Preamble code detection method, system and device based on segmented dynamic time regularization

Abstract

The present invention relates to a preamble code detection method, system and device based on segmented dynamic time warping. The method adopts a sliding window method to segment signals, controls the detector switch in real time according to the signal and preamble code detection conditions in the window, calculates the normalized dynamic time warping distance segment by segment, finds the best matching segment of the preamble code in the window and compares it with the set threshold, can effectively detect the existence of the preamble code in the window, and accurately locate the position of the preamble code, thereby reducing the false alarm rate and improving the operation efficiency. Finally, a higher detection rate and a lower false alarm rate are achieved when the frequency deviation is large and the signal is distorted, so as to achieve the purpose of efficiently realizing the accurate detection of the preamble code in the backscatter communication under complex background.

Description

Technical Field

[0001] The present invention belongs to the field of Internet of Things communication technology, and relates to a preamble code detection method, system and device based on segmented dynamic time regularization. Background Art

[0002] With the popularity of applications such as wearable devices, smart homes and smart cities, hundreds of billions of devices are connected to the Internet of Things, and their access needs are becoming increasingly difficult to meet, mainly manifested in insufficient reliable access, high costs and battery dependence. Passive Internet of Things technology has become a research hotspot because it supports massive devices, low costs and does not require battery power; zero-power communication can meet new needs through energy harvesting, backscatter communication and ultra-low power computing, and is expected to become the next generation of Internet of Things technology. Among them, backscatter communication uses the received RF signal as a carrier, and modulates the information onto the reflected carrier by adjusting the impedance or baseband signal frequency to perform wireless communication. Its advantage is that it does not need to generate a carrier by itself, avoiding high-power modules, and making the node power consumption as low as μW (microwatt) level, which is suitable for ultra-low power transmission. The radio frequency identification (RFID) system is a typical backscatter communication application system.

[0003] Due to the limited energy of RFID chips, the clock generation circuit usually uses a simple relaxation oscillator, which leads to large clock frequency errors. For example, in some RFID chips, the maximum error can reach 17% when the clock frequency is 1.60MHz. In addition, node motion, background changes and multi-node interference in backscatter communication can cause signal distortion. These problems bring great challenges to receiver design, and simple cross-correlation algorithms can no longer meet the detection requirements of preamble codes in backscatter communication under complex backgrounds. Summary of the invention

[0004] In response to the problems existing in the above-mentioned traditional methods, the present invention proposes a preamble code detection method based on segmented dynamic time regularization, a preamble code detection system based on segmented dynamic time regularization, and a computer device, which can efficiently realize accurate detection of preamble codes in backscatter communications under complex backgrounds.

[0005] In order to achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0006] On the one hand, a preamble detection method based on segmented dynamic time warping is provided, comprising the steps of:

[0007] Obtain the signal to be detected;

[0008] Use a sliding window to intercept the signal to be detected and obtain the signal in the current window;

[0009] Predict whether the signal in the current window contains a scattered signal according to the baseline pass rate, and adjust the detector switch of the current window in combination with the signal prediction result of the previous window;

[0010] If the detector switch of the current window is turned on, the minimum normalized dynamic time warping distance of the signal in the current window is calculated by the SDTW algorithm; otherwise, the sliding window is used to intercept the next segment of the signal to be detected;

[0011] If the minimum normalized dynamic time warping distance is less than the set distance threshold, it is determined that there is a preamble code in the signal in the current window and the detector switch is turned off, otherwise it is determined that there is no preamble code in the signal in the current window.

[0012] In one embodiment, the process of calculating the minimum normalized dynamic time warping distance of the signal in the current window by the SDTW algorithm includes the steps of:

[0013] Perform data preprocessing on the signal in the current window;

[0014] According to the number of level flips of the signal in the current window, the preprocessed signal in the current window is segmented to generate multiple signal segments;

[0015] Generate a preamble template corresponding to each signal segment respectively, and use the DTW algorithm to calculate the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one;

[0016] The minimum normalized dynamic time warping distance value is selected as the minimum normalized dynamic time warping distance output.

[0017] In one of the embodiments, in the process of calculating the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one using the DTW algorithm, a curved window around the main diagonal is introduced as a calculation constraint.

[0018] On the other hand, a preamble code detection system based on segmented dynamic time warping is also provided, including:

[0019] A signal acquisition module, used for acquiring a signal to be detected;

[0020] A sliding window module is used to intercept the signal to be detected by using a sliding window to obtain the signal in the current window;

[0021] The detection judgment module is used to predict whether the signal in the current window contains a scattered signal according to the baseline pass rate, and adjust the detector switch of the current window in combination with the signal prediction result of the previous window;

[0022] The distance calculation module is used to calculate the minimum normalized dynamic time warping distance of the signal in the current window by using the SDTW algorithm when the detector switch of the current window is turned on; otherwise, the sliding window is used to intercept the next segment of the signal to be detected;

[0023] The preamble determination module is used to determine whether there is a preamble code in the signal in the current window and turn off the detector switch when the minimum normalized dynamic time warping distance is less than the set distance threshold, otherwise it is determined that there is no preamble code in the signal in the current window.

[0024] In one of the embodiments, the distance calculation module is used to perform data preprocessing on the signal in the current window during the process of calculating the minimum normalized dynamic time warping distance of the signal in the current window through the SDTW algorithm. The preprocessed signal in the current window is segmented according to the number of level flips of the signal in the current window to generate multiple signal segments, and a preamble code template corresponding to each signal segment is generated respectively. The normalized dynamic time warping distance value between each signal segment and the corresponding preamble code template is calculated one by one using the DTW algorithm, and the minimum normalized dynamic time warping distance value is selected as the minimum normalized dynamic time warping distance output.

[0025] In one of the embodiments, in the process of calculating the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one using the DTW algorithm, a curved window around the main diagonal is introduced as a calculation constraint.

[0026] On the other hand, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned preamble code detection method based on segmented dynamic time regularization are implemented.

[0027] One of the above technical solutions has the following advantages and beneficial effects:

[0028] The above-mentioned preamble detection method, system and device based on segmented dynamic time warping, after obtaining the signal to be detected, uses a sliding window to judge in real time whether there is a scattered signal in the signal in the window, combines the preamble detection situation and the signal prediction result of the preceding window, and turns on the detector switch for detection if certain judgment conditions are met, that is, the minimum normalized dynamic time warping distance of the signal in the window is calculated by the SDTW algorithm and then compared with the set distance threshold, and finally determines whether there is a preamble in the signal in the window according to the comparison result. Compared with the traditional technology, the signal is segmented by a sliding window, and the detector switch is controlled in real time according to the signal in the window and the preamble detection situation. By calculating the normalized dynamic time warping distance segment by segment, the best matching segment of the preamble in the window is found and compared with the set threshold, the existence of the preamble in the window can be effectively detected, and the position of the preamble can be accurately located, thereby reducing the false alarm rate and improving the operation efficiency. Finally, a high detection rate and a low false alarm rate are achieved when the frequency deviation is large and the signal is distorted, so as to achieve the purpose of accurately detecting the preamble in the backscatter communication under complex background. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the conventional technology, the drawings required for use in the embodiments or the conventional technology descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 It is the principle diagram of the backscatter system;

[0031] Figure 2 1 is a schematic diagram of the FM0 preamble format in an embodiment, wherein (a) is the FM0 preamble (TR ext =0 b ), (b) is the FM0 preamble code (TR ext =1 b );

[0032] Figure 3 1 is a flow chart of a preamble code detection method based on segmented dynamic time warping in one embodiment;

[0033] Figure 4 A schematic diagram of the overall preamble identification process in one embodiment;

[0034] Figure 5 Schematic diagram of the flow of the SDTW algorithm in one embodiment;

[0035] Figure 6Schematic diagram of signal amplitude in one embodiment, wherein (a) is amplitude translation, and (b) is amplitude expansion;

[0036] Figure 7 Schematic diagram of a preamble code detection result in an embodiment, wherein (a) is a signal sequence, (b) is a sliding window signal, (c) is a schematic diagram of an original comparison signal, and (d) is a DTW detection result;

[0037] Figure 8 The detection ROC performance curve of the SDTW algorithm in a conventional condition data set in one embodiment;

[0038] Fig. 9 The detection ROC performance curve of the SDTW algorithm in an extreme condition data set in one embodiment;

[0039] Fig.10 The module structure block diagram of a preamble code detection system based on segmented dynamic time warping in one embodiment. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and Examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0041] It should be noted that the reference to "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The presentation of this phrase at various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It will be appreciated by those skilled in the art that the embodiments described herein may be combined with other embodiments. The term "and / or" used in the specification of the present invention and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0042] The following will describe the implementation of the present invention in detail with reference to the accompanying drawings in the embodiment diagram of the present invention.

[0043] The principle of the backscatter system is as follows Figure 1 As shown, the scattering node receives the externally transmitted sinusoidal signal and adjusts the impedance ( Z 1 and Z2) to send information. When a signal 1 needs to be sent, the impedance is adjusted to equal resistance and opposite reactance, and the carrier is completely reflected; when a signal 0 needs to be sent, the impedance is precisely matched, the carrier is absorbed, and there is no reflection. After the receiver receives the reflected signal, it distinguishes between 0 and 1 through envelope detection and demodulation, and decodes and restores the information.

[0044] In actual backscatter systems, scatter nodes usually use FM0 to encode baseband data and send response data frames in different formats as needed. In order to wake up the receiver and synchronize the scatter node and the receiver, the data frame header usually contains a group of bits as a preamble. Figure 2 One of the sequences shown, determined by the specific parameters in the inventory command, Figure 2 (a) is the FM0 preamble (TR ext =0 b ), (b) is the FM0 preamble code (TR ext =1 b ), V is a symbol that does not conform to the FM0 encoding rules.

[0045] The actual receiver needs to perform preamble detection on the mixed signal to confirm the existence of the scattered signal, and then perform subsequent detection, demodulation and decoding. Therefore, the matching algorithm of the preamble directly affects the sensitivity of the receiver.

[0046] The received scattered signal is affected by many factors, such as the distance between the scattering node and the receiver, the motion state of the scattering node and the environmental electromagnetic interference, which will affect the waveform characteristics. In addition, the operating temperature and process parameters will also affect the signal quality of the relaxation oscillator, resulting in frequency errors.

[0047] Experiments show that scattered signals show different waveforms with different transmission distances. According to the RSSI (Received Signal Strength Indication) value, they can be divided into rectangular waves, sine waves or triangular waves, and some waveforms will collapse abnormally. Therefore, the simple cross-correlation algorithm cannot adapt to the preamble matching under the diversified waveforms and frequency deviation problems.

[0048] In order to solve the problem of abnormal preamble detection caused by signal distortion, the design adopted is: refer to the number of flip levels to segment the signal in the window, calculate the normalized DTW (Dynamic Time Warping) distance (NDTW) segment by segment, find the best matching segment of the preamble in the window and compare it with the set threshold, which can effectively detect the existence of the preamble in the window and accurately locate the position of the preamble. This design achieves a high detection rate and a low false alarm rate when the frequency deviation is large and the signal is distorted, providing an effective solution for the system's preamble detection in complex backgrounds.

[0049] In one embodiment, Figure 3 As shown, a preamble detection method based on segmented dynamic time warping (SDTW) is provided, which may include the following processing steps S10 to S18:

[0050] S10, obtaining a signal to be detected;

[0051] S12, using a sliding window to intercept the signal to be detected to obtain the signal in the current window;

[0052] S14, predicting whether the signal in the current window contains a scattered signal according to the baseline pass rate, and adjusting the detector switch of the current window in combination with the signal prediction result of the previous window; wherein, the signal prediction result is true = the current window contains a scattered signal ≠ the detector switch is turned on, therefore, the purpose of not using the signal prediction result alone to set the detector switch of the window is that: the signal in the window after the preamble code detection is successful is still a scattered signal containing information, and at this time the signal prediction result is still true, but there is no need to perform the preamble code detection;

[0053] S16, if the detector switch of the current window is turned on, the minimum normalized dynamic time warping distance of the signal in the current window is calculated by the SDTW algorithm; otherwise, the next segment of the signal to be detected is intercepted by a sliding window;

[0054] S18, if the minimum normalized dynamic time warping distance is less than the set distance threshold, it is determined that there is a preamble code in the signal in the current window and the detector switch is turned off, otherwise it is determined that there is no preamble code in the signal in the current window.

[0055] It is understandable that Figure 4 As shown, it is a more specific schematic diagram of the preamble detection process in this embodiment. In the preamble detection process, after obtaining the signal to be detected, segmented calculation and detection will be performed by sliding window. The calculation and detection process is the same for each signal in the window. Therefore, taking the signal in the current window currently intercepted as an example, firstly, it is predicted whether the signal in the window contains a scattered signal according to the baseline pass rate, and the detector (the functional module corresponding to the process part of the SDTW algorithm for judging whether the preamble exists) is adjusted in combination with the signal prediction result of the previous window. When the detector is turned on, the SDTW algorithm is introduced into the signal in the current window and the normalized DTW distance NDTW is used as an indicator to retrieve the part of the signal in the current window that best matches its template, and record the best NDTW value (that is, the minimum normalized dynamic time warping distance).

[0056] Among them, the baseline pass rate is the number of times the signal in the current window crosses the baseline. For the scattered signal under FM0 coding, under ideal conditions, the baseline pass rate of the signal in the window with a length of n times the code width is at least n (i.e., n 1s) and at most 2n (i.e., n 0s). Compared with the scattered signal containing information, the baseline pass rate of the noise signal will be much greater than 2n. Therefore, in order to prevent the non-ideal baseline pass rate caused by frequency deviation, signal distortion and noise superposition, the lower limit of the baseline pass rate can be set to 0.8n and the upper limit can be set to 4n accordingly in the prediction stage.

[0057] Finally, by comparing the optimal NDTW value with the set distance threshold, it is determined whether there is a preamble in the window. The distance threshold can be set according to the empirical value, or it can be adjusted more finely according to the actual effect in the actual application, as long as the NDTW value can be used to accurately determine whether the preamble exists. In this way, by real-time judgment and adjustment of the detector switch, false alarms can be effectively reduced and the accuracy and efficiency of preamble detection can be improved. In general, by locally finding the optimal alignment of two sequences and quantifying the similarity of the two sequences, different waveforms and frequency offsets can be processed more accurately and robustly, providing reliable preamble identification.

[0058] The above-mentioned preamble detection method based on segmented dynamic time warping, after obtaining the signal to be detected, uses a sliding window to judge in real time whether there is a scattered signal in the signal in the window, combines the preamble detection situation and the signal prediction result of the preceding window, and turns on the detector switch for detection if certain judgment conditions are met, that is, the minimum normalized dynamic time warping distance of the signal in the window is calculated by the SDTW algorithm and then compared with the set distance threshold, and finally determines whether there is a preamble in the signal in the window according to the comparison result. Compared with the traditional technology, the signal is segmented by a sliding window, and the detector switch is controlled in real time according to the signal in the window and the preamble detection situation. By calculating the normalized dynamic time warping distance segment by segment, the best matching segment of the preamble in the window is found and compared with the set threshold, the existence of the preamble in the window can be effectively detected, and the position of the preamble can be accurately located, thereby reducing the false alarm rate and improving the operation efficiency. Finally, a high detection rate and a low false alarm rate are achieved when the frequency offset is large and the signal is distorted, so as to achieve the purpose of accurately detecting the preamble in the backscatter communication under complex background.

[0059] In one embodiment, regarding the above step S16, the process of calculating the minimum normalized dynamic time warping distance of the signal in the current window by using the SDTW algorithm may specifically include the following steps:

[0060] Perform data preprocessing on the signal in the current window;

[0061] According to the number of level flips of the signal in the current window, the preprocessed signal in the current window is segmented to generate multiple signal segments;

[0062] Generate a preamble template corresponding to each signal segment respectively, and use the DTW algorithm to calculate the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one;

[0063] The minimum normalized dynamic time warping distance value is selected as the minimum normalized dynamic time warping distance output.

[0064] Specifically, Figure 5 As shown in the figure, it is a flowchart of the SDTW algorithm. The SDTW algorithm performs the following processing steps on the signal in the window. First, data preprocessing is performed to remove the interference of amplitude translation and amplitude expansion; then the preprocessed signal is segmented according to the number of flips to generate multiple signal segments; then a corresponding preamble template is generated for each signal segment, and the DTW algorithm is used to calculate the NDTW value between each signal segment and its corresponding template one by one; SNDTW represents the minimum normalized dynamic time warping distance of the previous signal segment. Finally, the smallest NDTW value (NDTW min ) and its corresponding signal segment as the best NDTW value matching result within the window.

[0065] Since the intensity of the backscattered signal is affected by factors such as distance, equipment, and environment, the Euclidean distance is easily affected by amplitude translation and amplitude expansion, such as Figure 6 The signal amplitude diagram shown in the figure, where (a) is amplitude translation and (b) is amplitude expansion. t Indicates time, X In order to eliminate the above potential influences, the data in the window needs to be standardized during data preprocessing, and the horizontal baseline is adjusted to zero and the amplitude is adjusted to unit amplitude.

[0066] In the signal segmentation and preamble template generation stage, the traditional SDTW algorithm usually evenly slides the segments on the query sequence based on the constraint parameters. Considering the characteristics of the preamble, the sequence start and end points of the preamble must be located at the position where the high and low levels of the signal in the window are flipped. In this embodiment, the preamble under FM0 coding contains 10 flip levels, so ten consecutive flip levels in the window are intercepted each time the slide is performed. According to the result of each signal segmentation, the code element width is estimated to generate a preamble template of the same length as the segmentation sequence (i.e., the signal segment).

[0067] Dynamic Time Warping (DTW) is an algorithm for comparing the similarity of two time series. It quantifies the similarity between the two sequences by finding the optimal alignment between them. For a given two sequences , , and define its distance matrix as D ,in, Represents a point in a sequence and The distance between N Representation sequence X The total number of sampling points, M Representation sequence Y The total number of sampling points, this embodiment uses the Euclidean distance metric, that is, The cumulative distance matrix is ​​calculated by the following recursive formula C , and finally obtained Cumulative distance for the optimal alignment of the two sequences above.

[0068] (1)

[0069] In one embodiment, in the process of calculating the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one using the DTW algorithm, a curved window around the main diagonal (Sakoe-Chiba) is introduced as a calculation constraint.

[0070] It can be understood that, without adding constraints, on the one hand, unconstrained dynamic time warping needs to calculate the complete cumulative distance matrix, resulting in a large amount of computation; on the other hand, considering the main characteristics of the pulse width 0 / 1 signal, for two segments of high and low level inversion times, even if they represent different binary array information, they will produce extremely high similarity after optimal alignment. Therefore, the Sakoe-Chiba curved window is introduced to prevent misjudgment caused by over-distorted matching and reduce the amount of computation at the same time.

[0071] The optimal alignment between two sequences can be obtained using the time warping function Description, where , and They represent the first k coordinates, under the Sakoe-Chiba constraint, requiring In this embodiment, define , Codewidth Indicates code width.

[0072] When other conditions are the same, a longer sequence will result in a larger DTW distance. In order to solve the problem of sequence length differences caused by sampling rate, backscattering frequency and matching results, NDTW is used to measure the degree of matching.

[0073] (2)

[0074] in, KIndicates the current optimal alignment path W The logarithm of the midpoint. Figure 7 The figure shows the preamble matching result of a single experiment, (a) is the signal sequence, (b) is the sliding window signal, (c) is the original comparison signal, (d) is the DTW detection result, the ordinate is the signal amplitude (volts), and the abscissa is the frequency (Hz). In the case of waveform distortion and frequency deviation problems in the signal, the preamble detection method based on segmented dynamic time warping can still successfully detect and accurately locate.

[0075] In some embodiments, in order to verify the effectiveness of the above-mentioned preamble detection method based on segmented dynamic time warping (also known as the SDTW algorithm), a reader was used to conduct experimental tests under various conditions. The test conditions include different backscatter communication frequencies, different tag materials, different temperatures, different distances between the tag and the reader, and scattered signals at different angles. Under these conditions, a total of 906 preambles were detected.

[0076] In extreme environments such as 640K backscatter communication frequency, anti-metal tags, high temperature, long-distance and large-angle communication, the backscatter signal has a large frequency deviation and abnormal waveform collapse. According to the degree of interference to the preamble code, two data sets are constructed: the normal condition data set and the extreme condition data set. The normal condition data set contains 666 preamble codes, and the extreme condition data set contains 240 preamble codes. By setting different setting thresholds, the receiver operating characteristic (ROC) curves are drawn respectively, such as Figure 8 and Fig. 9 shown.

[0077] Experimental results show that the preamble detection method based on segmented dynamic time warping exhibits excellent preamble detection performance under both normal and extreme conditions. It can significantly reduce the false alarm rate while maintaining a high detection rate, verifying the reliability and robustness of the preamble detection method based on segmented dynamic time warping in complex environments.

[0078] It should be understood that although Figure 3 The steps in the flowchart are shown in sequence as indicated by the arrows, but the steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of the steps, and the steps can be executed in other orders. Moreover, Figure 3 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0079] In one embodiment, Fig.10 As shown, a preamble detection system 100 based on segmented dynamic time warping is also provided, including a signal acquisition module 11, a sliding window module 13, a detection judgment module 15, a distance calculation module 17 and a preamble determination module 19. Among them, the signal acquisition module 11 is used to obtain the signal to be detected. The sliding window module 13 is used to intercept the signal to be detected using a sliding window to obtain the signal in the current window. The detection judgment module 15 is used to predict whether the signal in the current window contains a scattered signal according to the baseline pass rate, and adjust the detector switch of the current window in combination with the signal prediction result of the previous window. The distance calculation module 17 is used to calculate the minimum normalized dynamic time warping distance of the signal in the current window by the SDTW algorithm when the detector switch of the current window is turned on; otherwise, the sliding window is used to intercept the next segment of the signal to be detected. The preamble determination module 19 is used to determine that the signal in the current window has a preamble and turn off the detector switch when the minimum normalized dynamic time warping distance is less than the set distance threshold, otherwise it is determined that the signal in the current window does not have a preamble.

[0080] The above-mentioned preamble code detection system 100 based on segmented dynamic time warping, after obtaining the signal to be detected, uses a sliding window to determine in real time whether there is a scattered signal in the signal in the window, combines the preamble code detection situation and the signal prejudgment result of the preceding window, and turns on the detector switch for detection if a certain judgment condition is met, that is, the minimum normalized dynamic time warping distance of the signal in the window is calculated by the SDTW algorithm and then compared with the set distance threshold, and finally determines whether there is a preamble code in the signal in the window according to the comparison result. Compared with the traditional technology, the signal is segmented by a sliding window, and the detector switch is controlled in real time according to the signal in the window and the preamble code detection situation. By calculating the normalized dynamic time warping distance segment by segment, the best matching segment of the preamble code in the window is found and compared with the set threshold, the existence of the preamble code in the window can be effectively detected, and the position of the preamble code can be accurately located, thereby reducing the false alarm rate and improving the operation efficiency. Finally, a higher detection rate and a lower false alarm rate are achieved when the frequency deviation is large and the signal is distorted, so as to achieve the purpose of accurately detecting the preamble code in the backscatter communication under complex background.

[0081] In one embodiment, the distance calculation module 17 is used to perform data preprocessing on the signal in the current window during the process of calculating the minimum normalized dynamic time warping distance of the signal in the current window through the SDTW algorithm. According to the number of level flips of the signal in the current window, the preprocessed signal in the current window is segmented to generate multiple signal segments, and a preamble code template corresponding to each signal segment is generated respectively. The normalized dynamic time warping distance value between each signal segment and the corresponding preamble code template is calculated one by one using the DTW algorithm, and the minimum normalized dynamic time warping distance value is selected as the minimum normalized dynamic time warping distance output.

[0082] In one embodiment, in the process of calculating the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one using the DTW algorithm, a curved window around the main diagonal is introduced as a calculation constraint.

[0083] For the specific limitations of the preamble detection system 100 based on segmented dynamic time regularization, please refer to the limitations of the preamble detection method based on segmented dynamic time regularization above, which will not be repeated here. The various modules in the above-mentioned preamble detection system 100 based on segmented dynamic time regularization can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0084] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor implementing the following processing steps when executing the computer program: obtaining a signal to be detected; using a sliding window to intercept the signal to be detected to obtain a signal in a current window; predicting whether the signal in the current window contains a scattered signal based on a baseline pass rate, and adjusting the detector switch of the current window in combination with the signal prediction result of the previous window; if the detector switch of the current window is turned on, calculating the minimum normalized dynamic time warping distance of the signal in the current window through the SDTW algorithm; otherwise, using a sliding window to intercept the next segment of the signal to be detected; if the minimum normalized dynamic time warping distance is less than a set distance threshold, determining that a preamble code exists in the signal in the current window, otherwise determining that a preamble code does not exist in the signal in the current window.

[0085] It can be understood that the above-mentioned computer device, in addition to the memory and processor mentioned above, may also include other software and hardware components not listed in this specification. The specific components can be determined according to the model of the communication device in the specific backscatter system under different application scenarios, and this specification will not list them one by one in detail.

[0086] In one embodiment, when the processor executes the computer program, it can also implement the steps or sub-steps added in each embodiment of the above-mentioned preamble code detection method based on segmented dynamic time warping.

[0087] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program implements the following processing steps when executed by a processor: obtaining a signal to be detected; using a sliding window to intercept the signal to be detected to obtain a signal in a current window; predicting whether the signal in the current window contains a scattered signal based on a baseline pass rate, and adjusting the detector switch of the current window in combination with the signal prediction result of the previous window; if the detector switch of the current window is turned on, calculating the minimum normalized dynamic time warping distance of the signal in the current window through the SDTW algorithm; otherwise, using a sliding window to intercept the next segment of the signal to be detected; if the minimum normalized dynamic time warping distance is less than a set distance threshold, determining that a preamble code exists in the signal in the current window, otherwise determining that a preamble code does not exist in the signal in the current window.

[0088] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus dynamic random access memory (RambusDRAM, referred to as RDRAM) and interface dynamic random access memory (DRDRAM).

[0089] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of protection of the invention. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the attached claims.

Claims

1. A preamble detection method based on segmented dynamic time warping, characterized in that: Includes steps: Obtain the signal to be detected; Adopting a sliding window to intercept the signal to be detected to obtain a signal in a current window; Predict whether the signal in the current window contains a scattered signal according to the baseline pass rate, and adjust the detector switch of the current window in combination with the signal prediction result of the previous window; If the detector switch of the current window is turned on, the minimum normalized dynamic time warping distance of the signal in the current window is calculated by the SDTW algorithm; Otherwise, a sliding window is used to intercept the next segment of the signal to be detected; If the minimum normalized dynamic time warping distance is less than the set distance threshold, it is determined that a preamble code exists in the signal in the current window and the detector switch is turned off; otherwise, it is determined that no preamble code exists in the signal in the current window; The process of calculating the minimum normalized dynamic time warping distance of the signal in the current window by the SDTW algorithm includes the following steps: Performing data preprocessing on the signal in the current window; According to the number of level flips of the signal in the current window, segmenting the preprocessed signal in the current window to generate a plurality of signal segments; Generate a preamble template corresponding to each signal segment respectively, and use the DTW algorithm to calculate the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one; Selecting the minimum normalized dynamic time warping distance value as the minimum normalized dynamic time warping distance output; In the process of calculating the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one using the DTW algorithm, a curved window around the main diagonal is introduced as a calculation constraint.

2. A preamble detection system based on segmented dynamic time warping, characterized in that: include: A signal acquisition module, used for acquiring a signal to be detected; A sliding window module, used for intercepting the signal to be detected by using a sliding window to obtain a signal in a current window; The detection judgment module is used to predict whether the signal in the current window contains a scattered signal according to the baseline pass rate, and adjust the detector switch of the current window in combination with the signal prediction result of the previous window; A distance calculation module, used to calculate the minimum normalized dynamic time warping distance of the signal in the current window by using the SDTW algorithm when the detector switch of the current window is turned on; Otherwise, a sliding window is used to intercept the next segment of the signal to be detected; A preamble determination module, used to determine that a preamble code exists in the signal in the current window and turn off the detector switch when the minimum normalized dynamic time warping distance is less than a set distance threshold, otherwise determine that a preamble code does not exist in the signal in the current window; Among them, the distance calculation module is used to perform data preprocessing on the signal in the current window during the process of calculating the minimum normalized dynamic time warping distance of the signal in the current window through the SDTW algorithm, and segment the preprocessed signal in the current window according to the number of level flips of the signal in the current window to generate multiple signal segments, and respectively generate a preamble code template corresponding to each signal segment, and use the DTW algorithm to calculate the normalized dynamic time warping distance value between each signal segment and the corresponding preamble code template one by one, and select the minimum normalized dynamic time warping distance value as the minimum normalized dynamic time warping distance output; In the process of calculating the normalized dynamic time warping distance value between each signal segment and the corresponding preamble template one by one using the DTW algorithm, a curved window around the main diagonal is introduced as a calculation constraint.

3. 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, the steps of the preamble code detection method based on segmented dynamic time warping according to claim 1 are implemented.

Images