A contactless object dimensioning method, system, device, and storage medium

Abstract

This invention relates to a non-contact object size measurement method, system, device, and storage medium, comprising the following steps: arranging RF transceiver equipment according to a pre-established relationship model between diffraction signals and moving objects, and measurement accuracy requirements; and processing the diffraction signals acquired by the RF transceiver equipment to obtain the size of the target moving object. This invention demonstrates for the first time that it is possible to accurately measure the size of objects using low-frequency, narrow-bandwidth WiFi signals. By establishing a relationship model between diffraction signals and moving objects, and by extracting the number of singularities in the diffraction signals to measure the object size, an astonishingly high accuracy (i.e., 2.6 mm) can be achieved, with robustness to environmental, material, and speed variations. This invention can be widely applied in the field of measurement technology.

Description

Technical Field

[0001] This invention relates to a non-contact object size measurement method, system, device, and storage medium, and particularly to an object size measurement method, system, device, and storage medium based on a commercial WiFi system, belonging to the field of measurement technology. Background Technology

[0002] Over the past few years, a wide variety of wireless signals, including Wi-Fi, RFID, ultra-wideband, and millimeter waves, have been used for sensing. Among these wireless sensing modes, Wi-Fi sensing has garnered attention due to the widespread availability of Wi-Fi infrastructure. While Wi-Fi sensing has achieved great success in capturing information ranging from coarse-grained target activity (such as gestures) to fine-grained vital signs, the low frequency and limited bandwidth of Wi-Fi signals still make it difficult to accurately obtain target size information. Even millimeter-wave radar can only achieve very coarse-grained measurements. High-precision object size sensing requires the use of high-frequency RF signals (such as terahertz bands). Therefore, utilizing low-frequency Wi-Fi signals to achieve accurate object size measurement is crucial.

[0003] Research into non-contact sensing using wireless technology for imaging began in the late 1970s. In the past few years, various methods, from millimeter-wave radar and terahertz radar to lidar, have been explored for imaging and sizing. The fundamental principle behind sizing is to capture the point cloud of a target and obtain accurate timing information of its reflection points by projecting a narrow beam of signal at the target. Forming a narrow beam requires a high-frequency, large antenna array. Obtaining accurate timing information requires a large bandwidth. However, low-frequency signals (2.4 GHz or 5 GHz WiFi signals) are limited by narrow bandwidth (below 160 MHz) and wide beamwidth (over 5°), making it impossible to image objects. Therefore, obtaining target sizing information using low-frequency signals such as WiFi signals presents a fundamental challenge. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide a non-contact object size measurement method, system, device, and storage medium. Based on any transceiver-separated radio frequency (RF) signal device, it can classify targets (boxes) of different sizes in logistics with near 100% accuracy without the moving target needing to carry or contact any device, and achieves a median measurement error of 0.26 mm.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a non-contact method for measuring the size of an object, comprising the following steps:

[0007] Based on the pre-established relationship model between diffraction signals and moving objects, and the measurement accuracy requirements, the RF transceiver equipment is arranged.

[0008] The size of the moving target object is obtained by processing the diffraction signals collected by the RF transceiver.

[0009] Furthermore, the established relationship model between the diffraction signal and the moving object includes:

[0010] Establish a quantitative relationship between the diffraction signal and the width of the moving object;

[0011] Based on the quantitative relationship between diffraction signals and the size of moving objects, the relationship between the width of the moving object, the length of the Loss of Space (LoS), and the number of singularities is established.

[0012] Furthermore, the quantitative relationship between the diffraction signal and the width of the moving object is as follows:

[0013]

[0014] Where H(t) is the diffracted signal received by the RF receiving device when a pair of RF transceivers with fixed LoS paths are given; H wo It is a static signal; H obj (t) represents the diffraction signal caused by the motion of the object; d c (t) is the perpendicular distance from the center of the object to LoS ​​at time t, where L = l T +l R It is the path length of the diffraction point, l T and l R λ represents the distance from the integration point at a vertical distance x from the LoS path to the RF transmitting device Tx and the RF receiving device Rx, respectively; A is the signal wavelength; W is the signal amplitude; and λ is the width of the object.

[0015] Furthermore, the establishment of the relationship between the width of the moving object, the LoS length, and the number of singularities based on the quantitative relationship between the diffraction signal and the size of the moving object includes:

[0016] Based on the quantitative relationship between the diffraction signal and the width of the moving object, the relationship between the path length difference caused by the moving object moving away from the LoS path and the number of singularities on the diffraction signal curve is calculated.

[0017] Based on the above relationships, the relationships between the endpoint position of the moving object, the object width, the LoS path length, the signal wavelength, and the number of singularities on the diffraction signal curve are established.

[0018] Furthermore, the arrangement of the RF transceiver equipment based on the pre-established relationship model between the diffraction signal and the moving object, and the measurement accuracy requirements, includes:

[0019] Determine the RoS path length of the basic RF transceiver for coarse-grained classification of object size;

[0020] Based on the measurement accuracy requirements, the number of other RF transceiver pairs and the LoS path length of each pair of RF transceiver pairs are determined for fine-grained classification of object dimensions.

[0021] Furthermore, the process of obtaining the size of the moving target object by processing the diffraction signal acquired using the RF transceiver includes:

[0022] The diffraction signal acquired by the RF receiving device Rx is processed to extract the CSI signal used to measure the size of the moving object;

[0023] The number of singularities is calculated based on the extracted CSI signal, and the size of the moving target object is obtained based on the number of singularities.

[0024] Furthermore, the processing of the diffraction signal acquired by the RF receiving device Rx to extract the CSI signal used for measuring the size of the moving object includes:

[0025] For each RF receiving device, eliminate random phase shifts caused by clock asynchrony between transmitting and receiving devices;

[0026] The starting and ending distance ranges for counting singularities are determined, and the CSI signal acquired by the RF receiving device is automatically segmented to obtain the most suitable CSI segment for size measurement.

[0027] Secondly, the present invention provides a non-contact object size measurement system, comprising:

[0028] The equipment layout module is used to arrange RF transceiver equipment according to a pre-established relationship model between diffraction signals and moving objects and measurement accuracy requirements;

[0029] The object size measurement module uses diffraction signals collected by RF transceiver equipment to process and obtain the size of the target moving object.

[0030] Thirdly, the present invention provides a computer-readable storage medium for storing one or more programs, said one or more programs including instructions that, when executed by a computing device, cause the computing device to perform any of the methods.

[0031] Fourthly, the present invention provides a computing device comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for performing any of the methods.

[0032] The present invention has the following advantages due to the adoption of the above technical solutions:

[0033] 1. This invention simulates the effect of object motion on CSI signal changes and further quantifies the relationship between the number of CSI singularities and the target size, providing a theoretical basis for measuring object size using Wi-Fi signals and realizing accurate measurement of object size using Wi-Fi signals for the first time.

[0034] 2. This invention uses the CSI quotient to reduce hardware noise and takes the derivative of CSI to enhance the robustness of detection, so that the object size measurement can be achieved accurately and robustly using commercial Wi-Fi devices.

[0035] 3. This invention realizes the WiMeasure system by reasonably setting the logarithm of the RF receiving device and the LoS path length. Experimental verification shows that our system can classify boxes of different sizes in logistics with near 100% accuracy and achieve a median measurement error of 0.26mm.

[0036] Therefore, this invention can be widely applied in the field of measurement technology. Attached Figure Description

[0037] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0038] Figure 1 This is a schematic diagram of the diffraction model in an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of an object of a certain width moving 25cm outward from the LosS path along the vertical bisector of the transceiver device in an embodiment of the present invention.

[0040] Figure 3 This is a CSI signal diagram in the IQ plane when an object of a certain width moves 25cm outward from the LosS path along the vertical bisector of the transceiver device in an embodiment of the present invention.

[0041] Figure 4 This is the region from which singularities are extracted from the diffraction signal in this embodiment of the invention;

[0042] Figure 5 This is a CSI signal diagram in the IQ plane when objects of different widths move 25cm outward from the LosS path along the vertical bisector of the transceiver device in an embodiment of the present invention.

[0043] Figure 6 This invention relates to the impact of LoS distance on the number of singularities and measurement capabilities in this embodiment.

[0044] Figures 7a to 7d In this embodiment of the invention, fine-grained size measurement is achieved by using one (or more) pairs of devices. Figure 7a It determines the Loss path length of a pair of RF transceivers. Figure 7b This is a schematic diagram illustrating the use of a pair of transceiver devices for measuring the dimensions of an object. Figure 7c It determines the Loss path length of the two pairs of RF transceivers. Figure 7d This is a schematic diagram of measuring the size of an object using two pairs of RF transceivers.

[0045] Figure 8 This refers to the CSI signal segment of an object that has moved 0.25m in this embodiment of the invention.

[0046] Figure 9a and Figure 9b This is a schematic diagram illustrating the extraction of singularities using curvature in an embodiment of the present invention, wherein, Figure 9a This is a diagram illustrating curvature calculation. Figure 9b It is the theoretical signal curvature. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0048] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0049] In this invention, the specific terms are as follows: RF represents radio frequency signal, CSI represents channel state information, and LoS (Line of Sight) represents the distance between the transceiver and the transceiver.

[0050] In some embodiments of the present invention, a non-contact object size measurement method is disclosed. First, by analyzing the motion and diffraction signals of the object near the LoS path, a relationship model between the diffraction signals and the moving object is established. Then, the diffraction signals collected by the RF transceiver device are processed to obtain the number of singularities, which is used to measure the size of the moving object.

[0051] Correspondingly, other embodiments of the present invention provide a non-contact object size measurement system, device, and storage medium.

[0052] Example 1

[0053] This embodiment provides a non-contact object size measurement method, including the following steps:

[0054] S1. Establish a model relating diffraction signals to moving objects;

[0055] S2. Based on the established relationship model between the diffraction signal and the moving object and the measurement accuracy requirements, the RF transceiver equipment is arranged, and the size of the target moving object is obtained by processing the diffraction signal collected by the RF transceiver equipment.

[0056] Preferably, step S1 above includes the following steps:

[0057] S11. Establish a quantitative relationship between the diffraction signal and the width of the moving object;

[0058] S12. Based on the quantitative relationship between the diffraction signal and the width of the moving object, establish the relationship between the width of the moving object, the length of the Loss function, and the number of singularities.

[0059] Preferably, in step S11 above, as follows: Figure 1 As shown, assuming a pair of RF transceivers with fixed Loss of Sight (LoS) paths, when an object of finite size is located in the diffraction region of the RF transceiver, the signal received by the RF receiver can be divided into two parts: the signal passing through the upper region of the object and the signal passing through the lower region of the object. In other words, the diffraction signal received by the RF receiver is the sum of these two parts, expressed as:

[0060]

[0061] Among them, H u and H l These are the CSI (Content Indicator) signals from the upper and lower regions of the object, respectively. u It can be obtained from the upper boundary d of the object u Integrating to infinity, we get d u H is the distance from the upper boundary of the object to the Loss of Suppression (LoS) path. l It can be obtained by extending from negative infinity to the lower boundary d of the object. lThe integral is obtained as d l λ is the distance from the lower boundary of the object to the LoS path; λ is the signal wavelength, and A is the signal amplitude; l T and l R These are the distances from the integration point at a vertical distance x from the LoS path to the RF transmitting device T and the RF receiving device Rx, respectively, and their calculation formulas are as follows:

[0062]

[0063]

[0064] Among them, l To and l Ro These are the distances from the projection point of the object's vertical direction on the LoS path to the RF transmitting device Tx and the RF receiving device Rx, respectively.

[0065] Based on Babiné's principle, formula (1) can be transformed into the following form, which includes the object width W as a variable:

[0066]

[0067] Among them, H wo It is the signal when there is no object (i.e., the integral from negative infinity to positive infinity); H obj It is a signal that is blocked by an object; d c W is the vertical distance from the center of the object to the path of Loss; W is the width of the object.

[0068] If the object moves within the diffraction region, then formula (4) can be further expressed as:

[0069]

[0070] Where, d c (t) is the perpendicular distance from the center of the moving object to LoS ​​at time t, where L = l T +l R H is the path length of the diffraction point; wo This is a static signal (i.e., the diffraction signal when there is no object); H obj (t) represents the diffraction signal caused by the motion of the object, which changes with the position of the object.

[0071] Preferably, step S12 above includes the following steps:

[0072] S121. Based on the quantitative relationship between the diffraction signal and the width of the moving object, the relationship between the path length difference caused by the moving object moving away from the LoS path and the number of singularities on the diffraction signal curve is calculated.

[0073] S122. Based on the above relationships, establish the relationship between the endpoint position of the moving object, the object width, the LoS path length, the signal wavelength, and the number of singularities on the diffraction signal curve.

[0074] Preferably, step S121 above includes the following steps:

[0075] First, determine the relationship between the path length difference caused by the width of the moving object and the singularity.

[0076] To facilitate understanding, the concept of a singularity will be introduced here, for example, such as Figure 2 As shown, for an object with a width of 12cm, with a LoS path length of 1m, assume it moves from 0cm (P1) to 25cm (P3). Figure 3 As shown, the diffraction signal pattern is obtained by simulation based on formula (5). It can be observed that there is a sharp and sudden change at P2, which is called the singularity.

[0077] To explore the timing and location of the singularity, we use curvature to characterize the rate of change of the direction of the CSI curve points on the complex plane, as a feature of the signal. In equation (5), H wo We can assume that the object remains constant during motion, and focus on the diffraction signal H caused by the object's motion. obj (t) fluctuation. First, the definition of the curvature κ of the diffraction signal vector on the complex plane is given:

[0078]

[0079] in, ω=imag(H obj (t) are the diffraction signals H and H respectively. obj The real and imaginary parts of (t). When the curvature approaches positive infinity (i.e., the denominator of formula (6) is 0), a singularity will appear on the curve. Therefore, a singularity on the curve should satisfy the following condition:

[0080]

[0081] Specifically, according to formula (5), the diffraction signal H is obtained. obj The real part of (t) is represented as:

[0082]

[0083] Based on the properties of differentiation of finite integrals The derivative with respect to time t can be expressed as:

[0084]

[0085] in, d′c (t) is the velocity of the object; L u =l Tu +l Ru It is the path length of the upper boundary of the moving object; L1 = l Tl +l Rl It is the length of the lower boundary of the object; l Tu and l Ru These are the diffraction distances from the upper boundary of the moving object to the RF transmitting device Tx and the RF receiving device Rx, respectively. Tl and l Rl These are the diffraction distances from the lower boundary of the moving object to Tx and Rx, respectively, and the formulas for calculating each diffraction distance are as follows:

[0086]

[0087]

[0088]

[0089]

[0090] Similarly, the diffraction signal H obj The imaginary part of (t) is represented as:

[0091]

[0092] The derivative of ω(t) with respect to time t is:

[0093]

[0094] in,

[0095] Then, the sum of squares of formula (9) and formula (15) can be expressed as:

[0096]

[0097] In addition, such as Figure 4 As shown, we can divide the area around the RF transceiver into three zones. When an object moves in the middle zone (i.e., ... Figure 4 When the object size is smaller than the LoS path length (in region ②), then (l) Tu l Ru -l Tl l Rl )<<l Tu l Ru l Tl l Rl Therefore, the first term in the above formula The first term becomes very small compared to the second term, so it can be ignored. When the LoS path length is 2m, the minimum horizontal distance in region ② is 1.6m. After ignoring the first term, formula (16) can be simplified to:

[0098]

[0099] From formula (17), it can be seen that when focusing on measuring the size of a moving object (the object's velocity is not 0, i.e., d′), c (t)≠0), if Singularities occur when k∈N. Different object widths lead to different path length differences. A singularity occurs when the path length difference is an integer multiple of the wavelength. A singularity appears on the diffraction signal when the path length difference introduced by the object is exactly one wavelength. Note that the relationship between singularities and object width applies not only to objects on the perpendicular bisectors of the two transceivers but also to objects at other locations in the diffraction region.

[0100] Secondly, based on the path length difference caused by the object at the endpoint, the number of singularities on the diffraction signal curve during the process of the object moving away from the LoS path to the endpoint is calculated.

[0101] Specifically, when the object's center is located on the LoS path, the path length difference caused by the object's upper and lower boundaries is zero. As the object moves upward, the path length difference gradually increases, and singularities occur when the path length difference is λ, 2λ, ... . If the object moves a fixed distance from the LoS path, the number N of singularities on the diffraction signal curve during the object's motion can be calculated based on the path length difference at the object's endpoint:

[0102]

[0103] in, The signal path length is the location of the upper boundary of the object at the endpoint. The signal path length is the location of the lower boundary of the object at the endpoint.

[0104] Preferably, in step S122 above, we can observe from formula (18) that the number of singularities is directly related to the difference in path length between the upper and lower boundaries of the object at the endpoint position. This path length difference further depends on four parameters: endpoint position, signal wavelength, object width, and LoS path length. Specifically: (i) Endpoint position. The farther the endpoint position is from the LoS path, the greater the path length difference, and the more singularities there are. (ii) Signal wavelength. For objects of the same size and endpoint position, the smaller the wavelength, the more singularities there are. (iii) Object width. The wider the object, the greater the difference in path length, and the more singularities reach the same endpoint position. (iv) LoS path length. As the LoS path length increases, the path length difference decreases, and the number of singularities decreases.

[0105] like Figure 5 As shown, we consider five different object widths: 0.06m, 0.12m, 0.18m, 0.24m, and 0.3m. We move the object 0.25m along the perpendicular bisector of the LoS path and obtain the corresponding diffraction signals. It can be clearly seen that for the five objects with different widths, the number of singularities is 0, 1, 2, 3, and 4, respectively. When the object is at 0.25m, the path length differences caused by the upper and lower boundaries of the object are 0.053m, 0.106m, 0.159m, 0.210m, and 0.260m, respectively, corresponding to 0.94, 1.87, 2.79, 3.69, and 4.57 times the wavelength (0.057m). The larger the object width, the more singularities there are, indicating that we can use the number of singularities to estimate the object width.

[0106] like Figure 6 As shown, a theoretical heatmap of the number of singularities is presented for different LosS path lengths and different object widths. We can observe that when the number of singularities is the same, the larger the LosS path length, the lower the resolution of the object width. This is because a larger object width range corresponds to the same number of singularities, indicating a weaker object width measurement capability. For example, when the LosS path length is 0.5m, 10 different object width ranges can be detected within the 0–50cm range, with each singularity corresponding to one object width range. When the LosS path length increases to 2m, only 4 different target width ranges can be obtained within the 0–50cm range.

[0107] Preferably, step S2 above includes the following steps:

[0108] S21. Arrange RF transmitting equipment Tx and RF receiving equipment Rx in pairs on both sides of the moving object's path of motion, according to the measurement accuracy requirements.

[0109] S22. Process the diffraction signal acquired by the RF receiving device Rx and extract the CSI signal used to measure the size of the moving object;

[0110] S23. Calculate the number of singularities based on the extracted CSI signal, and obtain the size of the target moving object based on the number of singularities.

[0111] Preferably, step S21 above includes the following steps:

[0112] S211. Determine the RoS path length of the basic RF transceiver device for coarse-grained classification of object size.

[0113] To improve the accuracy and speed of object size measurement, this embodiment first sets up a pair of RF transceivers as basic RF transceivers for coarse-grained classification of object size.

[0114] Depend on Figure 6 It is known that a smaller LoS path length can achieve finer resolution in object size measurement. However, the LoS path distance cannot be continuously reduced because the LoS path length must be greater than the object size to allow the object to pass through. For the sake of generality, this embodiment uses a LoS path length of 0.5m as an example to illustrate this concept. Based on the number of singularities, object sizes can be divided into 5 categories: from 4cm to 24cm, with a step size of 4cm. That is, after coarse-grained size measurement, object sizes can be classified with an accuracy of several centimeters.

[0115] S212. Based on the measurement accuracy requirements, determine the number of pairs of other RF transceivers and the LoS path length of each pair of RF transceivers for fine-grained classification of object size.

[0116] Specifically, after the coarse-grained size measurement step, this range information can be used to configure other pairs of RF transceivers and the LoS path distances between each pair of RF transceivers for fine-grained measurement. The basic idea of ​​fine-grained size measurement is to further divide the coarse-grained range in step S211 into finer-grained range intervals. For example, the 12 cm to 16 cm interval is now divided into two smaller intervals (i.e., 12 cm to 14 cm and 14 cm to 16 cm). To achieve this, we need to carefully design the LoS path distances using the properties revealed in S122.

[0117] For simplicity, this embodiment divides a large range into smaller ranges and uses the median value of each smaller range as the measurement value. For example... Figure 7aAs shown, for a given range, the number of singularities varies with the length of the Loss-of-Stake (LoS) path (taking 12 cm to 16 cm as an example). First, the midpoint of the range is determined (14 cm), and this midpoint is used to select a LoS path length (0.66 m) such that different numbers of singularities appear in the two smaller ranges (i.e., two singularities in the 12 cm to 14 cm range, and three singularities in the 14 cm to 16 cm range). Therefore, if a LoS path distance of 0.66 m is chosen, the measured width is 13 cm when two singularities exist. Figure 7b When three singularities exist, the measured width of the object is 15 centimeters. Therefore, the maximum error of a pair of transceivers is one-quarter of the object's width range, or 1 centimeter.

[0118] Similarly, using two pairs of transceiver devices, the range can be divided into three equal smaller ranges, such as... Figure 7d As shown. One pair of transceivers is used to identify the first and second smaller range intervals, while a second pair of transceivers is used to identify the second and third smaller range intervals.

[0119] like Figure 7c As shown, the breakpoints are 13.33cm and 14.67cm, corresponding to LoS ​​path distances of 0.6m and 0.7m, respectively. Figure 7d As shown, when there are two singularities in both the 0.6m and 0.7m LoS path distances, the measured size is 12.67cm. If there are two singularities on a 0.7m LoS path and three singularities on a 0.6m LoS path, then the measured size is 14cm. When measurements are taken along both Loss paths and each has three singularities, the measured size is 15.33 cm. In this two-transceiver pair, we can achieve less than

[0120] An error of 0.66 cm This system utilizes n pairs of transceiver devices with n different Loss of Path (LoS) distances to achieve an error of less than [missing value]. This result is twice the range of the first step's coarse-grained measurement. Theoretically, it is possible to measure the target width using an infinite number of transmitter-receiver pairs within an arbitrarily small range. In this embodiment, millimeter-level measurement accuracy can be achieved using only 3 transmitter-receiver pairs.

[0121] It is important to note that the object size measured in this embodiment cannot be too small or too large. For example, when the object size is 0.5 cm, which is much smaller than the signal wavelength (i.e., 5.7 cm), the system does not work well. This is because the proposed system relies on diffraction effects, and when the target size is much smaller than the signal wavelength, the diffraction effect becomes too weak to be used for size measurement. On the other hand, the target size cannot be too large. For example, if the LoS path length is 0.5 m, we do observe a performance degradation when the target size is greater than 0.3 m. This is because when the target is relatively large relative to the LoS path length, the object blocks a large portion of the signal, thus weakening the diffraction effect. To measure the size of larger targets, we need to deploy the transmitter and receiver at a greater distance.

[0122] People moving around can interfere with dimensional measurements. However, the interference from people's movement is quite limited. This is because most of the signal energy is concentrated in the first Fresnel zone near the Loss-of-Stake (LoS) path. Therefore, the reflected energy is much smaller than the diffraction energy used for dimensional measurements.

[0123] Preferably, in step S211 above, the RF transceiver device can be a laptop, MiniPC, 4G / 5G device, RFID device, LoRa device, or any device that supports RF signal transmission and reception. For example, if the RF transmitting device is a router, the corresponding RF receiving device can be a mobile terminal with WiFi receiving capabilities, such as a mobile phone or computer; if the RF transmitting device is a 4G / 5G base station, the corresponding RF receiving device can be a mobile terminal with 4G / 5G capabilities, such as a mobile phone or computer.

[0124] The RF transmitting device Tx is configured with one transmitting antenna for transmitting RF signals, and the FR receiving device Rx is configured with at least two receiving antennas for measuring CSI (Channel State Information). More preferably, both the transmitting and receiving antennas are vertically polarized omnidirectional antennas, which can be placed perpendicular to the ground or parallel to the ground.

[0125] In this embodiment, 1 to 3 pairs of RF transceivers are arranged, and a WiFi signal with a center frequency of 5.32 GHz is used as the RF signal. A MiniPC equipped with an 8 dB omnidirectional antenna and an Intel 5300 network card is used as the RF transceiver.

[0126] Preferably, in step S22 above, extracting the CSI signal for measuring the size of the moving object includes the following steps:

[0127] S221, Signal noise reduction: For each RF receiving device, eliminate random phase offset caused by clock asynchrony between the transmitting and receiving devices.

[0128] In this embodiment, for each RF receiving device, the RF receiving device simultaneously receives RF signals from the same RF transmitting device from at least two of its antennas. The RF receiving device acquires the Channel State Information (CSI) on at least two antennas and divides the CSI acquired simultaneously on each of the at least two antennas to eliminate random phase shifts in the signal caused by time asynchrony between the RF receiving device and the RF transmitting device. For example, at time t, for an RF signal with frequency f, its channel state information on one antenna is H1(f,t), and its channel state information on the other antenna is H2(f,t). The new signal after eliminating random phase shifts is: S(f,t) = H1(f,t) / H2(f,t). Next, a least-squares smoothing filter, such as a Savitzky-Golay filter, is used to further reduce the amplitude of the obtained CSI quotient.

[0129] S222 Automatic segmentation: Determine the starting and ending distance ranges for counting singularities, and automatically segment the CSI signal acquired by the RF receiving device to obtain the most suitable CSI segment for size measurement.

[0130] Since the number of singularities is related to the distance traveled, to measure the width of an object using the number of singularities, we need to determine which segment of the CSI (Cross-Signal Intersection) is best suited for dimensional measurement and use a fixed distance traveled by the object. Because the diffraction effect is stronger near the Loss of Sight (LoS) path, based on theoretical analysis and experiments, we choose a CSI segment near the LoS path for dimensional measurement. Interestingly, when an object traverses the LoS path, we can accurately determine the point on the CSI trajectory without any prior knowledge; that is, the center of the object lies precisely on the LoS path.

[0131] like Figure 8 As shown, the amplitude of the diffraction signal changes in a "W" shape during the process along the LoS path. More importantly, the pattern of change of the diffraction signal is symmetrical with respect to the LoS path. Therefore, we can use this symmetry to determine the point where the center of the object lies exactly on the LoS path as the starting timestamp (i.e., t). start Specifically, we identify the two minimum values ​​on the "W"-shaped signal and average the time values ​​of the two minimum values. As the starting time t start After determining the starting point, we also need to determine the distance range we will use to count the singularities. A larger distance means a greater number of singularities. However, the diffraction effect is weaker when the object is far from the center of the Loss of Singularity (LoS). Based on our experience, we set the distance range to 0.25m. When the object is far from the center of the LoS path (t... start When it starts moving to a distance of 0.25m from the Loss path (t) endWe will calculate the number of singularities. Since the slide rail speed or conveyor belt speed is known and constant, the required CSI segments can be easily identified and segmented for dimensional measurement. Applying the above method, the signal segments corresponding to targets within 0.25m of the LoS center can be accurately identified.

[0132] Preferably, in step S23 above, by Figure 3 It is known that there is a sharp change in direction at the singularity, but no sharp change in power. Therefore, the most direct solution to accurately detect a singularity from a CSI segment is to find the point where the diffraction signal vector direction deviates sharply in time. Mathematically, we use curvature to describe the rate of change in direction. If we know three adjacent points on the CSI trajectory (e.g., A, B, C...),... Figure 9a As shown in the image, we can calculate the curvature of these three points. This curvature information provides us with a method for extracting singularities. Figure 9b As shown, we present a curvature plot of an object moving 0.25m along the perpendicular bisectors of two transceivers. The curvature values ​​at singularities are very large, so we can achieve robust singularity detection by applying a simple peak detection algorithm.

[0133] Now, let's illustrate how to calculate curvature using three adjacent points on a CSI trajectory. The curvature of a curve at a point is the rate of change in the tangential direction. For example, in... Figure 9a Consider three points A, B, and C. The changes in the tangent angles at points A and C are: Furthermore, the length of AC is Δs. The curvature κ can be calculated from point A and point B as they infinitely approach each other:

[0134]

[0135] like Figure 9b As shown, the curvature values ​​estimated over time are displayed when an object is in motion. The peak curvature represents a singularity, and the number of singularities during the motion can be extracted by counting the number of peak curvature.

[0136] Example 2

[0137] The above-described embodiment 1 provides a non-contact object size measurement method. Correspondingly, this embodiment provides a non-contact object size measurement system. The system provided in this embodiment can implement the non-contact object size measurement method of embodiment 1. The system can be implemented through software, hardware, or a combination of both. For example, the system may include integrated or separate functional modules or units to perform the corresponding steps in the methods of embodiment 1. Since the system in this embodiment is basically similar to the method embodiment, the description process in this embodiment is relatively simple. Relevant details can be found in the description of embodiment 1. The system embodiment provided in this embodiment is merely illustrative.

[0138] The non-contact object size measurement system provided in this embodiment includes:

[0139] The equipment layout module is used to arrange RF transceiver equipment according to a pre-established relationship model between diffraction signals and moving objects and measurement accuracy requirements;

[0140] The object size measurement module uses diffraction signals collected by RF transceiver equipment to process and obtain the size of the target moving object.

[0141] Example 3

[0142] This embodiment provides a processing device corresponding to the non-contact object size measurement method provided in Embodiment 1. The processing device can be a client-side processing device, such as a mobile phone, laptop, tablet computer, desktop computer, etc., to execute the method of Embodiment 1.

[0143] The processing device includes a processor, a memory, a communication interface, and a bus. The processor, memory, and communication interface are connected via the bus to enable communication between them. The memory stores a computer program that can run on the processor. When the processor runs the computer program, it executes the non-contact object size measurement method provided in Embodiment 1.

[0144] In some embodiments, the memory may be high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device.

[0145] In other embodiments, the processor can be a general-purpose processor of various types, such as a central processing unit (CPU) or a digital signal processor (DSP), and is not limited thereto.

[0146] Example 4

[0147] The non-contact object size measurement method of this embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the non-contact object size measurement method of this embodiment 1 are loaded.

[0148] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A non-contact method for measuring the size of an object, characterized in that, Includes the following steps: Based on the pre-established relationship model between diffraction signals and moving objects, and the measurement accuracy requirements, the RF transceiver equipment is arranged. The size of the moving target object is obtained by processing the diffraction signals collected by the RF transceiver. The established model relating the diffraction signal to the moving object includes: Establish a quantitative relationship between the diffraction signal and the width of the moving object; Based on the quantitative relationship between diffraction signals and the size of moving objects, the relationship between the endpoint position of the moving object, the object width, the LoS path length, the signal wavelength, and the number of singularities on the diffraction signal curve is established. The quantitative relationship between the diffraction signal and the width of the moving object is as follows: in, It is the diffracted signal received by the RF receiving device when given a pair of RF transceivers with fixed Loss paths; It is a static signal; The diffraction signal caused by the motion of the object; It is the perpendicular distance from the center of the object to LoS ​​at time t. It is the path length of the diffraction point. and These are the vertical distances from the Loss path. Integration point to RF transmitting device The distance to the RF receiving device Rx; It is the signal wavelength; It is the amplitude of the signal; It is the width of the object; The process of obtaining the size of the moving target object by processing the diffraction signal acquired using the RF transceiver includes: The diffraction signal acquired by the RF receiving device Rx is processed to extract the CSI signal used to measure the size of the moving object; The number of singularities is calculated based on the extracted CSI signal, and the size of the moving target object is obtained based on the number of singularities.

2. The non-contact object size measurement method as described in claim 1, characterized in that, The quantitative relationship between the diffraction signal and the size of the moving object, establishing the relationship between the width of the moving object, the length of the Loss of Space (LoS), and the number of singularities, includes: Based on the quantitative relationship between the diffraction signal and the width of the moving object, the relationship between the path length difference caused by the moving object moving away from the LoS path and the number of singularities on the diffraction signal curve is calculated. Based on the above relationships, the relationship between the object width, the LoS path length, and the number of singularities on the diffraction signal curve is established.

3. The non-contact object size measurement method as described in claim 1, characterized in that, The arrangement of the RF transceiver equipment based on a pre-established relationship model between the diffraction signal and the moving object, and the measurement accuracy requirements, includes: Determine the RoS path length of the basic RF transceiver for coarse-grained classification of object size; Based on the measurement accuracy requirements, the number of other RF transceiver pairs and the LoS path length of each pair of RF transceiver pairs are determined for fine-grained classification of object dimensions.

4. The non-contact object size measurement method as described in claim 1, characterized in that, The process of processing the diffraction signal acquired by the RF receiving device Rx to extract the CSI signal used for measuring the size of the moving object includes: For each RF receiving device, eliminate random phase shifts caused by clock asynchrony between transmitting and receiving devices; The starting and ending distance ranges for counting singularities are determined, and the CSI signal acquired by the RF receiving device is automatically segmented to obtain the most suitable CSI segment for size measurement.

5. A non-contact object size measurement system, characterized in that, include: The equipment layout module is used to arrange RF transceiver equipment according to a pre-established relationship model between diffraction signals and moving objects and measurement accuracy requirements; The object size measurement module uses the diffraction signals collected by the RF transceiver to process and obtain the size of the target moving object; The established model relating the diffraction signal to the moving object includes: Establish a quantitative relationship between the diffraction signal and the width of the moving object; Based on the quantitative relationship between diffraction signals and the size of moving objects, the relationship between the endpoint position of the moving object, the object width, the LoS path length, the signal wavelength, and the number of singularities on the diffraction signal curve is established. The quantitative relationship between the diffraction signal and the width of the moving object is as follows: in, It is the diffracted signal received by the RF receiving device when given a pair of RF transceivers with fixed Loss paths; It is a static signal; The diffraction signal caused by the motion of the object; It is the perpendicular distance from the center of the object to LoS ​​at time t. It is the path length of the diffraction point. and These are the vertical distances from the Loss path. Integration point to RF transmitting device The distance to the RF receiving device Rx; It is the signal wavelength; It is the amplitude of the signal; It is the width of the object; The process of obtaining the size of the moving target object by processing the diffraction signal acquired using the RF transceiver includes: The diffraction signal acquired by the RF receiving device Rx is processed to extract the CSI signal used to measure the size of the moving object; The number of singularities is calculated based on the extracted CSI signal, and the size of the moving target object is obtained based on the number of singularities.

6. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods described in claims 1 to 4.

7. A computing device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods described in claims 1 to 4.

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