Radar ranging method, apparatus, device, and storage medium

Abstract

The application discloses a radar ranging method, device, equipment and storage medium, and the method comprises the steps of controlling the radar to emit electromagnetic wave signals to multiple reflectors and receiving first echo signals reflected by the shaft; converting the first echo signals into a first frequency spectrum diagram; extracting a first feature presented by a first target object and a second target object in distribution from the first echo signals; matching the first feature with a second feature learned in advance for the first target object and the second target object in distribution; and if the matching is successful, extracting a distance between the radar and the first target object, which is labeled for the second feature, as a position of the car in the shaft.

Description

Technical Field

[0001] This application relates to the field of elevator technology, for example to a radar ranging method, device, equipment and storage medium. Background Technology

[0002] With the development of urbanization, high-rise buildings have become widespread, and elevators have become an important means of transportation for people's lives, studies, and work.

[0003] During elevator operation, in order to monitor the position of the car in the shaft, the current method is mostly to use radar and reflectors for distance measurement. That is, by measuring the time it takes for the radar to emit and receive electromagnetic wave signals, and combining this with the speed of light, the distance between the radar and the reflector is calculated, which is then mapped to the position of the car in the shaft.

[0004] However, in addition to the reflector, there are other metals in the wellbore. These metals reflect some of the electromagnetic waves emitted by the radar, causing interference. This is especially noticeable when the distance between the radar and the reflector is large, which reduces the accuracy of ranging. Summary of the Invention

[0005] This application provides a radar ranging method, apparatus, device, and storage medium to improve the accuracy of measuring the position of a car.

[0006] According to one aspect of this application, a radar ranging method is provided, wherein a plurality of reflectors are arranged in a shaft, the reflectors including a first target located at one end of the shaft and a second target located at a non-end of the shaft, and a radar is arranged in a car sliding in the shaft, the method comprising:

[0007] The radar is controlled to transmit electromagnetic wave signals to multiple reflectors and to receive the first echo signal reflected by the wellbore.

[0008] Convert the first echo signal to the first spectrum diagram;

[0009] Extract the first feature in the distribution of the first target and the second target from the first echo signal;

[0010] The first feature is matched with a second feature that has been pre-learned on the distribution of the first target and the second target;

[0011] If a match is successful, the distance between the radar and the first target object, which is labeled with the second feature, is extracted as the position of the car in the shaft.

[0012] According to another aspect of this application, a radar ranging device is provided, comprising a plurality of reflectors arranged in a shaft, the reflectors including a first target located at one end of the shaft and a second target located at a non-end of the shaft, and a radar installed in a car traveling in the shaft, the device comprising:

[0013] The first echo signal receiving module is used to control the radar to transmit electromagnetic wave signals to the multiple reflectors and to receive the first echo signal reflected by the well.

[0014] The first spectrum conversion module is used to convert the first echo signal to a first spectrum.

[0015] The first feature extraction module is used to extract the first feature of the distribution of the first target object and the second target object from the first echo signal;

[0016] The first feature matching module is used to match the first feature with a second feature that has been pre-learned on the distribution of the first target object and the second target object;

[0017] The second feature extraction module is used to extract the distance between the radar and the first target object, which are both labeled with the second feature, if the match is successful, as the position of the car in the shaft.

[0018] According to another aspect of this application, an electronic device is provided, the electronic device comprising:

[0019] At least one processor; and

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the ranging method described in any embodiment of this application.

[0022] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program for causing a processor to execute and implement the radar ranging method described in any embodiment of this application.

[0023] In this embodiment, the control radar transmits electromagnetic wave signals to multiple reflectors and receives the first echo signal reflected by the shaft; the first echo signal is converted into a first spectrum; a first feature of the distribution of the first target object and the second target object is extracted from the first echo signal; the first feature is matched with a second feature pre-learned from the distribution of the first target object and the second target object; if the match is successful, the distance between the radar and the first target object, which is labeled with the second feature, is extracted as the position of the car in the shaft. This radar absolute position measurement scheme utilizes reflectors installed at the top of the elevator shaft and radar ranging sensors at the top of the car to achieve absolute position measurement of the elevator car, avoiding malfunctions such as misalignment and improving elevator safety. Furthermore, since the absolute position of the elevator is known, numerous switching components within the shaft can be eliminated, reducing costs. Attached Figure Description

[0024] Figure 1A It is based on the diagram showing the relationship between the car and the hoistway provided in this application;

[0025] Figure 1B It is a side projection view of the radar and reflector installation position provided in this application;

[0026] Figure 2 It is based on the distance-amplitude spectrum diagram between the radar and the reflector at the same vertical position provided in this application;

[0027] Figure 3 This is a flowchart of a radar ranging method according to Embodiment 1 of this application;

[0028] Figure 4 This is a simplified frontal projection diagram of the radar and reflector installation positions provided in this application;

[0029] Figure 5A It is a second spectrum obtained by radar scanning according to Embodiment 1 of this application;

[0030] Figure 5B It is a third spectrum obtained by radar scanning according to Embodiment 1 of this application;

[0031] Figure 6 This is a flowchart of a radar ranging method according to Embodiment 2 of this application;

[0032] Figure 7 This is a flowchart of a radar ranging method according to Embodiment 3 of this application;

[0033] Figure 8 This is a beamwidth diagram of the electromagnetic wave signal received by the first target object according to Embodiment 3 of this application;

[0034] Figure 9This is a flowchart of a radar ranging method according to Embodiment 4 of this application;

[0035] Figure 10 This is a flowchart of a radar ranging method according to Embodiment 5 of this application;

[0036] Figure 11 This is a flowchart of a radar ranging method according to Embodiment Six of this application;

[0037] Figure 12 This is a second spectrum diagram obtained by radar scanning when the car is located at 5 meters, according to Embodiment Six of this application;

[0038] Figure 13 This is a flowchart of a radar ranging method according to Embodiment Seven of this application;

[0039] Figure 14 This is a flowchart of a radar ranging method provided according to Embodiment 8 of this application;

[0040] Figure 15 This is a flowchart of a radar ranging method according to Embodiment Nine of this application;

[0041] Figure 16 This is an angle view provided according to Embodiment Nine of this application;

[0042] Figure 17 This is a schematic diagram of a radar ranging device according to Embodiment 10 of this application;

[0043] Figure 18 This is a schematic diagram of the structure of an electronic device provided in Embodiment 11 of this application. Detailed Implementation

[0044] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0045] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0046] Generally speaking, elevators come in different types and have different functions, such as passenger elevators, freight elevators, and sightseeing elevators. Therefore, the components installed in elevators are also different.

[0047] In one example, the components of a certain type of elevator include a traction machine, control cabinet, speed governor, door operator, car frame, car door, counterweight guide rail, car guide rail, guide rail support, traveling cable, counterweight device, compensating chain (cable), landing door, guide device for compensating chain (cable), and buffer.

[0048] Of course, in some types of elevators, the traction machine, control cabinet, speed governor, and traveling cable can be omitted, and this embodiment does not impose any restrictions on this.

[0049] like Figure 1A As shown, a shaft 110 is installed inside or outside buildings such as teaching buildings, office buildings, and residences. The elevator car 120 is used to move (i.e., glide) in the shaft 110. A control panel is installed on each floor or the first floor of the building. The control panel is generally equipped with buttons for calling the elevator up and down. Passengers can press these buttons to make an elevator call request.

[0050] Of course, in addition to the control panel, passengers can also use a client, remote control, or other means to make an elevator call request, and this embodiment does not limit this.

[0051] When the elevator receives a call request, it controls the car 120 to slide in the shaft 110 to the floor where the passenger 130 is located, opens the car door, and closes the car door after the passenger 130 enters the car 120. A control panel is installed inside the car 120, which is generally equipped with buttons for each floor, open door, close door, alarm, etc. The passenger 130 can press the buttons for each floor to send a call request.

[0052] Of course, in addition to the control panel, passengers can also use a client, remote control, or other means to make an elevator request, and this embodiment does not impose any restrictions on this.

[0053] When the elevator receives a passenger request, it controls the car 120 to slide in the shaft 110 to the destination floor indicated by the passenger 130, opens the car door, and closes the car door after the passenger 130 exits the car 120.

[0054] In this embodiment, in order to measure the position of the car 120 in the hoistway 110, a radar 140 can be installed outside the car 120, especially a millimeter-wave radar using FMCW (Frequency Modulated Continuous Wave). In this case, the radar 140 will move up and down in the hoistway 110 along with the car 120.

[0055] Accordingly, multiple (≥2) reflectors are provided in the shaft 110. The reflectors can be passive reflective devices such as corner reflectors and flat plates, or active signal reflective devices. This embodiment does not limit this.

[0056] When detecting the position of the car in the hoistway, the radar emits electromagnetic wave signals. These signals are reflected back by obstacles (including reflectors) in the hoistway, forming echo signals. Upon receiving the echo signals, the radar can calculate the distance between the radar and the reflector, thus mapping the absolute position of the car in the hoistway.

[0057] In addition to reflectors, there may be some highly reflective obstacles in the hoistway, especially metal objects with horizontal bottoms and exceeding a certain size, such as guide rail supports and thresholds. These obstacles can also effectively reflect the electromagnetic wave signals emitted by the radar and be received by the radar, thus interfering with the detection of the car's position in the hoistway.

[0058] Due to the limitations of the shaft size, the size of the reflector cannot be infinitely large. Therefore, it cannot be guaranteed that the effective cross-sectional area (RCS) of the reflector is larger than the effective cross-sectional area (RCS) of other metal objects in the shaft. Consequently, the amplitude of the peak signal of the electromagnetic wave reflected by the reflector in the spectrum is not necessarily the strongest.

[0059] like Figure 2 As shown, if a reflector is installed in the shaft, when the distance between the radar and the reflector exceeds a certain threshold, in the spectrum diagram (horizontal axis is distance S, vertical axis is amplitude A), the peak signal 210 of the reflector's echo signal may be weaker than the peak signal of the echo signal of other obstacles (especially metal objects) in the shaft. When the radar is powered on again at that location, it cannot determine which peak signal in the spectrum diagram is the peak signal of the echo signal reflected by the reflector, and the initial position cannot be located.

[0060] Therefore, in this embodiment, multiple reflectors are installed in the shaft. The reflectors include a first target located at the end of the shaft and a second target located at a non-end point of the shaft. The number of the first target is one, and the number of the second target is one or more. In order to enable those skilled in the art to better understand this application, three reflectors are used as an example in this embodiment.

[0061] In one installation method, when the radar 140 is installed on the top of the car, the first target 150 can be installed on the top of the hoistway, and the second target 160 and the second target 170 can be installed on the top of the hoistway and on the side close to the guide rail.

[0062] In another installation method, when the radar is installed at the bottom of the car, the first target can be installed at the bottom of the hoistway, and the second target can be installed near the bottom of the hoistway and on the side close to the guide rail.

[0063] Regardless of the installation method, the first target and the radar are on the same vertical line, especially the center of the radar and the center of the reflector lens are on the same vertical line, while any second target and the radar are not on the same vertical line.

[0064] In addition, such as Figure 1A and Figure 1B As shown, in order to avoid mutual obstruction when multiple reflectors (including the first target 150, the second target 160 and the second target 170) reflect electromagnetic wave signals, the projections of the multiple reflectors (including the first target 150, the second target 160 and the second target 170) on the horizontal plane do not overlap, and the projections of the multiple reflectors (including the first target 150, the second target 160 and the second target 170) on the vertical plane do not overlap.

[0065] Since the environment of the hoistway is fixed over a period of time, and the peak signal of the echo signal reflected by reflectors and other obstacles (such as metal objects) is related to distance, when the car moves to the same position in the hoistway each time, the distance and amplitude (also known as intensity) of the peak signal of the echo signal reflected by reflectors and other obstacles (such as metal objects) are basically the same. However, when the car moves to different positions in the hoistway, the distance and amplitude of the peak signal of the echo signal reflected by reflectors and other obstacles (such as metal objects), as well as the number of echo signals reflected by other obstacles (such as metal objects), are mostly different. Therefore, this embodiment can learn the spectral characteristics of each reflector by recording the different positions of the car in the hoistway, and then search for the position of the car in the hoistway based on the recorded characteristics.

[0066] Since the first target and the radar are on the same vertical line, while each of the second targets is offset from the radar in the vertical direction, the distance corresponding to the peak signal of the electromagnetic wave signal reflected by each reflector on the spectrum diagram reflects the straight-line distance between each reflector and the radar. As the car moves, the distance between the first target and the second target on the spectrum diagram, as well as the distance between each of the second targets, changes. Therefore, it is not suitable to use a fixed distance to search for each reflector.

[0067] When the reflectors are installed, they are fixed together. Therefore, the distribution characteristics of each reflector are unchanged. Thus, before the radar and transmitter are put into use, the radar can follow the car through the hoistway, learn the distribution characteristics of the reflectors at different positions in the hoistway, and mark the position of the car in the hoistway based on these characteristics.

[0068] When the radar and reflector are engaged, the currently acquired spectrum information is matched with the distribution characteristics of the reflector stored during learning. This allows the echo signal of the reflector to be identified from the many echo signals in the spectrum, thereby confirming the position of the car in the hoistway.

[0069] Example 1

[0070] Figure 3 This is a flowchart illustrating a radar ranging method provided in this application embodiment. This embodiment is applicable to situations where radar is used to learn the distribution characteristics of various reflectors in a shaft. The radar ranging device can be implemented in hardware and / or software, and can be configured in electronic devices, such as... Figure 3 As shown, the method includes:

[0071] Step 301: Starting from the marker closest to the first target, control the car to move sequentially to each marker in the hoistway.

[0072] When the elevator is in the stage of using radar to learn the distribution characteristics of each reflector, it can indicate to the outside that the elevator is under maintenance or is not normally carrying people or goods.

[0073] At this point, multiple marker positions can be divided in the shaft. When the shaft is used as a reference object, the marker positions remain fixed, so that radar can be used at each marker position to learn the distribution characteristics of each reflector.

[0074] Generally, the interval between two adjacent markers is a preset step size, that is, the markers are evenly distributed in the wellbore. This step size can be set according to factors such as the accuracy of the radar, such as 1 millimeter.

[0075] Of course, in addition to the markers being evenly distributed in the shaft, the markers can also be evenly distributed in the shaft. For example, the interval between markers can be smaller near the reflector, resulting in a higher density of markers, while the interval between markers can be larger away from the reflector, resulting in a lower density of markers, and so on. This embodiment does not limit this.

[0076] In this embodiment, the car is controlled to move sequentially to each marker position in the hoistway. The starting marker position is closest to the first target object. That is, when the radar starts learning the distribution characteristics of each reflector, the initial position of the car is closest to the first target object. Then, the car can be controlled to move sequentially to each marker position in a direction away from the first target object.

[0077] Because different buildings have different environments, the elevators installed will vary, and the range of motion of the car will also vary. Therefore, the position of the car closest to the first target object refers to the position closest to the first target object within its range of motion.

[0078] like Figure 1A As shown, when the radar 140 is installed on the top of the car, the first target 150 is installed on the top of the hoistway, and the second target 160 and the second target 170 are installed near the top of the hoistway and on one side of the guide rail, when the radar is used to learn the distribution characteristics of each reflector, the initial position of the car 120 is the top layer (marker position). After that, the car 120 is controlled to move to each mark position from top to bottom.

[0079] Furthermore, since the speed at which the car moves in the hoistway is controllable, and the step size between the marker positions is preset, the car can estimate the distance it moves in a short time using methods such as uniform motion, uniform acceleration motion, and Kalman linear filtering, so that it conforms to the step size between two adjacent marker positions.

[0080] Step 302: In each flag position, control the radar to send electromagnetic wave signals to multiple reflectors and receive the second echo signal reflected by the well passage.

[0081] When the car moves to each marker position, it pauses briefly. At this time, the car control radar can be controlled to send electromagnetic wave signals in the direction of the reflector. The electromagnetic wave signals propagate in the atmosphere and reach various obstacles within the radar's scanning range in the hoistway. At this time, the electromagnetic wave signals will be reflected and scattered on the surface of the obstacles.

[0082] These obstacles can include reflectors, guide rails, thresholds and other highly reflective metal objects, as well as side walls and other obstacles with low reflectivity.

[0083] The radar can receive electromagnetic wave signals reflected from within the radar's scan range in the shaft. Because the electromagnetic wave signal absorbs some of its energy through the reflector, it generates an original electromagnetic wave signal with attenuation delay. This original electromagnetic wave signal is superimposed on the original electromagnetic wave signal to form an echo signal. For ease of distinction, this echo signal is referred to as the second echo signal.

[0084] Step 303: Convert the second echo signal to the second spectrum diagram.

[0085] In this embodiment, operations such as FT (Fourier Transform) and FFT (Fast Fourier Transform) can be performed on the second echo signal to convert the second echo signal from the time domain to the frequency domain, resulting in a spectrum diagram (also known as a spectrum distribution diagram). This spectrum diagram reflects the relationship between the echo signal in terms of distance (i.e., the distance between the obstacle and the radar) and energy (also known as intensity, amplitude, or magnitude). For ease of distinction, this spectrum diagram is referred to as the second spectrum diagram.

[0086] Step 304: Extract the second feature of the distribution of the first target object and the second target object from the second spectrum map.

[0087] For the second echo signal collected by the radar at each marker position in the car, the first target and the second target can be searched from the second echo signal according to the preset feature extraction method, and the features distributed in the frequency domain can be extracted, which are denoted as the second spectrum features.

[0088] When the car is at the same marker position, the distribution of the first target and the second target relative to the car is the same within the radar's scan range. Therefore, the second echo signals collected when the car is at the same marker position are similar or the same, making the second feature extracted from the second echo signal that the first target and the second target in terms of distribution are also similar or the same.

[0089] When the car is in different marker positions, the distribution of each first target and second target within the radar's scan range relative to the car is different. Even with the same reflector, its straight-line distance relative to the radar will change. Therefore, the second echo signal collected by the car at different marker positions will be different, resulting in different extraction of the second characteristics of the first and second targets in terms of distribution from the second echo signal. In one embodiment of this application, step 304 may include the following steps:

[0090] Step 3041: Locate the second peak points representing the first target object and the second target object respectively in the second spectrum diagram.

[0091] In this embodiment, the second spectrum map has multiple peak points, referred to as the second peak points. The second peak points are traversed in the second spectrum map to find the second peak points that represent the distribution of the first target object and the second target object.

[0092] In one embodiment of this application, step 3041 may further include the following steps:

[0093] S411. Query the actual distance between the radar and the first target, and use it as the first baseline length.

[0094] Since the first target and the radar are on the same vertical line, when the car stops at the marker position closest to the first target, the technician can manually measure the actual distance between the radar and the first target (i.e., the straight-line distance between the radar and the first target) and store it in the database. At this time, under the given marker position, the actual distance between the radar and the first target can be queried from the database and recorded as the first baseline length.

[0095] S412, query the length of the first side and the length of the second side respectively.

[0096] S413. Calculate the actual distance between the radar and the second target using the first side length, the second side length, and the first baseline length according to the geometric relationship, and use this distance as the second baseline length.

[0097] Since the second target and the radar are not on the same vertical line, when the car stops at each marker position, the actual distance between the radar and the second target can be measured indirectly (i.e., the straight-line distance between the radar and the second target), and recorded as the second baseline length.

[0098] In practice, when the car stops at the marker position closest to the first target object, technicians can manually measure the first side length and the second side length. The first side length is the vertical distance between the first target object and the second target object, and the second side length is the horizontal distance between the first target object and the second target object. The first side length and the second side length are stored in the database. At this time, under the given marker position, the first side length and the second side length can be queried in the database respectively.

[0099] At this point, the actual distance between the radar and the second target can be calculated using the first side length, the second side length, and the first baseline length, based on geometric relationships such as the Pythagorean theorem, and used as the second baseline length.

[0100] For example, such as Figure 4As shown, the relationship between radar 140, first target 150, second target 160 and second target 170 is simplified. Radar 140 is marked as point F, first target 150 is marked as point A, second target 160 is marked as point B, and second target 170 is marked as point C. Point B is projected vertically to point D, and point C is projected vertically to point E.

[0101] In this example, the technician can pre-measure AF (first baseline length), AD (first side length), and BD (second side length).

[0102] In triangle FBD, BF (second baseline length):

[0103]

[0104] In triangle FCE, CF (second baseline length):

[0105]

[0106] S414. If a second peak point is found whose distance matches the length of the first baseline, then the second peak point is marked as the first target object.

[0107] In this embodiment, the distance between the first baseline length and each second peak point is compared. If the difference between the two is within a preset range, it can be considered that the distance between the first baseline length and the second peak point is small, and the distance between the first baseline length and the second peak point is matched. At this time, the second peak point can be marked as the first target object, that is, the second peak point represents the first target object.

[0108] S415. If a second peak point is found whose distance matches the length of the second baseline, then mark the second peak point as the second target object.

[0109] In this embodiment, the distances between each second baseline length and each second peak point are compared. If the difference between the two is within a preset range, it can be considered that the distance between the second baseline length and the second peak point is small, and the distance between the second baseline length and the second peak point is matched. At this time, the second peak point can be marked as the second target object, that is, the second peak point represents the second target object.

[0110] S416. Track the first target and the second target respectively, and mark the first target and the second target to the second peak point.

[0111] If the car moves from the marker position closest to the first target object, but is not located at the initial marker position thereafter, then based on the marker positions where each reflector (including the first reflector and the second reflector) has been marked, methods such as uniform motion, uniform acceleration motion, and Kalman linear filtering can be used to track each reflector (including the first reflector and the second reflector), thereby marking each reflector (including the first reflector and the second reflector) to the corresponding second peak point.

[0112] In another embodiment of this application, considering that the first baseline length is manually measured in the above method, and the second baseline length is calculated using the manually measured first side length and second side length, and the second peak point of the first target object and the second target object in the spectrum is determined by matching the first baseline length and the second baseline length, the manual measurement input increases the probability of error. In this regard, this embodiment proposes an automatic learning method to avoid the probability of error in manual measurement.

[0113] In this embodiment, step 3041 may further include the following steps:

[0114] S417. In the second spectrum diagram, mark the second peak point with the largest amplitude as the first target object.

[0115] When the car stops at the marker position closest to the first target, given the installation position of the first target, the amplitude of the second peak point corresponding to the echo signal reflected by the first target is generally the highest. Therefore, the amplitudes of different second peak points can be compared in the second spectrum diagram to obtain the second peak point with the largest amplitude, and this second peak point is marked as the first target.

[0116] S418. Query the third spectrum diagram converted from the third echo signal.

[0117] In this embodiment, when the first target has been installed but the second target has not been installed, the car stops at the marker position closest to the first target, and the control radar sends an electromagnetic wave signal to the first target and receives the echo signal reflected by the shaft, which is recorded as the third echo signal. That is, the third echo signal is the electromagnetic wave signal sent by the radar to the first target and reflected by the shaft when the first target has been installed but the second target has not been installed.

[0118] Perform FT, FFT and other operations on the third echo signal to convert the third echo signal from the time domain to the frequency domain and obtain a spectrum diagram, which reflects the relationship between the echo signal in distance (i.e. the distance between the obstacle and the radar) and energy (also known as intensity, amplitude, or magnitude). For easy distinction, this spectrum diagram is denoted as the third spectrum diagram.

[0119] S419. Compare the differences between the second and third spectrograms.

[0120] S420. Mark the second peak point representing the difference on the second spectrum as the second target object.

[0121] Since the difference between the second and third spectrograms lies in whether a second target object is installed, we can compare each second peak point in the second spectrogram with each third peak point in the third spectrogram to find the difference between them. This difference is that the second spectrogram has one or more additional second peak points compared to the third spectrogram. At this time, the second peak point can be marked as the second target object.

[0122] Furthermore, when there are two or more second targets, the second spectrum map has two or more additional second peak points compared to the third spectrum map. Considering that the order of the distances between the second targets and the radar is known, and the order of the distances between the second peak points is also known, the second peak point can be labeled as the second target for the second peak point and the second target that are in the same order.

[0123] For example, such as Figure 4 As shown, the first target 150 is marked as R1, the second target 160 as R2, and the third target 170 as R3. When R1, R2, and R3 are installed, a radar scan is performed, yielding the following results: Figure 5A The second spectrum diagram shown was obtained by scanning with radar during the installation of R1 and the removal of R2 and R3. Figure 5B The third spectrum diagram shown, in such a way Figure 5A In the second spectrum diagram shown, the second peak point with the largest amplitude is marked as R1, as follows: Figure 5A The second spectrum diagram shown is relative to, for example, Figure 5B The third spectrum diagram shown has two more second peak points. Since the vertical height of R2 is higher than that of R3, the second peak point with a larger distance is labeled R2 and the second peak point with a smaller distance is labeled R3.

[0124] S421. Track the first target and the second target respectively, and mark the first target and the second target to the second peak point.

[0125] Step 3042: If a second peak point representing the first target object and the second target object is found, calculate the second distance between the distances of the second peak points corresponding to two adjacent reflectors, as the second feature of the distribution of the first target object and the second target object.

[0126] In this embodiment, the reflectors (including the first target and the second target) can be sorted in a certain way, such as sorting them according to their height in the vertical direction, so as to obtain the adjacency relationship of each reflector.

[0127] If a second peak point representing the first target and the second target is found on the second spectrogram, the difference between the distances of the second peak points corresponding to two adjacent reflectors can be calculated to obtain the second spacing, which can be used as the second feature of the distribution of the first target and the second target.

[0128] For example, such as Figure 4 As shown, the first target object 150 is marked as R1, the second target object 160 is marked as R2, and the second target object 170 is marked as R3. Then, the second distance between R1 and R2 is D(R1,R2) = AF - BF, and the second distance between R2 and R3 is D(R2,R3) = BF - CF.

[0129] Step 305: Mark the distance between the radar and the first target object using the second feature.

[0130] In this embodiment, a second peak point representing the first target can be found in the second spectrum. The distance of the second peak point represents the distance between the radar and the first target. This distance is marked in the second feature as the position of the car in the hoistway.

[0131] In one example, such as Figure 4 As shown, the car is controlled to move from the top of the hoistway to the bottom of the hoistway. At each interval, the distance and amplitude corresponding to the second peak point of each reflector (including the first target 150, the second target 160 and the second target 170) are recorded at the corresponding marker position. The second interval between each reflector (including the first target 150, the second target 160 and the second target 170) is calculated, and the position of the car in the hoistway is recorded.

[0132] If the first target object 150 is marked as R1, the second target object 160 as R2, and the second target object 170 as R3, then the following record can be formed:

[0133] The distance and amplitude of reflector R1 (S) i1 A i1 )

[0134] The distance of reflector R2 and the amplitude R2(S) i2 A i2 )

[0135] The distance and amplitude of reflector R3 (S) i3 Ai3 )

[0136] The second distance d between reflector R1 and reflector R2 i (R1,R2)

[0137] The second distance d between reflectors R2 and R3 i (R2,R3)

[0138] The position S of the car in the hoistway i =S i1 .

[0139] Where S represents distance, A represents amplitude, i = 0, 1, 2, 3, ..., N, N is the number of flag bits, and i is the flag bit number.

[0140] Example 2

[0141] Figure 6 This is a flowchart of a radar ranging method provided in Embodiment 2 of this application. This embodiment applies a matching method to detect the position of the car in the hoistway, based on Embodiment 1. Figure 6 As shown, the method includes:

[0142] Step 601: Control the radar to transmit electromagnetic wave signals to multiple reflectors and receive the first echo signal reflected by the shaft.

[0143] When the elevator is in normal operation, it carries people or goods. Passengers in the waiting hall and inside the car can control the elevator car to glide in the shaft and move to different floors.

[0144] During normal elevator operation, at initial power-on and at preset time intervals, the car control radar can be controlled to send electromagnetic wave signals toward multiple reflectors (including the first target and the second target). The electromagnetic wave signals propagate through the atmosphere and reach various obstacles within the radar's scanning range in the shaft. At this time, the electromagnetic wave signals will be reflected and scattered on the surface of the obstacles.

[0145] These obstacles may include reflectors (including the first target and the second target), guide rail supports, thresholds and other highly reflective metal objects, as well as obstacles with low reflectivity such as side walls, and so on.

[0146] The radar can receive electromagnetic wave signals reflected from various obstacles within the radar's scan range in the shaft. Because the electromagnetic wave signal absorbs some of its energy through the reflector, it generates an original electromagnetic wave signal with attenuation delay. This original electromagnetic wave signal is superimposed on the original electromagnetic wave signal to form an echo signal. For ease of distinction, this echo signal is denoted as the first echo signal.

[0147] Step 602: Convert the first echo signal to the first spectrum diagram.

[0148] In this embodiment, operations such as FT and FFT can be performed on the first echo signal to convert the first echo signal from the time domain to the frequency domain and obtain a spectrum diagram. For easy distinction, this spectrum diagram is referred to as the first spectrum diagram.

[0149] Step 603: Extract the first feature of the distribution of the first target object and the second target object from the first echo signal.

[0150] In this embodiment, the features of the first target object and the second target object distributed in the frequency domain can be extracted from the first echo signal according to a preset feature extraction method, and denoted as the first feature.

[0151] Furthermore, the feature extraction method for extracting the first feature from the first echo signal is the same as the feature extraction method for extracting the second feature from the second echo signal. In one embodiment of this application, step 603 may include the following steps:

[0152] Step 6031: Sort the multiple first peak points with the highest amplitude in the first spectrum according to the distance to obtain the peak point sequence.

[0153] The first spectrum has multiple peak points, denoted as the first peak point, which can be recorded as (S1,A1), (S2,A2)...(S...). N A N ), where S represents distance, A represents amplitude, and N represents the number of first peak points.

[0154] Considering that the amplitude of the first peak point corresponding to any reflector is relatively high, in order to reduce the number of first peak points and reduce the amount of computation for subsequent matching, the first peak points with the first m (m is a positive integer) positions of amplitude can be extracted from the first spectrum diagram, that is, the m first peak points with the highest amplitude can be extracted.

[0155] Where m is an empirical value that can cover the range of the wellbore, thereby ensuring that the first peak point corresponding to any reflector is among the m first peak points.

[0156] In this embodiment, the first peak points can be sorted sequentially according to their distances to obtain the peak point sequence X. j (S j A j ), where j takes values ​​of 1, 2, ..., m.

[0157] Furthermore, the sorting order can be either sorting multiple first peak points from largest to smallest distance or sorting multiple first peak points from smallest to largest distance; this embodiment does not impose any restrictions on this.

[0158] Step 6032: Extract multiple first peak points from the peak point sequence, with the same number as the reflector.

[0159] In this embodiment, multiple first peak points can be extracted sequentially from the peak point sequence according to the sorting order. In each first peak point, the first peak points are sorted consecutively, and the number of first peak points is equal to the number of reflectors.

[0160] Taking three reflectors as an example, three consecutive first peak points are extracted from the peak point sequence in order of distance, denoted as X. j (S j A j ), X j+1 (S j+1 A j+1 ), X j+2 (S j+2 A j+2 ).

[0161] Step 6033: For each first peak point, calculate the first distance between two adjacent first peak points, as the first feature of the distribution of the first target object and the second target object.

[0162] In each set of first peak points, the first peak points have a sorting order. According to this sorting order, the adjacency relationship between the first peak points can be determined. At this time, the difference between the distances of two adjacent first peak points can be calculated to obtain the first spacing. The first spacing is set as the first feature of the distribution of the first target and the second target.

[0163] Taking the three first peak points as an example, the first spacing corresponding to these three first peak points can be expressed as d(x) j ,x j+1 ) = S j -S j+1， d(x j+1 ,x j+2 ) = S j+1 -S j+2 .

[0164] Step 604: Match the first feature with the second feature that has been learned in advance on the distribution of the first target object and the second target object.

[0165] In this embodiment, the second features of the distribution of the first target object and the second target object can be queried in advance, and the first feature can be matched with each second feature to calculate the similarity between the first feature and each second feature.

[0166] In a practical implementation, a second feature that has been pre-learned in terms of the distribution of the first target object and the second target object can be retrieved from a database or cache, and then matched with the first spectral feature.

[0167] The first feature includes a first spacing between multiple first peak points, and the second feature includes a second spacing between multiple second peak points, where the second peak points represent reflectors.

[0168] For each first feature, the difference between the first spacing and the second spacing is calculated as the spacing deviation. Each spacing deviation is compared with a preset spacing threshold. Since radar measurements may contain noise, the measured distance may be too large or too small. For ease of comparison, the distance deviation can be taken as the absolute value. Each spacing deviation (absolute value) is compared with the preset spacing threshold.

[0169] If all spacing deviations are less than or equal to the spacing threshold, it means that the distribution of obstacles represented by the first peak point is close to the distribution of reflectors represented by the second peak point, and then it can be determined that the first feature and the second feature are successfully matched.

[0170] If at least one spacing deviation is greater than the spacing threshold, it indicates that there is a large deviation between the distribution of obstacles represented by the first peak point and the distribution of reflectors represented by the second peak point, and the first feature and the second feature are determined to be mismatched.

[0171] When a first feature and a second feature match successfully, the matching can be stopped.

[0172] When a first feature fails to match a second feature, the process continues by matching the next set of first features with the second feature, until all first features fail to match the second feature. Then, the first feature of the current first spectrogram is matched with the next set of second features, and this process is repeated. For example, suppose three reflectors are installed in a shaft, and the second spacing in the pre-learned second features is represented by d. i (R1, R2), d i (R2, R3), during ranging, three first peak points are extracted sequentially from the first spectrum. Therefore, the first spacing in the first feature is represented as d(x). j ,x j+1 ), d(x j+1 ,x j+2 Match the first spacing in the first feature with the second spacing in the second feature, when |d(x j ,x j+1 )-d i (R1, R2)|≤ threshold, and when |d(x j+1 ,x j+2 )-d iIf (R2, R3)| ≤ the threshold, then the first feature and the second feature are successfully matched. If the result of one of the calculations is greater than the threshold, then the first feature and the second feature are not matched, and the next first peak point X can be extracted. j+1 (S j+1 A j+1 ), X j+2 (S j+2 A j+2 ), X j+3 (S j+3 A j+3 Matching is performed.

[0173] Step 605: If the match is successful, extract the distance between the radar and the first target object that is labeled with the second feature, and use it as the position of the car in the hoistway.

[0174] In this embodiment, when learning the second feature, the distance between the radar and the first target can be marked on the second feature at that time.

[0175] When the first feature successfully matches a set of second features, the car can be considered to be in the same position as when the second feature was learned. Then, the distance between the radar and the first target object, which is labeled with the second feature, can be queried and assigned as the current distance between the radar and the first target object, thus mapping it to the position of the car in the hoistway.

[0176] In this embodiment, multiple reflectors are installed in the hoistway. The reflectors include a first target object located at one end of the hoistway and a second target object located at a non-end point of the hoistway. A radar is installed in the car sliding in the hoistway. The radar is controlled to emit electromagnetic wave signals to the multiple reflectors and receive the first echo signal reflected by the hoistway. The first echo signal is converted into a first spectrum. A first feature of the distribution of the first target object and the second target object is extracted from the first echo signal. The first feature is matched with a second feature that has been pre-learned on the distribution of the first target object and the second target object. If the match is successful, the distance between the radar and the first target object, which is labeled with the second feature, is extracted as the position of the car in the hoistway. When the car is in the same position, the distribution of reflectors within the radar's scanning range is the same. The collected echo signals are similar or identical, making the extracted features of each reflector's distribution similar or identical. When the car is in different positions, the distribution of reflectors within the radar's scanning range differs, resulting in different collected echo signals and thus different extracted features of each reflector's distribution. Reflectors and highly reflective obstacles such as metal objects do not affect the distribution of each reflector. Therefore, the second target object plays an auxiliary role in positioning the first target object. By matching the first and second features, the position of the car in the hoistway can be measured. This reduces interference from highly reflective obstacles such as metal objects, ensuring positional accuracy. Regardless of where the radar is powered on, the position of the car in the hoistway can be measured normally, ensuring the safe operation of the elevator.

[0177] Furthermore, compared to methods that indirectly measure the car's position in the hoistway, such as leveling sensors and traction machine encoders, this embodiment uses radar to directly measure the car's position in the hoistway, saving on various switches within the hoistway and significantly reducing costs.

[0178] Example 3

[0179] In Example 1, it is required that the car is in the hoistway and the radar receives the second echo signals of all reflectors (including the first target and the second target). However, for hoistways with a low top floor height or shallow bottom floor depth, when the car moves to the end point of the hoistway (i.e., the top or bottom floor), the radar may scan the first target but not all the second targets (it may not scan any second target or may scan only some second targets). This results in the radar receiving the second echo signal of the first target but not the second echo signal of the second target. Therefore, in a certain area at the end point of the hoistway, since not all second targets can be illuminated, the second targets that are not illuminated do not have a corresponding second peak point for the second echo signal. Therefore, it is impossible to find each reflector (including the first target and the second target) using the second spacing of each reflector (including the first target and the second target) throughout the entire hoistway.

[0180] Figure 7 This is a flowchart of a radar ranging method provided in Embodiment 3 of this application. Based on Embodiment 1, this embodiment transitions from learning the distribution features of a first target object to learning the distribution features of both the first and second target objects.

[0181] Specifically, when the car is near the end of the hoistway, the vertical distance between the first target and the radar is kept within a certain range to ensure that the second peak point corresponding to the second echo signal of the first target is at its maximum amplitude. As the car moves, the distance between the first target and the radar gradually increases, and the amplitude of the second peak point corresponding to the second echo signal of the first target gradually decreases. Before the second target falls, the radar can illuminate the second target, and thus learn the second distance between the first and second targets.

[0182] like Figure 7 As shown, the method includes the following steps:

[0183] Step 701: Starting from the marker closest to the first target, control the car to move sequentially to each marker in the hoistway.

[0184] When the car reaches the end of the hoistway, the radiation intensity of the second echo signal of the first target object should be maximized.

[0185] like Figure 8 As shown, let the patterned beamwidth (FNBW) of the radar in the antenna direction be α, and the patterned beamwidth (FNBW) of the electromagnetic wave signal received by the first target be β. In order to ensure that the second echo signal of the first target has the maximum radiation intensity, it is sufficient to ensure that the radiation intensity of the electromagnetic wave signal received by the first target is greater than 50% of the total radiation intensity. The distance between the first target and the radar can be calculated through this relationship, and the distance value is denoted as L0. Therefore, when installing the first target, if the radar can just receive the second echo signal reflected by the second target, the actual distance between the first target and the radar is less than L0, which satisfies the requirement that the amplitude of the second peak point corresponding to the second echo signal reflected by the first target is the maximum.

[0186] Step 702: In each flag position, control the radar to send electromagnetic wave signals to multiple reflectors and receive the second echo signal reflected by the well passage.

[0187] Step 703: Convert the second echo signal to the second spectrum diagram.

[0188] Step 704: Locate the second peak points representing the first target object and the second target object respectively in the second spectrum diagram.

[0189] In this embodiment, each marker in the hoistway is divided into a local scanning stage and a global scanning stage. In the local scanning stage, the car's radar can scan the first target object, but cannot scan the second target object or scans only part of the second target object. In the global scanning stage, the car's radar can scan the first target object and scan all the second target objects.

[0190] The starting position of the local scanning phase is the marker closest to the first target object.

[0191] During the local scanning phase, for each flag bit, determine whether the first target object and the second target object that match the prior knowledge are found in the second spectrogram.

[0192] Furthermore, the actual distance between the radar and the first target is queried and used as the first baseline length; the first side length and the second side length are queried respectively, where the first side length is the vertical distance between the first and second targets and the second side length is the horizontal distance between the first and second targets; the actual distance between the radar and the second target is calculated using the first side length, the second side length, and the first baseline length according to geometric relationships, and used as the second baseline length; in the second spectrum diagram, it is determined whether a second peak point matching the distance of the first and second baseline lengths is found. If not found, it is determined that the system is in the local scanning stage; if found, it is determined that the system is in the global scanning stage, and the determination stops.

[0193] If the car is in the partial scanning stage, the amplitude of each second peak point in the second spectrum can be compared, and the second peak point with the largest amplitude can be marked as the first target object in the second spectrum.

[0194] If the car is in the global scanning phase, query the actual distance between the radar and the first target object, and use it as the first baseline length; query the first side length and the second side length respectively, where the first side length is the vertical distance between the first target object and the second target object, and the second side length is the horizontal distance between the first target object and the second target object; calculate the actual distance between the radar and the second target object according to the geometric relationship using the first side length, the second side length, and the first baseline length, and use it as the second baseline length; if a second peak point is found whose distance matches the first baseline length, then mark the second peak point as the first target object; if a second peak point is found whose distance matches the second baseline length, then mark the second peak point as the second target object.

[0195] Step 705: If a second peak point representing the first target object is found, but no second peak point representing the second target object is found, then the distance between the second peak point representing the first target object is set as the second feature of the distribution of the first target object and the second target object.

[0196] When searching for a second peak point representing the first target in the second spectrum, and not finding a second peak point corresponding to all second targets, it indicates that when the car reaches the end point of the hoistway (i.e., the top or bottom floor), the radar may scan the first target but cannot scan all the second targets (cannot scan any second target or scans some second targets). In this case, the distance of the second peak point representing the first target can be set as the second characteristic of the distribution of the first and second targets.

[0197] Step 706: If a second peak point representing the first target and the second target is found, calculate the second distance between the distances of the second peak points corresponding to two adjacent transmitters, as the second feature of the distribution of the first target and the second target.

[0198] Step 707: Track the first target object and the second target object respectively, so as to mark the first target object and the second target object to the second peak point.

[0199] Step 708: Mark the distance between the radar and the first target object using the second feature.

[0200] In this embodiment, a second peak point representing the first target can be found in the second spectrum. The distance of the second peak point represents the distance between the radar and the first target. This distance is marked in the second feature as the position of the car in the hoistway.

[0201] In one example, such as Figure 4 As shown, the car is controlled to move from the top of the hoistway to the bottom of the hoistway. At each interval, the distance and amplitude corresponding to the second peak point of each reflector (including the first target 150, the second target 160 and the second target 170) are recorded at the corresponding marker position. The second interval between each reflector (including the first target 150, the second target 160 and the second target 170) is calculated, and the position of the car in the hoistway is recorded.

[0202] If the first target object 150 is marked as R1, the second target object 160 as R2, and the second target object 170 as R3, then the following record can be generated during the local scanning phase:

[0203] The distance and amplitude of reflector R1 (S) i1 A i1 )

[0204] The position S of the car in the hoistway i =S i1 .

[0205] During the global scan phase, the following records can be generated:

[0206] The distance and amplitude of reflector R1 (S) i1 A i1 )

[0207] The distance of reflector R2 and the amplitude R2(S) i2 A i2 )

[0208] The distance and amplitude of reflector R3 (S) i3 A i3 )

[0209] The second distance d between reflector R1 and reflector R2 i (R1,R2)

[0210] The second distance d between reflectors R2 and R3 i (R2,R3)

[0211] The position S of the car in the hoistway i =S i1 .

[0212] Where S represents distance, A represents amplitude, i = 0, 1, 2, 3, ..., N, N is the number of flag bits, and i is the flag bit number.

[0213] Example 4

[0214] Figure 9 This is a flowchart of a radar ranging method provided in Embodiment 4 of this application. Based on Embodiment 3, this embodiment applies a matching method to detect the position of the car in the hoistway. Figure 9 As shown, the method includes:

[0215] Step 901: Control the radar to transmit electromagnetic wave signals to multiple reflectors and receive the first echo signal reflected by the shaft.

[0216] Step 902: Convert the first echo signal to the first spectrum diagram.

[0217] Step 903: Extract the first feature of the distribution of the first target object and the second target object from the first echo signal.

[0218] In this embodiment, each marker in the hoistway is divided into a local scanning stage and a global scanning stage. In the local scanning stage, the car's radar can scan the first target object, but cannot scan the second target object or scans only part of the second target object. In the global scanning stage, the car's radar can scan the first target object and scan all the second target objects.

[0219] For the local scanning stage, the amplitudes of each first peak point on the first spectrogram can be compared to find the first peak point with the largest amplitude on the first spectrogram, which can be used as the first feature of the distribution of the first target and the second target.

[0220] For the global scanning phase, the highest amplitude peaks in the first spectrum can be sorted by distance to obtain a peak sequence. Multiple sets of peaks, each equal in number to the reflector, are then extracted from this peak sequence.

[0221] For each first peak point, the first gap between two adjacent first peak points is calculated as the first feature of the distribution of the first target object and the second target object.

[0222] Step 904: Find the second feature that was learned in advance on the distribution of the first target object and the second target object.

[0223] The second feature includes a second spacing between multiple second peak points.

[0224] Step 905: Calculate the difference between each first spacing and the second spacing, as the spacing deviation.

[0225] Step 906: If all spacing deviations are less than or equal to the spacing threshold, then the first feature and the second feature are determined to be a successful match.

[0226] Step 907: If at least one spacing deviation is greater than the spacing threshold, then it is determined that the first feature and the second feature have failed to match.

[0227] Step 908: If the first feature and the second feature fail to match multiple times, then compare the first peak point with the largest amplitude in the first feature with the second peak point with the largest amplitude in the second feature.

[0228] If multiple matching attempts between the first feature and the second feature fail, it indicates that the car is likely in the local scanning phase. In this case, the first feature extracted during the local scanning phase (i.e., the first peak point with the largest amplitude) can be compared with the second feature learned during the local scanning phase (i.e., the second peak point with the largest amplitude).

[0229] In one embodiment of this application, step 908 may include the following steps:

[0230] Step 9081: Calculate the first difference between the distance to the first peak point with the largest amplitude in the first feature and the distance to the second peak point with the largest amplitude in the second feature.

[0231] In this embodiment, the first peak point P(S,A) with the largest amplitude is selected on the first spectrogram, where S is the distance and A is the amplitude. The first peak point P with the largest amplitude among the pre-learned groups of second features is selected. i1 (S i1 A i1 ), where i is the group number.

[0232] Therefore, the distance S between the first peak point P(S,A) and the second peak point P is calculated. i1 (S i1 A i1 The distance S) i1 The difference between them is denoted as the first difference.

[0233] For example, a first difference is calculated between the distance to the first peak point with the largest amplitude in the first feature and the distance to the second peak point with the largest amplitude in the second feature. The first difference is obtained by squaring the first difference.

[0234] Step 9082: Calculate the second difference between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature.

[0235] In this embodiment, the amplitude A of the first peak point P(S,A) and the amplitude of the second peak point P are calculated. i1 (S i1 A i1 The amplitude A i1 The difference between them is denoted as the second difference.

[0236] For example, a second difference is calculated between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature. The second difference is obtained by squaring the second difference.

[0237] Step 9083: Merge the first difference and the second difference into the third difference.

[0238] In this embodiment, the first peak point with the largest amplitude is extracted from the first feature, and the second peak point with the largest amplitude is extracted from the second feature. The first difference in distance and the second difference in amplitude are linearly or non-linearly fused into the difference between the first peak point and the second peak point, which is denoted as the third difference.

[0239] For example, the first difference is multiplied by the first weight to obtain the first adjustment value; the second difference is multiplied by the second weight to obtain the second adjustment value.

[0240] The third difference is obtained by taking the square root of the sum between the first and second adjustment weights.

[0241] Normally, the sum of the first weight and the second weight is 1. Considering that the reflector in the shaft may have tilting, deformation, etc., which may cause the first echo signal to change to a certain extent relative to the second echo signal, and these situations will not affect the distance between the reflector and the radar, that is, the distance generally will not change, therefore, the first weight can be set to be greater than or equal to the second weight.

[0242] In this example, the third difference is represented as follows:

[0243]

[0244] Where Δ is the third difference, α is the first weight, β is the second weight, α+β=1, and α≥β.

[0245] Step 9084: If the third difference is less than or equal to the preset deviation threshold, then the first peak point with the largest amplitude in the first feature is determined to be the same as the second peak point with the largest amplitude in the second feature.

[0246] Generally, the greater the third difference, the lower the similarity between the first and second features; conversely, the smaller the third difference, the higher the similarity between the first and second features.

[0247] In this embodiment, the third difference is compared with a preset deviation threshold. When the third difference is less than or equal to the deviation threshold, it indicates that the similarity between the first feature and the second feature is high. Therefore, it can be determined that the first peak point with the largest amplitude in the first feature is the same as the second peak point with the largest amplitude in the second feature.

[0248] Step 909: If the first peak point with the largest amplitude in the first feature is the same as the second peak point with the largest amplitude in the second feature, then the first feature and the second feature are successfully matched.

[0249] If the first peak point with the largest amplitude in the first feature is the same as the second peak point with the largest amplitude in the second feature, then the first feature (the first peak point with the largest amplitude) and the second feature (the second peak point with the largest amplitude) are successfully matched.

[0250] Step 910: If the match is successful, extract the distance between the radar and the first target object that is labeled with the second feature, and use it as the position of the car in the hoistway.

[0251] If the first feature (the first peak point with the largest amplitude) matches the second feature (the second peak point with the largest amplitude), it indicates that the car has a high probability of being in the local scanning phase. Then, the distance between the radar and the first target object, which is labeled with the second feature, is extracted and assigned as the current distance between the radar and the first target object, thus mapping it to the car's position in the hoistway.

[0252] Example 5

[0253] In Example 1, the second spacing between the second echo signals of each reflector (including the first target and the second target) is matched in real time in the first spectrum diagram to locate each reflector. Due to the complex environment of the shaft, there are numerous other obstacles reflecting echo signals in the first spectrum diagram. There is a possibility that the spacing between the first peak points of multiple interference signals exactly matches the second spacing between the second echo signals of each reflector (including the first target and the second target). In this case, these obstacles can be recorded as interference objects, and their echo signals can be recorded as interference signals.

[0254] Figure 10 This is a flowchart of a radar ranging method provided in Embodiment 5 of this application. This embodiment learns the characteristics of obstacles (i.e., interference signals) that are similar or the same as the reflector in distribution, based on Embodiment 1.

[0255] Specifically, at any time when the second characteristics of the first target object and the second target object are learned in advance in the distribution, while storing the second characteristics of the first target object and the second target object, the second characteristic information of the first target object and the second target object in the distribution is used to search for interference signals that are the same as or similar to the second characteristic information of the first target object and the second target object in the distribution in the second spectrum.

[0256] like Figure 10 As shown, the method includes the following steps:

[0257] Step 1001: Starting from the marker closest to the first target, control the car to move sequentially to each marker in the hoistway.

[0258] Step 1002: In each flag position, control the radar to send electromagnetic wave signals to multiple reflectors and receive the second echo signal reflected by the well passage.

[0259] Step 1003: Convert the second echo signal to the second spectrum diagram.

[0260] Step 1004: Locate the second peak points representing the first target object and the second target object respectively in the second spectrum diagram.

[0261] In this embodiment, it can be referred to Figure 5A and Figure 5B In this way, the second peak points corresponding to the first target and the second target are found and tracked in the second spectrum, and the distance and amplitude of these second peak points are recorded.

[0262] Taking three reflectors as an example, the second peak point can be denoted as (S 01 A 02 ), (S02 A 03 ), (S 03 A 04 ).

[0263] Step 1005: If a second peak point representing the first target and the second target is found, calculate the second distance between the distances of the second peak points corresponding to two adjacent transmitters, as the second feature of the distribution of the first target and the second target.

[0264] When a second peak point representing the first target and the second target is found in the second spectrum, two second peak points representing two adjacent transmitters are found in the second spectrum, and the second spacing between the distances corresponding to the two second peak points is calculated as a second feature of the distribution of the first target and the second target.

[0265] Step 1006: Extract the second peak points representing interference objects from the second spectrum diagram, with the same number as the number of reflectors.

[0266] If the second peak points representing the first target and the second target are already marked in the second spectrum diagram, the second peak points representing the first target and the second target can be excluded, and the number of second peak points representing the interfering objects can be extracted from the other second peak points, which is equal to the number of the reflector.

[0267] Considering that the amplitude of the second peak point corresponding to any reflector is relatively high, the amplitude of the second peak point of the interfering object causing the interference is also relatively high. In order to reduce the number of second peak points and reduce the amount of computation for subsequent matching, the second peak points with the first m (m is a positive integer) amplitudes can be extracted from the second spectrum diagram, that is, the m second peak points with the highest amplitudes can be extracted.

[0268] Where m is an empirical value that can cover the range of the wellbore, thereby ensuring that the second peak point corresponding to any reflector is among the m second peak points.

[0269] In this embodiment, the second peak points can be sorted sequentially according to their distances to obtain a learning sequence, where j takes values ​​of 1, 2, ..., m.

[0270] Furthermore, the sorting order can be either sorting multiple second peak points from largest to smallest distance or sorting multiple second peak points from smallest to largest distance; this embodiment does not impose any restrictions on this.

[0271] Multiple second peak points are extracted sequentially from the learning sequence according to the sorting order. In each second peak point, the second peak points are sorted consecutively, and the number of second peak points is equal to the number of reflectors.

[0272] Step 1007: Calculate the third spacing between the distances of the second peak points corresponding to two adjacent interfering objects.

[0273] In each set of second peak points, the second peak points have a sorting order. According to this sorting order, the adjacency relationship between the second peak points can be determined. At this time, the difference between the distances of two adjacent second peak points can be calculated to obtain the third spacing.

[0274] Taking three second peak points as an example, three consecutive second peak points are extracted from the learning sequence in order of distance, denoted as X. j (S j A j ), X j+1 (S j+1 A j+1 ), X j+2 (S j+2 A j+2 The third spacing corresponding to these three second peak points can be expressed as d(x). j ,x j+1 ) = S j -S j+1， d(x j+1 ,x j+2 ) = S j+1 -S j+2 .

[0275] Step 1008: Calculate the difference between each second spacing and each third spacing, as the interference deviation.

[0276] In this embodiment, multiple spacing pairs can be divided, including second and third spacing pairs with the same order. For each second spacing pair, the difference between the second and third spacing pairs is calculated and recorded as the interference deviation.

[0277] Step 1009: If all interference deviations are less than or equal to the interference threshold, then the second spacing and the third spacing are successfully matched, and the third spacing is added as the second feature of the distribution of the first target and the second target.

[0278] In this embodiment, the interference deviation is compared with a preset distance threshold.

[0279] If all interference deviations are greater than the interference threshold, it indicates that the distribution of the reflector and a certain group of interfering objects on the echo signal is significantly different, and it can be determined that the second spacing and the third spacing have failed to match.

[0280] If all interference deviations are less than or equal to the interference threshold, it indicates that the reflector and a group of interfering objects are distributed relatively closely in the echo signal. It can then be determined that the second spacing and the third spacing are successfully matched, and the third spacing is added as the second feature of the distribution of the first target and the second target.

[0281] Considering that there may be more than one group of interfering objects whose distribution on the echo signal is the same or similar to that of the reflector, for a certain group of interfering objects, regardless of whether the third spacing and the second spacing match successfully or not, the third spacing and the second spacing of the next group of interfering objects can be matched until all interfering objects have been traversed. Step 1010: Mark the distance between the radar and the first target object using the second feature.

[0282] In one example, such as Figure 4 As shown, the car is controlled to move from the top of the hoistway to the bottom of the hoistway. At each interval, the distance and amplitude corresponding to the second peak point of each reflector (including the first target 150, the second target 160 and the second target 170) are recorded at the corresponding marker position. The second interval between each reflector (including the first target 150, the second target 160 and the second target 170) is calculated, and the position of the car in the hoistway is recorded.

[0283] If the first target object 150 is marked as R1, the second target object 160 as R2, and the second target object 170 as R3, then the following record can be formed:

[0284] The distance and amplitude of reflector R1 (S) i1 A i1 )

[0285] The distance of reflector R2 and the amplitude R2(S) i2 A i2 )

[0286] The distance and amplitude of reflector R3 (S) i3 A i3 )

[0287] The second distance d between reflector R1 and reflector R2 i (R1,R2)

[0288] The second distance d between reflectors R2 and R3 i (R2,R3)

[0289] The distance S of the first group of interfering objects d1

[0290] Distance and amplitude of the first group of interfering objects x j (S j Aj ),x j+1 (S j+1 A j+1 ),x j+2 (S j+2 A j+2 )

[0291] The third spacing d(x) between the first group of interfering reflectors j ,x j+1 ),d(x j+1 ,x j+2 )

[0292] …

[0293] The distance S of the M group of interfering objects dM ;

[0294] Distance and amplitude x of the M group of interfering objects j (S j A j ),x j+1 (S j+1 A j+1 ),x j+2 (S j+2 A j+2 )

[0295] The third spacing d(x) between the M group of interfering objects j ,x j+1 ),d(x j+1 ,x j+2 )

[0296] The position S of the car in the hoistway i =S i1 .

[0297] Where S represents distance, A represents amplitude, i = 0, 1, 2, 3, ..., N, N is the number of flag bits, and i is the flag bit number.

[0298] Example 6

[0299] Figure 11 This is a flowchart of a radar ranging method provided in Embodiment Six of this application. Based on Embodiment Five, this embodiment applies a matching method to detect the position of the car in the hoistway. Figure 11 As shown, the method includes:

[0300] Step 1101: Control the radar to transmit electromagnetic wave signals to multiple reflectors and receive the first echo signal reflected by the shaft.

[0301] Step 1102: Convert the first echo signal to the first spectrum diagram.

[0302] Step 1103: Extract the first feature of the distribution of the first target object and the second target object from the first echo signal.

[0303] Step 1104: Find the second feature that was learned in advance on the distribution of the first target object and the second target object.

[0304] The first feature includes a first spacing between multiple first peak points, and the second feature includes a second spacing between multiple second peak points.

[0305] Step 1105: For each first spacing, calculate the difference between each first spacing and each second spacing, as the spacing deviation.

[0306] Step 1106: If all spacing deviations are less than or equal to the spacing threshold, then it is determined that a certain first spacing and second spacing are successfully matched.

[0307] Considering that there may be more than one set of interfering objects whose distribution on the echo signal is the same or similar to that of the reflector on the echo signal, regardless of whether a first spacing and a second spacing are successfully matched or not, the next first spacing and the second spacing can be matched until all first spacings have been traversed.

[0308] Step 1107: If the first feature contains at least two successfully matched first gaps, then compare the distribution of the first peak point in the first feature with the second peak point in the second feature representing the reflector and the interference object, respectively.

[0309] If the first feature contains at least two first gaps that successfully match the second gap, it indicates that there are interfering objects on the echo signal that are the same as or similar to the reflector. In this case, a second feature can be found that was learned in advance based on the distance of the first peak point corresponding to each first gap, and is denoted as the third feature.

[0310] Step 1108: If the distributions are the same, then the first feature and the second feature are successfully matched.

[0311] To distinguish the transmitter from the interfering object by the first spacing that is successfully matched with the second spacing, the distribution of the first peak point in the first feature can be compared with the distribution of the second peak point in the third feature that represents the reflector and the interfering object.

[0312] If the distributions are different, it can be determined that the first feature and the second feature failed to match.

[0313] If the distributions are the same, then the first feature and the second feature have matched successfully. Step 1110: If the match is successful, extract the distance between the radar and the first target object, which are both labeled with the second feature, as the position of the car in the hoistway.

[0314] For example, such as Figure 12 As shown, when the car is 5 meters in the hoistway, a second spectrum diagram 1210 is obtained by radar scanning, which includes the second peak point 1211 corresponding to the reflector and the second peak point 1212 corresponding to the interference. When the car is 10 meters in the hoistway, a second spectrum diagram 1220 is obtained by radar scanning, which includes the second peak point 1221 corresponding to the reflector.

[0315] When the car moves in the hoistway, a radar scan is used at a certain moment to obtain a first spectrum map 1230, in which the first spacing between the first peak points 1231 and the second spacing between the second peak points 1211 are successfully matched, and the first spacing between the first peak points 1232 and the second spacing between the second peak points 1212 are successfully matched. Comparing the first peak points 1231 and 1232 on the first spectrum diagram 1230 with the second peak points 1211 and 1212 on the second spectrum diagram 1210 and the second peak point 1221 on the second spectrum diagram 1220, it is found that the first peak points 1231 and 1232 on the first spectrum diagram 1230 are similar in distribution to the second peak points 1211 and 1212 on the second spectrum diagram 1210, while the first peak points 1231 and 1232 on the first spectrum diagram 1230 are different in distribution from the second peak point 1221 on the second spectrum diagram 1220. At this point, it can be confirmed that the first feature corresponding to the first spectrum diagram 1230 matches the corresponding second feature corresponding to the second spectrum diagram 1210 successfully, while the first feature corresponding to the first spectrum diagram 1230 fails to match the corresponding second feature corresponding to the second spectrum diagram 1220, confirming that the car is located 5 meters from the shaft.

[0316] Example 7

[0317] Figure 13 This is a flowchart of a radar ranging method provided in Embodiment Seven of this application. This embodiment uses the peak value method to track the position of the car in the hoistway, based on Embodiments Two, Four, and / or Six. Figure 13 As shown, the method includes:

[0318] Step 1301: When the car is sliding in the hoistway, predict the first incremental value of the car's sliding between two adjacent moments based on uniform motion.

[0319] When the car is powered on in the hoistway, the initial position of the car in the hoistway can be detected using the matching method. After that, as the car slides in the hoistway, the position of the car in the hoistway can be tracked using the peak method.

[0320] The radar transmits one frame of electromagnetic wave signal at each moment. Since the radar frequency is relatively high, and the car's sliding speed is limited, the motion state of the car between two adjacent moments can be regarded as unchanged. It can be considered that the car moves at a constant speed between two adjacent moments, especially as a constant direct motion.

[0321] Then, by modeling the motion of the car according to uniform motion, the distance the car slides between two adjacent moments is predicted and denoted as the first increment value.

[0322] In practical implementation, the speed v of car k-1 sliding in the shaft at the previous moment can be queried from the elevator control system. k-1 The speed v k-1 Multiplying by the time interval ΔT between two adjacent moments yields the first incremental value v of the car's gliding distance between two adjacent moments. k-1 *ΔT.

[0323] Step 1302: For each reflector, add the distance at the previous moment to the first increment value to obtain the distance at the current moment.

[0324] For each reflector, the distance between the transmitter and the radar measured at the previous time k-1 can be queried. The distance at the previous time k-1 is added to the first increment value at the current time to obtain the distance between the transmitter and the radar measured at the current time k, thus realizing the tracking of each radar.

[0325] Therefore, the tracking process can be expressed as follows:

[0326] S′ k =S k-1 +v k-1 *ΔT

[0327] Among them, S′ k S is the distance at the current time k. k-1 This is the distance at the previous time step k-1.

[0328] Step 1303: Find the first peak point in the first spectrum that is closest to the first target object at the current time, and use it as the target peak point.

[0329] Step 1304: Map the distance to the target peak point to the current position of the car in the hoistway.

[0330] In the first spectrum graph, traverse each first peak point, compare the distance of each first peak point with the distance of the first target object at the current time, and find the first peak point that is closest to the distance of the first target object at the current time, and record it as the target peak point.

[0331] Since the target peak point has a high probability of representing the first target object, the distance expressed by the target peak point, that is, the distance between the radar and the first target object, can be mapped to the current position of the car in the hoistway.

[0332] Example 8

[0333] Figure 14 This is a flowchart of a radar ranging method provided in Embodiment 8 of this application. This embodiment, based on Embodiment 1, describes the process of detecting the position of a stationary car within the car, particularly in shafts with high lifting heights (e.g., greater than 20 meters), to ensure accuracy. Figure 14 As shown, the method includes:

[0334] Step 1401: When the car is stationary, control the radar to transmit multiple frames of electromagnetic wave signals to the reflector and receive multiple frames of electromagnetic wave signals reflected by the hoistway.

[0335] Step 1402: Coherently accumulate the multi-frame reflected electromagnetic wave signals to obtain the first echo signal.

[0336] In practical applications, the peak method uses the position of the first peak point on the first spectrum to locate the car in the hoistway. The accuracy formula for radar ranging is as follows:

[0337]

[0338] Where c is the speed of light, B is the bandwidth of the radar's electromagnetic wave signal, and SNR is the signal-to-noise ratio of the echo signal.

[0339] In order to ensure the accuracy of ranging, the signal-to-noise ratio (SNR) should be high enough. However, when the radar's transmit power and the size of the reflector are limited, the intensity of the first echo signal reflected by the reflector decreases as the distance between them increases. This means that the SNR of the peak value of the first echo signal decreases, and the accuracy of ranging decreases.

[0340] Therefore, when using the peak method to track the position of the car in the hoistway, the measurement accuracy is slightly worse.

[0341] To further improve the accuracy of ranging, in this embodiment, the car is kept stationary, such as when the elevator control system is powered on and started, or when the car is idle and waiting to be called on a certain floor. At this time, the car control radar can be controlled to continuously send multiple frames of electromagnetic wave signals in the direction of the reflector. Each frame of electromagnetic wave signal propagates in the atmosphere and reaches various obstacles in the radar's scanning range in the shaft. At this time, the electromagnetic wave signal will be reflected and scattered on the surface of the obstacle.

[0342] These obstacles can include reflectors, guide rails, thresholds and other highly reflective metal objects, as well as side walls and other obstacles with low reflectivity.

[0343] Therefore, the radar can receive multiple frames of electromagnetic wave signals reflected from various obstacles within the radar's scan range in the shaft. Because the electromagnetic wave signals absorb some energy from the reflectors, they generate an original electromagnetic wave signal with attenuation delay, which is then superimposed on the original electromagnetic wave signal.

[0344] During the time the car is stationary, the electromagnetic wave signal reflected in each frame can be regarded as a coherent signal. The electromagnetic wave signals reflected in multiple frames are coherently accumulated and recorded as the first echo signal. This enhances the intensity of the first echo signal reflected by the reflector. The noise can be regarded as Gaussian white noise with an expected value of zero. Therefore, this can improve the signal-to-noise ratio (SNR) of the first echo signal reflected by the reflector, thereby improving the accuracy of detecting the position of the car in the hoistway.

[0345] Step 1403: Convert the first echo signal to the first spectrum diagram.

[0346] Step 1404: Extract the first feature of the distribution of the first target object and the second target object from the first echo signal.

[0347] Step 1405: Match the first feature with the second feature that has been learned in advance on the distribution of the first target object and the second target object.

[0348] Step 1406: If the match is successful, extract the distance between the radar and the first target object that is labeled with the second feature, and use it as the position of the car in the hoistway.

[0349] Example 9

[0350] Figure 15 This is a flowchart of a radar ranging method provided in Embodiment Nine of this application. This embodiment adds a process for detecting the car's position in the hoistway using a phase method during the continuous operation phase of Embodiment Eight. For example... Figure 15 As shown, the method includes:

[0351] Step 1501: When the car is sliding in the hoistway, predict the second increment value of the car's sliding between two adjacent moments according to the phase.

[0352] In this embodiment, the radar on the car is assumed to be a linear frequency modulated continuous wave (LFMCW) radar with a bandwidth of 4 GHz and a frequency of 60 GHz. Let the wavelength of the electromagnetic signal emitted by the radar be λ. When the distance between the reflector and the radar changes by λ / 2 (λ represents one round trip, i.e., from transmission to reception), the phase changes by one period of 360° (2π). A small change in distance corresponds to a larger change in phase angle.

[0353] When the radar is operating normally, after determining the initial position S0, the change in range is calculated using the phase change. By accumulating the range changes, the current position can be obtained, as follows:

[0354]

[0355] Where k is a positive integer, S k Let S be the position at time k. k-1 The position at time k-1. λ is the phase difference between time k and time (k-1), 2π is 360°, and λ is the wavelength of the electromagnetic wave signal emitted by the radar.

[0356] Furthermore, Let k be the phase at time k. The phase at time k-1 is the phase difference between the reflector at time k and time k-1, which is the phase at time k minus the phase at time k-1.

[0357] Since ranging radars typically employ dual-channel reception (in-phase and out-of-phase), the first echo signal from the reflector at time k is represented by the complex number a. k +b ki , where b k Let a be the imaginary part of the first peak point corresponding to the reflector. k Let i be the real part and i be the imaginary number.

[0358] Then the phase difference at time k:

[0359]

[0360] Where m = 0, 1, 2, 3...

[0361] Phase difference There are multiple values, and these values ​​differ by 2π. To ensure the phase difference... The uniqueness of this guarantee is that within the time interval ΔT between two electromagnetic wave signals, the phase difference is constant. The change does not exceed 2π, and the corresponding radar movement distance does not exceed λ / 2.

[0362] To ensure this, calculations were performed based on the elevator's usage scenarios, for a rated speed v of 0.4 m / s. 额 For household elevators, when the wavelength λ = 5mm, in order to ensure the uniqueness of the phase value, the time interval between electromagnetic wave signals is:

[0363]

[0364] like Figure 16 The angle diagram shown has a phase of 225° at time k-1 and a phase of 160° at time k. Since the radar has two possibilities of moving away from or approaching the reflector, this is reflected in the angle diagram. From 225° at time k-1 to 160° at time k, it is possible to reach the radar by rotating 295° counterclockwise or 65° clockwise.

[0365] Therefore, by limiting the change in angle to half a period π, the phase difference can be distinguished and determined. Assuming the radar travels within a distance of λ / 4, and considering the elevator usage scenario, for a home elevator with a rated speed of 0.4 m / s, when the wavelength λ = 5 mm, to ensure the uniqueness of the phase value, the time interval between two adjacent moments is:

[0366]

[0367] because

[0368]

[0369] Where n = 0, 1, 2, 3…, it can be seen from the above formula that the measured distance S… k The measurement accuracy is related to the initial position S0 and the initial phase. Phase of the kth measurement The measurement is related to the phase of the intermediate process, but not to the phase of the intermediate process. Therefore, the phase measurement error in the intermediate process will not affect the final result, which greatly improves the accuracy of the measurement.

[0370] In this embodiment, when the car is sliding in the hoistway, the distance the car slides between two adjacent moments can be predicted according to the phase and recorded as the second incremental value.

[0371] In the specific implementation, it is assumed that the car moves at a constant speed between two adjacent moments, especially a constant speed direct motion. Then, the motion of the car is modeled according to the constant speed motion, and the speed v of the car sliding in the hoistway at the previous moment k-1 is queried. k-1 Multiplying the speed by the time interval ΔT between two adjacent moments yields the first candidate value v for the car's gliding distance between two adjacent moments. k-1 *ΔT.

[0372] For each reflector, the distance between the transmitter and the radar measured at the previous time k-1 can be queried, and the distance S at the previous time k-1 can be expressed as... k-1 Adding this to the first candidate value yields the second candidate value S′ at the current time k. k This process can be represented as S′ k =S k-1 +v k-1 *ΔT.

[0373] Traverse each first peak point in the first spectrum at the current time k, thus obtaining the first spectrum at the current time k.

[0374]

[0375] Searching for the second candidate value S k The closest first peak point is used as the reference peak point R. p .

[0376] For the reference peak point R p Calculate the phase difference between the previous time k-1 and the current time k. Among them, phase difference The phase of the current time k Subtract the phase of the previous time k-1 Right now,

[0377] Multiplying the ratio of the phase difference to 2π (360°) by half the wavelength λ / 2 of the electromagnetic wave signal yields the second increment of the car's travel between two adjacent moments. This process is expressed as follows:

[0378] Step 1502: For each reflector, add the distance at the previous moment to the second increment value to obtain the distance at the current moment.

[0379] For each reflector, the distance between the transmitter and the radar measured at the previous time k-1 can be queried. The distance at the previous time k-1 is added to the first increment value at the current time to obtain the distance between the transmitter and the radar measured at the current time k, thus realizing the tracking of each radar.

[0380] Therefore, the tracking process can be expressed as follows:

[0381]

[0382] Among them, S k S is the distance at the current time k. k-1 This is the distance at the previous time step k-1.

[0383] Step 1503: Map the distance of the first target object to the current position of the car in the hoistway.

[0384] In each reflector, the distance to the first target is used as a positioning reference for the car, thus the distance between the radar and the first target can be mapped to the current position of the car in the hoistway.

[0385] In one embodiment of this application, the position of the car in the hoistway can be calculated simultaneously using the matching method, the peak method, and the phase method. Specifically, the position of the car in the hoistway calculated using the matching method can refer to the position matched based on the second feature in Embodiments 2, 4, and 6. The position of the car in the hoistway calculated using the peak method can refer to the position calculated based on the target peak point in Embodiment 7. The position of the car in the hoistway calculated using the phase method can refer to the position calculated based on the target peak point in Embodiment 9.

[0386] Generally, there are some differences in the calculation of the car's position in the hoistway using the matching method, peak method, and phase method, but these differences are small.

[0387] In terms of measurement accuracy, the phase method is more accurate than both the matching method and the peak method. Therefore, the phase method can be used as the primary method to calculate the car's position in the hoistway and output to other modules. The matching method and peak method can be used as supplementary methods to calculate the car's position in the hoistway, and are used to correct the position calculated by the phase method.

[0388] Therefore, in order to further improve the accuracy of ranging, the difference between the position matched according to the second feature, the position calculated according to the target peak point, and the position calculated according to the phase can be calculated as the position deviation. This position deviation reflects the stability of the matching method, the peak method, and the phase method to a certain extent.

[0389] Each positional deviation is compared to a preset valid range.

[0390] If all position deviations are within the preset legal range, it means that all position deviations are small, the differences between the matching method, peak method and phase method are small, which is a reasonable error, and the matching method, peak method and phase method are operating stably. Considering that the accuracy of the phase method is the highest among the three, it can be determined that the position calculated based on the phase is valid, and the position calculated based on the phase is output externally.

[0391] If any positional deviation is outside the preset legal range, it indicates that the positional deviation is large, and at least two of the matching method, peak method, and phase method have a large difference, which is an illegal error. At least one of the matching method, peak method, and phase method may be malfunctioning. In this case, a fault alarm operation is executed to prompt management personnel, maintenance personnel, and other users to check and repair, so as to ensure the safe operation of the elevator.

[0392] In one embodiment of this application, since the information of each reflector during normal operation has been learned in advance, and the information of each reflector during elevator operation has also been recorded, the following anomaly detection can be performed based on this information.

[0393] I. Signal Strength Detection

[0394] During the learning phase, the distances of reflectors at different locations and the amplitudes of the corresponding second echo signals were recorded. When the elevator is working normally, if the amplitudes of the first peak points in the first spectrum are significantly different from the amplitudes recorded during the learning phase, making it impossible to filter out reflectors in the first spectrum, an abnormal message is generated.

[0395] II. Tracking of the Reflector

[0396] Among multiple reflectors, the second target object is mainly used to match and find the first peak point of the first target object. The position of the car in the hoistway is calculated based on the distance of the first target object. In the process of calculating the position of the car in the hoistway, in order to ensure accuracy, each reflector (including the first target object and the second target object) can be tracked. When the position of one of the reflectors cannot be tracked, an anomaly message is generated.

[0397] III. Fault Diagnosis

[0398] In this embodiment, the features on the first spectrogram can be used to achieve self-fault diagnosis, detect various possible faults such as angular tilt, falling, and displacement, and save additional hardware costs.

[0399] If, on the first spectrum diagram, any first peak point representing a reflector decreases in amplitude and the magnitude of the decrease is greater than a preset amplitude threshold, that is, the intensity of the first echo signal reflected by any reflector is significantly weakened, then the tilt angle of the reflector is determined to be abnormal.

[0400] If, on the first spectrum diagram, all the first peak points representing reflectors decrease in amplitude and the magnitude of the decrease is greater than a preset amplitude threshold, that is, the intensity of the first echo signal reflected by all reflectors is significantly weakened, then the tilt angle of the radar is determined to be abnormal.

[0401] If any first peak point representing a reflector disappears on the first spectrogram, that is, if the first echo signal reflected by any reflector becomes small, then it is determined that the reflector has fallen.

[0402] On the first spectrum diagram, if the first peak point representing the current reflector is displaced relative to the first peak point representing other reflectors, that is, the first echo signal reflected by any reflector is displaced relative to the first echo signal reflected by other reflectors, then it is determined that the current reflector has displaced relative to the reflector.

[0403] For example, three reflectors R1, R2, and R3 are installed in the shaft, where R1 is the first target object and R2 and R3 are the second target objects.

[0404] In this example, the fault diagnosis process is shown in the table below:

[0405]

[0406] Example 10

[0407] Figure 17 This is a schematic diagram of a radar ranging device provided in Embodiment 10 of this application. Figure 17 As shown, the device includes:

[0408] According to another aspect of this application, a radar ranging device is provided, comprising a plurality of reflectors arranged in a shaft, the reflectors including a first target located at one end of the shaft and a second target located at a non-end of the shaft, and a radar installed in a car traveling in the shaft, the device comprising:

[0409] The first echo signal receiving module 1701 is used to control the radar to transmit electromagnetic wave signals to the multiple reflectors and to receive the first echo signal reflected by the well.

[0410] The first spectrum conversion module 1702 is used to convert the first echo signal to a first spectrum.

[0411] The first feature extraction module 1703 is used to extract the first feature of the distribution of the first target object and the second target object from the first echo signal;

[0412] The first feature matching module 1704 is used to match the first feature with a second feature that has been pre-learned on the distribution of the first target object and the second target object;

[0413] The second feature extraction module 1705 is used to extract the distance between the radar and the first target object, which are both labeled with the second feature, as the position of the car in the shaft if the match is successful.

[0414] In this embodiment of the application, the first target and the radar are on the same vertical line, the second target and the radar are not on the same vertical line, the projections of the multiple reflectors on the horizontal plane do not overlap, and the projections of the multiple reflectors on the vertical plane do not overlap.

[0415] In this embodiment of the application, the first feature extraction module 1703 includes:

[0416] The first peak point sorting module is used to sort the multiple first peak points with the highest amplitude in the first spectrum according to the distance to obtain the peak point sequence;

[0417] The peak point extraction module is used to sequentially extract multiple first peak points from the peak point sequence, the number of which is equal to that of the reflector;

[0418] The first spacing calculation module is used to calculate the first spacing between two adjacent first peak points for each first peak point, as a first feature of the distribution of the first target and the second target;

[0419] And / or,

[0420] The first peak point amplitude query module is used to query the first peak point with the largest amplitude on the first spectrum map, which serves as the first feature of the distribution of the first target object and the second target object.

[0421] In this embodiment of the application, the first feature includes a first spacing between a plurality of first peak points, and the first feature matching module 1704 includes:

[0422] The second feature lookup module is used to look up a second feature that has been learned in advance on the distribution of the first target and the second target, the second feature including a second spacing between multiple second peak points;

[0423] The spacing deviation calculation module is used to calculate the difference between each first spacing and each second spacing for each first spacing, as the spacing deviation;

[0424] The spacing matching module is used to determine that a certain first spacing and the second spacing are successfully matched if all the spacing deviations are less than or equal to the spacing threshold.

[0425] The matching success determination module is used to determine that the first feature and the second feature are successfully matched if the first feature contains a successfully matched first spacing.

[0426] The matching failure determination module is used to determine that the first feature and the second feature have failed to match if at least one of the spacing deviations is greater than the spacing threshold.

[0427] In this embodiment of the application, the second feature includes the second peak point with the largest amplitude;

[0428] The first feature matching module 1704 further includes:

[0429] The comparison module is used to compare the first peak point with the largest amplitude in the first feature with the second peak point with the largest amplitude in the second feature if the first feature and the second feature fail to match multiple times.

[0430] The feature amplitude matching module is used to determine that the first feature and the second feature are successfully matched if the first peak point with the largest amplitude in the first feature is the same as the second peak point with the largest amplitude in the second feature.

[0431] In this embodiment of the application, the spectrum information includes distance and amplitude;

[0432] The comparison module includes:

[0433] The first difference calculation module is used to calculate the first difference between the distance of the first peak point with the largest amplitude in the first feature and the distance of the second peak point with the largest amplitude in the second feature;

[0434] The second difference calculation module is used to calculate the second difference between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature;

[0435] The third difference acquisition module is used to merge the first difference and the second difference into a third difference;

[0436] The third difference and threshold comparison module is used to determine that if the third difference is less than or equal to a preset deviation threshold, the first peak point with the largest amplitude in the first feature is the same as the second peak point with the largest amplitude in the second feature.

[0437] In this embodiment of the application, the first difference calculation module includes:

[0438] The first difference calculation module is used to calculate the first difference between the distance of the first peak point with the largest amplitude in the first feature and the distance of the second peak point with the largest amplitude in the second feature;

[0439] The first difference squaring module is used to square the first difference to obtain the first difference;

[0440] The second difference calculation module includes:

[0441] The second peak point second difference calculation module is used to calculate the second difference between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature;

[0442] The second difference squaring module is used to square the second difference to obtain the second difference;

[0443] The third difference acquisition module includes:

[0444] The first adjustment value calculation module is used to multiply the first difference by the first weight to obtain the first adjustment value;

[0445] The second adjustment weight calculation module is used to multiply the second difference by the second weight to obtain the second adjustment weight, wherein the first weight is greater than or equal to the second weight.

[0446] The third difference calculation module is used to take the square root of the sum between the first adjustment value and the second adjustment value to obtain the third difference.

[0447] In this embodiment of the application, the spacing matching module includes:

[0448] The third feature acquisition module is used to compare the first peak point in the first feature with the second peak point in the second feature representing the reflector and the interfering object in terms of distribution if the first feature contains at least two successfully matched first gaps.

[0449] The feature distribution matching module is used to determine that the first feature and the second feature are successfully matched if the distributions are the same.

[0450] In this embodiment of the application, the first echo signal receiving module 1701 includes:

[0451] A multi-frame electromagnetic wave signal transmission and reception module is used to control the radar to transmit multi-frame electromagnetic wave signals to the reflector and receive multi-frame electromagnetic wave signals reflected by the shaft when the car is stationary.

[0452] A multi-frame electromagnetic wave signal coherent accumulation module is used to coherently accumulate multiple frames of reflected electromagnetic wave signals to obtain a first echo signal.

[0453] This application embodiment also includes:

[0454] The first incremental value prediction module is used to predict the first incremental value of the car's sliding between two adjacent moments when the car is sliding in the hoistway, based on uniform motion.

[0455] The distance-to-first-increment-value addition module is used to add the distance at the previous moment to the first increment value for each of the reflectors to obtain the distance at the current moment;

[0456] The target peak point search module is used to find the first peak point in the first spectrum that is closest to the first target object at the current time, and use it as the target peak point;

[0457] The distance mapping position module is used to map the distance of the target peak point to the current position of the car in the hoistway.

[0458] and / or

[0459] The second incremental value prediction module is used to predict the second incremental value of the car's movement between two adjacent moments according to the phase when the car is sliding in the hoistway.

[0460] The distance-to-second-increment-value addition module is used to add the distance at the previous moment to the second increment value for each of the reflectors to obtain the distance at the current moment.

[0461] The first target object distance mapping position module uses language to map the distance of the first target object to the current position of the car in the hoistway.

[0462] In the embodiments of this application,

[0463] The first incremental prediction module includes:

[0464] The first sliding speed query module is used to query the speed at which the car slides in the shaft.

[0465] The speed-time multiplication module is used to multiply the speed by the time interval between two adjacent moments to obtain the first incremental value of the car's sliding between two adjacent moments.

[0466] The second incremental value prediction module includes:

[0467] The second sliding speed query module queries the speed at which the car slides in the hoistway.

[0468] The first candidate value calculation module is used to multiply the speed by the time interval between two adjacent moments to obtain the first candidate value of the car sliding between two adjacent moments.

[0469] The second candidate value calculation module is used to add the distance at the previous moment to the incremental value for each of the reflectors to obtain the second candidate value at the current moment.

[0470] The reference peak point search module is used to find the first peak point that is closest to the second candidate value in the first spectrum at the current time, and use it as the reference peak point;

[0471] The phase difference calculation module is used to calculate the phase difference between the reference peak point at the previous time and the current time.

[0472] The second increment value calculation module is used to multiply the ratio between the phase difference and 2π by half the wavelength of the electromagnetic wave signal to obtain the second increment value of the car's gliding between two adjacent moments.

[0473] This application embodiment also includes:

[0474] The position deviation calculation module is used to calculate the difference between each pair of the position matched according to the second feature, the position calculated according to the target peak point, and the position calculated according to the phase, as the position deviation;

[0475] The effective position determination module is used to determine that the position calculated based on the phase is valid if all the position deviations are within a preset legal range.

[0476] The alarm operation module is used to execute a fault alarm operation if any of the aforementioned position deviations is outside the preset legal range.

[0477] In summary, the embodiments of this application also include:

[0478] The reflector tilt angle anomaly determination module is used to determine that the reflector tilt angle is abnormal if any first peak point representing the reflector on the first spectrum diagram decreases in amplitude and the decrease is greater than a preset amplitude threshold.

[0479] The radar tilt angle anomaly determination module is used to determine that the radar tilt angle is abnormal if, on the first spectrum, all the first peak points representing the reflector decrease in amplitude and the magnitude of the decrease is greater than a preset amplitude threshold.

[0480] A reflector drop determination module is used to determine that the reflector has dropped if any first peak point representing the reflector disappears on the first spectrogram.

[0481] The reflector displacement determination module is used to determine that the current reflector has been displaced if, on the first spectrum, a first peak point representing the current reflector is displaced relative to a first peak point representing another reflector.

[0482] This application embodiment also includes:

[0483] The car movement control module is used to control the car to move sequentially to each marker in the hoistway, starting from the marker closest to the first target object.

[0484] The second echo signal receiving module is used to control the radar to send electromagnetic wave signals to the multiple reflectors and receive the second echo signal reflected by the wellbore in each of the flag bits;

[0485] The second echo signal conversion module is used to convert the second echo signal to a second spectrum diagram;

[0486] The second feature extraction module of the second spectrum map is used to extract the second feature of the distribution of the first target object and the second target object from the second spectrum map;

[0487] The second feature annotation module is used to annotate the distance between the radar and the first target object using the second feature.

[0488] In this embodiment of the application, the second feature extraction module of the second spectrogram includes:

[0489] The second peak point search module is used to search for second peak points in the second spectrum diagram that respectively represent the first target object and the second target object;

[0490] The second spacing calculation module is used to calculate the second spacing between the distances of the second peak points corresponding to two adjacent transmitters if a second peak point representing the first target and the second target is found, as a second feature of the distribution of the first target and the second target.

[0491] In this embodiment of the application, the second feature extraction module of the second spectrogram further includes:

[0492] The distance setting second feature module is used to set the distance of the second peak point representing the first target object as the second feature of the distribution of the first target object and the second target object if a second peak point representing the first target object is found but no second peak point representing the second target object is found.

[0493] In this embodiment of the application, the second peak point search module includes:

[0494] The first baseline length query module is used to query the actual distance between the radar and the first target, which is used as the first baseline length;

[0495] The distance query module is used to query the first side length and the second side length respectively. The first side length is the vertical distance between the first target object and the second target object, and the second side length is the horizontal distance between the first target object and the second target object.

[0496] The geometric relationship determining second baseline length module is used to calculate the actual distance between the radar and the second target object according to the geometric relationship using the first side length, the second side length and the first baseline length, as the second baseline length;

[0497] The first target object labeling module is used to label the second peak point as the first target object if a second peak point whose distance matches the length of the first baseline is found.

[0498] The third baseline matching module is used to mark the second target object on the second peak point if a second peak point whose distance matches the length of the second baseline is found.

[0499] The first tracking module is used to track the first target object and the second target object respectively, so as to mark the first target object and the second target object to the second peak point;

[0500] or,

[0501] The second spectrum map first target object labeling module is used to label the first target object with the second peak point with the largest amplitude in the second spectrum map;

[0502] In this embodiment of the application, the second peak point search module includes:

[0503] The module for marking the first target object with the largest amplitude of the second peak point is used to mark the first target object with the largest amplitude of the second peak point in the second spectrum.

[0504] The signal query module is used to query the third spectrum diagram converted from the third echo signal. The third echo signal is the electromagnetic wave signal that the radar sends to multiple first targets and reflects through the well channel when the first target is installed but the second target is not installed.

[0505] A difference comparison module is used to compare the differences between the second spectrogram and the third spectrogram;

[0506] The second peak point and second target object labeling module is used to label the second peak point on the second spectrum map, which represents the difference, as the second target object;

[0507] The first target object and the second target object tracking module are used to track the first target object and the second target object respectively, so as to mark the first target object and the second target object to the second peak point.

[0508] In this embodiment of the application, the second feature extraction module of the second spectrogram further includes:

[0509] The interference second peak point extraction module is used to extract, in the second spectrum, a number of second peak points representing interference points equal to the number of reflectors;

[0510] The third spacing calculation module is used to calculate the third spacing between the distances of the second peak points corresponding to two adjacent interference objects;

[0511] An interference deviation calculation module is used to calculate the difference between each of the second spacing and each of the third spacing, as the interference deviation.

[0512] The third spacing matching success determination module is used to determine that the second spacing and the third spacing are successfully matched if all the interference deviations are less than or equal to the interference threshold, and to supplement the third spacing as the second feature of the distribution of the first target and the second target.

[0513] Example 11

[0514] Figure 18 A schematic diagram of an electronic device 10, which can be used to implement embodiments of this application, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0515] like Figure 18 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0516] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0517] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as ranging methods.

[0518] In some embodiments, the ranging method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the ranging method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the ranging method by any other suitable means (e.g., by means of firmware).

[0519] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0520] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0521] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0522] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0523] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0524] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0525] Example 12

[0526] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the ranging method provided in any embodiment of this application.

[0527] In the implementation of the computer program product, computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0528] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0529] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors.

Claims

1. A radar ranging method, characterized in that, Multiple reflectors are installed in the hoistway, the reflectors including a first target located at one end of the hoistway and a second target located at a non-end point of the hoistway. A radar is installed in the car traveling in the hoistway. The method includes: The radar is controlled to transmit electromagnetic wave signals to multiple reflectors and to receive the first echo signal reflected by the wellbore. Convert the first echo signal to the first spectrum diagram; Extract the first feature in the distribution of the first target and the second target from the first echo signal; The first feature is matched with a second feature that has been pre-learned on the distribution of the first target and the second target; If the match is successful, the distance between the radar and the first target object, which is labeled with the second feature, is extracted as the position of the car in the shaft. The step of extracting the first feature in the distribution of the first target object and the second target object from the first echo signal includes: The first peak points with the highest amplitude in the first spectrum are sorted by distance to obtain a peak point sequence; Multiple sets of the first peak points, with the same number as the reflector, are sequentially extracted from the peak point sequence; For each of the first peak points, calculate the first distance between two adjacent first peak points, which is used as the first feature of the distribution of the first target and the second target; And / or, The first peak point with the largest amplitude on the first spectrum is used as the first feature of the distribution of the first target and the second target.

2. The method according to claim 1, characterized in that, The first target and the radar are on the same vertical line, while the second target and the radar are not on the same vertical line. The projections of the multiple reflectors on the horizontal plane do not overlap, and the projections of the multiple reflectors on the vertical plane do not overlap.

3. The method according to claim 1, characterized in that, The first feature includes a first spacing between multiple first peak points, and the matching of the first feature with a second feature pre-learned on the distribution of the first target object and the second target object includes: Find a second feature that was previously learned on the distribution of the first target and the second target, the second feature including a second spacing between a plurality of second peak points; For each of the first spacings, the difference between each of the first spacings and each of the second spacings is calculated as the spacing deviation; If all the aforementioned spacing deviations are less than or equal to the spacing threshold, then it is determined that a certain first spacing and the second spacing are successfully matched; If the first feature contains a successfully matched first gap, then the first feature is determined to be a successful match with the second feature; If at least one of the spacing deviations is greater than the spacing threshold, then it is determined that the first feature and the second feature have failed to match.

4. The method according to claim 3, characterized in that, The second feature includes the second peak point with the largest amplitude; The step of matching the first feature with a second feature pre-learned on the distribution of the first target and the second target further includes: If the first feature and the second feature fail to match multiple times, the first peak point with the largest amplitude in the first feature will be compared with the second peak point with the largest amplitude in the second feature. If the first peak point with the largest amplitude in the first feature is the same as the second peak point with the largest amplitude in the second feature, then the first feature and the second feature are determined to be a successful match.

5. The method according to claim 4, characterized in that, The first spectrum includes distance and amplitude; The comparison of the first peak point with the largest amplitude in the first feature with the second peak point with the largest amplitude in the second feature includes: Calculate the first difference between the distance to the first peak point with the largest amplitude in the first feature and the distance to the second peak point with the largest amplitude in the second feature; Calculate the second difference between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature; The first difference and the second difference are merged into a third difference; If the third difference is less than or equal to a preset deviation threshold, then the first peak point with the largest amplitude in the first feature is determined to be the same as the second peak point with the largest amplitude in the second feature.

6. The method according to claim 5, characterized in that, The calculation of the first difference between the distance to the first peak point with the largest amplitude in the first feature and the distance to the second peak point with the largest amplitude in the second feature includes: Calculate the first difference between the distance to the first peak point with the largest amplitude in the first feature and the distance to the second peak point with the largest amplitude in the second feature; Squaring the first difference yields the first difference; The calculation of the second difference between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature includes: Calculate the second difference between the amplitude of the first peak point with the largest amplitude in the first feature and the amplitude of the second peak point with the largest amplitude in the second feature; Squaring the second difference yields the second difference; The step of fusing the first difference and the second difference into a third difference includes: Multiply the first difference by the first weight to obtain the first adjustment value; Multiply the second difference by the second weight to obtain the second adjustment value, wherein the first weight is greater than or equal to the second weight; The third difference is obtained by taking the square root of the sum between the first and second adjustment values.

7. The method according to claim 3, characterized in that, The step of determining that the first feature and the second feature are successfully matched if all the spacing deviations are less than or equal to the spacing threshold includes: If the first feature contains at least two successfully matched first gaps, then the first peak point in the first feature is compared with the second peak point in the second feature representing the reflector and the interfering object in terms of distribution. If the distributions are the same, then the first feature and the second feature are determined to be a successful match.

8. The method according to claim 1, characterized in that, The control of the radar to transmit electromagnetic wave signals to the reflector and to receive the first echo signal reflected by the shaft includes: When the car is stationary, the radar is controlled to transmit multiple frames of electromagnetic wave signals to the reflector and receive multiple frames of electromagnetic wave signals reflected by the shaft. The reflected electromagnetic wave signals from multiple frames are coherently accumulated to obtain the first echo signal.

9. The method according to claim 1, characterized in that, Also includes: When the car slides in the hoistway, the first incremental value of the car's sliding between two adjacent moments is predicted according to uniform motion. For each of the aforementioned reflectors, the distance at the previous moment is added to the first increment value to obtain the distance at the current moment; In the first spectrum, find the first peak point that is closest to the distance of the first target object at the current time, and use it as the target peak point; Map the distance to the target peak point to the current position of the car in the shaft; and / or As the car slides in the hoistway, a second incremental value of the car's sliding distance between two adjacent moments is predicted according to the phase. For each of the aforementioned reflectors, the distance at the previous moment is added to the second increment value to obtain the distance at the current moment; The distance to the first target object is mapped to the current position of the car in the shaft.

10. The method according to claim 9, characterized in that, The prediction of the first incremental value of the car's sliding distance between two adjacent moments based on uniform motion includes: Query the speed at which the car slides in the shaft; Multiplying the speed by the time interval between two adjacent moments yields the first incremental value of the car's gliding distance between two adjacent moments; The second incremental value of the car's gliding distance between two adjacent moments, predicted according to phase, includes: Query the speed at which the car slides in the shaft; Multiplying the speed by the time interval between two adjacent moments yields the first candidate value of the car's gliding distance between two adjacent moments; For each of the aforementioned reflectors, the distance from the previous moment is added to the incremental value to obtain the second candidate value for the current moment; In the first spectrum at the current moment, find the first peak point that is closest to the second candidate value and use it as a reference peak point; Calculate the phase difference between the reference peak point at the previous time and the current time. Multiplying the ratio between the phase difference and 2π by half the wavelength of the electromagnetic wave signal yields the second incremental value of the car's gliding distance between two adjacent moments.

11. The method according to claim 9, characterized in that, Also includes: The differences between each pair of the position matched according to the second feature, the position calculated according to the target peak point, and the position calculated according to the phase are used as position deviations; If all the position deviations are within the preset legal range, then the position calculated based on the phase is determined to be valid; If any of the aforementioned positional deviations is outside the preset legal range, a fault alarm operation will be executed.

12. The method according to claim 9, characterized in that, Also includes: If, on the first spectrogram, any peak point representing the reflector decreases in amplitude and the magnitude of the decrease is greater than a preset amplitude threshold, then the tilt angle of the reflector is determined to be abnormal. If, on the first spectrogram, all the first peak points representing the reflector decrease in amplitude and the magnitude of the decrease is greater than a preset amplitude threshold, then the tilt angle of the radar is determined to be abnormal. If any peak point representing the reflector disappears on the first spectrogram, then the reflector is determined to have fallen. If, on the first spectrogram, the first peak point representing the current reflector is displaced relative to the first peak point representing other reflectors, then it is determined that the current reflector has been displaced.

13. The method according to any one of claims 1-12, characterized in that, Also includes: Starting from the marker closest to the first target, the car is controlled to move sequentially to each marker in the shaft. In each of the flag bits, the radar is controlled to send electromagnetic wave signals to multiple reflectors and receive second echo signals reflected by the wellbore; The second echo signal is converted to the second spectrum diagram; Extract the second feature of the distribution of the first target and the second target from the second spectrogram; The distance between the radar and the first target is marked by the second feature.

14. The method according to claim 13, characterized in that, Extracting the second feature from the second spectrogram showing the distribution of the first target and the second target includes: Locate the second peak points representing the first target and the second target in the second spectrum; If a second peak point representing the first target and the second target is found, then the second distance between the distances of the second peak points corresponding to two adjacent reflectors is calculated as a second feature of the distribution of the first target and the second target.

15. The method according to claim 14, characterized in that, The step of extracting the second feature of the distribution of the first target and the second target from the second spectrogram further includes: If a second peak point representing the first target object is found, but no second peak point representing the second target object is found, then the distance of the second peak point representing the first target object is set as the second feature of the distribution of the first target object and the second target object.

16. The method according to claim 14, characterized in that, The step of searching for second peak points representing the first target and the second target respectively in the second spectrum includes: The actual distance between the radar and the first target is queried and used as the first baseline length; Query the first side length and the second side length respectively. The first side length is the vertical distance between the first target and the second target, and the second side length is the horizontal distance between the first target and the second target. The actual distance between the radar and the second target is calculated using the first side length, the second side length, and the first baseline length according to geometric relationships, and is used as the second baseline length; If a second peak point is found that matches the distance of the first baseline length, then the first target object is marked on the second peak point; If a second peak point is found that matches the distance to the second baseline length, then the second target object is marked on the second peak point; The first target and the second target are tracked separately to mark the first target and the second target at the second peak point; or, In the second spectrum, the first target object is marked with the second peak point with the largest amplitude.

17. The method according to claim 14, characterized in that, The step of searching for second peak points representing the first target and the second target respectively in the second spectrum includes: In the second spectrum diagram, the first target object is marked with the second peak point with the largest amplitude. The third spectrum diagram converted from the third echo signal is obtained by querying the third echo signal. When the first target is installed but the second target is not installed, the third echo signal is the electromagnetic wave signal that the radar sends to the first target and is reflected by the well. Compare the differences between the second spectrogram and the third spectrogram; The second peak point on the second spectrogram that represents the difference is marked as the second target object; The first target and the second target are tracked separately to mark the first target and the second target at the second peak point.

18. The method according to claim 14, characterized in that, The step of extracting the second feature of the distribution of the first target and the second target from the second spectrogram further includes: Extract a second peak point representing the interference, with the same number as the reflector, from the second spectrogram; Calculate the third spacing between the distances of the second peak points corresponding to two adjacent interfering objects; The difference between each of the second spacings and each of the third spacings is calculated as the interference deviation; If all the interference deviations are less than or equal to the interference threshold, then the second spacing is determined to be a successful match with the third spacing, and the third spacing is added as a second feature in the distribution of the first target and the second target.

19. A radar ranging device, characterized in that, Multiple reflectors are installed in the hoistway, including a first target located at one end of the hoistway and a second target located at a non-end point of the hoistway. A radar is installed in the car traveling in the hoistway. The device includes: The first echo signal receiving module is used to control the radar to transmit electromagnetic wave signals to the multiple reflectors and to receive the first echo signal reflected by the well. The first spectrum conversion module is used to convert the first echo signal to a first spectrum. The first feature extraction module is used to extract the first feature of the distribution of the first target object and the second target object from the first echo signal; The first feature matching module is used to match the first feature with a second feature that has been pre-learned on the distribution of the first target object and the second target object; The second feature extraction module is used to extract the distance between the radar and the first target object, which are labeled with the second feature, if the match is successful, as the position of the car in the shaft. The first feature extraction module includes: The first peak point sorting module is used to sort the multiple first peak points with the highest amplitude in the first spectrum according to the distance to obtain the peak point sequence; The peak point extraction module is used to sequentially extract multiple first peak points from the peak point sequence, the number of which is equal to that of the reflector; The first spacing calculation module is used to calculate the first spacing between two adjacent first peak points for each first peak point, as a first feature of the distribution of the first target and the second target; And / or, The first peak point amplitude query module is used to query the first peak point with the largest amplitude on the first spectrum map, which serves as the first feature of the distribution of the first target object and the second target object.

20. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the ranging method according to any one of claims 1-18.

21. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the ranging method according to any one of claims 1-18.

22. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the ranging method according to any one of claims 1-18.

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