Method, apparatus and device for performing sensing processing using sensing signal

Abstract

The present application relates to a method, apparatus, and device for performing sensing processing using a sensing signal, the method including the steps of: generating and transmitting a sequence of first sensing signals distributed along the diagonal of a resource block of a signal; receiving a sequence of second sensing signals reflected by a target; normalizing the sequence of second sensing signals in the modulation symbol domain to obtain a sequence of normalized sensing signals in the modulation symbol domain; and performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain to calculate distance information and velocity information of the target according to the 1D-DFT result. By using the present application, the distance information and velocity information of the target contained in the normalized sensing signal in the modulation symbol domain can be simultaneously obtained, thereby significantly reducing the computational complexity of the sensing processing of the sensing signal, and significantly reducing the overhead of the sensing signal due to the waveform structure.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims priority to a Chinese patent application filed with the China Patent Office on October 17, 2022, bearing application number 202211291287.9 ​​and entitled "Method, apparatus and device for performing sensing processing using sensing signals," the entire contents of which are incorporated herein by reference.

[0002] The present application relates to the field of wireless communication technology, and in particular to a method, apparatus and device for performing sensing processing using a sensing signal. [Background technology]

[0003] The goal of waveform design for 6G Joint Communication and Sensing (JCAS) is to design an appropriate waveform that allows communication signals and sensing signals to operate in the same frequency band and share radio and hardware resources. Currently, one of the main research ideas for waveform design for joint communication and sensing is based on Orthogonal Frequency Division Multiplexing (OFDM), a waveform used in traditional 4G / 5G communication systems. An important application of 6G joint communication and sensing is wireless sensing for positioning.

[0004] Figure 1 shows a grid signal resource block in which sensing signals are distributed at equal intervals in the time and frequency domains of the grid signal resource block. In the figure, black represents sensing signal symbols and white represents communication symbols. The mainstream distance and velocity measurement method for OFDM radar uses maximum likelihood estimation (MLE) to perform a two-dimensional discrete Fourier transform (2D-DFT) on the normalized modulation symbol matrix in the modulation symbol domain included in the grid signal resource block in Figure 1 to obtain distance and velocity information of the measured target. This method has the following problems:

[0005] 1) 2D-DFT requires first performing a one-dimensional discrete Fourier transform (1D-DFT) on the modulation symbol matrix row by row, and then performing a 1D-IDFT on the resulting matrix column by column. When the accuracy requirements for distance and velocity measurement are high, the order of the Fourier transform becomes high, and the calculation of the maximum likelihood estimation method becomes extremely complex; 2) The sensing waveform required for the maximum likelihood estimation method is a waveform in which the sensing signal is distributed in a grid pattern at equal intervals in the frequency domain and the time domain.This waveform has a very large sensing overhead and has a significant impact on communication performance. Summary of the Invention [Problem to be solved by the invention]

[0006] To solve the problem in the related art that the sensing signals in the time domain and frequency domain of the resource blocks of the grid-shaped signal are distributed at equal intervals, making the calculation of the maximum likelihood estimation method extremely complex and causing high waveform sensing overhead, the present application provides a solution that can reduce the calculation complexity and waveform sensing overhead. [Means for solving the problem]

[0007] According to a first embodiment of the present application, the present application provides a method for performing a sensing process using a sensing signal, the method comprising: generating and transmitting a sequence of first sensing signals distributed along a diagonal of a resource block of the signal; receiving a sequence of second sensing signals reflected by a target, and normalizing the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; and performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain, and calculating distance information and velocity information of the target according to the 1D-DFT result.

[0008] In one or more possible embodiments, the step of generating a sequence of first sensing signals distributed along diagonals of a resource block of a signal comprises: generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; The first sequence of sensing signals includes a plurality of sensing signals, and each resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

[0009] In one or more possible embodiments, the step of calculating range information and velocity information of the target according to the 1D-DFT result includes: Determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; calculating distance information based on the frequency containing the distance information, and calculating speed information based on the frequency containing the speed information.

[0010] In one or more possible embodiments, a frequency including distance information and a frequency including velocity information are selected based on the first bin index and the second bin index. Calculate The steps are: frequency f H and frequency f L determining

number

number

[0011] In one or more possible embodiments, Calculate distance information based on frequencies containing distance information, and calculate speed information based on frequencies containing speed information The steps are: The frequency containing distance information is

number

number

[0012] In one or more embodiments, based on a linear motion model of the target, a frequency f H is the frequency that contains distance information, and frequency f L is the frequency that contains velocity information, or L is the frequency that contains distance information, and frequency f H is a frequency containing velocity information, frequency f H and obtains the first distance information using the frequency f L The first speed information is obtained using f L and calculate the second distance information using f H determining second velocity information using using the linear motion model, based on the first distance information and the first velocity information, to obtain third distance information and a ... Third and predicting the speed information of the target object at a different time in the future. Third determining a first 1D-DFT result corresponding to velocity information of using the linear motion model to predict fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at a different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, H is the frequency containing distance information, and frequency f L is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f L is the frequency containing distance information, and frequency f H is a frequency that contains velocity information.

[0013] In one or more embodiments, the step of normalizing the second sequence of sensing signals in the modulation symbol domain to obtain a sequence of normalized sensing signals in the modulation symbol domain comprises: The method includes comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in the modulation symbol domain.

[0014] According to a second embodiment of the present application, there is provided a device for performing sensing processing using a sensing signal, the device comprising: a memory and at least one processor; the memory is used to store computer programs; The at least one processor reads a program in the memory and: generating and transmitting a sequence of first sensing signals distributed along a diagonal of a resource block of the signal; receiving a sequence of second sensing signals reflected by a target, and normalizing the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; and performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain, and calculating the range information and velocity information of the target according to the 1D-DFT result.

[0015] In one or more possible embodiments, the at least one processor is configured to: minutes generating a sequence of first sensing signals to be distributed over the entire image; generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; The first sequence of sensing signals includes a plurality of sensing signals, and each resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

[0016] In one or more possible embodiments, the step of calculating range information and velocity information of the target according to the 1D-DFT result by the at least one processor includes: Determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; calculating distance information based on the frequency containing the distance information, and calculating speed information based on the frequency containing the speed information.

[0017] In one or more possible embodiments, the at least one processor may select a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index. Calculate The steps are: frequency f H and frequency f L determining

number

number

[0018] In one or more possible embodiments, the at least one processor: Calculate distance information based on frequencies containing distance information, and calculate speed information based on frequencies containing speed information The steps are: The frequency containing distance information is

number

number

[0019] In one or more possible embodiments, the at least one processor may be configured to generate a frequency f H is the frequency that contains distance information, and frequency f Lis the frequency that contains velocity information, or L is the frequency that contains distance information, and frequency f H is a frequency containing velocity information, frequency f H and obtains the first distance information using the frequency f L The first speed information is obtained using f L and calculate the second distance information using f H determining second velocity information using using the linear motion model, based on the first distance information and the first velocity information, to obtain third distance information and a ... Third and predicting the speed information of the target object at a different time in the future. Third determining a first 1D-DFT result corresponding to velocity information of using the linear motion model to predict fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at a different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, H is the frequency containing distance information, and frequency f L is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f L is the frequency containing distance information, and frequency f H is a frequency that contains velocity information.

[0020] In one or more possible embodiments, the step of the at least one processor normalizing the second sequence of sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain includes: The method includes comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in the modulation symbol domain.

[0021] According to a third aspect of the present application, there is provided an apparatus for performing a sensing process using a sensing signal, comprising: a sensing signal generation module for generating and transmitting a sequence of first sensing signals distributed along diagonals of a resource block of the signal; a sensing signal receiving module for receiving a sequence of second sensing signals reflected by a target, and normalizing the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; and a sensing information acquisition module for performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain, and calculating distance information and velocity information of a target according to the 1D-DFT result.

[0022] In one or more possible embodiments, the step of the sensing signal generation module generating a sequence of first sensing signals distributed along diagonals of the resource block of the signal comprises: generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; The first sequence of sensing signals includes a plurality of sensing signals, and each resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

[0023] In one or more possible embodiments, the step of the sensing information acquisition module calculating the distance information and velocity information of the target according to the 1D-DFT result includes: Determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; calculating distance information based on the frequency containing the distance information, and calculating speed information based on the frequency containing the speed information.

[0024] In one or more possible embodiments, a sensing information acquisition module acquires a frequency including distance information and a frequency including speed information based on the first bin index and the second bin index. Calculate The steps are: frequency f H and frequency f L determining

number

number

[0025] In one or more possible embodiments, the sensing information acquisition module: Calculate distance information based on frequencies containing distance information, and calculate speed information based on frequencies containing speed information The steps are: The frequency containing distance information is

number

number

[0026] In one or more possible embodiments, the sensing information acquisition module acquires the frequency f based on a linear motion model of the target. H is the frequency that contains distance information, and frequency f L is the frequency that contains velocity information, or L is the frequency that contains distance information, and frequency f H is a frequency containing velocity information, frequency f H and obtains the first distance information using the frequency f L The first speed information is obtained using f L and calculate the second distance information using f H determining second velocity information using using the linear motion model, based on the first distance information and the first velocity information, to obtain third distance information and a ... Thirdand predicting the speed information of the target object at a different time in the future. Third determining a first 1D-DFT result corresponding to velocity information of using the linear motion model to predict fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at a different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, H is the frequency containing distance information, and frequency f L is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f L is the frequency containing distance information, and frequency f H is a frequency that contains velocity information.

[0027] In one or more possible embodiments, the step of the sensing signal receiving module normalizing the second sequence of sensing signals in the modulation symbol domain to obtain a sequence of normalized sensing signals in the modulation symbol domain includes: The method includes comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in a modulation symbol domain.

[0028] According to a fourth aspect of the present application, a chip is provided, the chip being coupled to a memory in a device, and the chip, when operating, calls program instructions stored in the memory to perform the above-mentioned examples of the embodiments of the present application and any of the methods mentioned in the examples.

[0029] According to a fifth aspect of the present application, there is provided a computer-readable storage medium, which stores program instructions that, when executed on a computer, cause the computer to perform the above-mentioned examples of embodiments of the present application and any of the methods mentioned in the examples.

[0030] According to a sixth aspect of the present application, a computer program product is provided, which, when executed on an electronic device, causes the electronic device to perform any of the above-mentioned examples and any of the methods mentioned in the examples of the embodiments of the present application. [Effects of the Invention]

[0031] The method, apparatus and device for performing sensing processing using the sensing signal provided by the present application can provide the following beneficial effects.

[0032] By simultaneously obtaining the distance information and velocity information of the target reflector contained in the normalized sensing signal in the modulation symbol domain, the calculation complexity in the sensing processing of the sensing signal is greatly reduced, and the waveform structure significantly reduces the overhead of the sensing signal.In addition, the higher the order of DFT processing, the more the diagonal waveform of the present application can reduce the sensing overhead compared to the conventional grid waveform.

[0033] In order to more clearly describe the technical solutions in the embodiments of the present application, the following will briefly describe the drawings that need to be used in describing the embodiments. However, the drawings in the following description are only some embodiments of the present application, and it is obvious that those skilled in the art can obtain other drawings based on these drawings without performing creative work. [Brief explanation of the drawings]

[0034] [Figure 1]1 is a schematic diagram of the structure of a resource block of a grid-like signal in the related art; [Figure 2] 1 is a schematic diagram of resource blocks of multiple signals transmitted consecutively in the related art; [Figure 3] FIG. 1 is a block schematic diagram of an OFDM radar signal transceiver in the related art. [Figure 4] 4 is a flowchart of a method for performing sensing processing using a sensing signal in an embodiment of the present application. [Figure 5] FIG. 10 is a structural schematic diagram of a resource block of a signal provided with a diagonal sensing signal in an embodiment of the present application; [Figure 6] FIG. 2 is a schematic diagram showing the result of performing 1D-DFT on d(k) corresponding to a diagonal sensing signal in an embodiment of the present application. [Figure 7a] This is a schematic diagram of the 1D-DFT results using a linear motion model to predict the corresponding velocity-distance at different times in the future when the target is moving at a constant velocity based on Profile A. [Figure 7b] This is a schematic diagram of the 1D-DFT results using a linear motion model to predict the corresponding velocity-distance at different times in the future when the target is moving at a constant velocity based on Profile B. [Figure 7c] This is a schematic diagram of the 1D-DFT results using a linear motion model to predict the corresponding velocity-distance at different times in the future when the target is moving at constant acceleration based on Profile A. [Figure 7d] This is a schematic diagram of the 1D-DFT results using a linear motion model to predict the corresponding velocity-distance at different times in the future when the target is moving at constant acceleration based on Profile B. [Figure 8] 1 is a structural schematic diagram of an apparatus for performing sensing processing using a sensing signal in an embodiment of the present application; [Figure 9] 1 is a structural schematic diagram of a device that performs sensing processing using a sensing signal; DETAILED DESCRIPTION OF THE INVENTION

[0035] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be described in more detail below with reference to the accompanying drawings, but it is clear that the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments that can be obtained by those skilled in the art based on the embodiments of the present application without any creative work fall within the scope of protection of the present application.

[0036] The main distance and speed measurement algorithm for existing OFDM radars is the Maximum Likelihood Estimation (MLE) method based on the modulation symbol domain. This algorithm is briefly explained using a traffic monitoring scenario as an example. The radar index requirements for this scenario are shown in Table 1.

[0037] Table 1: Traffic monitoring scenario metrics requirements [Table 1]

[0038] The range resolution ΔR is the minimum distance at which the radar can distinguish two targets located at the same azimuth angle. The range resolution is determined by the radar operating bandwidth B.

[0039]

number

[0040] Here, C0 represents the speed of light.

[0041] The velocity resolution Δv is the minimum velocity at which the radar can distinguish two targets located at the same azimuth angle. The velocity resolution is the duration T of the radar sensing signal. b is determined by

[0042]

number

[0043] where C0 represents the speed of light and f c represents the carrier frequency, and T b is the time domain duration of the sensing signal.

[0044] The result of radar signal processing based on DFT is periodic. Therefore, OFDM radar has an unambiguous maximum distance measurement range, i.e., the maximum detection distance, which is expressed by the following formula:

[0045]

number

[0046] where C0 represents the speed of light, Δf represents the subcarrier spacing, and N f represents the number of frequency domain sensing signals, and N c represents the total number of subcarriers.

[0047] Similarly, the maximum detection speed is given by the following formula:

[0048]

number

[0049] By combining equations (1) to (4), the waveform of the sensing signal that satisfies the index requirements in Table 1 can be designed as a time-frequency resource as shown in Figure 1. In this embodiment, this time-frequency resource will be referred to as a grid-like signal resource block. The signal resource block is a time-domain resource block with a duration T b The time domain is 30 ms, it contains 239 time slots, the frequency domain bandwidth is 400 MHz, and there are 3359 Subcarrier The sensing signal is distributed between symbols 2 and 9 in each time slot, and the frequency domain interval is 7. SubcarrierThe waveform of the resource block of this grid signal can achieve a distance resolution of 0.375 m, a velocity resolution of 0.65 km / h, a maximum detection distance of 1250 m, and a maximum detection velocity of 2300 km / h.

[0050] The resource blocks of this grid signal are distributed at equal intervals between the sensing signals in the time and frequency domains. By performing DFT processing on the modulation symbol domain sensing signal data matrix contained in the resource block in Figure 1, a distance and speed radar chart for that time can be obtained.

[0051] When the resource blocks of the grid-shaped signal shown in Figure 1 are transmitted continuously in the time domain, the sensing signal is transmitted continuously at multiple different times t0, t1, t2, etc., as shown in Figure 2, and a dynamic distance and speed radar chart can be obtained by performing DFT processing on the modulation symbol domain information contained in the resource blocks of each grid-shaped signal.

[0052] The following is the OFDM radar signal processing process based on modulation symbol domain:

[0053] FIG. 3 is a schematic diagram of the overall process in which the transmitting end transmits the sensing signal with the waveform shown in FIGS. 1 and 2, and the details are as follows:

[0054] Modulation symbol domain signal d Tx (m,n) is transmitted from the transmitting antenna after undergoing IFFT (Inverse Fast Fourier Transform), CP (Cyclic Prefix) insertion, and digital-to-analog conversion. The sensing signal is reflected by the sensing target in space, and the echo is received by the receiving antenna. It undergoes analog-to-digital conversion, CP removal, and FFT to produce a modulated symbol domain signal d at the receiving end. Rx (m,n) is generated. d Rx (m, n) is expressed by the following formula.

[0055]

number

[0056] where A(m,n) is the change in signal strength of the sensing signal, and two exponential terms

number

number

[0057] d Rx (m,n) for each item Tx By dividing by (m, n), the information contained in the sensing signal is removed and expressed in matrix form.

[0058]

number

[0059] where:

number

[0060] Vector y R N in (m) f The linear phase change of each unit contains distance information of the sensing object and can be obtained by IDFT.

[0061]

number

[0062] The IDFT result is Nf Among the bins, one bin takes the maximum value, and the bin index p peak and the distance to the object can be obtained using the following equation (10):

[0063]

number

[0064] Vector y D In (n), N t The linear phase change of this unit contains velocity information of the sensing object and can be obtained by DFT.

[0065]

number

[0066] The DFT result is N t Among the bins, one bin takes the maximum value, and the bin index of that maximum value is q peak and the velocity of the object can be obtained using the following equation (12).

[0067]

number

[0068] Equation (6) can also be expressed in matrix form.

[0069]

number

[0070] First, the data of the matrix D(m,n) in equation (13) is subjected to a DFT transformation for each row, and then the results of the DFT transformation for each row are subjected to an IDFT transformation for each column, thereby obtaining a radar range-velocity image.

[0071] When the accuracy requirement for distance and velocity measurement is high, the order of the Fourier transform also becomes high, and the calculation of the maximum likelihood estimation method becomes extremely complex. Taking the waveform of the sensing signal shown in Figure 1 as an example, the calculation complexity of the first-order DFT is O(N 2 ), where N is the order of the DFT. When a 2D-DFT is performed on a resource block of one grid-shaped signal of the waveform of the sensing signal shown in Figure 1, the computational complexity is 960O(N 2 ) is high, that is, 2N 3 By calculating the multiplication of complex numbers of order =221,184,000, a first-order distance and speed radar chart can be obtained.

[0072] Furthermore, the sensing waveform required for maximum likelihood estimation is a waveform in which the sensing signal is distributed in a grid pattern at equal intervals in both the frequency and time domains. This waveform has a very large sensing overhead, which significantly affects communication performance.

[0073] In view of this, an embodiment of the present application proposes a method for performing sensing processing using a sensing signal, and as shown in FIG. 4, the method includes the following steps:

[0074] In step 401, a sequence of first sensing signals distributed along the diagonals of a resource block of the signal is generated and transmitted.

[0075] The signal resource block includes resources corresponding to different time and frequency domain positions. For the grid-shaped signal resource block, in an embodiment of the present application, sensing signals are distributed along the diagonals of the signal resource block to provide a diagonal sensing waveform. A plurality of sensing sequence numbers are numbered on the diagonals to form a one-dimensional sensing signal sequence, and the one-dimensional sensing signal sequence is transmitted to detect a target.

[0076] In step 402, receive a sequence of second sensing signals reflected by a target, and normalize the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain.

[0077] In one or more possible embodiments, the step of normalizing the second sequence of sensing signals in the modulation symbol domain to obtain a sequence of normalized sensing signals in the modulation symbol domain includes: The method includes performing element-wise division of the second sensing signal sequence and the transmitted first sensing signal sequence to obtain a normalized sensing signal sequence in the modulation symbol domain.

[0078] The sequence of normalized sensing signals that has been normalized contains both distance information and velocity information.

[0079] In step 403, a one-dimensional discrete Fourier transform (1D-DFT) is performed using the sequence of normalized sensing signals in the modulation symbol domain, and the distance information and velocity information of the target are calculated according to the 1D-DFT result.

[0080] In the embodiment of the present application, the sequence of the normalized sensing signal in the modulation symbol domain is a one-dimensional sequence, so only a one-dimensional discrete Fourier transform (1D-DFT) is required, and the obtained 1D-DFT result contains both the distance information and velocity information of the target. The present application can simultaneously obtain both the distance information and velocity information of the target reflector contained in the normalized sensing signal in the modulation symbol domain, which significantly reduces the calculation complexity of the sensing processing of the sensing signal, and the waveform structure significantly reduces the overhead of the sensing signal. Furthermore, the higher the order of the DFT processing, the more the sensing overhead of the diagonal waveform in the present application is reduced compared to the conventional grid-shaped sensing waveform.

[0081] In one or more possible embodiments, the step of generating a sequence of first sensing signals distributed along diagonals of a resource block of a signal comprises: The method includes generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal.

[0082] Here, the first sensing signal sequence includes multiple sensing signals, and each of the signal resource blocks includes the same number of sensing signals in the time domain and the frequency domain. The specific structure is shown in Figure 5, where the signal resource block required for calculating the primary range velocity of the diagonal sensing waveform is the same as the grid signal resource block shown in Figure 1. The signal resource block has a duration T b The time domain is 30 ms, it contains 239 time slots, the frequency domain bandwidth is 400 MHz, and there are 3359 Subcarrier The sensing signal is distributed between symbols 2 and 9 in each time slot, and the frequency domain interval is 7. Subcarrier The sensing signals are distributed diagonally across the resource block of the signal. The sensing signals are transmitted in symbols 2 and 9 of each time slot. In this way, the 480 sensing signals are uniformly distributed in both the frequency and time domains.

[0083] The first sensing signal sequence d in the modulation symbol domain of the transmitting end Tx (k) is transmitted by the transmitting antenna after undergoing OFDM processing. The sensing signal is reflected by the sensing object in space, and the echo is received by the receiving antenna. The receiving end receives the second sensing signal sequence d in the modulation symbol domain. Rx (k) is obtained by the second sensing signal sequence d in the modulation symbol domain. Rx(k) is normalized to obtain a sequence of normalized sensing signals in the modulation symbol domain. In the embodiment of the present application, the sequence of normalized sensing signals in the modulation symbol domain is defined as a vector d(k), which is specifically obtained using the following calculation method:

[0084]

number

[0085] where:

number

[0086] The vector d(k) has N = 480 units, and the linear phase change of these units not only contains the distance information of the sensing object, but also the velocity information of the sensing object. Taking a target with a distance R = 40 m and a velocity v = 5 m / s as an example, we perform an N = 480-order 1D-DFT transformation on the normalized sensing signal sequence d(k).

[0087]

number

[0088] An N=480 order 1D-DFT transform is performed on the normalized sensing signal sequence d(k), and the results are shown in Figure 6. The 1D-DFT transform result contains two peak locations, which correspond to the first bin index l1 and the second bin index l2 in the frequency domain, respectively. The first bin index and the second bin index are the bin indices of the DFT. Taking a target with a distance R=40 m and a velocity v=5 m / s as an example, the 1D-DFT transform result contains two peaks, one of which is located at DFT bin index 81 and recorded as l1, and the other peak is located at DFT bin index 134 and recorded as l2.

[0089] In one or more possible embodiments, the step of calculating range information and velocity information of the target according to the 1D-DFT result includes: Determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; determining a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; determining distance information using the frequency containing distance information, and determining velocity information using the frequency containing velocity information.

[0090] Two DFT frequencies f from the first bin index l1 and the second bin index l2 H and f L get.

[0091]

number

[0092] Two DFT frequencies f H and f L One of them contains the target's range information and the other contains its velocity information. That is, the two DFT frequencies f H and f L One of the frequencies contains distance information, and the other contains velocity information. H is 107.5MHz, f L is 26.5MHz.

[0093] In one or more possible embodiments, the step of determining distance information using frequencies including distance information and determining velocity information using frequencies including velocity information comprises: The frequency containing distance information is

number

number

[0094] where Δf represents the subcarrier spacing of the sensing signal sequence, and N c represents the total number of subcarriers in the sensing signal sequence, R is the distance, C0 represents the speed of light, and N sym is the duration T b represents the number of symbols in the sequence of the sensing signal in f c represents the carrier frequency, and T b is the time domain duration of the sequence of sensing signals.

[0095] In the embodiment of the present application, the distance and velocity calculated by the normalized sensing signal of the modulation symbol area included along the resource block of one signal may have uncertainties, and a multi-phase data fusion method needs to be adopted to determine the correct distance-velocity information.

[0096] That is, the above two DFT frequencies f H and f L One possibility is f H is the frequency that contains distance information, f L is the frequency that contains the velocity information, and another possibility is f L is the frequency that contains distance information, f H is the frequency that contains velocity information. Therefore, the distance and velocity can be calculated from equation (20) or (21).

[0097]

number

[0098] Taking the 1D-DFT results generated by the target with distance R = 40 m and velocity v = 5 m / s as an example, the 1D-DFT results are similar to those generated by the target with distance R = 10 m and velocity v = 20 m / s. This is because the unmarked DFT frequency f H and f L This is because the distance and velocity information is included in the DFT result. Two range-velocity values ​​can be obtained from the two peak indexes l1 and l2 shown in Figure 5. One of them is the correct distance-velocity value, and the other is the incorrect distance-velocity value.

[0099] In the embodiment of the present application, these two distance velocity values ​​are recorded as profile A and profile B, respectively.

[0100] Profile A: R = 40 m, v = 5 m / s; Profile B: R = 10 m, v = 20 m / s.

[0101] In the embodiment of the present application, a multi-phase data fusion method is used to select one of Equation (20) and Equation (21) to determine the correct range-velocity information, i.e., to select a set of correct values ​​from profile A and profile B.

[0102] In one or more possible embodiments, the step of determining a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index includes: frequency f H and frequency f L determining

number

number

[0103] Here, the linear motion model is a model constructed to predict the corresponding distance and velocity of the target at different times based on the motion characteristics of the target.

[0104] The target motion characteristics are determined according to the target motion scenarios, reflecting the characteristics of time-varying velocity and distance, including, but not limited to, constant velocity motion characteristics and constant acceleration motion characteristics. In the case of constant acceleration motion characteristics, corresponding accelerations are determined based on the target motion characteristics in different scenarios.

[0105] In one or more possible embodiments, based on a linear motion model of the target, a frequency f H is the frequency that contains distance information, and frequency f L is the frequency that contains velocity information, or L is the frequency that contains distance information, and frequency f H is a frequency containing velocity information, frequency f H and obtains the first distance information using the frequency f L The first speed information is obtained using f L and calculate the second distance information using f H determining second velocity information using using the linear motion model, based on the first distance information and the first velocity information, to obtain third distance information and a ... Third and predicting the speed information of the target object at a different time in the future. Thirddetermining a first 1D-DFT result corresponding to velocity information of using the linear motion model to predict fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at a different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, H is the frequency containing distance information, and frequency f L is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f L is the frequency containing distance information, and frequency f H is a frequency that contains velocity information.

[0106] the third distance information; and Third When the fourth speed information, the fourth distance information and the fourth speed information, the fifth distance information and the fifth speed information are acquired, the frequency including the distance information is

number

number

[0107] In the embodiment of the present application, a traffic monitoring scenario is used as an example. A linear motion model is a model commonly used in kinematics research. The linear motion model is a model constructed to predict the corresponding distance and speed of a target at different times based on the target's motion characteristics. This model assumes that the target maintains constant velocity or constant acceleration within a sufficiently short time. It is assumed that vehicles in the traffic monitoring scenario conform to the linear motion model. It is also assumed that Profile A and Profile B are obtained by performing 1D-FFT processing on d(k) contained in a diagonal sensing waveform transmitted at time t0=0. For a vehicle conforming to the linear motion model of constant velocity, the corresponding distance and speed at times t1=30 ms, t2=60 ms, t3=90 ms, and t4=120 ms for a vehicle corresponding to Profile A and Profile B calculated and acquired at time t0 can be predicted, respectively.

[0108] For a vehicle that conforms to the linear motion model of uniform acceleration, the maximum vehicle acceleration is set to 5.4 m / s 2 Assume that the velocity is 5.4m / s. 2 The acceleration corresponds to the acceleration from 0 to 100 km / h in 5 seconds. Normally, it is 5.4 m / s 2 This acceleration is considered to be the maximum acceleration capability of a high-performance vehicle. It is also possible to estimate the distance-velocity of a vehicle in uniform acceleration motion corresponding to Profile A and Profile B at times t1 = 30 ms, t2 = 60 ms, t3 = 90 ms, and t4 = 120 ms. Table 2 shows the predicted distance-velocity values ​​for Profile A and Profile B at times t1 = 30 ms, t2 = 60 ms, t3 = 90 ms, and t4 = 120 ms. Table 2

[0109]

Table 2

[0110] Figure 7a shows the results of 1D-DFT using a linear motion model to predict the corresponding speed-distance at different future times during the target's constant velocity motion based on Profile A. The speed corresponding to t0 obtained based on Profile A is 5 m / s and the distance is 40 m. Using the linear motion model, the distance-velocity is predicted at different future times t1 = 30 ms, t2 = 60 ms, t3 = 90 ms, and t4 = 120 ms during the target's constant velocity motion, and the corresponding 1D-DFT results are obtained based on the predicted distance-velocity. Figure 7b shows the results of 1D-DFT using a linear motion model to predict the corresponding speed-distance at different future times during the target's constant velocity motion based on Profile B. The speed corresponding to t0 obtained based on Profile A is 20 m / s and the distance is 10 m. Using the linear motion model, the distance-velocity is predicted at different future times t1 = 30 ms, t2 = 60 ms, t3 = 90 ms, and t4 = 120 ms during the target's constant velocity motion. Based on the predicted distance-velocity, the corresponding 1D-DFT results are obtained. Figure 7c shows the results of 1D-DFT using a linear motion model to predict the corresponding velocity-distance at different future times during the target's constant acceleration motion based on Profile A. The velocity corresponding to t0 obtained based on Profile A is 5 m / s and the distance is 40 m. Using the linear motion model, the distance-velocity is predicted at different future times t1 = 30 ms, t2 = 60 ms, t3 = 90 ms, and t4 = 120 ms during the target's constant acceleration motion, and the corresponding 1D-DFT results are obtained based on the predicted distance-velocity. Figure 7d shows the results of 1D-DFT using a linear motion model to predict the corresponding velocity-distance at different future times during the target's constant acceleration motion based on Profile B. Using a linear motion model, the velocity corresponding to t0 obtained based on Profile A is 20 m / s and the distance is 10 m. The distance-velocity is predicted at different future times t1 = 30 ms, t2 = 60 ms, t3 = 90 ms, and t4 = 120 ms during the target's constant acceleration motion, and the corresponding 1D-DFT results are obtained based on the predicted distance-velocity.

[0111] The corresponding peak values ​​in each figure are shown enlarged in the dashed frame. The peak values ​​from right to left in each dashed frame are t0 = 0 ms, t1 = 30 ms, t2 = 60 ms, t 3 = The 1D-DFT results for t = 90 ms and t = 120 ms are shown in order. As can be seen from Figure 7a, the change in the peak position in the DFT results due to the change in time is extremely small. Since the DFT bins are integers, the distance and velocity estimates are quantized onto bins with fixed intervals. If y R (k) and y D If a frequency contained in (k) does not fall into one of its bins, the actual frequency is quantized to a nearby bin, thus introducing a quantization error. Since the speed of the vehicle is constant, a constant speed causes f L does not change over time. Also, the speed of the vehicle is very slow (5 m / s), and the change in distance within 120 ms is extremely small due to the slow speed. Therefore, f H The change in is also very small. The peak energy at times t1 to t4 is distributed between DFT bin indices 78 to 81 and 133 to 134. At some adjacent times, the bin index of the peak does not change. For example, the bin index of the peak at time t1 and the bin index of the peak at time t2 are both 80. For the uniform velocity motion of profile B shown in Figure 7b, it can be seen that the results are significantly different from those in Figure 7a. Because the vehicle speed is constant, the constant velocity causes f H does not change over time. Also, the speed of the vehicle is fast (20 m / s), and the change in distance within 120 ms is very large due to the high speed. Therefore, f L From the above analysis, by comparing the two predicted 1D-DFT results with the actual 1D-DFT results for uniform motion, it is possible to determine which of the two profiles obtained at time t0 is correct.

[0112] In traffic monitoring applications, the vehicle acceleration is limited by the vehicle's performance and very large acceleration is not possible. The vehicle acceleration is completely unpredictable and for vehicles with non-zero acceleration, fH and f L f varies with time. However, the corresponding 1D-DFT results for Profile A and Profile B at times t1 to t4 are still significantly different. For Profile A, the velocity does not change much due to the limited acceleration. As shown in Figure 7c, the low velocity (5 m / s) and small acceleration at time t0 result in a large f H and f L The changes in f at times t1 to t4 are small, and the movement of each peak over time is very small. For Profile B, the high velocity (20 m / s) at time t0 L The change in velocity at time t0 is large, which causes the peaks at each time in Figure 7d to be sparser than those in Figure 7c. Therefore, the speed at time t0 is an important factor in distinguishing Profile A from Profile B. Because the acceleration is low in the traffic monitoring application scenario, acceleration has little effect on the change in the DFT results over time. This significantly reduces the computational complexity. As above, by comparing the two predicted 1D-DFT results with the actual 1D-DFT results for constant velocity motion, it is possible to determine which of the two profiles obtained at time t0 is correct.

[0113] In the related art, 2D-DFT is performed on the waveform of the grid-shaped sensing signal shown in Figure 1, and the computational complexity is 960O(N 2 ), and a first-order distance / speed radar chart can be obtained. By using the diagonal sensing waveform and the corresponding sensing signal processing algorithm proposed in the embodiment of the present application, the computational complexity of processing the resource block of one signal is O(N 2 In the related art, the overhead of the grid-shaped waveform sensing signal is

number

number

[0114] The waveform structure of the present application significantly reduces the overhead of the sensing signal, and the higher the order of the DFT processing, the more the sensing overhead of the diagonal waveform of the present application is reduced compared to the conventional grid waveform.

[0115] According to equations (1) to (4), the present application and the related art have exactly the same index performance such as distance resolution, velocity resolution, maximum detection distance, and maximum detection velocity from the distribution of sensing signals in the time-frequency domain.

[0116] Referring to FIG. 8 , an embodiment of the present application further provides an apparatus for performing sensing processing using a sensing signal, a sensing signal generation module 801 for generating and transmitting a sequence of first sensing signals distributed along a diagonal of a resource block of a signal; a sensing signal receiving module 802 for receiving a sequence of second sensing signals reflected by a target, and performing normalization processing on the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; and a sensing information acquisition module 803 for performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain, and calculating distance information and velocity information of a target according to the 1D-DFT result.

[0117] In one or more possible embodiments, the step of the sensing signal generation module generating a sequence of first sensing signals distributed along diagonals of the resource block of the signal comprises: generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; The first sequence of sensing signals includes a plurality of sensing signals, and each resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

[0118] In one or more possible embodiments, the step of the sensing information acquisition module calculating the distance information and velocity information of the target according to the 1D-DFT result includes: Determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; calculating distance information based on the frequency containing the distance information, and calculating speed information based on the frequency containing the speed information.

[0119] In one or more possible embodiments, a sensing information acquisition module acquires a frequency including distance information and a frequency including speed information based on the first bin index and the second bin index. Calculate The steps are: frequency f H and frequency f L determining

number

number

[0120] In one or more possible embodiments, the sensing information acquisition module: Calculate distance information based on frequencies containing distance information, and calculate speed information based on frequencies containing speed information The steps are: The frequency containing distance information is

number

number

[0121] In one or more possible embodiments, the sensing information acquisition module acquires the frequency f based on a linear motion model of the target. H is the frequency that contains distance information, and frequency f L is the frequency that contains velocity information, or L is the frequency that contains distance information, and frequency f H is a frequency containing velocity information, frequency f H and obtains the first distance information using the frequency f L The first speed information is obtained using f Land calculate the second distance information using f H determining second velocity information using using the linear motion model, based on the first distance information and the first velocity information, to obtain third distance information and a ... Third and predicting the speed information of the target object at a different time in the future. Third determining a first 1D-DFT result corresponding to velocity information of using the linear motion model to predict fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at a different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, H is the frequency containing distance information, and frequency f L is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f L is the frequency containing distance information, and frequency f H is a frequency that contains velocity information.

[0122] In one or more possible embodiments, the step of the sensing signal receiving module normalizing the second sequence of sensing signals in the modulation symbol domain to obtain a sequence of normalized sensing signals in the modulation symbol domain includes: The method includes comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in the modulation symbol domain.

[0123] The device for performing sensing processing using the sensing signal provided by the embodiment of the present application and the method for performing sensing processing using the sensing signal provided by the embodiment of the present application belong to the same inventive concept, and various embodiments of the method for performing sensing processing using the sensing signal provided by the embodiment can be applied and implemented to the device for performing sensing processing using the sensing signal in this embodiment, so the description thereof will not be repeated here.

[0124] The above describes the apparatus for performing sensing processing using sensing signals in the embodiments of the present application from the perspective of modularized functional entities. Hereinafter, the device for performing sensing processing using sensing signals in the embodiments of the present application will be described from the perspective of hardware processing.

[0125] Referring to FIG. 9, a device for performing sensing processing using a sensing signal in an embodiment of the present application includes: It comprises at least one processor 900, a memory 901, a transceiver 902, and a bus interface 903.

[0126] The at least one processor 900 is responsible for managing and normal processing of the bus architecture, and the memory 901 can store data used by the at least one processor 900 when performing operations. The transceiver 902 is used to transmit and receive data under the control of the at least one processor 900.

[0127] The bus architecture may include any number of interconnected buses and bridges, specifically connected by various circuits, one or more at least one processor, such as at least one processor 900, and memory, such as memory 901. The bus architecture may also connect various other circuits, such as peripherals, voltage regulators, and power management circuits, all of which are well known in the art and will not be described further herein. The bus interface provides an interface. The at least one processor 900 is responsible for managing the bus architecture and normal processing, and the memory 901 may store data used by the at least one processor 900 when performing operations.

[0128] The flow disclosed in the embodiments of the present application is applied to or executed by at least one processor 900. In execution, each step of the signal processing flow can be performed by an integrated logic circuit of hardware or instructions in software form in the at least one processor 900. The at least one processor 900 can be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or another programmable logic device, a discrete gate, a transistor logic device, or a discrete hardware component, and can implement or execute each method, step, and logic block diagram disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the method according to the embodiments of the present application can be directly executed by a hardware processor or can be executed by a combination of hardware and software modules in the processor. The software modules can be located in storage media well known in the art, such as random memory, flash memory, read-only memory, programmable read-only memory, electrically erasable and programmable memory, registers, etc. The storage medium is placed in memory 901, and at least one processor 900 reads the information in memory 901 and combines its hardware to execute the steps of the signal processing flow.

[0129] Specifically, at least one processor 900 reads a program in memory 901 and: above The sensing signal provided by the embodiment is used to perform a sensing process.

[0130] An embodiment of the present application further provides a computer-readable storage medium comprising instructions, when executed on a computer, that cause the computer to perform a method for performing sensing processing using a sensing signal provided by the above embodiment of the present application.

[0131] Those skilled in the art can clearly understand that for convenience and simplicity of description, the specific operation processes of the above devices and modules can refer to the corresponding processes in the above method embodiments, and the description thereof will not be repeated here.

[0132] It should be understood that in some embodiments provided by the present application, the disclosed systems, devices, and methods may be implemented in other ways. For example, the device embodiments described above are merely exemplary. For example, the module divisions are merely logical function divisions, and actual implementations may involve other divisions. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not implemented. Furthermore, the couplings or direct couplings or communication connections between the components shown or discussed may be indirect couplings or communication connections via interfaces, devices, or modules, and may be electrical, mechanical, or other types of couplings.

[0133] The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place or may be arranged in multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the objective of the solution of this embodiment.

[0134] Furthermore, the functional modules in each embodiment of the present application may be integrated into a single processing module, may exist independently, or two or more modules may be integrated into a single module. The integrated modules may be implemented in the form of hardware or software functional modules. When the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may be stored in a computer-readable storage medium.

[0135] The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. If implemented using software, they may be implemented in whole or in part in the form of a computer program product.

[0136] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function described in the embodiments of the present application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optics, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium on which a computer can store data, or a data storage device such as a server or data center integrated with one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0137] The above has described in detail the technical solutions provided by the present application. The present application uses specific examples to explain the principles and embodiments of the present application, and the above description of the embodiments is used to facilitate understanding of the method and core idea of ​​the present application, and those skilled in the art may make changes in the specific embodiments and application scope based on the idea of ​​the present application. In summary, the contents of this specification should not be understood as limitations on the present application.

[0138] Those skilled in the art will appreciate that embodiments of the present application may be provided as a method, a system, or a computer program product. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. The present application may also take the form of a computer program product embodied in one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0139] This application has been described based on flow diagrams and / or block diagrams of the methods, devices (systems), and computer program products of this application. It should be understood that each flow and / or block in the flow charts and / or block diagrams, and combinations of flows and / or blocks in the flow charts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to at least one processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to generate an apparatus, and the instructions executed by at least one processor of the computer or other programmable data processing device generate an apparatus for implementing the function(s) specified in one or more flows in the flow charts and / or one or more blocks in the block diagrams.

[0140] These computer program instructions may further be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, where the instructions stored in the computer-readable memory produce an article of manufacture that includes an instruction apparatus, which implements the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams.

[0141] These computer program instructions may then be loaded into a computer or other programmable data processing device and cause the computer or other programmable apparatus to perform a series of operational steps to generate a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams.

[0142] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. If these modifications and variations to the present application fall within the scope of the claims of the present application and their equivalents, the present application intends to include these modifications and variations. [Explanation of symbols]

[0143] 78 DFT bin indexes 79 DFT bin index 80 DFT bin indexes 81 DFT bin index 133 DFT bin index 134 DFT bin index 401 Steps 402 Step 403 Step 801 Sensing Signal Generation Module 802 Sensing Signal Receiving Module 803 Sensing Information Acquisition Module 900 processor 901 Memory 902 Transceiver 903 Bus Interface

Claims

1. A method for performing a sensing process using a sensing signal, comprising: generating and transmitting a sequence of first sensing signals distributed along diagonals of a resource block of the signal; receiving a sequence of second sensing signals reflected by a target, and normalizing the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain, and calculating distance information and velocity information of the target according to the 1D-DFT result.

2. The step of generating a sequence of first sensing signals distributed along a diagonal of a resource block of the signal comprises: generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; The method of claim 1 , wherein the first sequence of sensing signals includes a plurality of sensing signals, and each resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

3. The step of calculating distance information and velocity information of the target according to the 1D-DFT result includes: determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information according to the first bin index and the second bin index; 3. The method according to claim 1, further comprising the steps of: calculating distance information based on frequencies containing distance information; and calculating speed information based on frequencies containing speed information.

4. The step of obtaining a frequency including distance information and a frequency including velocity information according to the first bin index and the second bin index includes: frequency f Ｈ and frequency f Ｌ determining [Equation 1] 、 [Equation 2] , l １ is the first bin index, and ２ is the second bin index; Based on the linear motion model of the target, the frequency f Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, or Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information; 4. The method of claim 3, wherein the linear kinematic model is a model constructed to predict the corresponding distance and velocity of the target at different times based on the kinematic characteristics of the target.

5. The step of determining distance information using a frequency including distance information and determining speed information using a frequency including speed information includes: The frequency containing distance information is [Equation 3] determining distance information using The frequency containing the speed information is [Equation 4] and determining velocity information using the fact that Δf represents a subcarrier spacing of the sequence of sensing signals, and N ｃ represents the total number of subcarriers in the sequence of the sensing signal, R is the distance, and C ０ represents the speed of light, and N ｓｙｍ is the duration T ｂ represents the number of symbols in the sequence of the sensing signal in ｃ represents the carrier frequency, and T ｂ 4. The method of claim 3, wherein: is the time domain duration of the sequence of sensing signals.

6. Based on the linear motion model of the target, the frequency f Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, or Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information, frequency f Ｈ and determining the first distance information using a frequency f Ｌ and determining the first velocity information using f Ｌ and determining second distance information using f Ｈ determining second velocity information using predicting third distance information and fourth speed information at a different time in the future based on the first distance information and the first speed information using the linear motion model, and determining a first 1D-DFT result corresponding to the third distance information and fourth speed information at a different time in the future; predicting fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information using the linear motion model, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at the different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information.

7. Normalizing the second sequence of sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain includes:

3. The method according to claim 1, further comprising the step of comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in the modulation symbol domain.

8. A device that performs sensing processing using a sensing signal, a memory and at least one processor; the memory is used to store computer programs; The at least one processor reads a program in the memory and generating and transmitting a sequence of first sensing signals distributed along diagonals of a resource block of the signal; receiving a sequence of second sensing signals reflected by a target, and normalizing the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; a step of performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain, and calculating distance information and velocity information of a target according to the 1D-DFT result.

9. The step of generating a sequence of first sensing signals spaced along a diagonal of a resource block of a signal by the at least one processor includes: generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; The device of claim 8 , wherein the first sequence of sensing signals includes a plurality of sensing signals, and each resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

10. The step of calculating distance information and velocity information of the target according to the 1D-DFT result by the at least one processor includes: determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; 10. The device according to claim 8 or 9, further comprising the steps of: calculating distance information based on frequencies containing distance information; and calculating speed information based on frequencies containing speed information.

11. The step of determining a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index by the at least one processor includes: frequency f Ｈ and frequency f Ｌ determining [Equation 5] 、 [Equation 6] , l １ is the first bin index, and ２ is the second bin index; Based on the linear motion model of the target, the frequency f Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, or Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information; The device of claim 10 , wherein the linear motion model is a model constructed to predict corresponding distances and velocities of the target at different times based on the motion characteristics of the target.

12. The step of the at least one processor determining distance information using frequencies including distance information and determining velocity information using frequencies including velocity information includes: The frequency containing distance information is [Equation 7] determining distance information using The frequency containing the speed information is [Equation 8] and determining velocity information using the fact that Δf represents a subcarrier spacing of the sequence of sensing signals, and N ｃ represents the total number of subcarriers in the sequence of the sensing signal, R is the distance, and C ０ represents the speed of light, and N ｓｙｍ is the duration T ｂ represents the number of symbols in the sequence of the sensing signal in ｃ represents the carrier frequency, and T ｂ 11. The device of claim 10, wherein t is the time domain duration of the sequence of sensing signals.

13. The at least one processor calculates a frequency f based on a linear motion model of the target. Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, or Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information, frequency f Ｈ and determining the first distance information using a frequency f Ｌ and determining the first velocity information using f Ｌ and determining second distance information using f Ｈ determining second velocity information using predicting third distance information and fourth speed information at a different time in the future based on the first distance information and the first speed information using the linear motion model, and determining a first 1D-DFT result corresponding to the third distance information and fourth speed information at a different time in the future; predicting fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information using the linear motion model, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at the different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f Ｌ is a frequency containing distance information, and frequency f Ｈ and determining that is a frequency containing velocity information.

14. The step of the at least one processor normalizing the second sequence of sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain includes:

10. The device according to claim 8 or 9, further comprising a step of comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in the modulation symbol domain.

15. An apparatus for performing sensing processing using a sensing signal, a sensing signal generation module for generating and transmitting a sequence of first sensing signals distributed along diagonals of resource blocks of the signal; a sensing signal receiving module for receiving a sequence of second sensing signals reflected by a target, and normalizing the sequence of second sensing signals in a modulation symbol domain to obtain a sequence of normalized sensing signals in a modulation symbol domain; a sensing information acquisition module for performing a one-dimensional discrete Fourier transform (1D-DFT) using the sequence of normalized sensing signals in the modulation symbol domain and calculating distance information and velocity information of a target according to the 1D-DFT result.

16. The step of the sensing signal generation module generating a sequence of first sensing signals distributed along a diagonal of a resource block of the signal includes: generating a sequence of first sensing signals equally spaced along a diagonal of a resource block of the signal; 16. The apparatus of claim 15, wherein the first sequence of sensing signals includes a plurality of sensing signals, and a resource block of the signals includes the same number of sensing signals in the time domain and the frequency domain, respectively.

17. The step of the sensing information acquisition module calculating the distance information and the velocity information of the target according to the 1D-DFT result includes: determining a first bin index corresponding to a first peak position and a second bin index corresponding to a second peak position according to the 1D-DFT result; calculating a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index; 17. The apparatus according to claim 15 or 16, further comprising the steps of: calculating distance information based on frequencies containing distance information; and calculating speed information based on frequencies containing speed information.

18. The step of the sensing information acquisition module obtaining a frequency including distance information and a frequency including velocity information based on the first bin index and the second bin index includes: frequency f Ｈ and frequency f Ｌ determining [Equation 9] 、 [Equation 10] , l １ is the first bin index, and ２ is the second bin index; Based on the linear motion model of the target, the frequency f Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, or Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information; 18. The apparatus of claim 17, wherein the linear motion model is a model constructed to predict corresponding distances and velocities of the target at different times based on the motion characteristics of the target.

19. The step of the sensing information acquisition module obtaining distance information using a frequency including distance information and obtaining speed information using a frequency including speed information includes: The frequency containing distance information is [0011] determining distance information using The frequency containing the speed information is [0012] and determining velocity information using the fact that Δf represents a subcarrier spacing of the sequence of sensing signals, and N ｃ represents the total number of subcarriers in the sequence of the sensing signal, R is the distance, and C ０ represents the speed of light, and N ｓｙｍ is the duration T ｂ represents the number of symbols in the sequence of the sensing signal in ｃ represents the carrier frequency, and T ｂ 18. The apparatus of claim 17, wherein: is the time domain duration of the sequence of sensing signals.

20. The sensing information acquisition module acquires a frequency f Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, or Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information, frequency f Ｈ and determining the first distance information using a frequency f Ｌ and determining the first velocity information using f Ｌ and determining second distance information using f Ｈ determining second velocity information using predicting third distance information and fourth speed information at a different time in the future based on the first distance information and the first speed information using the linear motion model, and determining a first 1D-DFT result corresponding to the third distance information and fourth speed information at a different time in the future; predicting fourth distance information and fourth velocity information at a different time in the future based on the second distance information and second velocity information using the linear motion model, and determining a second 1D-DFT result corresponding to the fourth distance information and fourth velocity information at the different time in the future; measuring fifth range information and fifth velocity information at a different time in the future and determining a third 1D-DFT result corresponding to the fifth range information and fifth velocity information; If it is determined that the first 1D-DFT result and the third 1D-DFT result match, Ｈ is a frequency containing distance information, and frequency f Ｌ is a frequency containing velocity information, and if it is determined that the second 1D-DFT result and the third 1D-DFT result match, the frequency f Ｌ is a frequency containing distance information, and frequency f Ｈ is a frequency containing velocity information.

21. The step of the sensing signal receiving module normalizing the second sensing signal sequence in the modulation symbol domain to obtain a normalized sensing signal sequence in the modulation symbol domain includes:

17. The apparatus according to claim 15 or 16, further comprising a step of comparing the second sequence of sensing signals with the first sequence of sensing signals to obtain a normalized sequence of sensing signals in the modulation symbol domain.

22. A computer program medium having stored thereon a computer program, the computer program medium being characterized in that, when the computer program is executed by a processor, it performs the steps of the method according to any one of claims 1 to 7.

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