IQ data packet anomaly detection method, device, equipment and storage medium

Abstract

The present application relates to the field of wireless signal processing technology, and in particular to an IQ data packet anomaly detection method, device, equipment and storage medium, wherein the method comprises: collecting data from an IQ data packet based on a preset sampling data structure to obtain an IQ sample; determining whether the number of samples of the IQ sample is a preset number of samples, and the preset number of samples is preset based on the sampling data structure; if so, obtaining the sample value of the IQ sample, and determining whether the sample value exceeds a preset value range; if so, determining that the IQ data packet is abnormal. The present application facilitates the AOA base station to output normal electronic price tag location information.

Description

Technical Field

[0001] The present application relates to the field of wireless signal processing technology, and in particular to an IQ data packet anomaly detection method, device, equipment and storage medium. Background Art

[0002] In the process of digital upgrading and transformation of large supermarkets, electronic price tags will be used to replace traditional paper price tags. Electronic price tags can not only display the content displayed on paper price tags, but also can be used for fast picking, out-of-stock management, fast inventory and human-computer interaction. Electronic price tags can send IQ (In-phase and quadrature) data packets to the preset AOA base station, so that the AOA base station can obtain the location information of the corresponding electronic price tag based on the IQ data packet.

[0003] However, the antenna array of the AOA base station deployed in large supermarkets has a series of non-ideal factors, such as the tilt of the sub-board plane where the antenna array is located and the complexity of the deployment environment itself. The above imperfect factors will cause IQ data packets to be abnormal, thereby causing the AOA base station to output abnormal electronic price tag location information. For this reason, the AOA base station needs to perform anomaly detection on the received data packets. Summary of the invention

[0004] In order to facilitate the AOA base station to output normal electronic price tag location information, the present application provides an IQ data packet anomaly detection method, device, equipment and storage medium.

[0005] In a first aspect, the present application provides an IQ data packet anomaly detection method, comprising:

[0006] Based on a preset sampling data structure, data is collected on the IQ data packet to obtain an IQ sample point;

[0007] Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure;

[0008] If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range;

[0009] If so, it is determined that the IQ data packet is abnormal.

[0010] In a second aspect, the present application provides an IQ data packet anomaly detection device, comprising:

[0011] A sampling point sampling module is used to collect data from IQ data packets based on a preset sampling data structure to obtain IQ samples;

[0012] A quantity determination module, used to determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure;

[0013] a value judgment module, configured to obtain a sample value of the IQ sample point and judge whether the sample value exceeds a preset value range;

[0014] The abnormality determination module is used to determine that the IQ data packet is abnormal.

[0015] In a third aspect, the present application provides a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps in the above method when executing the computer program.

[0016] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the steps in the above method when executed by a processor.

[0017] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0018] The above-mentioned IQ data packet anomaly detection method, device, equipment and storage medium obtain IQ samples by collecting data from IQ data packets based on a preset sampling data structure; determine whether the number of samples of the IQ samples is a preset number of samples, and the preset number of samples is preset based on the sampling data structure; if so, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range; if so, determine that the IQ data packet is abnormal. Through the above implementation, after obtaining the IQ data packet sent by the electronic price tag, the anomaly detection of the IQ data packet can be achieved by sampling and judging the IQ data packet, so that the AOA base station can exclude abnormal IQ data packets, and then the AOA base station can output normal electronic price tag location information.

[0019] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A flow chart of an IQ data packet anomaly detection method provided in an embodiment of the present application;

[0022] Figure 2 A schematic diagram of a sampling data structure provided in an embodiment of the present application;

[0023] Figure 3 This is a schematic diagram of the structure of a first IQ data packet anomaly detection device provided in an embodiment of the present application;

[0024] Figure 4 This is a structural diagram of a second IQ data packet anomaly detection device provided in an embodiment of the present application;

[0025] Figure 5 This is a schematic diagram of the structure of a third IQ data packet anomaly detection device provided in an embodiment of the present application;

[0026] Figure 6 This is a schematic diagram of the structure of a fourth IQ data packet anomaly detection device provided in an embodiment of the present application;

[0027] Figure 7 A schematic diagram of the structure of a computer device provided in an embodiment of the present application;

[0028] Figure 8 This is a diagram of the internal structure of a computer-readable storage medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present disclosure more clear, the present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and are not used to limit the present disclosure.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this article described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0031] In this article, the term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the related objects before and after are in an "or" relationship.

[0032] Embodiment 1

[0033] Figure 1 A flowchart of an IQ data packet anomaly detection method provided in Example 1 of the present application is provided. Figure 1 The method may be performed by a device for performing the method, and the device may be implemented by software and / or hardware. The method includes:

[0034] S110 , collecting data from an IQ data packet based on a preset sampling data structure to obtain IQ samples.

[0035] Among them, the electronic price tags used in supermarkets can send IQ data packets to the AOA positioning base station, so that the AOA positioning base station obtains the location information of the corresponding electronic price tag according to the IQ data packet; in order to determine whether the IQ data packet is abnormal, the AOA base station needs to sample the IQ data packet to obtain IQ samples, and each IQ sample includes a co-directional signal and an orthogonal signal; the AOA base station can specifically sample the IQ data packet through a preset sampling data structure; exemplarily, the sampling data structure is a CTE (Constant Tone Extension) data structure, and the CTE data structure is as follows Figure 2As shown, the CTE data structure includes, in the order of time slots, a protection period, a reference time slot, and an alternating switching time slot and a sampling time slot, wherein the time slot length of the protection period is 4us, the time slot length of the reference time slot is 8us, the time slot length of the switching time slot is consistent with the time slot length of the sampling time slot, which is 1us or 2us, and the total time slot length of the CTE data structure is 16 to 160us; it should be noted that when collecting samples, 8 IQ samples are collected continuously in the reference time slot, and an IQ sample is collected once in each sampling time slot.

[0036] Specifically, the IQ data packet is continuously sampled 8 times in the reference time slot of the CTE data structure to obtain 8 IQ sample points, and then the IQ sample point is sampled once in each sampling time slot in the CTE data structure to obtain 1 IQ sample point, thereby realizing data collection of the IQ data packet according to the CTE data structure to obtain a certain number of IQ sample points.

[0037] S120: Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0038] Among them, 8 IQ sample points can be collected in the reference time slot of the sampling data structure, and 1 IQ sample point can be collected in each collection time slot of the sampling data structure. Since the total time slot length of the sampling data structure is limited, the number of IQ sample points collected within the total time slot length of the sampling data structure is limited; illustratively, assuming that the total time slot length of the sampling data structure is 16us, and the time slot lengths of the switching time slot and the sampling time slot are both 1us, then within the total time slot length of the sampling data structure, a total of 2 sampling time slots are set, so within the total time slot length of the sampling data structure, a total of 10 IQ sample points can be collected, and the preset number of sample points preset based on the sampling data structure is 10; the preset number of sample points is 10, indicating that 10 IQ sample points can be collected when the IQ data packet is normal, and by comparing the number of IQ sample points actually collected with the preset number of sample points to determine whether the number of IQ sample points is consistent with the preset number of sample points, it is possible to detect whether the IQ data packet is abnormal.

[0039] Specifically, the number of sample points of the collected IQ sample points is counted, and then it is determined whether the number of sample points is consistent with a preset number of sample points, so as to detect whether the IQ data packet is abnormal.

[0040] S130: If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0041] If it is determined that the number of samples is inconsistent with the preset number of samples, it means that the corresponding IQ data packet is abnormal; if it is determined that the number of samples is consistent with the preset number of samples, it means that the corresponding IQ data packet can be preliminarily determined to be normal; it should be noted that the IQ data in the general IQ data packet is integer data and has a specific value range. The sample value of the IQ data is in a specific value range when the IQ data packet is normal. For example, the signed 16-bit short integer data and the corresponding specific value range are (-32768, 32767); for some abnormal IQ data packets, the number of samples sampled may be consistent with the preset number of samples, but the sample value of the IQ data in the abnormal IQ data packet is not in a specific value range. For example, the sample value of an IQ sample collected is 32678, and 32678 is not in the specific value range of (-32768, 32767); therefore, when it is determined that the number of samples is consistent with the preset number of samples, it is necessary to further determine whether the sample value of the collected IQ sample is in the specific value range.

[0042] Specifically, when it is determined that the number of samples is consistent with the preset number of samples, further, a sample value of the collected IQ sample is obtained, and taking the sample value of an IQ sample collected as an example, it is determined whether the sample value of the IQ sample exceeds the corresponding value range.

[0043] S140: If yes, determine that the IQ data packet is abnormal.

[0044] Among them, if it is first determined that the number of sample points is consistent with the preset number of sample points, and it is also determined that the sample point value of at least one IQ sample point collected exceeds the corresponding value range, then it means that the corresponding IQ data packet is extremely likely to be abnormal, and the corresponding IQ data packet can be determined to be abnormal at this time; if it is first determined that the number of sample points is consistent with the preset number of sample points, and it is also determined that the sample point values ​​of the collected IQ sample points do not exceed the corresponding value range, then it means that the corresponding IQ data packet is extremely likely to be normal, and the corresponding IQ data packet can be determined to be normal at this time.

[0045] Specifically, if it is first determined that the number of samples is consistent with the preset number of samples, and it is also determined that the sample value of at least one collected IQ sample exceeds the corresponding value range, then the corresponding IQ data packet is determined to be abnormal.

[0046] It should be noted that this embodiment obtains IQ samples by collecting data from IQ data packets based on a preset sampling data structure; determines whether the number of samples of the IQ samples is a preset number of samples, and the preset number of samples is preset based on the sampling data structure; if so, obtains the sample value of the IQ sample, and determines whether the sample value exceeds a preset value range; if so, determines that the IQ data packet is abnormal. Through the above implementation, after obtaining the IQ data packet sent by the electronic price tag, the abnormality detection of the IQ data packet can be achieved by sampling and judging the IQ data packet, so that the AOA base station can exclude abnormal IQ data packets, and then the AOA base station can output normal electronic price tag location information.

[0047] Embodiment 2

[0048] Embodiment 2 of the present application provides an IQ data packet anomaly detection method, which can be performed by a device that performs the method, and the device can be implemented by software and / or hardware. The method includes:

[0049] S210: Collect data from an IQ data packet based on a preset sampling data structure to obtain IQ samples.

[0050] S220: Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0051] S230: If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0052] S240: If yes, determine that the IQ data packet is abnormal.

[0053] S250: If the sample value does not exceed a preset value range, obtain an IQ sample corresponding to a reference time slot in the sampling data structure to obtain a reference sample group.

[0054] It should be noted that, when it is determined that the number of IQ sample points is the preset number of sample points and the sample value does not exceed the preset value range, the corresponding IQ data packet still has a certain probability of being abnormal, which is specifically manifested in: if the phase difference between adjacent IQ sample points corresponding to the reference time slot collected for an IQ data packet fluctuates greatly, it means that the corresponding IQ data packet is abnormal, so it is necessary to continue to detect whether the IQ data packet is abnormal.

[0055] The IQ sample points corresponding to the reference time slot in the sampling data structure may be the 8 IQ sample points continuously collected in the reference time slot as shown in the first embodiment, and the 8 IQ sample points may be respectively recorded as , , , , , , , , , , , , , , , ; Get the 8 IQ samples to the reference sample group { , ; , ; , , , , , , }.

[0056] Specifically, when it is determined that the sample point value does not exceed the preset value range, the IQ sample point corresponding to the reference time slot in the sampling data structure is further obtained to obtain a reference sample point group.

[0057] S260: Calculate phase differences between adjacent IQ sample points in the reference sample point group, and obtain a fluctuation angle mean based on the phase differences.

[0058] Among them, the above reference sample group { , ; , ; , , , , , , } , is the first IQ sample point, , For the second IQ sample, ... , The eighth IQ sample point, each IQ sample point has its corresponding phase, and the phase difference between adjacent IQ sample points is the phase difference of adjacent IQ sample points in the reference sample point group. Taking the above reference sample point group as an example, the phase difference Δ corresponding to 7 groups of adjacent IQ sample points can be calculated through the eight IQ sample points. It should be noted that In this embodiment, the maximum value of n is 8, where Characterizes the phase of a later IQ sample in a group of adjacent IQ samples. Characterizes the phase of a front IQ sample point in a group of adjacent IQ samples. For example, a group of adjacent IQ samples is { , ; , }, Characterization , The phase of this IQ sample point, Characterization , The phase of this IQ sample.

[0059] The fluctuation angle mean is the mean of the phase differences of multiple adjacent IQ sample points calculated by the reference sample point group. Exemplarily, the fluctuation angle mean is the mean of the angles corresponding to the phase differences of the above 7 adjacent IQ sample points. The fluctuation angle mean is used to reflect the fluctuation of the phase difference between adjacent IQ sample points corresponding to the reference time slot. The fluctuation angle mean can be used to determine whether there is a large fluctuation in the phase difference between adjacent IQ sample points corresponding to the reference time slot, thereby determining whether the corresponding IQ data packet is abnormal.

[0060] Specifically, the phase difference between two adjacent IQ sample points in the reference sample point group is calculated to obtain multiple phase differences, and then the averages of the angles corresponding to the multiple phase differences are calculated to obtain the fluctuation angle average.

[0061] S270: Determine whether the fluctuation angle mean is greater than a preset angle mean threshold.

[0062] Among them, the angle mean threshold is a scale for measuring whether there is a large fluctuation in the phase difference between adjacent IQ sample points corresponding to the reference time slot. If the fluctuation angle mean is greater than the angle mean threshold, it means that the phase difference between adjacent IQ sample points corresponding to the reference time slot has a large fluctuation, which means that the corresponding IQ data packet is abnormal; if the fluctuation angle mean is not greater than the angle mean threshold, it means that there is no large fluctuation in the phase difference between adjacent IQ sample points corresponding to the reference time slot, which means that the corresponding IQ data packet is normal; exemplarily, when the modulation frequency deviation is 250kHz and the transmission rate of the IQ data packet is 1Mbps, the angle mean threshold is .

[0063] Specifically, it is determined whether the fluctuation angle mean is greater than a preset angle mean threshold.

[0064] S280: If yes, determine that the IQ data packet is abnormal.

[0065] Specifically, if it is determined that the fluctuation angle mean is greater than the angle mean threshold, then the corresponding IQ data packet is determined to be abnormal; otherwise, the corresponding IQ data packet is determined to be normal.

[0066] Embodiment 3

[0067] Embodiment 3 of the present application provides an IQ data packet anomaly detection method, which optimizes the "obtaining a fluctuation angle mean based on the phase difference" in Embodiment 2; it should be noted that for the parts not described in detail in this embodiment, reference may be made to the descriptions of other embodiments, and the method includes:

[0068] S310: Collect data from an IQ data packet based on a preset sampling data structure to obtain IQ samples.

[0069] S320: Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0070] S330: If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0071] S340: If yes, determine that the IQ data packet is abnormal.

[0072] S350: If the sample value does not exceed a preset value range, obtain an IQ sample corresponding to a reference time slot in the sampling data structure to obtain a reference sample group.

[0073] S361: Calculate the phase difference between adjacent IQ sample points in the reference sample point group, and perform angle mapping on the phase difference to obtain a fluctuation angle.

[0074] The angle mapping is also the phase difference Δ Mapped to an angle between 0° and 360°; for example, assuming a phase difference Δ is π / 4, which maps to 45° for angles between 0° and 360°.

[0075] Specifically, the phase difference Δ between every two adjacent IQ samples in the reference sample group is calculated. After that, each phase difference Δ The average angle is mapped to the corresponding angle, and this angle is recorded as the fluctuation angle.

[0076] S362, calculating the average of the fluctuation angles to obtain a fluctuation angle mean.

[0077] Among them, the fluctuation angle mean is the mean of multiple fluctuation angles obtained through step S361.

[0078] Specifically, the average of the multiple fluctuation angles obtained by calculation is used to obtain the fluctuation angle mean.

[0079] S370: Determine whether the fluctuation angle mean is greater than a preset angle mean threshold.

[0080] S380: If yes, determine that the IQ data packet is abnormal.

[0081] Embodiment 4

[0082] A method for detecting anomalies in an IQ data packet provided in a fourth embodiment of the present application may be performed by a device for performing the method, and the device may be implemented in software and / or hardware. The method includes:

[0083] S410: Collect data from an IQ data packet based on a preset sampling data structure to obtain IQ samples.

[0084] S420: Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0085] S430: If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0086] S440: If yes, determine that the IQ data packet is abnormal.

[0087] S450: If the sample value does not exceed a preset value range, the IQ sample is processed based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain a plurality of single-round phase difference features.

[0088] It should be noted that, when it is determined that the number of IQ sample points is the preset number of sample points and the sample value does not exceed the preset value range, the corresponding IQ data packet still has a certain probability of being abnormal, which is specifically manifested in: when sampling the IQ data packet, each antenna in the AOA positioning base station is used to collect the IQ sample points corresponding to the corresponding sampling time slot in the sampling data structure. Since the number of antennas in the AOA positioning base station is limited, when there are many corresponding sampling time slots set in the sampling data structure, it is necessary to perform multiple rounds of sampling on the IQ data packet through the antenna in the AOA positioning base station so that the number of IQ sample points collected is the preset number of sample points; it should be noted that if the phase fluctuation between the IQ sample points collected in different rounds is large, it means that the corresponding IQ data packet is abnormal, so it is necessary to continue to detect whether the IQ data packet is abnormal.

[0089] Among them, the collected IQ sample points are processed by sampling the data structure and the number of antennas of the AOA positioning base station to obtain multiple single-round phase difference features. Each round of sampling of the IQ data packet is performed through the antenna in the AOA positioning base station, and the single-round phase difference features corresponding to the multiple IQ sample points obtained by the round of sampling can be subsequently calculated. The single-round phase difference feature is used to reflect the phase difference between two adjacent IQ sample points in the multiple IQ sample points obtained by the corresponding round of sampling.

[0090] Specifically, when it is determined that the sample value does not exceed the preset value range, the collected IQ sample points are further processed according to the sampling data structure and the number of antennas of the AOA positioning base station, so as to obtain multiple single-round phase difference features.

[0091] S460, calculating the difference between the single-round phase difference features to obtain a feature difference matrix.

[0092] The elements in the feature difference matrix are the differences between any two single-round phase difference features among the multiple single-round phase difference features obtained.

[0093] Specifically, the difference between any two single-round phase difference features among the multiple single-round phase difference features is calculated, thereby obtaining multiple differences, and the multiple differences are used as elements of the feature difference matrix to construct a feature difference matrix =[ , … … , … ],in, The number of sampling rounds using the antenna for sampling within the total time slot length corresponding to the sampling data structure.

[0094] S470. Map the characteristic difference matrix based on trigonometric functions to obtain a group of matrix element tangent values.

[0095] Among them, the difference between any two rounds of single-round phase difference features is a phase difference. It should be noted that some phase differences are 0, and some phase differences are 2π. When the phase difference is both 0 and 2π, it is easy to cause a phase flip, thereby adversely affecting the abnormal detection of the IQ data packet; in order to prevent the phase flip from occurring, it is necessary to map each element in the feature difference matrix based on a trigonometric function; mapping each element in the feature difference matrix based on a trigonometric function, that is, calculating the tangent value of each element in the feature difference matrix (the phase difference between any two rounds of single-round phase difference features), the matrix element tangent value group is also the set of tangent values ​​corresponding to each element; the trigonometric functions used in this embodiment include sine function, cosine function and tangent function.

[0096] Specifically, the characteristic difference matrix Abbreviated as [ , … … ], where x=1,2… , y=1,2…… ; With the characteristic difference matrix An element in For example, the element is processed by the sine function Get the corresponding sine value , and also process this element through the cosine function Get the corresponding cosine value , then calculate the sine value and cosine The ratio of the tangent value of the element , the set characteristic difference matrix The tangent value corresponding to each element in is used to obtain the tangent value group of matrix elements.

[0097] S480. Determine the maximum value in the tangent value group of the matrix elements to obtain a target tangent value.

[0098] Among them, the maximum value in the matrix element tangent value group indicates that the phase difference between the corresponding two rounds of single-round phase difference features is the largest among all the phase differences between any two rounds of single-round phase difference features; the target tangent value is also the maximum value in the matrix element tangent value group; if the target tangent value is too large, it means that the phase fluctuation between the IQ samples collected in different rounds is large, which means that the corresponding IQ data packet is abnormal.

[0099] Specifically, determine the maximum value in the tangent value group of the matrix elements and use the maximum value as the target tangent value .

[0100] S490: Determine whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold.

[0101] The fluctuation angle threshold is a measure for measuring whether the target tangent value is too large. By comparing the angle corresponding to the target tangent value with the fluctuation angle threshold, it is possible to determine whether the IQ data packet is abnormal.

[0102] Specifically, the target tangent value is processed by a preset fluctuation angle threshold, thereby determining whether the IQ data packet is abnormal.

[0103] Embodiment 5

[0104] A method for detecting anomalies of an IQ data packet provided in a fifth embodiment of the present application optimizes the "processing the IQ sample points based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain multiple single-round phase difference features" in the fourth embodiment; it should be noted that for the parts not described in detail in this embodiment, reference may be made to the descriptions of other embodiments, and the method includes:

[0105] S510: Collect data from an IQ data packet based on a preset sampling data structure to obtain IQ samples.

[0106] S520: Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0107] S530: If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0108] S540: If yes, determine that the IQ data packet is abnormal.

[0109] S551: If the sample point value does not exceed a preset value range, determine the number of sampling rounds based on the sampling data structure and the number of antennas of the AOA positioning base station.

[0110] The total time slot length corresponding to the sampling data structure is recorded as T, and the number of IQ samples collected within T is for:

[0111] ;

[0112] in, Indicates rounding down. is the number of IQ samples collected in the reference time slot. In this embodiment, =8; 12 in the above formula indicates that the total time slot length of the protection period 4us and the reference time slot 8us in the sampling data structure is 12us, 2 indicates that when the sampling time slot is 1us, the total time slot length of a group of adjacent switching time slots and sampling time slots is 2us, and 4 indicates that when the sampling time slot is 2us, the total time slot length of a group of adjacent switching time slots and sampling time slots is 4us. The IQ sample points collected within T can form the corresponding IQ sample point array In this embodiment, .

[0113] The number of antennas of the AOA positioning base station is recorded as M, and the number of sampling rounds using the antennas for sampling within T is for: .

[0114] Specifically, obtain the total time slot length T corresponding to the sampling data structure, the total time slot length 12us of the protection period and the reference time slot, the total time slot length of a group of adjacent switching time slots and sampling time slots, and the number of IQ samples collected in the reference time slot. ,pass The calculation formula is used to process the acquired data to obtain the number of IQ samples collected within T. .

[0115] S552: Process the IQ samples based on the sampling round number to obtain a plurality of single-round phase difference features.

[0116] Among them, the number of sampling rounds can be used to determine the multiple IQ sample points corresponding to each round of sampling among all the collected IQ sample points. Taking the multiple IQ sample points corresponding to one round of sampling as an example, the phase difference between two adjacent IQ sample points in the multiple IQ sample points corresponding to the round of sampling is calculated, and the phase difference is collected to obtain the single-round phase difference feature

[0117] in, The phase difference between two adjacent IQ samples is =1,……, .

[0118] Specifically, multiple IQ sample points obtained in each round of sampling are determined according to the number of sampling rounds, the phase difference between two adjacent IQ sample points in the multiple IQ sample points corresponding to the round of sampling is calculated, and the phase difference is combined to obtain a single round phase difference feature .

[0119] S560, calculating the difference between the single-round phase difference features to obtain a feature difference matrix;

[0120] S570, mapping the characteristic difference matrix based on trigonometric functions to obtain a matrix element tangent value group;

[0121] S580, determining the maximum value in the tangent value group of the matrix elements to obtain a target tangent value;

[0122] S590: Determine whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold.

[0123] Embodiment 6

[0124] A method for detecting anomalies in an IQ data packet provided in a sixth embodiment of the present application optimizes the method for “determining whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold” in the fourth embodiment; it should be noted that for the parts not described in detail in this embodiment, reference may be made to the descriptions in other embodiments, and the method includes:

[0125] S610: Collect data from an IQ data packet based on a preset sampling data structure to obtain IQ samples.

[0126] S620: Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0127] S630: If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0128] S640: If yes, determine that the IQ data packet is abnormal.

[0129] S650: If the sample value does not exceed a preset value range, the IQ sample is processed based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain a plurality of single-round phase difference features;

[0130] S660, calculating the difference between the single-round phase difference features to obtain a feature difference matrix;

[0131] S670, mapping the characteristic difference matrix based on trigonometric functions to obtain a matrix element tangent value group;

[0132] S680, determining the maximum value in the tangent value group of the matrix elements to obtain a target tangent value;

[0133] S691. Calculate the maximum inter-wheel fluctuation angle based on the target tangent value.

[0134] The target tangent value is processed by the inverse tangent function arctan() The maximum fluctuation angle between wheels can be obtained .

[0135] Specifically, the target tangent value Input to the inverse tangent function arctan() for processing to obtain the maximum fluctuation angle between wheels .

[0136] S692: Determine whether the IQ data packet is abnormal based on the maximum inter-round fluctuation angle and a preset fluctuation angle threshold.

[0137] Among them, the fluctuation angle threshold is used to compare with the maximum fluctuation angle between rounds, so as to determine whether the corresponding IQ data packet is abnormal; illustratively, in this embodiment, the fluctuation angle threshold is 25°; if the maximum fluctuation angle between rounds is greater than the fluctuation angle threshold, it means that the corresponding IQ data packet is abnormal, otherwise, it means that the corresponding IQ data packet is normal.

[0138] Specifically, it is determined whether the maximum fluctuation angle between rounds is greater than the fluctuation angle threshold, so as to determine whether the corresponding IQ data packet is abnormal; if the maximum fluctuation angle between rounds is greater than the fluctuation angle threshold, it means that the corresponding IQ data packet is abnormal, otherwise, it means that the corresponding IQ data packet is normal.

[0139] Embodiment 7

[0140] Embodiment 7 of the present application provides an IQ data packet anomaly detection method, which can be performed by a device that performs the method, and the device can be implemented by software and / or hardware. The method includes:

[0141] 701. Perform data collection on an IQ data packet based on a preset sampling data structure to obtain an IQ sample point.

[0142] 702. Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure.

[0143] 703. If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range.

[0144] 704. If yes, determine that the IQ data packet is abnormal; if no, obtain the IQ sample points corresponding to the reference time slot in the sampling data structure to obtain a reference sample point group.

[0145] 705. Calculate phase differences between adjacent IQ sample points in the reference sample point group, perform angle mapping on the phase differences to obtain fluctuation angles; and calculate average values ​​of the fluctuation angles to obtain a fluctuation angle mean.

[0146] 706. Determine whether the fluctuation angle mean is greater than a preset angle mean threshold.

[0147] 707. If yes, determine that the IQ data packet is abnormal;

[0148] 708. If the sample value does not exceed a preset value range, determine the number of sampling rounds based on the sampling data structure and the number of antennas of the AOA positioning base station; and process the IQ sample points based on the number of sampling rounds to obtain multiple single-round phase difference features.

[0149] 709. Calculate the difference between the single-round phase difference features to obtain a feature difference matrix.

[0150] 710. Map the characteristic difference matrix based on trigonometric functions to obtain a group of tangent values ​​of matrix elements.

[0151] 711. Determine the maximum value in the tangent value group of the matrix elements to obtain a target tangent value.

[0152] 712. Calculate the maximum inter-wheel fluctuation angle based on the target tangent value.

[0153] 713. Determine whether the IQ data packet is abnormal based on the maximum inter-round fluctuation angle and a preset fluctuation angle threshold.

[0154] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0155] Embodiment 8

[0156] Based on the same inventive concept, the eighth embodiment of the present disclosure also provides an IQ data packet anomaly detection device for implementing the above-mentioned IQ data packet anomaly detection method. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above-mentioned method, so the specific limitations in one or more IQ data packet anomaly detection device embodiments provided below can refer to the above-mentioned limitations on the IQ data packet anomaly detection method, and will not be repeated here.

[0157] In this embodiment, Figure 3 As shown, an IQ data packet anomaly detection device is provided, comprising:

[0158] A sampling point sampling module is used to collect data from IQ data packets based on a preset sampling data structure to obtain IQ samples;

[0159] A quantity determination module, used to determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure;

[0160] a value judgment module, configured to obtain a sample value of the IQ sample point and judge whether the sample value exceeds a preset value range;

[0161] The abnormality determination module is used to determine that the IQ data packet is abnormal.

[0162] Each module in the above-mentioned IQ data packet anomaly detection device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0163] It should be noted that this embodiment obtains IQ samples by collecting data from IQ data packets based on a preset sampling data structure; determines whether the number of samples of the IQ samples is a preset number of samples, and the preset number of samples is preset based on the sampling data structure; if so, obtains the sample value of the IQ sample, and determines whether the sample value exceeds a preset value range; if so, determines that the IQ data packet is abnormal. Through the above implementation, after obtaining the IQ data packet sent by the electronic price tag, the abnormality detection of the IQ data packet can be achieved by sampling and judging the IQ data packet, so that the AOA base station can exclude abnormal IQ data packets, and then the AOA base station can output normal electronic price tag location information.

[0164] In one embodiment, referring to Figure 4 , the IQ data packet anomaly detection device described in embodiment 8 further includes:

[0165] A sample group acquisition module, configured to acquire the IQ sample points corresponding to the reference time slot in the sampling data structure to obtain a reference sample group if the sample point value does not exceed a preset value range;

[0166] An angle mean acquisition module, used to calculate the phase difference between adjacent IQ sample points in the reference sample point group, and obtain the fluctuation angle mean based on the phase difference;

[0167] A mean value judgment module is used to judge whether the fluctuation angle mean value is greater than a preset angle mean value threshold value;

[0168] The first abnormality judgment module is used to determine that the IQ data packet is abnormal.

[0169] In one embodiment, the angle mean acquisition module specifically includes:

[0170] An angle mapping unit, used for performing angle mapping on the phase difference to obtain a fluctuation angle;

[0171] The mean value calculation unit is used to calculate the mean value of each fluctuation angle to obtain the fluctuation angle mean value.

[0172] In one embodiment, referring to Figure 5 The IQ data packet anomaly detection device described in Embodiment 8 further includes:

[0173] A sample processing module, configured to process the IQ sample points based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain a plurality of single-round phase difference features if the sample value does not exceed a preset value range;

[0174] A difference calculation module, used for calculating the difference between the single-round phase difference features to obtain a feature difference matrix;

[0175] A matrix mapping module, used for mapping the characteristic difference matrix based on trigonometric functions to obtain a matrix element tangent value group;

[0176] A tangent value determination module, used to determine the maximum value in the tangent value group of the matrix elements to obtain a target tangent value;

[0177] The second abnormality judgment module is used to judge whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold.

[0178] In one embodiment, the sample point processing module specifically includes:

[0179] A round number determination unit, used to determine the number of sampling rounds based on the sampling data structure and the number of antennas of the AOA positioning base station;

[0180] A single-round phase difference feature acquisition unit is used to process the IQ sample points based on the sampling round number to obtain multiple single-round phase difference features.

[0181] In one embodiment, the second abnormality judgment module specifically includes:

[0182] An angle calculation unit, used for calculating the maximum inter-wheel fluctuation angle based on the target tangent value;

[0183] The abnormality judgment unit is used to judge whether the IQ data packet is abnormal based on the maximum fluctuation angle between rounds and a preset fluctuation angle threshold.

[0184] In one embodiment, referring to Figure 6 , provides an IQ data packet anomaly detection device, comprising:

[0185] A sampling point sampling module is used to collect data from IQ data packets based on a preset sampling data structure to obtain IQ samples;

[0186] A quantity determination module, used to determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure;

[0187] a value judgment module, configured to obtain a sample value of the IQ sample point and judge whether the sample value exceeds a preset value range;

[0188] An abnormality determination module, used for determining that the IQ data packet is abnormal;

[0189] A sample group acquisition module, configured to acquire the IQ sample points corresponding to the reference time slot in the sampling data structure to obtain a reference sample group if the sample point value does not exceed a preset value range;

[0190] An angle mean acquisition module, used to calculate the phase difference between adjacent IQ sample points in the reference sample point group, and obtain the fluctuation angle mean based on the phase difference;

[0191] A mean value judgment module is used to judge whether the fluctuation angle mean value is greater than a preset angle mean value threshold value;

[0192] A first abnormality judgment module, configured to judge that the IQ data packet is abnormal;

[0193] A sample processing module, configured to process the IQ sample points based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain a plurality of single-round phase difference features if the sample value does not exceed a preset value range;

[0194] A difference calculation module, used for calculating the difference between the single-round phase difference features to obtain a feature difference matrix;

[0195] A matrix mapping module, used for mapping the characteristic difference matrix based on trigonometric functions to obtain a matrix element tangent value group;

[0196] A tangent value determination module, used for determining the maximum value in the tangent value group of the matrix elements to obtain a target tangent value;

[0197] The second abnormality judgment module is used to judge whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold.

[0198] Embodiment 9

[0199] In the ninth embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an IQ data packet anomaly detection method is implemented.

[0200] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present disclosure, and does not constitute a limitation on the computer device to which the scheme of the present disclosure is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0201] Embodiment 10

[0202] In the tenth embodiment, a computer readable storage medium is provided. Figure 8 As shown, a computer program is stored thereon, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0203] Embodiment 11

[0204] In the eleventh embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0205] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0206] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method 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 the memory, database or other medium used in the embodiments provided by the present disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided by the present disclosure may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided by the present disclosure may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, etc., but are not limited to this.

[0207] 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.

[0208] The above-described embodiments only express several implementation methods of the present disclosure, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present disclosure, and these all belong to the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the attached claims.

Claims

1. A method for detecting anomalies in an IQ data packet, characterized in that: include: Based on a preset sampling data structure, data is collected on the IQ data packet to obtain an IQ sample point; Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure; If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range; If so, determining that the IQ data packet is abnormal; If the sample value does not exceed the preset value range, obtaining the IQ sample corresponding to the reference time slot in the sampling data structure to obtain a reference sample group; Calculating phase differences between adjacent IQ sample points in the reference sample point group, and obtaining a fluctuation angle mean based on the phase differences; Determine whether the fluctuation angle mean is greater than a preset angle mean threshold; If so, it is determined that the IQ data packet is abnormal.

2. The method according to claim 1, characterized in that The obtaining the fluctuation angle mean based on the phase difference comprises: Performing angle mapping on the phase difference to obtain a fluctuation angle; The average of the fluctuation angles is calculated to obtain the fluctuation angle mean.

3. A method for detecting anomalies in an IQ data packet, characterized in that: include: Based on a preset sampling data structure, data is collected on the IQ data packet to obtain an IQ sample point; Determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure; If yes, obtain the sample value of the IQ sample, and determine whether the sample value exceeds a preset value range; If so, determining that the IQ data packet is abnormal; If the sample value does not exceed a preset value range, the IQ sample is processed based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain a plurality of single-round phase difference features; wherein the single-round phase difference feature is a phase difference between two adjacent IQ sample points in the plurality of IQ sample points obtained by the corresponding round sampling; Calculating the difference between the single-round phase difference features to obtain a feature difference matrix; Mapping the characteristic difference matrix based on trigonometric functions to obtain a matrix element tangent value group; Determine the maximum value in the tangent value group of the matrix elements to obtain a target tangent value; Whether the IQ data packet is abnormal is determined based on the target tangent value and a preset fluctuation angle threshold.

4. The method according to claim 3, characterized in that The processing of the IQ sample points based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain multiple single-round phase difference features includes: Determine the number of sampling rounds based on the sampling data structure and the number of antennas of the AOA positioning base station; The IQ samples are processed based on the sampling round number to obtain a plurality of single-round phase difference features.

5. The method according to claim 3, characterized in that: The determining whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold includes: Calculating the maximum inter-wheel fluctuation angle based on the target tangent value; wherein the maximum inter-wheel fluctuation angle is the result obtained by inputting the target tangent value into an inverse tangent function for processing; Whether the IQ data packet is abnormal is determined based on the maximum inter-round fluctuation angle and a preset fluctuation angle threshold.

6. An IQ data packet anomaly detection device, characterized in that: The device comprises: A sampling point sampling module is used to collect data from IQ data packets based on a preset sampling data structure to obtain IQ samples; A quantity determination module, used to determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure; a value judgment module, configured to obtain a sample value of the IQ sample point and judge whether the sample value exceeds a preset value range; An abnormality determination module, used for determining that the IQ data packet is abnormal; A sample group acquisition module, configured to acquire the IQ sample points corresponding to the reference time slot in the sampling data structure to obtain a reference sample group if the sample point value does not exceed a preset value range; An angle mean acquisition module, used to calculate the phase difference between adjacent IQ sample points in the reference sample point group, and obtain the fluctuation angle mean based on the phase difference; A mean value judgment module is used to judge whether the fluctuation angle mean value is greater than a preset angle mean value threshold value; The first abnormality judgment module is used to judge that the IQ data packet is abnormal.

7. An IQ data packet anomaly detection device, characterized in that: The device comprises: A sampling point sampling module is used to collect data from IQ data packets based on a preset sampling data structure to obtain IQ samples; A quantity determination module, used to determine whether the number of samples of the IQ samples is a preset number of samples, where the preset number of samples is preset based on the sampling data structure; a value judgment module, configured to obtain a sample value of the IQ sample point and judge whether the sample value exceeds a preset value range; An abnormality determination module, used for determining that the IQ data packet is abnormal; A sample point processing module, configured to process the IQ sample points based on the sampling data structure and the number of antennas of the AOA positioning base station to obtain a plurality of single-round phase difference features if the sample point value does not exceed a preset value range; wherein the single-round phase difference feature is a phase difference between two adjacent IQ sample points in the plurality of IQ sample points obtained by the corresponding round sampling; A difference calculation module, used for calculating the difference between the single-round phase difference features to obtain a feature difference matrix; A matrix mapping module, used for mapping the characteristic difference matrix based on trigonometric functions to obtain a matrix element tangent value group; A tangent value determination module, used to determine the maximum value in the tangent value group of the matrix elements to obtain a target tangent value; The second abnormality judgment module is used to judge whether the IQ data packet is abnormal based on the target tangent value and a preset fluctuation angle threshold.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 2 or 3 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 or 3 to 5 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 or 3 to 5 are implemented.

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