Vibration measurement method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a vibration measurement method and device, electronic equipment and a storage medium, and belongs to the technical field of vibration measurement. The method comprises the following steps: acquiring an intermediate-frequency signal; estimating the distance between the to-be-measured object and the radar according to the intermediate frequency signal to obtain a first distance; estimating an additional phase change caused by a hardware circuit and a physical reflection characteristic of the radar according to the first distance to obtain an additional phase of the intermediate frequency signal; correcting the first distance according to the additional phase to obtain a target distance between the to-be-measured object and the radar; and taking the additional phase of the intermediate frequency signal and the target distance as a measurement result of vibration measurement of the to-be-measured object. According to the embodiment of the invention, the precision of vibration measurement can be improved.

Description

Technical Field

[0001] The present application relates to the field of vibration measurement technology, and in particular to a vibration measurement method, device, electronic device and storage medium. Background Art

[0002] Vibration measurement technology has broad application value in industrial inspection, structural health monitoring, autonomous driving, aerospace, and other fields. In recent years, millimeter-wave radar technology has gradually become a research hotspot in the field of vibration measurement due to its advantages such as non-contact, strong anti-interference capabilities, adaptability to complex environments, and relatively low cost. Millimeter-wave radar transmits electromagnetic waves and receives echo signals reflected by the target, using frequency, phase, and amplitude information to accurately measure the target's distance, speed, and vibration. Among them, linear frequency modulated continuous wave (LFMCW) millimeter-wave radar is widely used in the field of vibration measurement due to its high resolution, low power consumption, and ease of implementation. LFMCW millimeter-wave radar transmits a continuous wave signal whose frequency varies linearly with time, receives the echo signal reflected by the target, obtains an intermediate frequency signal through mixing, and then extracts the target's distance and vibration information from it.

[0003] Existing vibration measurement methods based on LFMCW millimeter-wave radar can be roughly divided into two categories: frequency and carrier phase. The former uses the frequency of the intermediate frequency signal for measurement, while the latter uses the carrier phase contained in the intermediate frequency signal for measurement. The carrier phase method has become the mainstream technical solution due to its significantly superior measurement accuracy. However, the carrier phase method suffers from phase ambiguity. When the vibration is too fast or the radar pulse repetition frequency is too low, the distance solution loses uniqueness, seriously affecting measurement accuracy. Summary of the Invention

[0004] The main purpose of the embodiments of the present application is to propose a vibration measurement method, device, electronic device and storage medium, which can solve the phase ambiguity problem in the carrier phase method in the prior art and improve the measurement accuracy.

[0005] To achieve the above objectives, a first aspect of an embodiment of the present application provides a vibration measurement method applied to a radar, the method comprising:

[0006] Acquire an intermediate frequency signal, where the intermediate frequency signal is obtained by mixing a transmission signal and an echo signal by a receiver of the radar, the transmission signal is sent by a signal transmitter of the radar, and the echo signal is a signal of the transmission signal received by an antenna of the radar after being reflected by the object to be measured;

[0007] estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance;

[0008] estimating an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar according to the first distance to obtain an additional phase of the intermediate frequency signal;

[0009] Correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar;

[0010] The additional phase of the intermediate frequency signal and the target distance are used as measurement results of the vibration measurement of the object to be measured.

[0011] In some embodiments, obtaining the intermediate frequency signal includes:

[0012] Periodically transmitting M frames of transmission signals, wherein the transmission signal is a linear frequency modulation continuous wave signal, and M is a positive integer greater than 1;

[0013] During each of the transmission signal transmission processes, the following steps are executed:

[0014] receiving, by the receiver, an echo signal corresponding to the transmitted signal;

[0015] The transmitting signal is mixed with the echo signal by the receiver to obtain an intermediate frequency signal corresponding to the transmitting signal.

[0016] In some embodiments, after acquiring the intermediate frequency signal and before estimating the distance between the object to be measured and the radar based on the intermediate frequency signal to obtain the first distance, the method further includes:

[0017] For each frame of the transmitted signal, the intermediate frequency signal is sampled to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer;

[0018] The estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance includes:

[0019] For each frame of the transmitted signal corresponding to an intermediate frequency signal, estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal, to obtain a temporary distance corresponding to the intermediate frequency signal, wherein the first distance includes M temporary distances corresponding to the intermediate frequency signals;

[0020] The estimating, based on the first distance, an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar to obtain an additional phase of the intermediate frequency signal includes:

[0021] Calculating according to the M phase angles corresponding to the M temporary distances to obtain the additional phase;

[0022] The step of correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar includes:

[0023] Based on the additional phase and the M temporary distances, the M target distances between the object to be measured and the radar are obtained.

[0024] In some embodiments, estimating the distance between the object to be measured and the radar based on N sampling points corresponding to the intermediate frequency signal for each frame of the transmitted signal to obtain a temporary distance corresponding to the intermediate frequency signal includes:

[0025] For each frame of the intermediate frequency signal corresponding to the transmitted signal, performing fast Fourier transform on N sampling points corresponding to the intermediate frequency signal to obtain a spectrum sequence;

[0026] Obtaining the frequency point corresponding to the maximum spectrum amplitude in the spectrum sequence and the initial distance corresponding to the frequency point;

[0027] Determine a first interval range of a binary iterative search according to the frequency point;

[0028] Taking the initial distance as the center, a binary iterative search is performed within the first interval to obtain a temporary distance corresponding to the intermediate frequency signal.

[0029] In some embodiments, obtaining the M target distances between the object to be measured and the radar based on the additional phase and the M first distances includes:

[0030] Performing maximum likelihood estimation based on the additional phase and the M temporary distances to obtain a first candidate sequence, where the first candidate sequence includes M first candidate target distances, and the first candidate sequence is a sequence obtained by estimating the target distance in the absence of phase ambiguity;

[0031] Performing maximum likelihood estimation based on the additional phase, π, and the M temporary distances to obtain a second candidate sequence, where the second candidate sequence includes M second candidate target distances, and the second candidate sequence is a sequence obtained by estimating the target distance in the case of phase ambiguity;

[0032] Calculating a loss function value of maximum likelihood estimation of the first candidate sequence and the second candidate sequence to obtain a first loss function value corresponding to the first candidate sequence and a second loss function value corresponding to the second candidate sequence;

[0033] If the first loss function value is greater than or equal to the second loss function value, taking the M first candidate target distances in the first candidate sequence as the M target distances;

[0034] If the first loss function value is less than the second loss function value, the M second candidate target distances in the second candidate sequence are used as the M target distances.

[0035] In some embodiments, obtaining the intermediate frequency signal includes:

[0036] Periodically transmitting M frames of transmission signals, wherein the transmission signal is a linear frequency modulation continuous wave signal, and M is a positive integer greater than 1;

[0037] During each of the transmission signal transmission processes, the following steps are executed:

[0038] receiving, by the receiver, an echo signal corresponding to the transmitted signal;

[0039] Mixing the transmission signal with the echo signal by the receiver to obtain an intermediate frequency signal corresponding to the transmission signal;

[0040] The estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance includes:

[0041] Each time a frame of the intermediate frequency signal is acquired, the intermediate frequency signal is sampled to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer;

[0042] estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal to obtain a first distance corresponding to the intermediate frequency signal;

[0043] The estimating, based on the first distance, an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar to obtain an additional phase of the intermediate frequency signal includes:

[0044] Each time a frame of the intermediate frequency signal is acquired, an additional phase change caused by the hardware circuit and physical reflection characteristics of the radar is estimated based on the first distance corresponding to the intermediate frequency signal and the first distance corresponding to the previous frame of the intermediate frequency signal to obtain the additional phase of the intermediate frequency signal;

[0045] The step of correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar includes:

[0046] A target distance between the object to be measured and the radar is obtained based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal.

[0047] In some embodiments, obtaining the target distance between the object to be measured and the radar based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal includes:

[0048] Determine a second interval range of the binary iterative search according to the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal;

[0049] Taking the first distance as the center, a binary iterative search is performed within the second interval to obtain the target distance between the object to be measured and the radar.

[0050] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a vibration measurement device for use in a radar, the device comprising:

[0051] an acquisition module, configured to acquire an intermediate frequency signal, wherein the intermediate frequency signal is obtained by mixing a transmission signal and an echo signal by a receiver of the radar, wherein the transmission signal is sent by a signal transmitter of the radar, and the echo signal is a signal of the transmission signal received by an antenna of the radar after being reflected by the object to be measured;

[0052] A first estimation module, configured to estimate the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance;

[0053] a second estimation module, configured to estimate an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar according to the first distance, to obtain an additional phase of the intermediate frequency signal;

[0054] a correction module, configured to correct the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar;

[0055] The measuring module is configured to use the additional phase of the intermediate frequency signal and the target distance as the measurement results of the vibration measurement of the object to be measured.

[0056] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0057] To achieve the above-mentioned purpose, the fourth aspect of the embodiments of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method described in the first aspect.

[0058] The vibration measurement method, device, electronic device, and storage medium proposed in this application obtain a rough distance estimate between the target and the radar based on an intermediate frequency signal. The method then estimates the additional phase variation caused by the radar's hardware circuitry and physical reflection characteristics based on the rough distance estimate to obtain an additional phase. The additional phase is used to correct the rough distance estimate to obtain a refined distance estimate. The additional phase and target distance are used as the final vibration measurement result of the target. By estimating and compensating for the additional phase of the intermediate frequency signal, high-precision vibration measurement is achieved, overcoming the phase ambiguity problem inherent in traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 1 is a flow chart of a vibration measurement method provided in an embodiment of the present application;

[0060] Figure 2 Schematic diagram of a Chirp signal of the vibration measurement method provided in an embodiment of the present application;

[0061] Figure 3 Schematic diagram of the signal processing result of scenario 1 provided in an embodiment of the present application;

[0062] Figure 4 Schematic diagram of the simulation experiment results of scenario 2 provided in the embodiment of the present application;

[0063] Figure 5 Schematic diagram of the structure of the vibration measurement device provided in an embodiment of the present application;

[0064] Figure 6 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0066] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0068] Vibration measurement technology has broad application value in industrial inspection, structural health monitoring, autonomous driving, aerospace, and other fields. For example, in industrial equipment monitoring, vibration measurement can be used to detect mechanical failures, provide early warning of equipment anomalies, and avoid production accidents. In the structural health monitoring of bridges and buildings, vibration measurement can assess the stability and safety of structures, providing a basis for maintenance decisions. In the field of autonomous driving, vibration measurement can be used to monitor the condition of vehicle suspension systems, improving driving safety and comfort.

[0069] Traditional vibration measurement methods rely primarily on contact sensors (such as accelerometers and strain gauges) or non-contact optical measurement devices (such as laser Doppler vibrometers). Although contact sensors are relatively inexpensive, they require installation on the surface of the object being measured, potentially interfering with the object's natural vibration state and making them unsuitable for high-temperature, high-pressure, or difficult-to-reach environments. Optical measurement devices, while offering the advantages of high precision and non-contact performance, are sensitive to ambient light, are costly, and exhibit significantly reduced performance in complex environments (such as dust and smoke).

[0070] In recent years, millimeter-wave radar technology has become a research hotspot in the field of vibration measurement due to its advantages, including non-contact, strong anti-interference capabilities, adaptability to complex environments, and relatively low cost. Millimeter-wave radar transmits electromagnetic waves and receives echo signals reflected by targets, leveraging frequency, phase, and amplitude information to accurately measure target distance, velocity, and vibration. Linear frequency modulated continuous wave (LFMCW) millimeter-wave radar has been widely used in vibration measurement due to its high resolution, low power consumption, and ease of implementation. LFMCW millimeter-wave radar transmits a continuous wave signal whose frequency varies linearly with time, receives echo signals reflected by targets, and then mixes them to generate an intermediate frequency signal from which it can extract target distance and vibration information.

[0071] Existing vibration measurement methods based on LFMCW millimeter-wave radar can be roughly divided into two categories, namely the frequency method and the carrier phase method. The former uses the frequency of the intermediate frequency signal for measurement, while the latter uses the carrier phase contained in the intermediate frequency signal for measurement. Among these two methods, the carrier phase method has become the mainstream technical solution because it can greatly improve the measurement accuracy compared to the frequency method. The carrier phase method can be divided into a method of phase unwrapping (PU) using the extracted carrier phase sequence (hereinafter referred to as the PU method) and a method of unbiased phase unwrapping (UPU) assisted by side information (hereinafter referred to as the UPU method) based on specific technical implementation details.

[0072] The PU method typically uses a classic phase unwrapping algorithm or a modified algorithm to improve its performance at low signal-to-noise ratios. However, when the target vibrates too quickly or the radar pulse repetition frequency is too low, the phase variation can exceed 2π, a phenomenon known as phase ambiguity. Phase ambiguity can cause the distance solution to lose its uniqueness, leading to significant deviations in the measurement results and even system failure. To address this phase ambiguity, the UPU method has emerged. This method typically requires first obtaining an unbiased estimate of the distance or displacement and using this estimate to help determine the possible range of the carrier phase. Existing UPU-based methods still have some issues, such as: some implementations require additional hardware support, increasing system complexity; additional phase calibration is required before each measurement, reducing measurement efficiency; and insufficient system robustness makes it difficult to adapt to complex and changing real-world application scenarios. These limitations have severely restricted the widespread application of millimeter-wave radar vibration measurement technology in industrial practice.

[0073] Based on this, the embodiments of the present application provide a vibration measurement method, device, electronic device and storage medium, which aims to combine the frequency method and the carrier phase method to jointly estimate the distance parameters in the frequency and carrier phase, thereby solving the phase ambiguity problem in the carrier phase method in the prior art. In terms of measurement accuracy, the embodiments of the present application provide accuracy performance that is superior to the UPU method; in terms of hardware design, the embodiments of the present application can work on a LFMCW millimeter wave radar device without the need for other hardware design; in terms of automation performance, the embodiments of the present application can automatically estimate and compensate for the additional phase of the intermediate frequency signal, thereby improving the robustness of the algorithm.

[0074] The vibration measurement method, device, electronic device, and storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the vibration measurement method in the embodiments of the present application is described.

[0075] The vibration measurement method provided in the embodiment of the present application relates to the field of vibration measurement technology. The vibration measurement method provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, or can be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the vibration measurement method, etc., but is not limited to the above forms.

[0076] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0077] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0078] Figure 1 This is an optional flow chart of the vibration measurement method provided by the embodiment of the present application, which is applied to radar. Figure 1 The method may include but is not limited to steps S100 to S500.

[0079] Step S100, obtaining an intermediate frequency signal, wherein the intermediate frequency signal is obtained by mixing the transmit signal and the echo signal by the radar receiver, the transmit signal is sent by the radar's signal transmitter, and the echo signal is a signal received by the radar's antenna after the transmit signal is reflected by the object to be measured.

[0080] In this embodiment, the radar may be a linear frequency modulated continuous wave millimeter wave radar. The transmission signal is a linear frequency modulated continuous wave signal, also known as a chirp signal, sent by the radar's signal transmitter. The characteristic of a chirp signal is that the instantaneous frequency of the signal increases linearly with time. Parameters such as the starting frequency, frequency change rate, and duration of the signal are set by the radar system. The radar's signal transmitter generates and sends a transmission signal, which is radiated into space through an antenna. The transmission signal is reflected after encountering the target to be measured, forming an echo signal, which is captured by the radar's receiving antenna. The radar receiver mixes the transmission signal and the echo signal to obtain an intermediate frequency signal. The frequency and phase changes of the intermediate frequency signal are closely related to the distance and vibration of the target.

[0081] Step S200: Estimate the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance.

[0082] In this embodiment, the intermediate frequency signal contains information about the target distance. By analyzing the frequency and phase of the intermediate frequency signal, a rough estimate of the target distance can be made. Specifically, a fast Fourier transform is performed on each frame of the intermediate frequency signal, converting the intermediate frequency signal from the time domain to the frequency domain. The fast Fourier transform decomposes the intermediate frequency signal into components of different frequencies. The peak position of the spectrum is then obtained. Since the target distance is proportional to the frequency variation of the radar signal, the peak position of the spectrum corresponds to a rough estimate of the target distance, namely the first distance.

[0083] Step S300: Estimate the additional phase change caused by the hardware circuit and physical reflection characteristics of the radar according to the first distance to obtain the additional phase of the intermediate frequency signal.

[0084] In this embodiment, additive phase refers to the additional phase change in the echo signal relative to the transmitted signal caused by factors such as hardware circuitry and physical reflection characteristics in a millimeter-wave radar system. This additional phase is superimposed on the phase change caused by target vibration, causing deviations in the measurement results and reducing vibration measurement accuracy. Specifically, the additional phase can be calculated using the phase difference between consecutive frames.

[0085] Step S400: Correct the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar.

[0086] In this embodiment, a fine estimate of the target distance is obtained by using the maximum likelihood estimation method for the additional phase first distance. Specifically, an iterative search solution can be performed through the bisection method, and the obtained fine estimated target distance is used as the target distance between the object to be measured and the radar, thereby eliminating the phase error caused by the hardware circuit and physical reflection characteristics, and improving the accuracy and robustness of the vibration measurement.

[0087] Step S500: Using the additional phase of the intermediate frequency signal and the target distance as the measurement result of the vibration measurement of the object to be measured.

[0088] By estimating and correcting the additional phase, this embodiment can obtain a more accurate target distance, thereby more accurately reflecting the vibration condition of the object to be measured, thereby improving the accuracy of vibration measurement; using both the additional phase and the target distance as measurement results can more comprehensively reflect the vibration condition of the object to be measured, including distance changes and phase changes; this embodiment can automatically estimate and compensate for the additional phase of the intermediate frequency signal, thereby improving the robustness of the algorithm.

[0089] In some embodiments, step S100 may include but is not limited to steps S110 to S140:

[0090] Step S110, periodically transmitting M frames of transmission signals, wherein the transmission signal is a linear frequency modulation continuous wave signal, and M is a positive integer greater than 1;

[0091] Step S120, performing during each transmission process of the transmission signal:

[0092] Step S130, receiving an echo signal corresponding to the transmitted signal through the receiver;

[0093] Step S140: Mixing the transmission signal with the echo signal through the receiver to obtain an intermediate frequency signal corresponding to the transmission signal.

[0094] In this embodiment, the radar transmits M frames of signals at a preset period, where M is a positive integer greater than 1, representing the number of times the signal is transmitted. The transmitted signal is a linear frequency modulated continuous wave (LFMCW) signal, characterized by a linear frequency variation over time. Each frame of the transmitted signal is processed as follows: the radar receiver receives the echo signal reflected from the target. The echo signal is also an LFMCW signal, but its frequency variation is different from that of the transmitted signal and contains target distance information. The receiver mixes the transmitted signal with the echo signal. The resulting intermediate frequency signal is a lower-frequency single-frequency signal that contains target distance information and can be used for subsequent processing and analysis.

[0095] Specifically, consider an LFMCW radar that is performing vibration measurement and periodically transmits M frames of transmission signals (Chirp signals). Assume that the starting frequency of the Chirp signal is f0 Hertz (Hz), the instantaneous frequency increases linearly with time at a rate of k Megahertz per microsecond (MHz / μs), and the transmission period is T c seconds (s), the total bandwidth of the signal is BHz, and the duration is T T s, the schematic diagram of Chirp signal is as follows Figure 2 shown.

[0096] Assume that there is a target whose distance from the radar is d[m] meters (m) when the mth Chirp signal is transmitted. Then the radar will transmit the Chirp signal Then an echo signal is received, where c is the speed of light, and the echo signal is also a Chirp signal. Figure 2 The receiver of the continuous wave radar couples the transmitted signal to the receiving chain and mixes it with the received signal. Ideally, the transmitted signal and the received signal can be considered to be subtracted. The result of mixing and down-conversion can be considered to be a single-frequency signal, which is also called an intermediate frequency signal or a beat signal. Next, the digital-to-analog converter will use the sampling frequency f s Hz samples the intermediate frequency signal. The sampling start time is t0s from the time when the Chirp signal is emitted. The number of sampling points is N. The sampling end time is t1s from the time when the Chirp signal is emitted. The sampling start and end times are shown as follows: Figure 2 The data organized into N sampling points can be called a frame of data. A frame represents the entire process of sending the chirp signal to the receiver for processing and sampling.

[0097] This embodiment periodically transmits LFMCW signals and receives echo signals, and obtains an intermediate frequency signal containing target distance information through mixing, providing a data basis for subsequent vibration measurement.

[0098] A signal processing model is constructed, in which the nth sampling point of the mth intermediate frequency signal is expressed as formula (1).

[0099] s[n,m]=A0e j(αd[m]n+βd[m]+γ) +w[n,m] (1);

[0100] Where s[n,m] represents the nth sampling point corresponding to the mth intermediate frequency signal echo, A0 is the signal amplitude of the echo, and A0 is a real number. α and β are constants related to system parameters, satisfying: β=αf s t0+4πf0c.

[0101] γ is the additional phase caused by hardware circuits and physical reflection characteristics. w[n,m] is the variance of σ 2 cyclically symmetric complex Gaussian noise. From the signal model equation (1), it can be seen that the sampling sequence of the mth intermediate frequency signal echo is actually a complex single-frequency signal with an angular frequency of αd[m] and an initial phase of βd[m]+γ. This embodiment estimates the additional phase γ from the collected signal and compensates for it, while also estimating d[m] as the final vibration measurement output.

[0102] In this embodiment, the radar echo signal model given by formula (1) can be used to solve the corresponding signal parameters under the framework of maximum likelihood estimation. If the total number of received signal frames is set to M frames, from the perspective of signal processing, a parameter vector to be estimated can be constructed as θ = [A0, γ, d t ], where d=[d0,d1,…,d M-1 ] T . Further, the maximum likelihood estimate of θ can be derived as follows:

[0103] max θ logf(Z;θ)(2);

[0104] Among them, f(Z;θ) is the likelihood function of Z with respect to parameter θ, and the expression of f(Z;θ) is:

[0105] Substituting equation (1) into the maximum likelihood estimation expression (2), the maximum likelihood estimation of the parameter vector θ can be expressed as:

[0106]

[0107] in:

[0108]

[0109] Equation (3) gives the optimization problem expression of the signal processing problem. In summary, the basic technical solution of this embodiment is to use the maximum likelihood estimation framework to estimate the target distance parameter by processing M frames of received signals at once or using a pipeline processing method, thereby completing the vibration measurement task.

[0110] Preferably, when there is prior information about the distance parameter of the object, a Bayesian estimation framework can be used to achieve a lower operating signal-to-noise ratio and higher vibration measurement accuracy.

[0111] This embodiment provides two signal collection and processing methods. Method 1: Collect M frames of radar signals at once. Since a single echo signal has N sampling points, the received data can be organized into an M×N signal matrix Z. Then, the M frames of data are processed to obtain an additional phase and M target ranges. Method 2: Collect echo signals in a pipelined manner. After each frame of data is received, it is immediately processed and an estimate of the range parameter is given. Processing is performed frame by frame to obtain the additional phase and target range for each frame.

[0112] In some embodiments, the first signal collection and processing method may include but is not limited to the following steps:

[0113] After acquiring the intermediate frequency signal and before estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain the first distance, the method further includes:

[0114] For each frame of the transmitted signal, the intermediate frequency signal is sampled to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer;

[0115] The estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance includes:

[0116] For each frame of the transmitted signal corresponding to an intermediate frequency signal, estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal, to obtain a temporary distance corresponding to the intermediate frequency signal, wherein the first distance includes M temporary distances corresponding to the intermediate frequency signals;

[0117] The estimating, based on the first distance, an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar to obtain an additional phase of the intermediate frequency signal includes:

[0118] Calculating according to the M phase angles corresponding to the M temporary distances to obtain the additional phase;

[0119] The step of correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar includes:

[0120] Based on the additional phase and the M temporary distances, the M target distances between the object to be measured and the radar are obtained.

[0121] The obtaining, based on the additional phase and the M first distances, the M target distances between the object to be measured and the radar, includes:

[0122] Performing maximum likelihood estimation based on the additional phase and the M temporary distances to obtain a first candidate sequence, where the first candidate sequence includes M first candidate target distances, and the first candidate sequence is a sequence obtained by estimating the target distance in the absence of phase ambiguity;

[0123] Performing maximum likelihood estimation based on the additional phase, π, and the M temporary distances to obtain a second candidate sequence, where the second candidate sequence includes M second candidate target distances, and the second candidate sequence is a sequence obtained by estimating the target distance in the case of phase ambiguity;

[0124] Calculating a loss function value of maximum likelihood estimation of the first candidate sequence and the second candidate sequence to obtain a first loss function value corresponding to the first candidate sequence and a second loss function value corresponding to the second candidate sequence;

[0125] If the first loss function value is greater than or equal to the second loss function value, taking the M first candidate target distances in the first candidate sequence as the M target distances;

[0126] If the first loss function value is less than the second loss function value, the M second candidate target distances in the second candidate sequence are used as the M target distances.

[0127] In this embodiment, first, M frames of intermediate frequency signals are sampled, and the number of sampling points of each frame of intermediate frequency signal is N, so M×N sampling points are obtained, where N is a positive integer. Using the N sampling points of a frame of intermediate frequency signal, a rough estimate of the distance parameter (i.e., temporary distance) can be obtained, and this rough distance estimate is recorded as It is obtained by maximizing the spectrum of the discrete-time Fourier transform (DTFT) of this sequence. The process of maximizing the DTFT spectrum can be expressed as an optimization problem:

[0128]

[0129] In formula (5), for The parameters at the maximum value are taken. Since there are M frames of signal in total, a total of M optimization problems need to be solved to obtain a rough estimate of the target distance for each frame:

[0130] Then, using the above steps to obtain Calculate an estimate of the additional phase

[0131]

[0132] Where ∠(·) represents the angle of the complex number. Additional phase estimate Substituted into formula (4), formula (4) becomes a one-variable function.

[0133] Finally, for the mth frame signal, the intermediate frequency signal of the mth frame and the additional phase estimation value obtained in the previous step are used estimate and (i.e., the first candidate target distance) and (i.e., the second candidate target distance) is a fine estimate of the target distance, is the distance estimation without phase ambiguity. It is the distance estimation considering the presence of phase ambiguity. and It is obtained by solving the following two optimization problems:

[0134]

[0135] Since the intermediate frequency signal matrix has a total of M frames of signals, a total of M optimization problems need to be solved. Repeat the above process for M frames of signals to obtain two distance estimation sequences (also called vectors): (i.e., the first candidate sequence) and (ie the second candidate sequence).

[0136] By comparison and Determine the final distance estimation sequence

[0137]

[0138] in, and It is a major part of the objective function (also called loss function or cost function) of maximum likelihood estimation. Bring in separately and And select the final distance estimation sequence according to formula (9). Greater than Then the final distance estimation sequence is Otherwise The final distance estimation sequence The M distance estimation values ​​in are the M target distances between the object to be measured and the radar.

[0139] This embodiment can quickly obtain a rough estimate of the target distance by maximizing the DTFT spectrum. The rough estimate can serve as the starting point for subsequent steps and help determine the search range of subsequent optimization problems, thereby improving the efficiency of the algorithm. By calculating the additional phase estimate value, the phase ambiguity problem is avoided, which makes the distance estimation unaffected by the target's excessively fast vibration speed or the radar pulse repetition frequency being too low, thereby improving the accuracy and robustness of the measurement. The rough estimate of the target distance and the additional phase estimate value are used to obtain two refined distance estimation sequences, one with and one without phase ambiguity. By comparing the two refined distance estimation sequences, the more reliable result is selected as the final distance estimate, which can further improve the accuracy of the distance estimation and reduce the impact of random errors.

[0140] Solution 1 is suitable for scenarios where M frames of radar signals are collected and processed at once. Jointly estimating multiple frames can improve the accuracy of distance parameter estimation, which is crucial for applications requiring high-precision measurements, such as precision instrument testing and structural health monitoring. Multiple frames can effectively suppress random noise, thereby improving the reliability of measurement results. Solution 1 avoids the random errors that can occur in single-frame signal processing, thereby improving the stability of measurement results. Jointly processing multiple frames of data can enhance the accuracy and robustness of distance estimation.

[0141] In some embodiments, the second signal collection and processing method may include but is not limited to the following steps:

[0142] The obtaining of the intermediate frequency signal includes:

[0143] Periodically transmitting M frames of transmission signals, wherein the transmission signal is a linear frequency modulation continuous wave signal, and M is a positive integer greater than 1;

[0144] During each of the transmission signal transmission processes, the following steps are executed:

[0145] receiving, by the receiver, an echo signal corresponding to the transmitted signal;

[0146] Mixing the transmission signal with the echo signal by the receiver to obtain an intermediate frequency signal corresponding to the transmission signal;

[0147] The estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance includes:

[0148] Each time a frame of the intermediate frequency signal is acquired, the intermediate frequency signal is sampled to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer;

[0149] estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal to obtain a first distance corresponding to the intermediate frequency signal;

[0150] The estimating, based on the first distance, an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar to obtain an additional phase of the intermediate frequency signal includes:

[0151] Each time a frame of the intermediate frequency signal is acquired, an additional phase change caused by the hardware circuit and physical reflection characteristics of the radar is estimated based on the first distance corresponding to the intermediate frequency signal and the first distance corresponding to the previous frame of the intermediate frequency signal to obtain the additional phase of the intermediate frequency signal;

[0152] The step of correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar includes:

[0153] A target distance between the object to be measured and the radar is obtained based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal.

[0154] In this embodiment, the received current frame intermediate frequency signal is sampled, and the number of sampling points of each frame intermediate frequency signal is N, where N is a positive integer. Assuming that K frames of data have been received, when the K+1 frame of data is received, the following steps are performed:

[0155] First, using the N sampling points of the K+1 frame data, a rough estimate of the distance parameter (i.e., the first distance) can be obtained, and this rough distance estimate is recorded as It is obtained by maximizing the spectrum of the discrete-time Fourier transform (DTFT) of this sequence. The process of maximizing the DTFT spectrum can be expressed as an optimization problem:

[0156]

[0157] in, It is a rough distance estimate obtained by processing the received data of the K+1th frame, which is obtained by solving the optimization problem of formula (10). is to make The largest parameter.

[0158] Then, the estimated value of the additional phase of the K+1 frame data is calculated

[0159]

[0160] Finally, calculate the refined estimate of the target distance for the K+1th frame

[0161]

[0162] Will As the target distance between the object to be measured and the radar in the K+1th frame.

[0163] This embodiment can quickly obtain a rough estimate of the target distance by maximizing the DTFT spectrum. The rough estimate can serve as the starting point for subsequent steps and help determine the search range of subsequent optimization problems, thereby improving the efficiency of the algorithm. By calculating the additional phase estimate, the phase ambiguity problem is avoided, which makes the distance estimate unaffected by excessively fast target vibration speed or excessively low radar pulse repetition frequency, thereby improving the accuracy and robustness of the measurement. The rough estimate of the target distance and the additional phase estimate are used to obtain a fine estimate of the target distance, which can further improve the accuracy of the distance estimation.

[0164] Solution 2 is suitable for pipeline signal processing scenarios. It estimates distance parameters immediately after receiving each frame of data and outputs the estimated distance parameter results in real time. This is crucial for applications requiring rapid response, such as autonomous driving and robotic navigation. It can also continuously monitor changes in target distance, enabling dynamic vibration measurement, which is useful for studying target motion trajectories and analyzing vibration patterns. Solution 2 only processes the current frame of data, which is computationally less complex and more efficient than Solution 1, which requires processing all frames. It also allows for timely correction of system errors, preventing them from accumulating over time, thereby improving measurement accuracy and stability.

[0165] In the above-mentioned Schemes 1 and 2, only the theoretical expressions of the optimization problems (5), (7), (8), (10), and (12) are given, without specific numerical solutions. In fact, the optimization problems (5) and (10) are the same optimization problem, namely, maximizing the discrete-time Fourier transform amplitude spectrum; the optimization problems (7), (8), and (12) are the same optimization problem. Next, specific numerical methods for solving the above two types of optimization problems will be given.

[0166] In some embodiments, the distance between the target object and the radar is estimated based on the intermediate frequency signal to obtain a first distance (i.e., a rough estimate of the target distance) in the following specific implementations:

[0167] For solution 1, for each frame of the transmitted signal corresponding to the intermediate frequency signal, estimating the distance between the object to be measured and the radar based on N sampling points corresponding to the intermediate frequency signal to obtain a temporary distance corresponding to the intermediate frequency signal includes:

[0168] For each frame of the intermediate frequency signal corresponding to the transmitted signal, performing fast Fourier transform on N sampling points corresponding to the intermediate frequency signal to obtain a spectrum sequence;

[0169] Obtaining the frequency point corresponding to the maximum spectrum amplitude in the spectrum sequence and the initial distance corresponding to the frequency point;

[0170] Determine a first interval range of a binary iterative search according to the frequency point;

[0171] Taking the initial distance as the center, a binary iterative search is performed within the first interval to obtain a temporary distance corresponding to the intermediate frequency signal.

[0172] For the second solution, estimating the distance between the object to be measured and the radar according to the N sampling points corresponding to the intermediate frequency signal to obtain the first distance corresponding to the intermediate frequency signal includes:

[0173] For each frame of the intermediate frequency signal corresponding to the transmitted signal, performing fast Fourier transform on N sampling points corresponding to the intermediate frequency signal to obtain a spectrum sequence;

[0174] Obtaining the frequency point corresponding to the maximum spectrum amplitude in the spectrum sequence and the initial distance corresponding to the frequency point;

[0175] Determine a third interval range of a binary iterative search according to the frequency point;

[0176] Taking the initial distance as the center, a binary iterative search is performed within the third interval to obtain a first distance corresponding to the intermediate frequency signal.

[0177] Faced with the optimization problem (5) and (10), we first obtain a rough estimate of the spectrum peak position by performing a Fast Fourier Transform (FFT) on the received signal of one frame. Specifically, this can be achieved by finding the maximum position of the zero-filled 4N-point FFT result. Then, we use the rough estimate of the spectrum peak position as the midpoint of the interval and calculate the peak position on the spectrum. is the interval width, and an iterative search is performed through bisection to obtain a rough estimate of the target distance The number of iterations is recorded as

[0178] Specifically, solve The numerical algorithm is as follows:

[0179] This algorithm uses one frame of echo data (N discrete sampling points) to perform a rough distance estimation, so m is a constant in the following algorithm.

[0180] Input: One frame of echo data (N discrete sampling points) s[n,m], n=0,1,…,N-1;

[0181] Output: A rough estimate of the distance

[0182] First, the Fast Fourier Transform (FFT) calculation set is performed on s[n,m], n=0,1,…,N-1 at 4N points. in

[0183] Then, find the variable corresponding to the largest element of the set and sequence number k * .

[0184] After that, determine the interval range of the binary search, and the left endpoint of the interval is The right endpoint of the interval is

[0185] (i.e. start the binary iteration, i is the number of the current iteration round; is the total number of iterations, typically 15 to 30. )

[0186]

[0187] (That is, if the function value corresponding to the left endpoint of the interval is greater than the function value corresponding to the right endpoint, then the right endpoint of the new interval is the midpoint of the original interval, and the left endpoint is the left endpoint at the beginning of this round of iteration.)

[0188] else

[0189] (That is, if the function value corresponding to the left endpoint of the interval is less than the function value corresponding to the right endpoint, then the left endpoint of the new interval is the midpoint of the original interval, and the right endpoint is the right endpoint at the beginning of this iteration.)

[0190] end

[0191] end

[0192] A rough estimate of the final distance is the midpoint of the iterated interval, which is obtained by taking the arithmetic mean of the interval endpoints.

[0193] This embodiment uses a combination of fast Fourier transform (FFT) and bisection to quickly locate spectrum peaks, significantly reducing computational complexity; uses zero-padded 4N-point FFT results for preliminary estimation, improving spectrum resolution and reducing noise interference with peak detection; is suitable for processing multiple frames of data at one time or pipeline processing, and can flexibly respond to different signal collection requirements; and automatically completes a rough estimate of the distance parameter without human intervention, providing a reliable initial value for subsequent fine-grained estimation.

[0194] In some embodiments, a specific implementation of correcting the first distance according to the additional phase to obtain the target distance between the object to be measured and the radar (i.e., a fine estimate of the target distance) is as follows:

[0195] For solution 1, performing maximum likelihood estimation based on the additional phase and the M temporary distances to obtain a first candidate sequence includes:

[0196] For each of the M intermediate frequency signals, perform:

[0197] Determining a fourth interval range of a binary iterative search according to the additional phase of the intermediate frequency signal and the temporary distance of the intermediate frequency signal;

[0198] Taking the temporary distance as the center, performing a binary iterative search within the fourth interval to obtain a first candidate target distance between the object to be measured and the radar;

[0199] Combining the M first candidate target distances in sequence to obtain the first candidate sequence;

[0200] The performing maximum likelihood estimation according to the additional phase, π, and the M temporary distances to obtain a second candidate sequence includes:

[0201] For each of the M intermediate frequency signals, perform:

[0202] Determining a fifth interval range of a binary iterative search according to the additional phase of the intermediate frequency signal, π, and the temporary distance of the intermediate frequency signal;

[0203] Taking the temporary distance as the center, performing a binary iterative search within the fifth interval to obtain a second candidate target distance between the object to be measured and the radar;

[0204] The M second candidate target distances are combined in sequence to obtain the second candidate sequence.

[0205] For the second solution, obtaining the target distance between the object to be measured and the radar based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal includes:

[0206] Determine a second interval range of the binary iterative search according to the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal;

[0207] Taking the first distance as the center, a binary iterative search is performed within the second interval to obtain the target distance between the object to be measured and the radar.

[0208] Faced with the optimization problems (7), (8) and (12), the same bisection method is used to perform iterative search to obtain a fine estimate of the target distance. by is the midpoint of the interval of bisection, and the width of the interval is

[0209] Specifically, solve The numerical algorithm is as follows:

[0210] This algorithm uses a frame of echo data (N discrete sampling points) to perform precise distance estimation, so m is a constant in the following algorithm.

[0211] Input: A rough estimate of the distance of the current frame Estimated value of additional phase and a frame of echo data s[n,m], n=0,1,…,N-1;

[0212] Output: A refined estimate of the distance

[0213] First, the constants are calculated using the known system parameters α, β, and N.

[0214] Then, determine the interval range of the binary search, and the left endpoint of the interval is The right endpoint of the interval is

[0215] Fori←1toN d do (i.e. start the binary iteration, i is the number of the current iteration round; N d is the total number of iterations, typically 15 to 30. )

[0216]

[0217] (That is, if the function value corresponding to the left endpoint of the interval is greater than the function value corresponding to the right endpoint, then the right endpoint of the new interval is the midpoint of the original interval, and the left endpoint is the left endpoint at the beginning of this round of iteration.)

[0218] else

[0219] (That is, if the function value corresponding to the left endpoint of the interval is less than the function value corresponding to the right endpoint, then the left endpoint of the new interval is the midpoint of the original interval, and the right endpoint is the right endpoint at the beginning of this iteration.)

[0220] end

[0221] end

[0222] The final refined estimate of the distance is the midpoint of the iterated interval, which is obtained by taking the arithmetic mean of the interval endpoints.

[0223] This embodiment further optimizes the distance parameter through the dichotomy method, thereby improving the accuracy of vibration measurement; by combining frequency and phase information, it avoids the measurement failure problem caused by phase ambiguity in traditional phase unwrapping methods; and can online estimate and compensate for the additional phase error of the system, thereby improving the robustness and adaptability of the algorithm.

[0224] This embodiment can be applied to the following two specific scenarios. In these two specific implementations, the signal parameters of the millimeter wave radar are the same except for the total number of received frames M. The same signal parameters are shown in Table 1:

[0225] Table 1:

[0226]

[0227]

[0228] Scenario 1: Simulating Rope Vibration Measurement. The specific experimental scenario is as follows: a corner reflector is suspended by a thin rope. The rope is manually struck to cause the corner reflector to vibrate, and the vibration of the corner reflector is then measured using radar.

[0229] Using the technical solution of this embodiment to process the signal, the following can be obtained: Figure 3 The results shown in the figure are: the lower line shows the result of the method proposed in this embodiment, and the upper line shows the result using a traditional phase unwrapping algorithm. It can be seen that the traditional phase unwrapping algorithm can make estimation errors when large vibrations occur, causing the vibration measurement system to fail. The vibration waveform recovered by the lower line clearly shows the vibrations caused by five human taps on the rope. The first four are relatively small, while the fifth is larger, with the maximum displacement reaching 0.06 meters.

[0230] Scenario 2: Simulate the performance of the method proposed in this embodiment under different signal-to-noise ratios, and compare it with the UPU method. The specific experimental scenario is as follows: Use a stepper motor to drive a corner reflector with a side length of 5 cm. The stepper motor is controlled by a program to generate a vibration waveform. At the same time, a Panasonic HL-G108-SJ laser displacement sensor is used to measure the vibration reference value to evaluate the accuracy of the millimeter-wave radar vibration measurement. The vibration generation and laser measurement equipment are placed on a wooden test platform. The signal-to-noise ratio of the received signal is controlled by changing the distance between the millimeter-wave radar and the test platform. A total of 9 groups of experiments were conducted in this scenario to correspond to different signal-to-noise ratios of the received signal.

[0231] The simulation results obtained by using the method proposed in this embodiment and the UPU method are as follows: Figure 4 The results shown in FIG. 3 show that the method proposed in this embodiment is superior to the UPU method at medium and high signal-to-noise ratios.

[0232] The embodiment of the present application overcomes the phase ambiguity problem of the traditional phase unwrapping method by jointly estimating the distance parameters in the frequency and phase of the intermediate frequency signal; establishes a mathematical model of the LFMCW radar echo signal, couples the distance information of the target into the frequency and phase, and uses the maximum likelihood estimation framework to construct a likelihood function to solve the estimated value of the target distance parameter; is suitable for collecting multiple frames of signals at one time or processing a single frame of signals in a pipeline manner; and provides two solution algorithms, which are used for rough estimation and fine estimation of the target distance, respectively, and uses a binary search to solve the optimization problem of the distance parameter. The embodiment of the present application can combine the frequency method and the carrier phase method to jointly estimate the distance parameters in the frequency and carrier phase, thereby avoiding the phase ambiguity problem, and the measurement accuracy is better than the existing UPU method; the embodiment of the present application can be implemented on a LFMCW millimeter wave radar device without the need for other hardware design; the embodiment of the present application can also automatically estimate and compensate for the additional phase of the intermediate frequency signal, thereby improving the robustness of the algorithm.

[0233] See also Figure 5 The present application also provides a vibration measurement device 700, which can implement the above-mentioned vibration measurement method. The device includes:

[0234] an acquisition module 10, configured to acquire an intermediate frequency signal, wherein the intermediate frequency signal is obtained by mixing a transmission signal and an echo signal by the radar receiver, wherein the transmission signal is sent by the radar's signal transmitter, and the echo signal is a signal of the transmission signal received by the radar's antenna after being reflected by the object to be measured;

[0235] A first estimation module 20 is configured to estimate the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance;

[0236] a second estimation module 30, configured to estimate an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar according to the first distance, to obtain an additional phase of the intermediate frequency signal;

[0237] a correction module 40, configured to correct the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar;

[0238] The measuring module 50 is configured to use the additional phase of the intermediate frequency signal and the target distance as a measurement result of the vibration measurement of the object to be measured.

[0239] In some embodiments, the acquisition module 10 may include:

[0240] The first transmitting submodule is configured to periodically transmit M frames of a transmitting signal, where the transmitting signal is a linear frequency modulated continuous wave signal, and M is a positive integer greater than 1;

[0241] The first mixing submodule is used to perform the following steps during each transmission process of the transmission signal: receiving an echo signal corresponding to the transmission signal through the receiver; and mixing the transmission signal with the echo signal through the receiver to obtain an intermediate frequency signal corresponding to the transmission signal.

[0242] In some embodiments, the device further comprises:

[0243] a sampling module, configured to sample the intermediate frequency signal corresponding to each frame of the transmitted signal to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer;

[0244] The first estimation module 20 may include:

[0245] a first estimation submodule, configured to estimate the distance between the object to be measured and the radar based on N sampling points corresponding to the intermediate frequency signal corresponding to each frame of the transmitted signal, to obtain a temporary distance corresponding to the intermediate frequency signal, wherein the first distance includes M temporary distances corresponding to the intermediate frequency signals;

[0246] The second estimation module 30 may include:

[0247] A second estimation submodule is configured to calculate the additional phase according to the M phase angles corresponding to the M temporary distances;

[0248] The correction module 40 may include:

[0249] The first correction submodule is configured to obtain the M target distances between the object to be measured and the radar based on the additional phase and the M temporary distances.

[0250] In some embodiments, the first estimation submodule may include:

[0251] A Fourier transform unit, configured to perform a fast Fourier transform on N sampling points corresponding to the intermediate frequency signal corresponding to each frame of the transmitted signal to obtain a spectrum sequence;

[0252] An acquiring unit, configured to acquire a frequency point corresponding to a spectrum amplitude with a maximum value in the spectrum sequence and an initial distance corresponding to the frequency point;

[0253] A first determining unit, configured to determine a first interval range of a binary iterative search according to the frequency point;

[0254] The first iterative unit is configured to perform a binary iterative search within the first interval with the initial distance as the center to obtain a temporary distance corresponding to the intermediate frequency signal.

[0255] In some implementations, the first correction submodule may include:

[0256] a first estimating unit, configured to perform maximum likelihood estimation based on the additional phase and the M temporary distances to obtain a first candidate sequence, where the first candidate sequence includes M first candidate target distances, and the first candidate sequence is a sequence obtained by estimating the target distance in a case where there is no phase ambiguity;

[0257] a second estimating unit, configured to perform maximum likelihood estimation based on the additional phase, π, and the M temporary distances to obtain a second candidate sequence, where the second candidate sequence includes M second candidate target distances, and the second candidate sequence is a sequence obtained by estimating the target distance in a phase ambiguity situation;

[0258] a calculation unit, configured to calculate a value of a loss function of maximum likelihood estimation of the first candidate sequence and the second candidate sequence, to obtain a first loss function value corresponding to the first candidate sequence and a second loss function value corresponding to the second candidate sequence;

[0259] a first judgment unit, configured to use the M first candidate target distances in the first candidate sequence as the M target distances if the first loss function value is greater than or equal to the second loss function value;

[0260] The second judgment unit is configured to use the M second candidate target distances in the second candidate sequence as the M target distances if the first loss function value is less than the second loss function value.

[0261] In some embodiments, the acquisition module 10 may further include:

[0262] The second transmitting submodule is configured to periodically transmit M frames of a transmitting signal, where the transmitting signal is a linear frequency modulated continuous wave signal, and M is a positive integer greater than 1;

[0263] A first mixing submodule is configured to perform, during each transmission process of the transmission signal, the following steps: receiving an echo signal corresponding to the transmission signal through the receiver; and mixing the transmission signal with the echo signal through the receiver to obtain an intermediate frequency signal corresponding to the transmission signal;

[0264] The first estimation module 20 may further include:

[0265] a sampling submodule, configured to sample the intermediate frequency signal every time a frame of the intermediate frequency signal is acquired, to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer;

[0266] a third estimation submodule, configured to estimate the distance between the object to be measured and the radar according to the N sampling points corresponding to the intermediate frequency signal, to obtain a first distance corresponding to the intermediate frequency signal;

[0267] The second estimation module 30 may further include:

[0268] a fourth estimation submodule, configured to estimate, upon acquiring each frame of the intermediate frequency signal, an additional phase change caused by the hardware circuit and physical reflection characteristics of the radar based on the first distance corresponding to the intermediate frequency signal and the first distance corresponding to the previous frame of the intermediate frequency signal, to obtain an additional phase of the intermediate frequency signal;

[0269] The correction module 40 may further include:

[0270] The second correction submodule is configured to obtain a target distance between the object to be measured and the radar based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal.

[0271] In some embodiments, the second correction submodule may include:

[0272] a second determining unit, configured to determine a second interval range of the binary iterative search according to the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal;

[0273] The second iterative unit is configured to perform a binary iterative search within the second interval with the first distance as the center to obtain a target distance between the object to be measured and the radar.

[0274] The specific implementation of the vibration measuring device is substantially the same as the specific embodiment of the vibration measuring method described above, and will not be described in detail here.

[0275] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the vibration measurement method when executing the computer program. The electronic device can be any smart terminal including a tablet computer, an in-vehicle computer, or the like.

[0276] See also Figure 6 , Figure 6 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:

[0277] The processor 601 may be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0278] The memory 602 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 602 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 602 and is called by the processor 601 to execute the vibration measurement method of the embodiments of this application.

[0279] Input / output interface 603, used to implement information input and output;

[0280] Communication interface 604, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0281] Bus 605 , which transmits information between various components of the device (e.g., processor 601 , memory 602 , input / output interface 603 , and communication interface 604 );

[0282] The processor 601 , the memory 602 , the input / output interface 603 and the communication interface 604 are connected to each other in communication within the device via a bus 605 .

[0283] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the vibration measurement method described above is implemented.

[0284] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0285] The vibration measurement method, vibration measurement device, electronic device, and storage medium provided in the embodiments of the present application obtain a rough distance estimate between the object to be measured and the radar based on an intermediate frequency signal. The method then estimates the additional phase change caused by the radar hardware circuit and physical reflection characteristics based on the rough distance estimate to obtain an additional phase. The additional phase is used to correct the rough distance estimate to obtain a refined distance estimate. The additional phase and target distance are used as the final result of the vibration measurement of the object to be measured. By estimating and compensating for the additional phase of the intermediate frequency signal, high-precision vibration measurement is achieved, overcoming the phase ambiguity problem in traditional methods.

[0286] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0287] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0288] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0289] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0290] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0291] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0292] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0293] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0294] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0295] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0296] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A vibration measurement method, characterized in that: Applied to radar, the method includes: Acquire an intermediate frequency signal, where the intermediate frequency signal is obtained by mixing a transmission signal and an echo signal by a receiver of the radar, the transmission signal is sent by a signal transmitter of the radar, and the echo signal is a signal of the transmission signal received by an antenna of the radar after being reflected by the object to be measured; estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance; estimating an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar according to the first distance to obtain an additional phase of the intermediate frequency signal; Correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar; The additional phase of the intermediate frequency signal and the target distance are used as measurement results of the vibration measurement of the object to be measured.

2. The method according to claim 1, characterized in that The obtaining of the intermediate frequency signal includes: Periodically transmitting M frames of transmission signals, wherein the transmission signal is a linear frequency modulation continuous wave signal, and M is a positive integer greater than 1; During each of the transmission signal transmission processes, the following steps are executed: receiving, by the receiver, an echo signal corresponding to the transmitted signal; The transmitting signal is mixed with the echo signal by the receiver to obtain an intermediate frequency signal corresponding to the transmitting signal.

3. The method according to claim 2, characterized in that After acquiring the intermediate frequency signal and before estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain the first distance, the method further includes: For each frame of the transmitted signal, the intermediate frequency signal is sampled to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer; The estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance includes: For each frame of the transmitted signal corresponding to an intermediate frequency signal, estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal, to obtain a temporary distance corresponding to the intermediate frequency signal, wherein the first distance includes M temporary distances corresponding to the intermediate frequency signals; The estimating, based on the first distance, an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar to obtain an additional phase of the intermediate frequency signal includes: Calculating according to the M phase angles corresponding to the M temporary distances to obtain the additional phase; The step of correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar includes: Based on the additional phase and the M temporary distances, the M target distances between the object to be measured and the radar are obtained.

4. The method according to claim 3, characterized in that The estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal for each frame of the transmitted signal to obtain a temporary distance corresponding to the intermediate frequency signal includes: For each frame of the intermediate frequency signal corresponding to the transmitted signal, performing fast Fourier transform on N sampling points corresponding to the intermediate frequency signal to obtain a spectrum sequence; Obtaining the frequency point corresponding to the maximum spectrum amplitude in the spectrum sequence and the initial distance corresponding to the frequency point; Determine a first interval range of a binary iterative search according to the frequency point; Taking the initial distance as the center, a binary iterative search is performed within the first interval to obtain a temporary distance corresponding to the intermediate frequency signal.

5. The method according to claim 3, characterized in that The obtaining, based on the additional phase and the M first distances, the M target distances between the object to be measured and the radar, includes: Performing maximum likelihood estimation based on the additional phase and the M temporary distances to obtain a first candidate sequence, where the first candidate sequence includes M first candidate target distances, and the first candidate sequence is a sequence obtained by estimating the target distance in the absence of phase ambiguity; Performing maximum likelihood estimation based on the additional phase, π, and the M temporary distances to obtain a second candidate sequence, where the second candidate sequence includes M second candidate target distances, and the second candidate sequence is a sequence obtained by estimating the target distance in the case of phase ambiguity; Calculating a loss function value of maximum likelihood estimation of the first candidate sequence and the second candidate sequence to obtain a first loss function value corresponding to the first candidate sequence and a second loss function value corresponding to the second candidate sequence; If the first loss function value is greater than or equal to the second loss function value, taking the M first candidate target distances in the first candidate sequence as the M target distances; If the first loss function value is less than the second loss function value, the M second candidate target distances in the second candidate sequence are used as the M target distances.

6. The method according to claim 1, characterized in that The obtaining of the intermediate frequency signal includes: Periodically transmitting M frames of transmission signals, wherein the transmission signal is a linear frequency modulation continuous wave signal, and M is a positive integer greater than 1; During each of the transmission signal transmission processes, the following steps are executed: receiving, by the receiver, an echo signal corresponding to the transmitted signal; Mixing the transmission signal with the echo signal by the receiver to obtain an intermediate frequency signal corresponding to the transmission signal; The estimating the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance includes: Each time a frame of the intermediate frequency signal is acquired, the intermediate frequency signal is sampled to obtain N sampling points corresponding to the intermediate frequency signal, where N is a positive integer; estimating the distance between the object to be measured and the radar according to N sampling points corresponding to the intermediate frequency signal to obtain a first distance corresponding to the intermediate frequency signal; The estimating, based on the first distance, an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar to obtain an additional phase of the intermediate frequency signal includes: Each time a frame of the intermediate frequency signal is acquired, an additional phase change caused by the hardware circuit and physical reflection characteristics of the radar is estimated based on the first distance corresponding to the intermediate frequency signal and the first distance corresponding to the previous frame of the intermediate frequency signal to obtain the additional phase of the intermediate frequency signal; The step of correcting the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar includes: A target distance between the object to be measured and the radar is obtained based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal.

7. The method according to claim 6, characterized in that The obtaining of a target distance between the object to be measured and the radar based on the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal includes: Determine a second interval range of the binary iterative search according to the additional phase of the intermediate frequency signal and the first distance of the intermediate frequency signal; Taking the first distance as the center, a binary iterative search is performed within the second interval to obtain the target distance between the object to be measured and the radar.

8. A vibration measuring device, characterized in that: Applied to radar, the device comprises: an acquisition module, configured to acquire an intermediate frequency signal, wherein the intermediate frequency signal is obtained by mixing a transmission signal and an echo signal by a receiver of the radar, wherein the transmission signal is sent by a signal transmitter of the radar, and the echo signal is a signal of the transmission signal received by an antenna of the radar after being reflected by the object to be measured; A first estimation module, configured to estimate the distance between the object to be measured and the radar according to the intermediate frequency signal to obtain a first distance; a second estimation module, configured to estimate an additional phase change caused by a hardware circuit and physical reflection characteristics of the radar according to the first distance, to obtain an additional phase of the intermediate frequency signal; a correction module, configured to correct the first distance according to the additional phase to obtain a target distance between the object to be measured and the radar; The measuring module is configured to use the additional phase of the intermediate frequency signal and the target distance as the measurement results of the vibration measurement of the object to be measured.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the vibration measurement method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the vibration measurement method according to any one of claims 1 to 7 is implemented.

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