the problem of Manchester encoding demodulation difficulties caused by signal distortion, environmental interference, and inconsistent hardware parameters in existing technologies.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for correcting AM demodulated waveforms, comprising the following steps: envelope detection processing of the subcarrier received by the antenna to obtain a preliminary demodulated waveform; low-pass filtering of the detected signal to obtain an approximate square wave shape; inputting the low-pass filtered signal into a comparator circuit for binary encoding conversion; acquiring signal data through AD sampling under signal distortion conditions to obtain AD sampling data, wherein the AD sampling data includes several AD sampling values ​​for several level time periods; performing data analysis on the AD sampling data to obtain a level threshold and an enhanced level representation value for each level time period; determining the high and low levels of the AD sampling data based on the level threshold and determining the level state of each time period according to the determination result; comparing and analyzing the enhanced level representation value for each level time period with a preset level reference value, and correcting the distorted waveform according to the comparison result.

[0008] Furthermore, when acquiring signal data through AD sampling, data sampling is performed within a fixed time interval.

[0009] Further, the specific steps to obtain the level threshold are as follows: by performing mean analysis on each AD sample value of each level time period, the average AD sample value of each level time period is obtained; by performing descending order analysis on the average AD sample value of each level time period, the average AD sample value sequence is obtained, and the median of the average AD sample value sequence is taken as the level threshold.

[0010] Furthermore, the specific steps to obtain the enhanced level representation value for each level period are as follows: compare and analyze each AD sample value for each level period to obtain the maximum and minimum AD sample values ​​for each level period; perform comprehensive analysis on the maximum and minimum AD sample values ​​for each level period to obtain the enhanced level representation value for each level period.

[0011] Furthermore, the specific formula for calculating the enhanced level representation value for each level period is as follows: ;in, For the first The enhancement level representation value for each level period. For the first The maximum value of AD sampling in each level time period, For the first Minimum value of AD sampling for each level period The scaling factor stored in the database.

[0012] The present invention has the following beneficial effects:

[0013] (1) The method for correcting AM demodulation waveforms can effectively reduce the impact of noise and interference by calculating the enhanced level representation value and threshold judgment of the distorted waveform, ensuring accurate signal recovery even when the signal quality is poor, and improving the stability and reliability of the system in complex environments.

[0014] (2) The AM demodulation waveform correction method can accurately determine the high and low levels in the signal by performing data analysis and waveform correction for each level period, ensuring that the information transmission during the signal demodulation process is not affected by waveform distortion, thereby ensuring accurate signal recovery.

[0015] (3) The AM demodulation waveform correction method adopts an adaptive method to dynamically adjust the threshold and enhancement level representation value based on the sampled data and preset reference value, so that it can automatically optimize the processing according to different signal conditions, thereby improving the adaptability and robustness of the method in various environments.

[0016] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for AM demodulation waveform correction according to the present invention.

[0018] Figure 2 This is a schematic diagram of SOF in an AM demodulation waveform correction method according to the present invention.

[0019] Figure 3This is a schematic diagram of logic 0 in an AM demodulation waveform correction method of the present invention.

[0020] Figure 4 This is a schematic diagram of logic 1 in an AM demodulation waveform correction method of the present invention.

[0021] Figure 5 This is a schematic diagram of the EOF in an AM demodulation waveform correction method of the present invention.

[0022] Figure 6 This is a schematic diagram of the Manchester waveform in an AM demodulation waveform correction method of the present invention.

[0023] Figure 7 This is a schematic diagram of a Manchester waveform that causes distortion in an AM demodulation waveform correction method according to the present invention.

[0024] Figure 8 This is a schematic diagram of array N in an AM demodulation waveform correction method of the present invention.

[0025] Figure 9 This is a schematic diagram showing the tag being 10cm away from the antenna in an AM demodulation waveform correction method according to the present invention.

[0026] Figure 10 This is a schematic diagram showing the tag being 20cm away from the antenna in an AM demodulation waveform correction method according to the present invention.

[0027] Figure 11 This is a schematic diagram showing the tag being 30cm away from the antenna in an AM demodulation waveform correction method according to the present invention.

[0028] Figure 12 This is a schematic diagram illustrating the relationship between RSSI and Q in an AM demodulation waveform correction method according to the present invention.

[0029] Figure 13 This is a schematic diagram of the reference value when the tag is 10cm away from the antenna in an AM demodulation waveform correction method according to the present invention.

[0030] Figure 14 This is a schematic diagram of the reference value when the tag is 20cm away from the antenna in an AM demodulation waveform correction method of the present invention.

[0031] Figure 15 This is a schematic diagram of the reference value when the tag is 30cm away from the antenna in an AM demodulation waveform correction method according to the present invention.

[0032] Figure 16 This is a schematic diagram of logic data D in an AM demodulation waveform correction method according to the present invention. Detailed Implementation

[0033] The problem addressed in this application's embodiments can be summarized as follows:

[0034] By performing envelope detection and low-pass filtering on the received subcarrier signal, the signal is extracted and smoothed. Then, data is acquired and analyzed through AD sampling. In the case of signal distortion, the average sampling value and the enhanced level representation value of each level period are calculated. Combined with the level threshold, the high and low levels of the signal are judged. By comparing with the preset reference value, the distorted waveform is corrected and the original signal is restored. This method effectively improves the anti-interference ability of the signal and ensures the accurate decoding and recovery of the signal.

[0035] Please see Figure 1 This invention provides a technical solution: a method for correcting AM demodulated waveforms, comprising the following steps: envelope detection processing of the subcarrier received by the antenna to obtain a preliminary demodulated waveform; low-pass filtering processing of the detected signal to obtain an approximate square wave shape; inputting the low-pass filtered signal into a comparator circuit for binary encoding conversion; acquiring signal data through AD sampling under signal distortion conditions to obtain AD sampling data, wherein the AD sampling data includes several AD sampling values ​​for several level time periods; performing data analysis on the AD sampling data to obtain level thresholds and enhanced level representation values ​​for each level time period; determining high and low levels of the AD sampling data based on the level thresholds, and determining the level state of each time period according to the determination results; comparing and analyzing the enhanced level representation values ​​for each level time period with preset level reference values, and correcting the distorted waveform according to the comparison results.

[0036] When acquiring signal data through AD sampling, data sampling is performed at fixed time intervals.

[0037] Specifically, the steps to obtain the level threshold are as follows: by performing mean analysis on each AD sample value for each level time period, the average AD sample value for each level time period is obtained; by performing descending order analysis on the average AD sample value for each level time period, the average AD sample value sequence is obtained, and the median of the average AD sample value sequence is taken as the level threshold.

[0038] In this process, after the VCD sends a read command to the VICC, the VICC begins to transmit data. When the VICC starts sending an 8-bit SOF, the MCU begins to sample the RSSI signal, performs Kalman filtering on the sampled data to obtain the RSSI signal value of the current transmitted data frame, and then uses the RSSI value returned by the VICC in real time to input the data. Figure 12The formula determines the Q value of the current VICC, further yielding the binary data of the frame. Due to distance and environmental factors, the RSSI values ​​of different VICCs vary. Therefore, this method also includes pre-calibrating the relationship between the RSSI values ​​returned by VICCs at different distances under the same environment and the high / low level thresholds Q, such as... Figure 12 As shown, the functional expressions for Q and RSSI can be obtained through polynomial fitting.

[0039] In this implementation scheme, mean analysis is performed on the AD sampling values ​​for each level period. This reduces the impact of individual outliers on level judgment. Since AD ​​sampling values ​​may be affected by noise interference, the mean method can smooth the sampling data and eliminate the instability caused by instantaneous fluctuations, thus providing a more stable reference value to judge the signal level state. By sorting the mean sequence in descending order and selecting the median as the level threshold, this approach can effectively resist the interference of noise and outlier data. The median itself is not sensitive to extreme values ​​(such as noise interference points). Compared with directly using the average value, it can more accurately reflect the typical value of most effective data, making the level threshold more reliable. Especially in the case of large noise interference, the median can effectively eliminate the influence of outlier sampling values ​​on the final level judgment. The median as a threshold is more robust than the mean. Especially when there are irregular fluctuations or interference in the sampling data, the median can effectively avoid abnormal high or low values ​​from affecting the overall judgment, thereby improving the accuracy of signal recovery. In this way, it is possible to more accurately determine whether the signal is high or low level, improving the accuracy of the signal demodulation process.

[0040] Specifically, the steps to obtain the enhanced level representation value for each level period are as follows: compare and analyze each AD sample value for each level period to obtain the maximum and minimum AD sample values ​​for each level period; perform comprehensive analysis on the maximum and minimum AD sample values ​​for each level period to obtain the enhanced level representation value for each level period.

[0041] The specific formula for calculating the enhanced level representation value for each level period is as follows: ;in, For the first The enhancement level representation value for each level period. For the first The maximum value of AD sampling in each level time period, For the first Minimum value of AD sampling for each level period The scaling factor stored in the database.

[0042] In this implementation scheme, by comparing the maximum and minimum values ​​of the AD sampling for each level period, the dynamic range of the signal can be effectively extracted. This process helps to reveal the amplitude of level changes, more accurately reflecting the signal strength and changes, and thus better distinguishing different levels. Comprehensive analysis of the maximum and minimum values ​​enhances signal contrast, highlighting the difference between high and low levels in the signal, making subsequent high / low level judgments more accurate. In real-world signals, instantaneous fluctuations often occur due to noise or signal instability. Relying solely on data from a single sampling point may be affected by these fluctuations. However, by calculating the maximum and minimum values, the fluctuation range of the level can be taken into account, thereby reducing the interference of a single abnormal sampling value on level judgment. Especially in cases of weak signals or significant noise interference, the enhanced level representation can effectively filter out irrelevant noise information. By introducing a scaling factor, the calculation results of the maximum and minimum values ​​can be further adjusted, allowing the enhanced level representation to be tailored to actual needs. By adjusting the scaling factor based on scenarios, the scaling factor can dynamically optimize calculations for different signal conditions and noise environments based on empirical values ​​stored in the database or actual test data. This improves the adaptability and calculation accuracy of the level representation value. In this way, the enhanced level representation value can not only more accurately reflect the true level state of the signal, but also respond more subtly to minute signal changes, which helps in the accurate recovery and demodulation of the signal. This method can more realistically reflect the fluctuation range and amplitude of the signal than simple mean or median analysis. Especially when the signal fluctuates drastically, the enhanced level representation value can more effectively adapt to various signal changes through comprehensive analysis of the maximum and minimum values, ensuring accurate signal judgment even in unstable or highly interfered environments. By calculating the enhanced level representation value, the contrast of the signal can be improved, especially when the difference between different levels is small or the signal is weak. The enhanced level representation value makes the signal level more prominent, helping the subsequent demodulation stage to more accurately restore the original data.

[0043] The following is a specific implementation example of the AM demodulation waveform correction method:

[0044] First, the detection circuit performs envelope detection on the subcarrier on the antenna. After processing, the signal is amplified and connected to the AD sampling port of the MCU. Since the communication between VCD and VICC is simplex, AD sampling is performed after VCD sends a message to VICC, and the sampled data is demodulated.

[0045] According to the ISO 15693 standard, the frame format returned by VICC consists of SOF + data field + EOF, such as... Figure 2-5 As shown.

[0046] When the tag is close to the antenna, after processing by the detection circuit and low-pass filter circuit, an approximate square wave waveform can be obtained, such as... Figure 6 As shown, the waveform can be converted into a binary code of logic 0 or 1 by the comparator circuit, and then the hexadecimal data can be obtained according to the corresponding protocol rules in the ISO15693 standard.

[0047] When the tag is far from the antenna and there is noise, the waveform obtained after processing by the detection circuit and low-pass filter is distorted. The waveform may fluctuate multiple times within one symbol period. In this case, if a comparator circuit is used, the corresponding binary code cannot be determined. Figure 7 As shown:

[0048] When the waveform starts to distort, the comparator circuit cannot accurately reproduce the data returned by VICC, so the distorted waveform needs to be corrected first.

[0049] First, the Manchester waveform is sampled using an analog-to-digital converter (ADC). Assuming the sampling array is M, according to ISO 15693, the time period for one symbol (logic 0 or logic 1) is 37.76µs, with each high and low level occupying 18.88µs. Assuming n ADC values ​​are sampled for each level, according to ISO 15693, when obtaining the RFID tag UID, VICC returns a total of 208 high and low level values, requiring the collection of 208*n ADC values. Next, the current level is determined to be high or low based on the data collected for each level segment. A common method is to calculate the average of the current data and then use the median of the average as the threshold for high and low levels. Assuming four data segments are collected as Data1-Data4, where Data1 and Data3 are high-level data, and Data2 and Data4 are low-level data, as shown in Table 1.

[0050] Table 1. Examples of collected AD value data

[0051] Data1 1317 1343 1379 1369 1320 1303 1339 1373 1383 1391 1401 1348 Data2 1271 1253 1253 1059 1025 1029 1077 1200 1195 1148 1175 1251 Data3 1318 1363 1376 1364 1284 1165 1267 1315 1349 1372 1320 1291 Data4 1073 1179 1173 1153 1024 878 979 878 935 1006 1091 1145

[0052] Calculate the average value of each data segment (Data1) avr =(Data1[0]+Data1[1]+…+Data1

[11] ) / 12; Similarly, Data2 can be derived. avr Data3 avr Data4 avr Then, use the averaging method to calculate the high and low level thresholds (Data). avr_ref =((Data1 avr +Data3 avr ) / 2+(Data2 avr +Data4 avr ) / 2) / 2; Calculate Data based on the data in Table 1avr_ref =1218.75, this threshold is similar to Data2 avr The difference is 57. If the amplitude of this data group is large, it will lead to misjudgment of the data level of this segment.

[0053] Using this method, the maximum and minimum AD values ​​within each level time period are found, then the average of the maximum and minimum values ​​is calculated, and then the average is squared to increase the AD difference between the high and low levels, thus obtaining a new representation value N for that level. j The formula is as follows: N j =(max(M 0-n )+min(M 0-n ))2 / ) 2 / k.

[0054] Let k=1000, and use the formula above to calculate the representation value of each data segment, Data1. N =1825.5、Data2 N =1302.8、Data3 N =1603、Data4 N =1035.1, then use the averaging method to calculate the threshold Data for high and low levels. maxmin_ref =((Data1 N +Data3 N ) / 2+(Data2 N +Data4 N ) / 2) / 2=1441.6; Compared with Data1N-Data4N, the minimum difference of this threshold is 137, which is more resistant to interference than the averaging method;

[0055] In the above formula, k represents the scaling factor. Using the same method, a new array N of 208 high and low level representation values ​​is obtained, and its value chart is shown below. Figure 8 As shown.

[0056] Compare the elements in array N with the reference value Qi. If Ni > Qi, it is a logic 1; otherwise, it is a logic 0. Then, combine the elements into hexadecimal data according to the ISO15693 protocol to obtain the UID information returned by VICC.

[0057] Because the data N changes with the distance between the tag and the antenna, such as Figure 9-11 As shown.

[0058] Therefore, different reference values ​​need to be set for different distances; the AD value of the RSSI signal strength indication corresponding to the tag's distance from the antenna is collected from 0-50cm away from the antenna, and the relationship between the tag's distance from the antenna and the reference value Qi is obtained through polynomial fitting, such as... Figure 12-16 As shown.

[0059] Qi=a*RSSIi 4 +b*RSSI i 3 +c*RSSI i 2 +d*RSSI i +e;

[0060] By comparing the sizes of corresponding elements in arrays N and Q, the logic values ​​0 or 1 corresponding to the high and low levels can be determined and stored in data D;

[0061] According to ISO 15693, the binary representation of SOF is 00011101B, the binary representation of EOF is 10111000B, the binary representation of logic 0 is 10B, and the binary representation of logic 1 is 01B. By iterating through and comparing array D, the UID information of the tag can be obtained.

[0062] In summary, this application has at least the following effects:

[0063] By calculating the enhanced level representation value and thresholding the distorted waveform, the method can effectively reduce the impact of noise and interference, ensure accurate signal recovery even under poor signal quality, and improve the stability and reliability of the system in complex environments.

[0064] By performing data analysis and waveform correction on each level period, the method can accurately determine the high and low levels in the signal, ensuring that information transmission during signal demodulation is not affected by waveform distortion, thereby guaranteeing accurate signal recovery.

[0065] By adopting an adaptive method, the threshold and enhanced level representation value are dynamically adjusted based on the sampled data and preset reference values, enabling the method to automatically optimize the processing according to different signal conditions, thereby improving the adaptability and robustness of the method in various environments.

[0066] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0067] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for AM demodulation waveform correction, characterized by, The method comprises the following steps: The subcarriers received by the antenna are subjected to envelope detection processing; The detected signal is subjected to low-pass filtering processing; The low-pass filtered signal is input into a comparator circuit for binary coding conversion; In the case of signal distortion, the signal is subjected to data acquisition by AD sampling to obtain AD sampling data, the AD sampling data comprising a plurality of AD sampling values of a plurality of level periods; The AD sampling data is subjected to data analysis to obtain a level threshold value and an enhanced level representation value of each level period; The AD sampling data is subjected to high-low level judgment based on the level threshold value, and the level state of each period is determined according to the judgment result; The enhanced level representation value of each level period is compared and analyzed with a preset level reference value, and the distorted waveform is corrected according to the comparison result; The specific steps of obtaining the level threshold value are as follows: The AD sampling average value of each level period is obtained by mean analysis of each AD sampling value of each level period; The AD sampling average value of each level period is subjected to descending analysis to obtain an AD sampling average sequence, and the median of the AD sampling average sequence is taken as the level threshold value; After the VCD sends a read command to the VICC, the VICC starts to return data, and when the VICC starts to send 8-bit SOF, the MCU starts to sample the RSSI signal, and the RSSI signal value of the current return data frame is obtained by Kalman filtering of the sampling data, the MCU determines the Q value of the current VICC by checking the RSSI value returned by the VICC in real time, and obtains the binary data of the data frame; The method further comprises calibrating the relationship between the RSSI value returned by the VICC at different distances in the same environment and the high-low level threshold Q in advance, and obtaining the function formula of Q and RSSI by polynomial fitting; The specific steps of obtaining the enhanced level representation value of each level period are as follows: Each AD sampling value of each level period is compared and analyzed to obtain the AD sampling maximum value and the AD sampling minimum value of each level period; The AD sampling maximum value and the AD sampling minimum value of each level period are subjected to comprehensive analysis to obtain the enhanced level representation value of each level period; The specific formula for calculating the enhanced level representation value of each level period is as follows: ； wherein, is the enhanced level representation value for the nth level period, is the AD sample maximum value for the nth level period, is the AD sample minimum value for the nth level period, is the AD sample maximum value for the nth level period, is the AD sample minimum value for the nth level period, is the AD sample minimum value for the nth level period, is the scaling factor stored in the database.

2. The method for AM demodulation waveform correction according to claim 1, wherein, When the signal is subjected to data acquisition by AD sampling, data sampling is performed within a fixed time interval.

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