Perception data processing method and device and storage medium

Abstract

The invention provides a perception data processing method and device and a storage medium, and the method comprises the steps: obtaining an initial estimation parameter of a target object in a perception period, the initial estimation parameter being obtained through data estimation according to a first perception signal, a second perception signal and an estimation algorithm, the first perception signal being used for perceiving the target object, and the second perception signal being used for perceiving the target object; the second sensing signal is an echo corresponding to the first sensing signal, and sending of the first sensing signal and receiving of the second sensing signal adopt sparse time-frequency resources; according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of an estimation algorithm, a correction value corresponding to the initial estimation parameter is determined, the resource allocation parameter reflects the sparse degree of the time-frequency resource, and the algorithm parameter comprises a data estimation threshold reflecting the algorithm estimation capability; and correcting the initial estimation parameter by using the correction value to obtain a target estimation parameter of the target object in the sensing period. Therefore, the accuracy of sensing measurement is improved by correcting the estimated parameters.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device and storage medium for processing perception data. Background Art

[0002] Joint communication and sensing (JCAS), referred to as joint sensing integration, is the integration of communication function and perception function on network equipment. It can be applied to scenarios such as distance measurement and speed measurement. Therefore, distance measurement and speed measurement algorithms can be deployed on joint sensing integration receivers.

[0003] The distance and speed measurement algorithm can use the two-dimensional fast fourier transform (2D-FFT) periodogram method. In the 2D-FFT periodogram method, the sensing signal of the transmitting end and the sensing signal of the receiving end are divided to obtain a two-dimensional matrix. For the two-dimensional matrix, each column of data is subjected to an inverse fast Fourier transform (IFFT), and then each row of data in the result of the IFFT transform is subjected to a discrete Fourier transform (FFT) to obtain a two-dimensional radar image in the distance and speed domain, and then the estimated distance and estimated speed are obtained.

[0004] However, in order to reduce computational complexity and improve resource utilization, perception signals are transmitted using sparse time-frequency resources, resulting in a decrease in the accuracy of data measurement in the above method. Summary of the invention

[0005] The present disclosure provides a perception data processing method, device and storage medium, which are used to solve the problem that perception signals are transmitted using sparse time-frequency resources, resulting in low data measurement accuracy.

[0006] In a first aspect, the present disclosure provides a perception data processing method, which is applied to a perception terminal, including: obtaining initial estimation parameters of a target object within a perception period, the initial estimation parameters are obtained by performing data estimation based on a first perception signal, a second perception signal and an estimation algorithm, the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources; determining a correction value corresponding to the initial estimation parameter based on a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold that reflects the estimation capability of the algorithm; and correcting the initial estimation parameter using the correction value to obtain a target estimation parameter of the target object within the perception period.

[0007] In a possible implementation, the initial estimation parameters include an initial estimation distance, the time-frequency resources include distance perception resources, the resource allocation parameters of the time-frequency resources include resource allocation parameters of the distance perception resources, and the correction values ​​corresponding to the initial estimation parameters include the distance correction values ​​corresponding to the initial estimation distance; determining the correction values ​​corresponding to the initial estimation parameters according to the resource allocation parameters of the time-frequency resources and / or the algorithm parameters of the estimation algorithm, including: obtaining a data offset between the first perception signal and the second perception signal; determining a threshold value according to the resource allocation parameters and algorithm parameters of the distance perception resources; and comparing the data offset and the threshold value to obtain the distance correction value.

[0008] In a possible implementation, obtaining a data offset between a first perception signal and a second perception signal includes: determining the number of sampling points according to a resource allocation parameter and an algorithm parameter of a distance perception resource; sampling the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; and determining the data offset based on the sampling values.

[0009] In a possible implementation, resource allocation parameters of distance sensing resources include subcarrier spacing and subcarrier sparse sorting interval number, the estimation algorithm is a Fourier transform algorithm, the data estimation threshold includes a distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm, and the algorithm parameters also include the number of FFT points and the number of IFFT points; according to the resource allocation parameters and algorithm parameters of the distance sensing resources, the number of sampling points is determined, including: determining the measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; determining the number of sampling points according to the distance estimation threshold, the measurement delay, the distance sensing threshold of the distance sensing resource, the subcarrier spacing and the number of FFT points; wherein the distance sensing threshold comes from the resource allocation parameters, or the distance sensing threshold is determined according to the subcarrier spacing and the number of subcarrier sparse sorting intervals.

[0010] In a possible implementation, a threshold value is determined according to resource allocation parameters and algorithm parameters of distance sensing resources, including: determining the threshold value according to a measurement delay, a subcarrier spacing, and an IFFT point number.

[0011] In a possible implementation, comparing the data offset and the threshold value to obtain the distance correction value includes: rounding the ratio of the data offset and the threshold value to obtain the distance correction value.

[0012] In a possible implementation, the initial estimation parameters also include a first estimated speed, the correction value corresponding to the initial estimation parameters also includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; after correcting the initial estimated distance to obtain the target estimated distance of the target object within the perception cycle, it also includes: determining the second estimated speed based on the target estimated distance of the target object within the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle; comparing the second estimated speed with the speed estimation threshold to obtain the speed correction value.

[0013] In a possible implementation, comparing the second estimated speed with the speed estimation threshold to obtain the speed correction value includes: rounding the ratio of the second estimated speed to the speed estimation threshold to obtain the speed correction value.

[0014] In one possible implementation, the difference between the initial estimated parameter and the true parameter is a correction value data estimation threshold, where the correction value is an integer; the initial estimated parameter is corrected using the correction value to obtain the target estimated parameter of the target object within the perception period, including: multiplying the correction value by the data estimation threshold to obtain the product; and determining the target estimated parameter as the sum of the product and the initial estimated parameter.

[0015] In one possible implementation, the data estimation threshold includes a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter includes an initial estimated distance and / or a first estimated speed, the target estimation parameter includes a target estimated distance and / or a target estimated speed, and the correction value includes a distance correction value and / or a speed correction value; multiplying the correction value by the data estimation threshold to obtain a product includes: multiplying the distance correction value by the distance estimation threshold to obtain a first product, and / or multiplying the speed correction value by the speed estimation threshold to obtain a second product; determining the target estimation parameter as the sum of the product and the initial estimation parameter includes: determining the target estimated distance as the sum of the first product and the initial estimated distance, and / or determining the target estimated speed as the sum of the second product and the first estimated speed.

[0016] In a possible implementation, before the correction value is used to correct the initial estimation parameter to obtain the target estimation parameter of the target object within the perception period, it also includes: determining that the initial estimation parameter belongs to fuzzy data based on the correction value and a configured threshold.

[0017] In a possible implementation, the perception data processing method further includes: receiving first information from a network device, where the first information includes a resource allocation parameter.

[0018] In a possible implementation, after the initial estimated parameters are corrected by using correction values ​​to obtain the target estimated parameters of the target object within the perception period, the method further includes: sending second information to the network device, the second information including the target estimated parameters and / or correction values.

[0019] In a second aspect, the present disclosure provides a perception data processing method, which is applied to a network device, comprising: receiving second information from a perception end; wherein the second information includes target estimation parameters of the target object within the perception period and / or correction values ​​corresponding to initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

[0020] In a third aspect, the present disclosure provides a perception data processing device, which is applied to a perception terminal, and the perception data processing device includes a memory, a transceiver, and a processor;

[0021] Memory for storing computer programs;

[0022] a transceiver for transmitting and receiving data under the control of the processor;

[0023] The processor is used to read the computer program in the memory and perform the following operations: obtain initial estimation parameters of the target object within the perception period, the initial estimation parameters are obtained by performing data estimation based on a first perception signal, a second perception signal and an estimation algorithm, the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources; determine correction values ​​corresponding to the initial estimation parameters based on resource allocation parameters of the time-frequency resources and / or algorithm parameters of the estimation algorithm, the resource allocation parameters reflect the sparsity of the time-frequency resources, and the algorithm parameters include data estimation thresholds that reflect the estimation capability of the algorithm; and use the correction values ​​to correct the initial estimation parameters to obtain target estimation parameters of the target object within the perception period.

[0024] In a possible implementation, the initial estimation parameters include an initial estimated distance, the time-frequency resources include distance sensing resources, the resource allocation parameters of the time-frequency resources include resource allocation parameters of the distance sensing resources, and the correction values ​​corresponding to the initial estimation parameters include the distance correction values ​​corresponding to the initial estimated distance; the processor is specifically used to: obtain a data offset between the first sensing signal and the second sensing signal; determine a threshold value based on the resource allocation parameters and algorithm parameters of the distance sensing resources; and compare the data offset and the threshold value to obtain a distance correction value.

[0025] In one possible implementation, the processor is specifically used to: determine the number of sampling points based on resource allocation parameters and algorithm parameters of distance perception resources; sample the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; and determine the data offset based on the sampling values.

[0026] In a possible implementation, resource allocation parameters of distance sensing resources include subcarrier spacing and subcarrier sparse sorting interval number, the estimation algorithm is a Fourier transform algorithm, the data estimation threshold includes a distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm, and the algorithm parameters also include the number of FFT points and the number of IFFT points; the processor is specifically used to: determine the measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; determine the number of sampling points according to the distance estimation threshold, the measurement delay, the distance sensing threshold of the distance sensing resource, the subcarrier spacing and the number of FFT points; wherein the distance sensing threshold comes from the resource allocation parameters, or the distance sensing threshold is determined according to the subcarrier spacing and the number of subcarrier sparse sorting intervals.

[0027] In a possible implementation manner, the processor is specifically configured to: determine a threshold value according to a measured delay, a subcarrier spacing, and an IFFT point number.

[0028] In one possible implementation, the initial estimation parameters also include a first estimated speed, the correction value corresponding to the initial estimation parameters also includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; the processor is also used to: determine the second estimated speed based on the target estimated distance of the target object within the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle; compare the second estimated speed with the speed estimation threshold to obtain the speed correction value.

[0029] In a possible implementation manner, the processor is specifically configured to: round the ratio of the second estimated speed to the speed estimation threshold to obtain a speed correction value.

[0030] In one possible implementation, the difference between the initial estimated parameter and the true parameter is a correction value data estimation threshold, where the correction value is an integer; the processor is specifically used to: multiply the correction value by the data estimation threshold to obtain a product; and determine the target estimated parameter as the sum of the product and the initial estimated parameter.

[0031] In one possible implementation, the data estimation threshold includes a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter includes an initial estimated distance and / or a first estimated speed, the target estimation parameter includes a target estimated distance and / or a target estimated speed, and the correction value includes a distance correction value and / or a speed correction value; the processor is specifically used to: multiply the distance correction value by the distance estimation threshold to obtain a first product, and / or, multiply the speed correction value by the speed estimation threshold to obtain a second product; determine the target estimation parameter as the sum of the product and the initial estimation parameter, including: determining the target estimated distance as the sum of the first product and the initial estimated distance, and / or, determining the target estimated speed as the sum of the second product and the first estimated speed.

[0032] In a possible implementation, the processor is further configured to: determine, based on the correction value and a configured threshold, that the initial estimation parameter belongs to fuzzy data.

[0033] In a possible implementation manner, the processor is further configured to: receive first information from a network device, where the first information includes a resource allocation parameter.

[0034] In a possible implementation manner, the processor is further configured to: send second information to the network device, where the second information includes the target estimation parameter and / or the correction value.

[0035] In a fourth aspect, the present disclosure provides a perception data processing device, which is applied to a network device, and the perception data processing device includes a memory, a transceiver and a processor; the memory is used to store a computer program; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer program in the memory and perform the following operations: receiving second information from the perception end; wherein the second information includes target estimation parameters of the target object within the perception period and / or correction values ​​corresponding to initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

[0036] In a fifth aspect, the present disclosure provides a perception data processing device, which is applied to a perception end, and the perception data processing device includes: an acquisition unit, which is used to acquire initial estimation parameters of a target object within a perception period, the initial estimation parameters are obtained by performing data estimation based on a first perception signal, a second perception signal and an estimation algorithm, the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources; a correction value determination unit, which is used to determine a correction value corresponding to the initial estimation parameter based on a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold that reflects the estimation capability of the algorithm; a correction unit, which is used to correct the initial estimation parameter using the correction value to obtain the target estimation parameter of the target object within the perception period.

[0037] In a possible implementation, the initial estimation parameters include an initial estimation distance, the time-frequency resources include distance perception resources, the resource allocation parameters of the time-frequency resources include resource allocation parameters of the distance perception resources, and the correction values ​​corresponding to the initial estimation parameters include the distance correction values ​​corresponding to the initial estimation distance; the correction value determination unit is specifically used to: obtain a data offset between the first perception signal and the second perception signal; determine a threshold value according to the resource allocation parameters and algorithm parameters of the distance perception resources; and compare the data offset and the threshold value to obtain the distance correction value.

[0038] In a possible implementation, the correction value determination unit is specifically used to: determine the number of sampling points according to the resource allocation parameters and algorithm parameters of the distance perception resource; sample the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; and determine the data offset based on the sampling values.

[0039] In a possible implementation, the resource allocation parameters of the distance sensing resource include the subcarrier spacing and the number of subcarrier sparse sorting intervals, the estimation algorithm is a Fourier transform algorithm, the data estimation threshold includes a distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm, and the algorithm parameters also include the number of FFT points and the number of IFFT points; the correction value determination unit is specifically used to: determine the measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; determine the number of sampling points according to the distance estimation threshold, the measurement delay, the distance sensing threshold of the distance sensing resource, the subcarrier spacing and the number of FFT points; wherein the distance sensing threshold comes from the resource allocation parameter, or the distance sensing threshold is determined according to the subcarrier spacing and the number of subcarrier sparse sorting intervals.

[0040] In a possible implementation manner, the correction value determination unit is specifically configured to determine a threshold value according to a measured delay, a subcarrier spacing, and an IFFT point number.

[0041] In a possible implementation manner, the correction value determination unit is specifically configured to: round the ratio of the data offset to the threshold value to obtain the distance correction value.

[0042] In a possible implementation, the initial estimation parameters also include a first estimated speed, the correction value corresponding to the initial estimation parameters also includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; the correction value determination unit is specifically used to: determine the second estimated speed based on the target estimated distance of the target object within the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle; compare the second estimated speed with the speed estimation threshold to obtain the speed correction value.

[0043] In a possible implementation manner, the correction value determination unit is specifically configured to: round the ratio of the second estimated speed to the speed estimation threshold to obtain the speed correction value.

[0044] In one possible implementation, the difference between the initial estimated parameter and the true parameter is a correction value data estimation threshold, where the correction value is an integer; the correction unit is specifically used to: multiply the correction value by the data estimation threshold to obtain a product; and determine the target estimated parameter as the sum of the product and the initial estimated parameter.

[0045] In one possible implementation, the data estimation threshold includes a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter includes an initial estimated distance and / or a first estimated speed, the target estimation parameter includes a target estimated distance and / or a target estimated speed, and the correction value includes a distance correction value and / or a speed correction value; the correction unit is specifically used to: multiply the distance correction value by the distance estimation threshold to obtain a first product, and / or, multiply the speed correction value by the speed estimation threshold to obtain a second product; determine the target estimated distance as the sum of the first product and the initial estimated distance, and / or, determine the target estimated speed as the sum of the second product and the first estimated speed.

[0046] In a possible implementation, the perception data processing device further includes: a fuzzy judgment unit, configured to determine whether the initial estimation parameter belongs to fuzzy data based on the correction value and a configured threshold.

[0047] In a possible implementation, the perception data processing apparatus further includes: a receiving unit, configured to receive first information from a network device, wherein the first information includes a resource allocation parameter.

[0048] In a possible implementation, the perception data processing apparatus further includes: a sending unit, configured to send second information to the network device, wherein the second information includes a target estimation parameter and / or a correction value.

[0049] In a sixth aspect, the present disclosure provides a perception data processing device, which is applied to a network device. The perception data processing device includes: a receiving unit, which is used to receive second information from a perception end; wherein the second information includes a target estimation parameter of the target object within the perception period and / or a correction value corresponding to an initial estimation parameter of the target object within the perception period, and the target estimation parameter is obtained by correcting the initial estimation parameter based on the correction value.

[0050] In a seventh aspect, the present disclosure provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the perception data processing method provided in the first aspect or the second aspect.

[0051] In an eighth aspect, the present disclosure provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the perceptual data processing method provided in the first aspect or the second aspect.

[0052] In a ninth aspect, the present disclosure provides a communication system, comprising any of the above-mentioned perception terminals and any of the above-mentioned network devices.

[0053] According to the perception data processing method, device and storage medium provided by the present disclosure, the first perception signal for perceiving the target object and the second perception signal as the echo of the first perception signal are transmitted using sparse time-frequency resources, resulting in a certain deviation in the initial estimation parameters obtained by data estimation based on the first perception signal, the second perception signal and the estimation algorithm. In order to improve the accuracy of data measurement through the perception signal, the correction value corresponding to the initial estimation parameter can be determined based on the resource allocation parameter of the time-frequency resource and / or the algorithm parameter of the estimation algorithm, and the initial estimation parameter is corrected using the correction value to obtain the target estimation parameter. Since the resource allocation parameter of the time-frequency resource can reflect the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation parameter that reflects the estimation capability of the algorithm, the resource allocation parameter and / or the algorithm parameter based on the time-frequency resource can improve the accuracy of the correction value, thereby improving the accuracy of the correction of the initial estimation parameter and the accuracy of the target estimation parameter. In this way, the accuracy of the perception measurement of the target object by the perception terminal is improved.

[0054] It should be understood that the contents described in the above summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the present disclosure or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0056] Figure 1 This is a flow chart of the OFDM radar signal transmission, reception and processing in JCAS;

[0057] Figure 2 It is a schematic diagram of the 2D-FFT ranging algorithm;

[0058] Figure 3 An example diagram of the time-frequency resource structure design in JCAS;

[0059] Figure 4 This is an example of the spectrum aliasing phenomenon caused by the large distance between the target object and the radar;

[0060] Figure 5 This is an example diagram of sampling below the Nyquist sampling frequency;

[0061] Figure 6 An example diagram of an application scenario provided by an embodiment of the present disclosure;

[0062] Figure 7 Schematic diagram of the process of the perception data processing method provided in the embodiment of the present disclosure Figure 1 ;

[0063] Figure 8 Schematic diagram of the process of the perception data processing method provided in the embodiment of the present disclosure Figure 2 ;

[0064] Fig. 9 A schematic diagram of the structure of the perception data processing device provided in the embodiment of the present disclosure Figure 1 ;

[0065] Fig.10 A schematic diagram of the structure of the perception data processing device provided in the embodiment of the present disclosure Figure 2 ;

[0066] Fig.11 A schematic diagram of the structure of the perception data processing device provided in the embodiment of the present disclosure Figure 3 ;

[0067] Fig.12 A schematic diagram of the structure of the perception data processing device provided in the embodiment of the present disclosure Figure 4 . DETAILED DESCRIPTION

[0068] In the present disclosure, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, 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" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or plural.

[0069] It is understandable that the steps or operations in the embodiments of the present disclosure are only examples, and the embodiments of the present disclosure may also perform other operations or variations of various operations. In addition, the steps may be performed in different orders presented in the embodiments of the present disclosure, and it is possible that not all operations in the embodiments of the present disclosure are to be performed.

[0070] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0071] The technical solution provided by the embodiments of the present disclosure can be applicable to a variety of systems, especially 5G and 6G systems. For example, the system to which the embodiments of the present disclosure are applicable can be a global system of mobile communication (GSM) system, a code division multiple access (CDMA) system, a wideband code division multiple access (WCDMA) general packet radio service (GPRS) system, a long term evolution (LTE) system, a LTE frequency division duplex (FDD) system, a LTE time division duplex (TDD) system, an advanced long term evolution (LTE-A) system, a universal mobile telecommunication system (UMTS), a world-wide interoperability for microwave access (WiMAX) system, a 5G new radio (NR) system, etc. These various systems include terminals and network equipment. The system may also include a core network part, such as an evolved packet system (EPS), a 5G system (5GS), etc.

[0072] The terminal involved in the embodiments of the present disclosure may be a device that provides voice and / or data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem. In different systems, the name of the terminal may also be different. For example, in a 5G system, the terminal may be called a user equipment (UE). A wireless terminal can communicate with one or more core networks (CN) via a radio access network (RAN). The wireless terminal may be a mobile terminal, such as a mobile phone (or a "cellular" phone) and a computer with a mobile terminal. For example, it may be a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device that exchanges language and / or data with a radio access network. For example, personal communication service (PCS) phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs) and other devices. A wireless terminal may also be referred to as a system, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, an access point, a remote terminal, an access terminal, a user terminal, a user agent, or a user device, but is not limited to these terms in the embodiments of the present disclosure.

[0073] The network device involved in the embodiments of the present disclosure may be a base station, which may include multiple cells providing services for the terminal. Depending on the specific application scenario, the base station may also be called an access point, or may be a device in the access network that communicates with the wireless terminal through one or more sectors on the air interface, or other names. The network device may be used to interchange received air frames with Internet Protocol (IP) packets, and serve as a router between the wireless terminal and the rest of the access network, wherein the rest of the access network may include an Internet Protocol (IP) communication network. The network device may also coordinate the attribute management of the air interface. For example, the network device involved in the embodiments of the present disclosure may be a network device (Base Transceiver Station, BTS) in the Global System for Mobile communications (Global System for Mobile communications, GSM) or Code Division Multiple Access (Code Division Multiple Access, CDMA), or a network device (NodeB) in Wide-band Code Division Multiple Access (WCDMA), or an evolutionary network device (evolutional Node B, eNB or e-NodeB) in the long term evolution (long term evolution, LTE) system, or a 5G base station (gNB) in the 5G network architecture (next generation system), or a home evolved Node B (Home evolved Node B, HeNB), a relay node, a home base station (femto), a pico base station (pico), etc., which is not limited in the embodiments of the present disclosure. The network device involved in the embodiments of the present disclosure may also be a core network device.

[0074] In joint communication and sensing (JCAS), pedestrians, vehicles and other objects can be sensed by sending sensing signals, and the distance, speed and the like of the objects can be measured. The sensing signals are, for example, orthogonal frequency division multiplexing (OFDM) radar signals. To facilitate understanding of the embodiments of the present disclosure, the following describes the processing of sensing signals in JCAS, the two-dimensional fastfourier transform (2D-FFT) periodogram method, the comb structure of time-frequency resources in JCAS, and the measurement ambiguity under the comb structure.

[0075] (1) Processing of perception signals in JCAS

[0076] Figure 1 The figure is a flow chart of the OFDM radar signal transmission, reception and processing in JCAS. Figure 1 As shown, the whole process can be divided into four stages: the signal receiving and transmitting stage in the analog domain, the signal modulation and demodulation stage of OFDM modulation / demodulation, periodogram calculation and post-processing.

[0077] In the signal modulation and demodulation stage of OFDM modulation / demodulation, the data is modulated by the modulator to obtain the transmitter perception signal F TX (This signal is an OFDM radar signal); F TX After being processed by inverse fast Fourier transform (IFFT), adding cyclic prefix (CP), and digit to analog converter (D / A converter), it is sent out by the transmitting antenna; TX After being reflected by the target object in space, an echo is formed, which is received by the receiving antenna. After passing through the analog to digit converter (A / D converter), removing the CP and fast Fourier transform (FFT), the receiving end perception signal F is obtained. RX .

[0078] F RX and F TX The signal strength relationship can be expressed as:

[0079] d RX (m,n)=A(m,n)d TX (m,n)exp(-j4πΔfRm / c)exp(j4πT sym f c vn / c)

[0080] Where m represents the subcarrier index, m = 0, ..., N f -1,N f is the number of subcarriers; n represents the OFDM symbol index, n = 0, ..., N t -1,N t is the number of OFDM symbols; d RX (m,n) represents F RX The signal strength, dTX (m,n) represents F TX The signal strength of A(m,n) is represented by the signal strength change value; j represents the imaginary number symbol, Δf represents the subcarrier spacing, and f c represents the subcarrier frequency, T sym represents the duration of the OFDM symbol, c represents the speed of light, R represents the distance information of the target object, which can be the estimated distance between the target object and the radar (also called the measured distance or the perceived distance), and v represents the speed information of the target object, which can be the estimated speed of the target object (also called the measured speed or the perceived speed).

[0081] Afterwards, if Figure 1 As shown, the divider is used to divide F RX and F TX Perform a division operation to eliminate the F RX Specifically, d RX (m,n) divided by d TX (m,n), the operation result can be expressed in matrix form, and the division operation formula can be expressed as:

[0082] D(m,n)=d RX (m,n) / d TX (m,n)=A(m,n)[y R (m)⊙y D (n)]

[0083] y R (m) = exp(-j4πΔfRm / c)

[0084] y D (n) = exp(j4πT sym f c vn / c)

[0085] Among them, the vector y R (m)N f Units (i.e. N f The linear phase change of the subcarrier) contains the distance information R of the target object, which can be obtained by R (m) is calculated to obtain the distance information R; vector y D (n)N t Units (i.e. N t OFDM symbols) contains the velocity information v of the target object, which can be obtained by D (n) Perform calculation to obtain speed information v.

[0086] In through y R In the process of calculating the distance information R, we can first calculate y R(m) Perform inverse fast Fourier transform (IFFT):

[0087]

[0088] Where p = 0, ..., N f -1.

[0089] It can be seen that in the IFFT result, that is, in Y r (p) contains N f sampling points. f Among the sampling points, there are one or more sampling point peaks. Using the sampling point sequence number corresponding to the sampling point peak, the distance information of the target object corresponding to the sampling point peak can be calculated:

[0090] R=(c×p peak ) / (2ΔfN f )

[0091] Among them, p peak Y r (p) is the sampling point number corresponding to the peak value of the sampling point.

[0092] In through y D (n) In the process of calculating the speed information v, we can first calculate y D (n) Perform fast Fourier transform (FFT):

[0093]

[0094] Where q=0,…,N t -1.

[0095] It can be seen that in the FFT result, that is, in Y v (q) contains N t sampling points. t Among the sampling points, there are one or more sampling point peaks. Using the sampling point sequence number corresponding to the sampling point peak, the speed information of the target object corresponding to the sampling point peak can be calculated:

[0096] v=(c×q peak ) / (2f c T sym N t )

[0097] Among them, q peak Y r (p) is the sampling point number corresponding to the peak value of the sampling point.

[0098] like Figure 1 As shown, after performing IFFT and FFT, some further processing operations (such as Figure 1 The absolute value of the calculated result is squared and then clipped) to obtain a periodogram with relative velocity on the horizontal axis and distance on the vertical axis, where Figure 1 An example of this periodogram is shown in Figure 1 The unit of relative speed is m / s, i.e., meter per second, with values ​​such as -20, 0, 20, etc. The unit of distance is m, i.e., meter, with values ​​such as 0, 20, 40, etc. After that, target detection is performed on the periodic graph, and then some post-processing is performed to detect the distance information and speed information of the target object on the periodic graph.

[0099] (2) 2D-FFT periodogram method

[0100] In the 2D-FFT periodogram method, for y in D(m,n) R (m) Perform IFFT, y D The process of performing FFT on (n) can be implemented as follows: first, D(m,n) is expressed as a matrix, where each column of the matrix represents an OFDM symbol, and each row of the matrix represents a subcarrier. The column vector and row vector are used to describe the distance information of the target object and the phase shift information caused by the Doppler frequency shift, respectively; Figure 2 ( Figure 2 As shown in the figure, each column of D(m,n) can be transformed by IFFT to obtain the IFFT transformation result; then each row of the IFFT transformation result can be transformed by FFT to obtain the matrix result, which is a two-dimensional radar image in the range and velocity domain.

[0101] (3) Comb structure of time-frequency resources in JCAS

[0102] In JCAS, in order to ensure communication performance and save spectrum resources, the time-frequency resources used to transmit perception signals will adopt a comb structure. Specifically, the time-frequency resources include time-frequency resources for communication signal transmission and time-frequency resources for perception signals. In order to ensure that the communication signal has sufficient time-frequency resources, the time-frequency resources used for perception signals are sparsely arranged.

[0103] Figure 3 An example diagram of the time-frequency resource structure design in JCAS is shown below: Figure 3 As shown, the horizontal axis represents the OFDM symbol, and a plurality of OFDM symbols are included in one time slot. Figure 1 Take a time slot including 14 OFDM symbols as an example; the vertical axis represents subcarriers. Figure 3In the , the frequency resources are 100 MHz, including 839 subcarriers; the time resources are 7.5 ms, which can be divided into multiple time slots. For the 1st and 2nd time slots, the 3rd and 10th OFDM symbols on the 0th, 7th, 14th, and 21st subcarriers are perception signal symbols, i.e., OFDM symbols used to carry perception signals; the remaining OFDM symbols are communication signal symbols, i.e., OFDM symbols used to carry communication signals. Figure 3 It can be seen that the structure of the time-frequency resources in JCAS looks like a comb, so it is called a comb structure.

[0104] (4) Measurement ambiguity under comb structure

[0105] The time-frequency resources of the comb structure are equivalent to Figure 1 Before the divider in the , a step of selecting time-frequency resources for the receiving end perception signal and the transmitting end perception signal is added. Among them, the comb arrangement in the frequency domain mainly affects the fuzzy distance of the 2D-FFT periodogram method. The larger the comb interval, the shorter the fuzzy distance and the smaller the estimated distance range; the comb arrangement in the frequency domain mainly affects the fuzzy speed of the 2D-FFT periodogram method. The larger the comb interval, the shorter the fuzzy speed and the smaller the estimated speed range.

[0106] Among them, the fuzzy distance can be understood as the fuzzy distance limit and the maximum unfuzzy distance. When the actual distance between the target object and the radar exceeds the fuzzy distance limit, the 2D-FFT periodogram method cannot accurately estimate the distance information of the target object; the fuzzy speed can be understood as the fuzzy speed limit and the maximum unfuzzy speed. When the speed of the target object exceeds the fuzzy speed limit, the 2D-FFT periodogram method cannot accurately estimate the speed information of the target object.

[0107] For ease of understanding, the principles of blur distance and blur speed are explained below.

[0108] (1) Principle of blur speed

[0109] Taking pulse Doppler radar as an example, when pulse Doppler radar works at a low repetition frequency, the sampling frequency is lower than twice the highest frequency, which is prone to spectrum aliasing, causing confusion of target speed and difficulty in distinguishing the true speed of the target object, that is, speed ambiguity. The reason for the appearance of speed ambiguity in 2D-FFT is the same as that of pulse Doppler radar.

[0110] For fuzzy speed, the performance of wireless sensing speed measurement can be evaluated by the maximum unambiguous speed (i.e., speed unambiguous measurement range, fuzzy speed limit), and the calculation formula is as follows:

[0111]

[0112] Where M represents the number of pulses, λ represents the subcarrier wavelength, and T r represents the pulse repetition period, v max Indicates the maximum unambiguous speed.

[0113] (2) Principle of fuzzy distance

[0114] Taking pulse Doppler radar as an example, when the distance between the target object and the radar is greater than the maximum unambiguous distance R corresponding to the pulse repetition period, max (i.e., there is no fuzzy measurement range or fuzzy distance limit), the echo corresponding to the sensing signal will not fall within the pulse repetition period of the sensing signal, but may fall within the next pulse repetition period, resulting in the measured distance not being the true distance, and the true distance will differ from the measured distance by an integer multiple of R max , causing speed blur.

[0115] Figure 4 The following is an example of spectrum aliasing caused by the large distance between the target object and the radar. Figure 4 As shown, R min is the minimum measuring distance, R max is the maximum unambiguous distance. The actual distance between the target object and the radar is greater than R max In this case, the echo of the first transmitted pulse will fall within the receiving interval of the second transmitted pulse, that is, the echo of the transmitted pulse in the first pulse repetition period will fall within the second pulse repetition period, and the measured distance will differ from the actual distance by an integer multiple of R. max .

[0116] R max Used to evaluate the performance of wireless sensing ranging, the calculation formula is as follows:

[0117]

[0118] For OFDM radar using 2D-FFT periodogram algorithm, the object of delay estimation is not the delay of echo in time sequence, but the frequency affected by delay in exp(-j4πΔfRm / c) shown in the above formula. Therefore, the cause of distance ambiguity in OFDM radar is more similar to the cause of speed ambiguity, that is, spectrum aliasing caused by low sampling frequency. That is, based on Nyquist sampling theorem, when the sampling frequency is lower than twice the highest frequency, the data in the original signal is difficult to restore. Figure 5 This is an example diagram of sampling below the Nyquist sampling frequency, such as Figure 5 As shown, when there are too few sampling points, the frequency estimated based on the sampling points is not the actual expected frequency, and spectrum aliasing occurs.

[0119] In related technologies, blur can be removed by:

[0120] Method 1: Reduce the pulse repetition frequency (PRF): By reducing the PRF and increasing the interval between pulses, the echo signal can fall within the original pulse repetition period, increasing the maximum unambiguous distance. For example, in a continuous wave radar, the PRF can be reduced by increasing the duration of the transmitted signal. However, the cause of speed ambiguity and distance ambiguity under the comb-structured time-frequency resources is the spectrum aliasing caused by the low sampling frequency, not the spectrum aliasing caused by the large distance between the target object and the radar. The distance ambiguity caused by the comb structure does not exceed the duration of the OFDM symbol under the comb structure. Reducing the PRF is not effective in solving speed ambiguity and distance ambiguity under the comb structure.

[0121] For example, when the subcarrier spacing is 120 kHz, the duration of an OFDM symbol without the CP is about 8.33 microseconds, and the corresponding maximum unambiguous distance is 2500 meters, which matches the symbol duration. When a comb configuration with 16 intervals is used, the symbol duration is actually unchanged at 8.33 microseconds, but the equivalent perceived symbol duration is reduced, and the maximum unambiguous distance is reduced to about 156.25 meters. If this method is used, the interval of the comb configuration needs to be reduced, and the time-frequency resources occupied by the perceived signal increase.

[0122] Method 2: Differentiate different pulses through waveform design: This method designs multiple waveforms for pulse signals, such as up and down frequency modulation waveforms, azimuth coding waveforms, block coding waveforms, and OFDM-linear frequency modulation (LFM) waveforms. After receiving the echo signal, the waveform of the echo can be used to distinguish which pulse signal the echo corresponds to, solving the ambiguity problem caused by the inability to distinguish echoes falling in other pulse repetition periods (i.e., the ambiguity caused by the spectrum aliasing phenomenon caused by the large distance between the target object and the radar). Since the cause of speed ambiguity and distance ambiguity under the comb-structured time-frequency resources is not the inability to distinguish waveforms with different transmission times, but the low sampling frequency, this method cannot solve the speed ambiguity and distance ambiguity under the comb-structured time-frequency resources.

[0123] In order to solve the measurement ambiguity problem when the perception signal adopts sparse time-frequency (such as time-frequency resources with a comb structure), the present disclosure proposes a perception data processing method, device and storage medium. For the initial estimated parameters obtained by estimating the target object through the estimation algorithm, the perception end can determine the appropriate correction value based on the resource allocation parameters of the time-frequency resources and / or the algorithm parameters of the estimation algorithm, and use the correction value to correct the initial estimated parameters to obtain the target estimated parameters of the target object. In this way, by correcting the initial estimated parameters obtained by the estimation algorithm, a more accurate target estimated parameter is obtained, which solves the measurement ambiguity problem when the perception signal adopts sparse time-frequency to a certain extent, and improves the accuracy of measuring the target object through the perception signal.

[0124] Among them, the method and the device are based on the same application concept. Since the method and the device solve the problem in a similar principle, the implementation of the device and the method can refer to each other, and the repeated parts will not be repeated.

[0125] Based on the above technical concept, the application scenarios of the embodiments of the present disclosure are as follows:

[0126] Figure 6 This is an example diagram of an application scenario provided by an embodiment of the present disclosure. Figure 6 As shown, the application scenario involved in this embodiment may include a core network device 601, an access network device 602 and a perception terminal 603, wherein the perception terminal 603 can perceive target objects such as pedestrians and vehicles through perception signals, and the access network device 602 can also serve as a perception terminal to perceive target objects such as pedestrians and vehicles.

[0127] When the perception terminal 603 serves as the perception end, the core network device 601 can allocate time and frequency resources for perception signal transmission to the perception terminal 603 through the access network device 602; when the access network device 602 serves as the perception end, the core network device 601 can allocate time and frequency resources for perception signal transmission to the access network device 602.

[0128] As an example, in a high-speed scenario, the device that provides the sensing service is mainly a base station, that is, Figure 6 In the application scenario shown, the access network device 602 may be a base station, which senses a vehicle traveling at a high speed and obtains distance information and speed information of the vehicle.

[0129] Combine the following Figure 6 For application scenarios, refer to Figure 7-Figure 8 It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principle of the present disclosure, and the embodiments of the present disclosure can also be applied to any applicable scenarios.

[0130] Figure 7 Schematic diagram of the process of the perception data processing method provided in the embodiment of the present disclosure Figure 1 The perception data processing method can be applied to the perception end, which can be a terminal or an access network device, and the access network device can be a base station. In particular, in a high-speed scenario, the perception end can be a base station. Figure 7 As shown, on the sensing end side, the sensing data processing method of this embodiment may include:

[0131] S701, obtaining initial estimation parameters of the target object within a sensing period.

[0132] The sensing period refers to the pulse repetition period. For example, if the current sensing period is the first pulse repetition period, the initial estimated parameters of the target object in the first pulse repetition period can be obtained. The target object can be an object, or a person, animal or other living thing.

[0133] Among them, the initial estimated parameters are obtained by performing data estimation based on the first perception signal, the second perception signal and the estimation algorithm. The first perception signal is used to perceive the target object, the second perception signal is the echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources. The process of obtaining the initial estimated parameters by performing data estimation based on the first perception signal, the second perception signal and the estimation algorithm can be performed on the perception end or on other devices. Sparse time-frequency resources are, for example, the time-frequency resources of the comb structure described in the aforementioned content.

[0134] Among them, in JCAS, the first perception signal can be an OFDM radar signal.

[0135] Among them, the estimation algorithm can be a 2D-FFT periodogram method, or other algorithms, such as an FFT algorithm, a deep learning algorithm for parameter estimation of the target object, etc.

[0136] In this embodiment, the first perception signal may be sent outward by the transmitting antenna of the perception end; after the first perception signal encounters the target object, a corresponding echo is generated. For the convenience of description, the echo of the first perception signal is called the second perception signal; the second perception signal may be received by the receiving antenna of the perception end. At the perception end or on other devices, the perception parameters of the target object may be estimated based on the first perception signal, the second perception signal and the estimation algorithm, and the initial estimation parameters of the target object within the perception period corresponding to the first perception signal may be obtained. Alternatively, the initial estimation parameters of the target object within the perception period corresponding to the first perception signal may be obtained from a database, and the database may store the initial estimation parameters of the target object within one or more perception periods. The estimation algorithm may be a 2D-FFT periodogram method or other algorithms, such as using deep learning to estimate the parameters of the target object.

[0137] S702: Determine a correction value corresponding to the initial estimation parameter according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm.

[0138] The time-frequency resource refers to the sparse time-frequency resource used for sending the first perception signal and receiving the second perception signal, and the resource allocation parameter of the time-frequency resource reflects the sparsity of the time-frequency resource. The algorithm parameter of the estimation algorithm includes a data estimation threshold reflecting the estimation capability of the algorithm.

[0139] In this embodiment, the sparser the time-frequency resources used for sending the first perception signal and receiving the second perception signal, the greater the error of the initial estimation parameter, that is, the more ambiguous the initial estimation parameter; the lower the algorithm estimation capability, the greater the error of the initial estimation parameter, that is, the more ambiguous the initial estimation parameter; since the resource allocation parameters of the time-frequency resources reflect the sparsity of the time-frequency resources and the algorithm parameters of the estimation algorithm include the data estimation threshold reflecting the algorithm estimation capability, the ambiguity of the initial estimation parameter can be determined based on the resource allocation parameters of the time-frequency resources and / or the algorithm parameters of the estimation algorithm; the corresponding correction value is determined for the initial estimation parameter according to the ambiguity of the initial estimation parameter. For example, when the resource allocation parameters of the time-frequency resources and / or the algorithm parameters of the estimation algorithm reflect that the initial estimation parameter has data ambiguity and the degree of ambiguity is high, a larger correction value is determined for the initial estimation parameter; when the resource allocation parameters of the time-frequency resources and / or the algorithm parameters of the estimation algorithm reflect that the initial estimation parameter has data ambiguity and the degree of ambiguity is low, a smaller correction value is determined for the initial estimation parameter. Thereby, the rationality and accuracy of the correction value are improved, and the accuracy of correcting the initial estimation parameter is improved.

[0140] S703, correcting the initial estimated parameters using correction values ​​corresponding to the initial estimated parameters to obtain target estimated parameters of the target object within the perception period.

[0141] In this embodiment, the initial estimation parameters are corrected using correction values ​​corresponding to the initial estimation parameters, that is, the initial estimation parameters are adjusted according to the correction values ​​to obtain adjusted initial estimation parameters, which are the target estimation parameters of the target object within the perception period.

[0142] For example, corresponding correction values ​​may be subtracted or added to the initial estimated parameters, or other calculation methods may be used to finally obtain the target estimated parameters.

[0143] In the embodiment of the present disclosure, when the first perception signal is sent and the second perception signal is received using sparse time-frequency resources, the initial estimation parameters obtained by estimating the data of the target object according to the first perception signal, the second perception signal and the estimation algorithm may have data ambiguity due to the low sampling frequency; in order to solve the data ambiguity problem caused by sparse time-frequency resources, based on resource allocation parameters that can reflect the sparsity of time-frequency resources and / or algorithm parameters that can reflect the estimation ability of the algorithm, the correction value corresponding to the initial estimation parameter is determined, thereby improving the accuracy and rationality of the correction value; the initial estimation parameter is adjusted based on the correction value, thereby improving the accuracy of the estimation parameter, improving the accuracy of data measurement through perception signals, and solving the data ambiguity problem. The embodiments of the present disclosure can be used to correct the initial estimation parameters of the target object in one or more perception cycles.

[0144] In some embodiments, the initial estimation parameters of the target object may include an initial estimated distance and / or a first estimated speed (i.e., an initial estimated speed. In subsequent embodiments, in addition to the initial estimated speed and the target estimated speed, there may be other estimated speeds. For ease of distinction, the initial estimated speed will be referred to as the first estimated speed). The target estimation parameters may include a target estimated distance and / or a target estimated speed, thereby improving the accuracy of measuring the distance and / or speed of the target object.

[0145] In addition to the initial estimated distance and the first estimated speed, the initial estimated parameter may also be an initial estimated angular velocity, an initial estimated acceleration, etc., which are not described one by one here.

[0146] In this embodiment, the initial estimation parameters based on the target object include the initial estimated distance, the sparse time-frequency resources may include the distance sensing resources, the resource allocation parameters of the time-frequency resources may include the resource allocation parameters of the distance sensing resources, and the correction values ​​corresponding to the initial estimation parameters may include the distance correction values ​​corresponding to the initial estimated distance. The distance correction value corresponding to the initial estimated distance may be determined according to the resource allocation parameters of the distance sensing resources and / or the algorithm parameters of the estimation algorithm, and the initial estimated distance may be corrected using the distance correction value to obtain the target estimated distance of the target object within the sensing period, thereby improving the distance measurement accuracy.

[0147] In this embodiment, the initial estimation parameters based on the target object include a first estimated speed, the sparse time-frequency resources may include speed-aware resources, the resource allocation parameters of the time-frequency resources may include resource allocation parameters of the speed-aware resources, and the positive values ​​corresponding to the initial estimation parameters may include a speed correction value corresponding to the first estimated speed. The speed correction value corresponding to the first estimated speed may be determined according to the resource allocation parameters of the speed-aware resources and / or the algorithm parameters of the estimation algorithm, and the first estimated speed may be corrected using the speed correction value to obtain the target estimated speed of the target object within the perception period, thereby improving the speed measurement accuracy.

[0148] Optionally, after obtaining the target estimated distance of the target object within the sensing period, the speed correction value corresponding to the first estimated speed can be determined with the aid of the target estimated distance to further improve the accuracy of the speed correction value. In other words, the speed correction value corresponding to the first estimated speed can be determined in the same manner as the distance correction value corresponding to the initial estimated distance, or can be determined based on the target estimated distance.

[0149] Figure 8 Schematic diagram of the process of the perception data processing method provided in the embodiment of the present disclosure Figure 2 .like Figure 8 As shown, on the sensing end side, the sensing data processing method of this embodiment may include:

[0150] S801, obtaining initial estimation parameters of the target object within the perception period.

[0151] The initial estimated parameters of the target object include an initial estimated distance of the target object, and the initial estimated distance is obtained by performing data estimation based on the first perception signal, the second perception signal and an estimation algorithm.

[0152] Among them, the first perception signal and the second perception signal can refer to the description of the aforementioned embodiment, and the implementation principle and technical effects of S801 can refer to the aforementioned embodiment, which will not be repeated here.

[0153] S802: Obtain a data offset between the first perception signal and the second perception signal.

[0154] Among them, the data offset between the first perception signal and the second perception signal can reflect the degree of ambiguity of distance estimation based on the first perception signal and the second perception signal to a certain extent. The larger the data offset, the more likely distance ambiguity will occur and the greater the degree of distance ambiguity.

[0155] In this embodiment, the first perception signal and the second perception signal may be sampled, and then the data offset between the first perception signal and the second perception signal may be obtained based on the sampling value statistics.

[0156] In one possible implementation, Figure 8 As shown, S802 may include: S8021, determining the number of sampling points according to the resource allocation parameters of the distance perception resources and the algorithm parameters of the estimation algorithm; S8022, sampling the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; S8023, determining the data offset based on the sampling values.

[0157] In this implementation, since the resource allocation parameters of the distance sensing resources can reflect the sparsity of the distance sensing resources, and the algorithm parameters of the estimation algorithm include a data estimation threshold that reflects the estimation capability of the algorithm, the number of sampling points can be reasonably determined by combining the resource allocation parameters of the distance sensing resources and the algorithm parameters of the estimation algorithm. When the distance sensing resources are relatively sparse and the algorithm estimation capability is relatively weak, more sampling points can be determined, and the accuracy of the data offset can be improved by more sampling values. After determining the number of sampling points, the first perception signal and the second perception signal are sampled according to the number of sampling points to obtain the sampling values ​​corresponding to the number of sampling points, and the sampling values ​​corresponding to the number of sampling points are counted to obtain the data offset between the first perception signal and the second perception signal. It can be seen that in this implementation, the rationality of the number of sampling points is improved by combining the resource allocation parameters and the algorithm parameters, thereby improving the accuracy of sampling based on the sampling points and determining the data offset.

[0158] Optionally, the resource allocation parameters of the distance sensing resource may include a subcarrier spacing and a subcarrier sparse sorting interval number, wherein the subcarrier sparse sorting interval number reflects the sparseness of the subcarriers in the distance sensing resource. The larger the subcarrier sparse sorting interval number, the sparser the distance sensing resource. Figure 3 A subcarrier carrying a sensing signal symbol appears every 6 subcarriers. The estimation algorithm is a Fourier transform algorithm, such as a 2D-FFT periodogram method. In the algorithm parameters of the estimation algorithm, the data estimation threshold includes a distance estimation threshold, and the distance estimation threshold reflects the distance estimation capability of the estimation algorithm. The algorithm parameters of the estimation algorithm also include the number of FFT points and the number of IFFT points.

[0159] The distance estimation threshold can be the maximum unambiguous distance R max , the above content describes R max The calculation formula of is not repeated here.

[0160] Based on this optional solution, in a possible implementation, S8021 may include: determining the measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; determining the number of sampling points according to the distance estimation threshold, the measurement delay, the distance perception threshold of the distance perception resource, the subcarrier spacing and the number of FFT points. Thus, the accuracy and rationality of the number of sampling points are improved by combining detailed subcarrier resource parameters and similar algorithm parameters.

[0161] The distance sensing threshold under the distance sensing resource reflects the maximum sensing distance after the distance sensing resource is determined. The distance sensing threshold may come from the resource allocation parameter of the distance sensing resource, or the distance sensing threshold may be determined according to the subcarrier spacing and the number of subcarrier sparse ordering intervals.

[0162] In this embodiment, the measurement delay corresponding to the distance estimation threshold can be determined based on the inverse of the product of the subcarrier spacing and the subcarrier coefficient sorting interval number; the distance estimation threshold can be compared with the distance perception threshold to obtain a comparison result, and the number of sampling points can be determined based on the comparison result, the measurement delay, the subcarrier spacing, and the product of the FFT points. Thus, the delay situation, resource allocation situation, and algorithm capability are integrated to improve the accuracy and rationality of the sampling points. The corresponding calculation formula is provided below.

[0163] Optionally, the distance estimation threshold R max The corresponding calculation formula for the measurement delay can be expressed as:

[0164]

[0165] Among them, τ max Indicates the measurement delay, N comb represents the number of subcarrier sparse ordering intervals, Δf represents the subcarrier spacing, and a is a constant, for example, a is 2.

[0166] Optionally, the calculation formula for the number of sampling points can be expressed as:

[0167]

[0168] Among them, N corr Represents the number of sampling points, also known as the number of data points, N FFT Indicates the number of FFT points, R tar_max Represents the distance perception threshold, R max represents the distance estimation threshold, Indicates that the ratio of the distance perception threshold to the distance estimation threshold is rounded down.

[0169] In a possible implementation, S8022 may include: determining a received data sequence corresponding to the first perception signal, determining a transmitted data sequence corresponding to the second perception signal, and determining conjugate data corresponding to the transmitted data sequence; correlating the sampling values ​​corresponding to the transmitted data sequence with the sampling values ​​corresponding to the conjugate data according to the number of sampling points to obtain a correlation result; and S8023 may include: determining a data offset according to the correlation result. Since the first perception signal is a transmitted perception signal and the second perception signal is a received perception signal, the data sequence corresponding to the first perception signal may be referred to as a transmitted perception sequence, and the data sequence corresponding to the second perception signal may be referred to as a received data sequence.

[0170] In this implementation, since there are multiple sampling points, multiple correlation results can be obtained by correlating the sampling values ​​corresponding to the transmitted data sequence with the sampling values ​​corresponding to the conjugate data according to the sampling points, and one of the correlation results can be selected as the data offset. Thus, by correlating the conjugate of the transmitted data sequence and the received data sequence, the first perception signal and the second perception signal are compared, thereby improving the accuracy of the data offset.

[0171] Optionally, the calculation formula of the relevant results can be expressed as:

[0172]

[0173] Where R(·) represents the transmitted data sequence, T * (·) represents the conjugate of the received data sequence, and D(x) represents the correlation result. Using the above formula, 2N can be calculated. corr +1 related result.

[0174] Optionally, the data offset may be determined as a maximum value among the relevant results.

[0175] Assuming that the correlation result is the largest when x = τ, the calculation formula for the data offset can be expressed as:

[0176] D(τ)=max(D(x))

[0177] Wherein, D(τ) represents the data offset.

[0178] In a possible implementation, in S802, the data offset between the first perception signal and the second perception signal can be obtained from the communication algorithm module. That is, the processing flow of traditional communication can replace the above-mentioned data offset calculation step, and the embodiment of the present disclosure can reuse the data offset calculated by the communication algorithm module to reduce the amount of calculation in the perception process and improve the measurement efficiency. In particular, when the data processing flow of the perception service and the communication service is concurrent, the perception service can reuse the data offset calculated by the communication algorithm module to save computing resources.

[0179] Optionally, when the sensing end is an access network device (such as a base station), the data offset between the first sensing signal and the second sensing signal can be obtained from a physical random access channel (PRACH) algorithm module; when the sensing end is a terminal, the data offset between the first sensing signal and the second sensing signal can be obtained from a cell search algorithm module. Thus, resources are saved, the amount of calculation in the sensing process is reduced, and measurement efficiency is improved.

[0180] S803: Determine a threshold value according to resource allocation parameters and algorithm parameters of the distance-aware resource.

[0181] The threshold value is a threshold used to measure whether the initial estimated distance is blurred and the degree of blur of the initial estimated distance.

[0182] In this embodiment, since the resource allocation parameters of the distance sensing resources can reflect the coefficient degree of the distance estimation resources, the algorithm parameters of the estimation algorithm include a distance estimation threshold that reflects the distance estimation capability of the estimation algorithm. In combination with the resource allocation parameters and algorithm parameters of the distance sensing resources, a reasonable threshold value can be determined for the initial estimation threshold, thereby improving the accuracy of judging whether distance ambiguity occurs in the initial estimation distance and the degree of ambiguity of the initial estimation distance, thereby improving the accuracy of the correction value.

[0183] In a possible implementation, the resource allocation parameters of the distance perception threshold may include the subcarrier spacing and the number of subcarrier sparse sorting intervals, the estimation algorithm is a Fourier transform algorithm, and in addition to the distance estimation threshold, the algorithm parameters of the estimation algorithm also include the number of IFFT points. Based on this, S803 may include: determining the threshold value according to the measured delay, subcarrier spacing and IFFT points. Among them, the calculation process of the measured delay can refer to the above description and will not be repeated. Therefore, by fusing the measured delay, subcarrier spacing and IFFT points, the accuracy of the threshold value is improved, thereby improving the accuracy of judging whether the initial estimated distance is fuzzy and the degree of distance fuzziness.

[0184] Optionally, the threshold value calculation formula can be expressed as:

[0185] loc=N IFFT *Δf*τ max

[0186] Among them, loc represents the threshold value, N IFFT It can be seen that in S8022, the threshold value can be determined as the product of the measurement delay, the subcarrier spacing and the IFFT point number, so as to improve the fusion effect of the measurement delay, the subcarrier spacing and the IFFT point number by multiplication, and improve the accuracy of the threshold value.

[0187] S804, comparing the data offset and the threshold value to obtain a distance correction value.

[0188] The distance correction value reflects the difference between the data offset and the threshold value. The greater the difference between the data offset and the threshold value, the greater the distance correction value.

[0189] In this embodiment, the data offset and the threshold value are compared to obtain the difference between the data offset and the threshold value, and the distance correction value is determined based on the difference between the data offset and the threshold value.

[0190] In a possible implementation, the data offset and the threshold value may be divided or subtracted to implement a comparison between the data offset and the threshold value, and the distance correction value may be obtained after the comparison.

[0191] Based on the above content, Y r (p) and Y v From the calculation formula of (q), we can know that the time delay and Doppler frequency shift to be estimated can be expressed as single-frequency signals. The problem of determining the distance correction value can be further transformed into the problem of whether the error between the estimated result of the single-frequency signal estimated under the condition that the Fourier transform algorithm does not satisfy the sampling theorem and the actual frequency is an integer multiple of the sampling rate. Assume that the frequency to be estimated is F0 and the sampling rate is F s , does not satisfy the sampling theorem, that is, F s <2F0, since the frequency range that can be obtained using the Fourier transform algorithm is [-F s / 2,F s / 2], the above problem can be further transformed into the aliased spectrum signal falling within the above frequency range [-F s / 2,F s / 2] and the difference between the estimated value and the frequency F0 to be estimated is the sampling rate F s The integer multiple of can be concluded through the following process:

[0192] when When , we can get:

[0193] -F s / 2 <F0-(N+1)F s <F s / 2

[0194] The above formula can prove that for single-frequency signal estimation, when the sampling rate F s When the sampling theorem is not satisfied (i.e., F s <2F0), the frequency estimation result F′0 obtained is always different from the frequency to be estimated F0 by an integer multiple of the sampling frequency F s . Where F′0=F0-(N+1)F s .

[0195] Based on the fact that the frequency estimation result F′0 and the frequency to be estimated F0 are always an integer multiple of the sampling frequency F s This conclusion can determine integer correction values ​​for the initial estimation parameters, including determining an integer correction value for the initial estimation distance and / or determining an integer correction value for the first estimation speed, so as to improve the accuracy of correcting the initial estimation parameters by integers.

[0196] In a possible implementation, the ratio of the data offset between the first perception signal and the second perception signal to the threshold value is rounded to obtain a distance correction value. Thus, a distance correction value of an integer data type is obtained. The calculation formula of the distance correction value can be expressed as:

[0197]

[0198] Among them, N fix,τ It represents the distance correction value corresponding to the initial estimated distance of the target object within the perception period τ, and the distance correction value can also be called the period correction value corresponding to the initial estimated distance.

[0199] S805, using the distance correction value to correct the initial estimated distance to obtain the target estimated distance of the target object within the sensing period.

[0200] In this embodiment, the initial estimated distance is corrected using the distance correction value, that is, the initial estimated distance is adjusted according to the distance correction value to obtain an adjusted initial estimated distance, which is the target estimated distance of the target object within the sensing period.

[0201] S806, determining a second estimated speed according to the target estimated distance of the target object in the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle, wherein the initial estimated parameters of the target object in the perception cycle also include the first estimated speed.

[0202] Among them, S806 to S808 are optional steps, which provide a correction process for the first estimated speed. S806 to S808 can be performed when the initial estimated parameters of the target object in the perception period include the initial estimated distance and the first estimated speed. It should be noted that when the initial estimated parameters of the target object in the perception period include the initial estimated distance and the first estimated speed, the first estimated speed can be corrected in a manner similar to the initial estimated distance, or can be corrected in the manner of S806 to S808.

[0203] In the case where the first estimated speed is corrected in a manner similar to the initial estimated distance, the resource allocation parameters of the sparse time-frequency resources also include resource allocation parameters of the speed-aware resources, and the resource allocation parameters of the speed-aware resources may include an OFDM symbol interval and a number of OFDM symbol sparse sorting intervals. The data estimation threshold of the estimation algorithm may include a speed estimation threshold, and the speed estimation threshold is the maximum unambiguous speed v mentioned in the aforementioned content. max The process of correcting the first estimated speed in a manner similar to the initial estimated distance may refer to the correction process of the initial estimated distance, and will not be described in detail.

[0204] In this embodiment, the perception cycle is the pulse repetition cycle, the previous perception cycle is the previous pulse repetition cycle, the target estimated distance of the target object in the perception cycle can be obtained by repairing the initial estimated distance of the target object in the perception cycle, and the target estimated distance of the target object in the previous perception cycle can be obtained by repairing the initial estimated distance of the target object in the previous perception cycle. The repair process refers to the above content and will not be repeated. The target estimated distance of the target object in the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle are obtained, and the speed is roughly estimated according to the target estimated distance of the target object in the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle to obtain a second estimated speed.

[0205] Optionally, the distance difference between the target estimated distance of the target object in the sensing cycle and the target estimated distance of the target object in the previous cycle is calculated, and the second estimated speed is calculated according to the distance difference and the duration of the sensing cycle. Specifically, the calculation formula of the second estimated speed can be expressed as:

[0206] v est =Δd / Δt

[0207] Among them, v est represents the second estimated speed, Δd represents the distance difference between the target estimated distance of the target object in the perception cycle and the target estimated distance of the target object in the previous cycle, and Δt is the duration of the perception cycle.

[0208] S807: Compare the second estimated speed with the speed estimation threshold to obtain a speed correction value.

[0209] The speed correction value reflects the difference between the second estimated speed and the speed estimation threshold. The greater the difference between the second estimated speed and the speed estimation threshold, the greater the speed correction value.

[0210] In this embodiment, the second estimated speed is compared with the speed estimation threshold to obtain a difference between the second estimated speed and the speed estimation threshold, and the speed correction value is determined based on the difference between the second estimated speed and the speed estimation threshold.

[0211] In a possible implementation, the second estimated speed and the speed estimation threshold may be divided or subtracted to compare the second estimated speed and the speed estimation threshold to obtain a distance correction value.

[0212] Based on the fact that the frequency estimation result F′0 and the frequency to be estimated F0 are always an integer multiple of the sampling frequency F s This conclusion can be used to determine an integer correction value for the initial estimation of the first estimated speed, so as to improve the accuracy of correcting the first estimated speed through the integer.

[0213] In a possible implementation, the ratio of the second estimated speed to the speed estimation threshold value may be rounded to obtain a speed correction value. Thus, a speed correction value of an integer data type is obtained. The calculation formula of the speed correction value may be expressed as:

[0214]

[0215] Among them, N fix,v Indicates the speed correction value.

[0216] S808: Use the speed correction value to correct the first estimated speed to obtain a target estimated speed of the target object within the perception period.

[0217] In this embodiment, the first estimated speed is corrected using the speed correction value, that is, the first estimated speed is adjusted according to the speed correction value to obtain an adjusted first estimated speed, and the adjusted first estimated speed is the target estimated distance of the target object within the sensing period.

[0218] In the disclosed embodiment, when performing distance correction, the resource allocation parameters of the time-frequency resources and the algorithm parameters of the estimation algorithm are used to improve the accuracy of the data offset and the threshold value, and the accuracy of the distance correction value is improved by comparing the data offset and the threshold value of the first perception signal with the second perception signal, thereby improving the accuracy of the correction of the initial estimated distance based on the distance correction value, and improving the accuracy of the target estimated distance; when performing speed correction, the corrected target estimated distance can be used to improve the accuracy of the speed correction value, thereby improving the accuracy of the correction of the initial estimated speed based on the speed correction value. In this way, the measurement ambiguity problem caused by sparse resources is solved, and the measurement accuracy is improved.

[0219] Based on the fact that the frequency estimation result F′0 and the frequency to be estimated F0 are always an integer multiple of the sampling frequency F s "This conclusion, the initial estimated parameters can be equivalent to the frequency estimation result F'0, the real parameters corresponding to the initial estimated parameters can be equivalent to the frequency to be estimated F0, the data estimation threshold reflects the algorithm estimation ability, and then reflects the algorithm sampling ability, the data estimation threshold can be equivalent to the sampling frequency F s . Therefore, optionally, the difference between the initial estimated parameters and the true parameters may be a correction value data estimation threshold, where the correction value is an integer. Based on this optional scheme, in a possible implementation method, the initial estimated parameters of the target object within the perception period are corrected by the correction value to obtain the target estimated parameters of the target object within the perception period, which may include: multiplying the correction value by the data estimation threshold to obtain the product; determining the target estimated parameter as the sum of the product and the initial estimated parameter. In this way, by using "the frequency estimation result F′0 and the frequency to be estimated F0 always differ by an integer multiple of the sampling frequency F sThis conclusion improves the accuracy of correcting the estimated parameters. The calculation of the correction value can refer to the above embodiment and will not be repeated here.

[0220] Further, based on the data estimation threshold including the distance estimation threshold and / or the speed estimation threshold, the initial estimation parameter including the initial estimation distance and / or the first estimation speed, the target estimation parameter including the target estimation distance and / or the target estimation speed, and the correction value including the distance correction value and / or the speed correction value, the correction of the initial estimation parameter may include the following implementation:

[0221] In a possible implementation, correcting the initial estimated distance may include: multiplying the distance correction value by the distance estimation threshold to obtain a first product; and determining the target estimated distance as the sum of the first product and the initial estimated distance. Thus, based on the difference between the initial estimated parameter and the actual parameter by the correction value data estimation threshold, the target estimated distance is obtained by calculating the product of the correction value and the data estimation threshold, and adding the product to the initial estimated parameter, thereby improving the accuracy of the target estimated distance.

[0222] Among them, the calculation formula of the target estimated distance can be expressed as:

[0223] R true =R 2DFFT +R max *N fix,τ

[0224] Among them, R true Represents the estimated target distance, R 2DFFT Represents the initial estimated distance.

[0225] In another possible implementation, correcting the first estimated speed may include: multiplying the speed correction value by the speed estimation threshold to obtain a second product, and determining the target estimated speed as the sum of the second product and the first estimated speed. Thus, based on the difference between the initial estimated parameter and the actual parameter by the correction value data estimation threshold, the product of the correction value and the speed estimation threshold is calculated, and the product is added to the first estimated speed to obtain the target estimated speed, thereby improving the accuracy of the target estimated speed.

[0226] Among them, the calculation formula of the target estimated speed can be expressed as:

[0227] v true =v 2DFFT +v max *N fix,v

[0228] Among them, v true represents the estimated target speed, v 2DFFT Represents the initial estimated velocity.

[0229] In some embodiments, before the correction value is used to correct the initial estimated parameter to obtain the target estimated parameter of the target object within the perception period, it can be determined based on the correction value and the configured threshold value whether the initial estimated parameter belongs to fuzzy data. That is, when it is determined that the initial estimated parameter belongs to modulus data, the correction value is used to correct the initial estimated parameter. If the initial estimated parameter does not belong to modulus data, the initial estimated parameter can be corrected. Thus, by judging whether the initial estimated parameter belongs to modulus data, different operations are adopted for different situations to ensure data measurement accuracy while saving resources.

[0230] If the initial estimated parameter is fuzzy data, it means that the initial estimated parameter has data fuzziness, including distance fuzziness in the initial estimated distance and / or speed fuzziness in the first estimated speed. If the initial estimated parameter is not fuzzy data, it means that the initial estimated parameter has no data fuzziness.

[0231] In this embodiment, the correction value can be compared with the configured threshold value, and whether the initial estimated parameter belongs to fuzzy data can be determined according to the comparison result. If the correction value is greater than the configured threshold value, it can be determined that the initial estimated parameter belongs to fuzzy data, otherwise it can be determined that the initial estimated parameter does not belong to fuzzy data.

[0232] In a possible implementation, it is determined whether the distance correction value is greater than 0. If the distance correction value is greater than 0, it can be determined that the initial estimated distance belongs to fuzzy data, otherwise it is determined that the initial estimated distance does not belong to fuzzy data. The calculation process of the distance correction value can refer to the above embodiment and will not be repeated.

[0233] In a possible implementation, it is determined whether the speed correction value is greater than 0. If the speed correction value is greater than 0, it can be determined that the first estimated speed belongs to fuzzy data, otherwise it is determined that the first estimated speed does not belong to fuzzy data. The calculation process of the speed correction value can refer to the above embodiment and will not be repeated.

[0234] As an example, when the distance correction value is the ratio of the data offset to the threshold value, taking the parameters in Table 1 as an example, if the time-frequency resources used for the perception signal transmission do not use comb sorting, and all 200 subcarriers are used for perception, the maximum unambiguous distance is 1250m. If the time-frequency resources used for the perception signal transmission use comb sorting, the maximum unambiguous distance is reduced to 78.125m. According to the above calculation formula, it can be calculated that 96 sampling points, that is, the received data (time domain data after removing cp) with a time length of about 0.266 microseconds, need to be correlated and processed, and the data offset is obtained by obtaining the maximum correlation data. Compare the data offset with the threshold value of 32. If the data offset is less than 32, no distance ambiguity is generated, and the output distance correction value is 0; if the data offset is greater than 32 and less than 64, a distance ambiguity is generated, and the distance correction value output is 1; if the data offset is greater than 64, it has exceeded the maximum ranging range of 150m, and no correction or measurement is required. Therefore, whether the initial estimated distance produces distance ambiguity can be determined based on whether the distance correction value is 0.

[0235] Table 1

[0236]

[0237]

[0238] In some embodiments, the sensing end may receive first information from a network device, the first information including resource allocation parameters of time-frequency resources, and the time-frequency resources including sparse time-frequency resources for sending the first perception signal and receiving the second perception signal. Thus, the sensing end is instructed to call the time-frequency resources through the first information, thereby improving the accuracy and rationality of the time-frequency resource call.

[0239] Optionally, the network device may allocate time-frequency resources for the transmission of the perception signal according to one or more information of the perception performance information, the communication performance information, the perception demand, and the communication demand, and obtain the resource allocation parameters of the time-frequency resources; and generate the first information according to the resource allocation parameters of the time-frequency resources. Thus, by referring to one or more information, the rationality of resource allocation is improved. Among them, the perception performance information reflects the performance of the perception measurement performed by the perception end, such as measurement accuracy, efficiency, etc.; the communication performance information reflects the communication performance of the perception end, such as communication quality, communication stability, etc. The perception demand may be one or more requirements of the perception range, perception accuracy, perception efficiency, etc., and the communication demand may be one or more requirements of the communication range, communication quality, communication efficiency, etc. The perception performance information and the communication performance information can be obtained by performing signal evaluation and measurement, and are not specifically limited.

[0240] Optionally, the network device can allocate time-frequency resources according to the configured resource allocation mode. The resource allocation mode refers to the resource ratio between the resources used by the perception signal and the resources used by the communication signal. In the sparsely structured time-frequency resources, the resources used by the perception signal are sparsely sorted in the overall time-frequency resources. Multiple resource allocation modes can be pre-configured, and the network device can select one from multiple resource allocation modes to allocate time-frequency resources based on one or more of the perception performance information, communication performance information, perception requirements, and communication requirements. Therefore, by pre-configuring the resource allocation mode, the rationality of resource allocation is improved.

[0241] Optionally, when the sensing end is a terminal, the resource allocation parameter of the time-frequency resource in the first information can be used to indicate the resource allocation mode, and the terminal can obtain multiple parameter information under the resource allocation mode according to the resource allocation mode, so as to reduce the amount of data transmitted between the network device and the terminal, improve the communication efficiency between the network device and the terminal, and save resources.

[0242] Optionally, when the perception end is an access network device, the resource allocation parameters of the time-frequency resources in the first information may include multiple parameter information under the resource allocation mode. Therefore, considering the strong data transmission capacity between the access network device and the network device, the specific parameters are directly transmitted to the access network device to improve the accuracy and precision of data transmission.

[0243] In some embodiments, after the initial estimated parameters are corrected using the correction values ​​to obtain the target estimated parameters of the target object within the sensing period, the sensing end may send second information to the network device, the second information including the target estimated parameters and / or the correction values. Thus, the network device may obtain the target estimated parameters and / or the correction values ​​and obtain accurate sensing measurement results.

[0244] Optionally, after obtaining the correction value, the network device may allocate time-frequency resources for the transmission of the perception signal according to the correction value, thereby improving the rationality of the time-frequency resource allocation.

[0245] In this optional method, the correction value can reflect the degree of error in the perception end data estimation. The network device can reduce the sparsity of time-frequency resources used for perception signal transmission when the correction value is large, and can maintain or increase the sparsity of time-frequency resources for perception signal transmission when the correction value is small, thereby ensuring the rationality of time-frequency resource allocation.

[0246] The present disclosure provides a perception data processing device. Fig. 9 As shown, on the perception end side, the perception data processing device may include a transceiver 901, a processor 902 and a memory 903.

[0247] The transceiver 901 is used to receive and send data under the control of the processor 902 .

[0248] Among them, Fig. 9 In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 702 and memory represented by memory 903. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface. The transceiver 901 may be a plurality of components, namely, a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, which transmission medium may include a wireless channel, a wired channel, an optical cable, and the like. The processor 902 is responsible for managing the bus architecture and general processing, and the memory 903 may store data used by the processor 902 when performing operations.

[0249] The processor 902 may be a CPU, an ASIC, an FPGA or a CPLD, and the processor may also adopt a multi-core architecture.

[0250] The processor 902 is used to execute the perception data processing method provided by the embodiment of the present disclosure according to the obtained executable instructions by calling the computer program stored in the memory 903. The processor and the memory can also be arranged physically separately.

[0251] Specifically, the processor 902 is used to perform the following operations: obtain initial estimation parameters of the target object within the perception period, the initial estimation parameters are obtained by performing data estimation based on the first perception signal, the second perception signal and the estimation algorithm, the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the sending of the first perception signal and the receiving of the second perception signal use sparse time-frequency resources; determine a correction value corresponding to the initial estimation parameter according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold that reflects the estimation capability of the algorithm; and use the correction value to correct the initial estimation parameter to obtain the target estimation parameter of the target object within the perception period.

[0252] In a possible implementation, the initial estimation parameters include an initial estimated distance, the time-frequency resources include distance sensing resources, the resource allocation parameters of the time-frequency resources include resource allocation parameters of the distance sensing resources, and the correction value corresponding to the initial estimation parameters includes a distance correction value corresponding to the initial estimated distance; the processor 902 is specifically used to: obtain a data offset between the first perception signal and the second perception signal; determine a threshold value according to the resource allocation parameters and algorithm parameters of the distance sensing resources; and compare the data offset and the threshold value to obtain a distance correction value.

[0253] In one possible implementation, the processor 902 is specifically used to: determine the number of sampling points based on the resource allocation parameters and algorithm parameters of the distance perception resource; sample the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; and determine the data offset based on the sampling values.

[0254] In a possible implementation, resource allocation parameters of distance-aware resources include subcarrier spacing and subcarrier sparse sorting interval number, the estimation algorithm is an FFT algorithm, the data estimation threshold includes a distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm, and the algorithm parameters also include the number of FFT points and the number of IFFT points; the processor 902 is specifically used to: determine the measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; determine the number of sampling points according to the distance estimation threshold, the measurement delay, the distance perception threshold of the distance perception resource, the subcarrier spacing and the number of FFT points; wherein the distance perception threshold comes from the resource allocation parameters, or the distance perception threshold is determined according to the subcarrier spacing and the number of subcarrier sparse sorting intervals.

[0255] In a possible implementation manner, the processor 902 is specifically configured to determine a threshold value according to a measured delay, a subcarrier spacing, and an IFFT point number.

[0256] In one possible implementation, the initial estimation parameters also include a first estimated speed, the correction value corresponding to the initial estimation parameters also includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; the processor 902 is also used to: determine the second estimated speed based on the target estimated distance of the target object within the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle; compare the second estimated speed with the speed estimation threshold to obtain the speed correction value.

[0257] In a possible implementation manner, the processor 902 is specifically configured to: round the ratio of the second estimated speed to the speed estimation threshold to obtain a speed correction value.

[0258] In one possible implementation, the difference between the initial estimated parameter and the actual parameter is a correction value data estimation threshold, where the correction value is an integer; the processor 902 is specifically used to: multiply the correction value by the data estimation threshold to obtain a product; and determine the target estimated parameter as the sum of the product and the initial estimated parameter.

[0259] In one possible implementation, the data estimation threshold includes a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter includes an initial estimated distance and / or a first estimated speed, the target estimation parameter includes a target estimated distance and / or a target estimated speed, and the correction value includes a distance correction value and / or a speed correction value; the processor 902 is specifically used to: multiply the distance correction value by the distance estimation threshold to obtain a first product, and / or, multiply the speed correction value by the speed estimation threshold to obtain a second product; determine the target estimated distance as the sum of the first product and the initial estimated distance, and / or, determine the target estimated speed as the sum of the second product and the first estimated speed.

[0260] In a possible implementation, the processor 902 is further configured to: determine, based on the correction value and a configured threshold, whether the initial estimation parameter belongs to fuzzy data.

[0261] In a possible implementation manner, the processor 902 is further configured to: receive first information from a network device, where the first information includes a resource allocation parameter.

[0262] In a possible implementation manner, the processor 902 is further configured to: send second information to the network device, where the second information includes the target estimation parameter and / or the correction value.

[0263] It should be noted here that the above-mentioned device provided by the present disclosure can implement all the method steps of the perception end in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0264] The present disclosure provides a perception data processing device. Fig.10 As shown, on the network device side, the perception data processing device may include a transceiver 1001, a processor 1002 and a memory 1003.

[0265] The transceiver 1001 is used to receive and send data under the control of the processor 1002 .

[0266] Among them, Fig.10In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 1002 and memory represented by memory 1003. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface. The transceiver 1001 may be a plurality of components, namely, a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, which transmission medium may include a wireless channel, a wired channel, an optical cable, and the like. The processor 1002 is responsible for managing the bus architecture and general processing, and the memory 1003 may store data used by the processor 1002 when performing operations.

[0267] The processor 1002 may be a CPU, an ASIC, an FPGA or a CPLD, and the processor may also adopt a multi-core architecture.

[0268] The processor 1002 is used to execute the sensing data processing method provided by the embodiment of the present disclosure according to the obtained executable instructions by calling the computer program stored in the memory 1003. The processor and the memory can also be arranged physically separately.

[0269] Specifically, processor 1002 is used to perform the following operations: receiving second information from the perception end; wherein the second information includes target estimation parameters of the target object within the perception period and / or correction values ​​corresponding to initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

[0270] In a possible implementation, the processor 1002 is further used to perform the following operation: sending first information to the perception end, wherein the first information includes resource allocation parameters of sparse time-frequency resources, and the sparse time-frequency resources are used for sending a first perception signal and receiving a second perception signal.

[0271] It should be noted here that the above-mentioned device provided by the present disclosure can implement all the method steps of the network device in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0272] The present disclosure also provides a perception data processing device. Fig.11 As shown, the perception data processing device includes: an acquisition unit 1101, a correction value determination unit 1102 and a correction unit 1103.

[0273] An acquiring unit 1101 is configured to acquire initial estimation parameters of a target object within a sensing period, where the initial estimation parameters are obtained by performing data estimation according to a first perception signal, a second perception signal, and an estimation algorithm, where the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources;

[0274] A correction value determining unit 1102 is used to determine a correction value corresponding to the initial estimation parameter according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, wherein the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold reflecting the estimation capability of the algorithm;

[0275] The correction unit 1103 is used to correct the initial estimation parameters using the correction values ​​to obtain the target estimation parameters of the target object within the perception period.

[0276] In a possible implementation, the initial estimation parameters include an initial estimation distance, the time-frequency resources include distance sensing resources, the resource allocation parameters of the time-frequency resources include resource allocation parameters of the distance sensing resources, and the correction value corresponding to the initial estimation parameters includes a distance correction value corresponding to the initial estimation distance; the correction value determination unit 1102 is specifically used to: obtain a data offset between the first perception signal and the second perception signal; determine a threshold value according to the resource allocation parameters and algorithm parameters of the distance sensing resources; and compare the data offset and the threshold value to obtain a distance correction value.

[0277] In a possible implementation, the correction value determination unit 1102 is specifically used to: determine the number of sampling points according to the resource allocation parameters and algorithm parameters of the distance perception resource; sample the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; and determine the data offset based on the sampling values.

[0278] In a possible implementation, the resource allocation parameters of the distance sensing resource include the subcarrier spacing and the number of subcarrier sparse sorting intervals, the estimation algorithm is the FFT algorithm, the data estimation threshold includes the distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm, and the algorithm parameters also include the number of FFT points and the number of IFFT points; the correction value determination unit 1102 is specifically used to: determine the measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; determine the number of sampling points according to the distance estimation threshold, the measurement delay, the distance sensing threshold of the distance sensing resource, the subcarrier spacing and the number of FFT points; wherein the distance sensing threshold comes from the resource allocation parameter, or the distance sensing threshold is determined according to the subcarrier spacing and the number of subcarrier sparse sorting intervals.

[0279] In a possible implementation, the correction value determining unit 1102 is specifically configured to determine a threshold value according to a measured delay, a subcarrier spacing, and an IFFT point number.

[0280] In a possible implementation, the correction value determining unit 1102 is specifically configured to: round the ratio of the data offset to the threshold value to obtain a distance correction value.

[0281] In a possible implementation, the initial estimation parameters also include a first estimated speed, the correction value corresponding to the initial estimation parameters also includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; the correction value determination unit 1102 is specifically used to: determine the second estimated speed based on the target estimated distance of the target object within the perception cycle, the target estimated distance of the target object in the previous cycle, and the duration of the perception cycle; compare the second estimated speed with the speed estimation threshold to obtain the speed correction value.

[0282] In a possible implementation, the correction value determining unit 1102 is specifically configured to: round the ratio of the second estimated speed to the speed estimation threshold to obtain the speed correction value.

[0283] In one possible implementation, the difference between the initial estimated parameter and the true parameter is a correction value data estimation threshold, where the correction value is an integer; the correction unit 1103 is specifically used to: multiply the correction value by the data estimation threshold to obtain a product; and determine the target estimated parameter as the sum of the product and the initial estimated parameter.

[0284] In one possible implementation, the data estimation threshold includes a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter includes an initial estimated distance and / or a first estimated speed, the target estimation parameter includes a target estimated distance and / or a target estimated speed, and the correction value includes a distance correction value and / or a speed correction value; the correction unit 1103 is specifically used to: multiply the distance correction value by the distance estimation threshold to obtain a first product, and / or, multiply the speed correction value by the speed estimation threshold to obtain a second product; determine the target estimated distance as the sum of the first product and the initial estimated distance, and / or, determine the target estimated speed as the sum of the second product and the first estimated speed.

[0285] In a possible implementation, the perception data processing device further includes: a fuzzy judgment unit 1104, configured to determine whether the initial estimation parameter belongs to fuzzy data based on the correction value and the configured threshold.

[0286] In a possible implementation, the perception data processing apparatus further includes: a receiving unit 1105, configured to receive first information from a network device, where the first information includes a resource allocation parameter.

[0287] In a possible implementation, the perception data processing apparatus further includes: a sending unit 1106, configured to send second information to the network device, where the second information includes target estimation parameters and / or correction values.

[0288] It should be noted here that the above-mentioned device provided by the present disclosure can implement all the method steps of the perception end in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0289] The embodiment of the present disclosure also provides a perception data processing device. Fig.12 As shown, the perception data processing device includes: a receiving unit 1201.

[0290] The receiving unit 1201 is used to receive the second information from the perception end; wherein the second information includes the target estimation parameters of the target object within the perception period and / or the correction values ​​corresponding to the initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

[0291] In a possible implementation, the perception data processing device also includes: a sending unit 1202, used to send first information to the perception end, wherein the first information includes resource allocation parameters of sparse time-frequency resources, and the sparse time-frequency resources are used for sending the first perception signal and receiving the second perception signal.

[0292] It should be noted that the division of units in the embodiments of the present disclosure is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0293] 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 processor-readable storage medium. Based on this understanding, the technical solution of the present disclosure is essentially 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, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0294] The embodiment of the present disclosure provides a processor-readable storage medium, which stores a computer program, and the computer program is used to enable the processor to execute any of the methods for processing sensory data provided in the embodiment of the present disclosure. The processor is enabled to implement the method steps of the sensory data processing method in the above method embodiment, and the same technical effect can be achieved. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0295] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.

[0296] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0297] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, apparatuses, and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer executable instructions. These computer executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0298] These processor executable instructions may also be stored in a processor readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0299] These processor-executable instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0300] Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A method for processing perception data, characterized in that: Applied to the perception end, including: acquiring initial estimation parameters of a target object within a sensing period, where the initial estimation parameters are obtained by performing data estimation according to a first perception signal, a second perception signal, and an estimation algorithm, where the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources; Determining a correction value corresponding to the initial estimation parameter according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, wherein the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold reflecting the estimation capability of the algorithm; The initial estimation parameters are corrected using the correction values ​​to obtain target estimation parameters of the target object within the sensing period.

2. The method for processing perception data according to claim 1, characterized in that: The initial estimation parameter includes an initial estimation distance, the time-frequency resource includes a distance-aware resource, the resource allocation parameter of the time-frequency resource includes a resource allocation parameter of the distance-aware resource, and the correction value corresponding to the initial estimation parameter includes a distance correction value corresponding to the initial estimation distance; The determining, according to the resource allocation parameter of the time-frequency resource and / or the algorithm parameter of the estimation algorithm, the correction value corresponding to the initial estimation parameter comprises: Acquire a data offset between the first perception signal and the second perception signal; Determining a threshold value according to a resource allocation parameter of the distance sensing resource and the algorithm parameter; The data offset is compared with the threshold value to obtain the distance correction value.

3. The method for processing perception data according to claim 2, characterized in that: The acquiring a data offset between the first perception signal and the second perception signal includes: Determining the number of sampling points according to the resource allocation parameters of the distance sensing resource and the algorithm parameters; Sampling the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; Based on the sampled value, the data offset is determined.

4. The method for processing perception data according to claim 3, characterized in that: The resource allocation parameters of the distance sensing resource include a subcarrier spacing and a number of subcarrier sparse sorting intervals, the estimation algorithm is a Fourier transform algorithm, the data estimation threshold includes a distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm, and the algorithm parameters also include a fast Fourier transform FFT point number and an inverse fast Fourier transform IFFT point number; The determining the number of sampling points according to the resource allocation parameter of the distance sensing resource and the algorithm parameter comprises: Determining a measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; Determining the number of sampling points according to the distance estimation threshold, the measurement delay, the distance sensing threshold of the distance sensing resource, the subcarrier spacing and the number of FFT points; The distance perception threshold is derived from the resource allocation parameter, or the distance perception threshold is determined according to the subcarrier spacing and the number of subcarrier sparse ordering intervals.

5. The method for processing perception data according to claim 4, characterized in that: The determining of the threshold value according to the resource allocation parameter of the distance sensing resource and the algorithm parameter includes: The threshold value is determined according to the measurement delay, the subcarrier spacing and the number of IFFT points.

6. The method for processing perception data according to claim 2, characterized in that: The comparing the data offset and the threshold value to obtain the distance correction value includes: The ratio of the data offset to the threshold value is rounded to obtain the distance correction value.

7. The method for processing perception data according to any one of claims 2 to 6, characterized in that: The initial estimation parameter further includes a first estimated speed, the correction value corresponding to the initial estimation parameter further includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; After the initial estimated distance is corrected to obtain the target estimated distance of the target object within the sensing period, the method further includes: Determining a second estimated speed according to the target estimated distance of the target object in the sensing cycle, the target estimated distance of the target object in the previous cycle, and the duration of the sensing cycle; The second estimated speed is compared with the speed estimation threshold to obtain the speed correction value.

8. The method for processing perception data according to claim 7, characterized in that: The comparing the second estimated speed with the speed estimation threshold to obtain the speed correction value includes: The ratio of the second estimated speed to the speed estimation threshold is rounded to obtain the speed correction value.

9. The method for processing perception data according to any one of claims 2 to 6, characterized in that: The difference between the initial estimated parameter and the true parameter is the correction value times the data estimation threshold, and the correction value is an integer; The using the correction value to correct the initial estimation parameter to obtain the target estimation parameter of the target object within the sensing period includes: multiplying the correction value by the data estimation threshold to obtain a product; The target estimated parameter is determined as the sum of the product and the initial estimated parameter.

10. The method for processing perception data according to claim 9, characterized in that: The data estimation threshold comprises a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter comprises an initial estimated distance and / or a first estimated speed, the target estimation parameter comprises a target estimated distance and / or a target estimated speed, and the correction value comprises a distance correction value and / or a speed correction value; The step of multiplying the correction value by the data estimation threshold to obtain a product includes: multiplying the distance correction value by the distance estimation threshold to obtain a first product, and / or multiplying the speed correction value by the speed estimation threshold to obtain a second product; The determining the target estimated parameter as the sum of the product and the initial estimated parameter comprises: The target estimated distance is determined as the sum of the first product and the initial estimated distance, and / or the target estimated speed is determined as the sum of the second product and the first estimated speed.

11. The method for processing perception data according to any one of claims 1 to 6, characterized in that: Before the initial estimation parameters are corrected by using the correction value to obtain the target estimation parameters of the target object within the sensing period, the method further includes: Based on the correction value and the configured threshold, it is determined that the initial estimation parameter belongs to fuzzy data.

12. The method for processing perception data according to any one of claims 1 to 6, characterized in that: Also includes: First information is received from a network device, where the first information includes the resource allocation parameter.

13. The method for processing perception data according to any one of claims 1 to 6, characterized in that: After the initial estimation parameters are corrected by using the correction value to obtain the target estimation parameters of the target object within the sensing period, the method further includes: Sending second information to the network device, wherein the second information includes the target estimation parameter and / or the correction value.

14. A method for processing perception data, characterized in that: Applied to network equipment, including: receiving second information from the sensing end; The second information includes target estimation parameters of the target object within the perception period and / or correction values ​​corresponding to initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

15. A perception data processing device, characterized in that: Applied to the sensing end, the sensing data processing device includes a memory, a transceiver and a processor; The memory is used to store computer programs; The transceiver is used to send and receive data under the control of the processor; The processor is configured to read the computer program in the memory and perform the following operations: acquiring initial estimation parameters of a target object within a sensing period, where the initial estimation parameters are obtained by performing data estimation according to a first perception signal, a second perception signal, and an estimation algorithm, where the first perception signal is used to perceive the target object, the second perception signal is an echo corresponding to the first perception signal, and the first perception signal is sent and the second perception signal is received using sparse time-frequency resources; Determining a correction value corresponding to the initial estimation parameter according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, wherein the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold reflecting the estimation capability of the algorithm; The initial estimation parameters are corrected using the correction values ​​to obtain target estimation parameters of the target object within the sensing period.

16. The sensing data processing device according to claim 15, characterized in that: The initial estimation parameter includes an initial estimation distance, the time-frequency resource includes a distance-aware resource, the resource allocation parameter of the time-frequency resource includes a resource allocation parameter of the distance-aware resource, and the correction value corresponding to the initial estimation parameter includes a distance correction value corresponding to the initial estimation distance; The processor is specifically used for: Acquire a data offset between the first perception signal and the second perception signal; Determining a threshold value according to a resource allocation parameter of the distance sensing resource and the algorithm parameter; The data offset is compared with the threshold value to obtain the distance correction value.

17. The sensing data processing device according to claim 16, characterized in that: The processor is specifically used for: Determining the number of sampling points according to the resource allocation parameters of the distance sensing resource and the algorithm parameters; Sampling the first perception signal and the second perception signal according to the number of sampling points to obtain sampling values ​​corresponding to the number of sampling points; Based on the sampled value, the data offset is determined.

18. The sensing data processing device according to claim 17, characterized in that: The resource allocation parameters of the distance-aware resource include a subcarrier spacing and a number of subcarrier sparse ordering intervals; the estimation algorithm is an FFT algorithm; the data estimation threshold includes a distance estimation threshold, the distance estimation threshold reflects the distance estimation capability of the estimation algorithm; and the algorithm parameters also include a number of FFT points and a number of IFFT points; The processor is specifically used for: Determining a measurement delay corresponding to the distance estimation threshold according to the subcarrier spacing and the number of subcarrier sparse sorting intervals; Determining the number of sampling points according to the distance estimation threshold, the measurement delay, the distance sensing threshold of the distance sensing resource, the subcarrier spacing and the number of FFT points; The distance perception threshold is derived from the resource allocation parameter, or the distance perception threshold is determined according to the subcarrier spacing and the number of subcarrier sparse ordering intervals.

19. The sensing data processing device according to claim 18, characterized in that: The processor is specifically used for: The threshold value is determined according to the measurement delay, the subcarrier spacing and the number of IFFT points.

20. The sensing data processing device according to any one of claims 16 to 19, characterized in that: The initial estimation parameter further includes a first estimated speed, the correction value corresponding to the initial estimation parameter further includes a speed correction value corresponding to the first estimated speed, the data estimation threshold includes a speed estimation threshold, and the speed estimation threshold reflects the speed estimation capability of the estimation algorithm; The processor is further configured to: Determining a second estimated speed according to the target estimated distance of the target object in the sensing cycle, the target estimated distance of the target object in the previous cycle, and the duration of the sensing cycle; The second estimated speed is compared with the speed estimation threshold to obtain the speed correction value.

21. The sensing data processing device according to claim 20, characterized in that: The processor is specifically used for: The ratio of the second estimated speed to the speed estimation threshold is rounded to obtain the speed correction value.

22. The sensing data processing device according to any one of claims 16 to 19, characterized in that: The difference between the initial estimated parameter and the true parameter is the correction value times the data estimation threshold, and the correction value is an integer; The processor is specifically used for: multiplying the correction value by the data estimation threshold to obtain a product; The target estimated parameter is determined as the sum of the product and the initial estimated parameter.

23. The sensing data processing device according to claim 22, characterized in that: The data estimation threshold comprises a distance estimation threshold and / or a speed estimation threshold, the initial estimation parameter comprises an initial estimated distance and / or a first estimated speed, the target estimation parameter comprises a target estimated distance and / or a target estimated speed, and the correction value comprises a distance correction value and / or a speed correction value; The processor is specifically used for: multiplying the distance correction value by the distance estimation threshold to obtain a first product, and / or multiplying the speed correction value by the speed estimation threshold to obtain a second product; The determining the target estimated parameter as the sum of the product and the initial estimated parameter comprises: The target estimated distance is determined as the sum of the first product and the initial estimated distance, and / or the target estimated speed is determined as the sum of the second product and the first estimated speed.

24. The sensing data processing device according to any one of claims 16 to 19, characterized in that: The processor is further configured to: Based on the correction value and the configured threshold, it is determined that the initial estimation parameter belongs to fuzzy data.

25. The sensing data processing device according to any one of claims 15 to 19, characterized in that: The processor is further configured to: First information is received from a network device, where the first information includes the resource allocation parameter.

26. The sensing data processing device according to any one of claims 15 to 19, characterized in that: The processor is further configured to: Sending second information to the network device, wherein the second information includes the target estimation parameter and / or the correction value.

27. A perception data processing device, characterized in that: Applied to network equipment, the sensing data processing device includes a memory, a transceiver and a processor; The memory is used to store computer programs; The transceiver is used to send and receive data under the control of the processor; The processor is configured to read the computer program in the memory and perform the following operations: receiving second information from the sensing end; The second information includes target estimation parameters of the target object within the perception period and / or correction values ​​corresponding to initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

28. A perception data processing device, characterized in that: Applied to the perception end, including: an acquiring unit, configured to acquire initial estimated parameters of a target object within a sensing period, where the initial estimated parameters are obtained by performing data estimation according to a first sensing signal, a second sensing signal, and an estimation algorithm, where the first sensing signal is used to sense the target object, the second sensing signal is an echo corresponding to the first sensing signal, and the first sensing signal is sent and the second sensing signal is received using sparse time-frequency resources; a correction value determination unit, configured to determine a correction value corresponding to the initial estimation parameter according to a resource allocation parameter of the time-frequency resource and / or an algorithm parameter of the estimation algorithm, wherein the resource allocation parameter reflects the sparsity of the time-frequency resource, and the algorithm parameter includes a data estimation threshold reflecting the estimation capability of the algorithm; The correction unit is used to correct the initial estimation parameters using the correction value to obtain the target estimation parameters of the target object within the perception period.

29. A perception data processing device, characterized in that: Applied to network equipment, including: A receiving unit, configured to receive second information from a sensing end; The second information includes target estimation parameters of the target object within the perception period and / or correction values ​​corresponding to initial estimation parameters of the target object within the perception period, and the target estimation parameters are obtained by correcting the initial estimation parameters based on the correction values.

30. A processor-readable storage medium, characterized in that: The processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the perception data processing method according to any one of claims 1 to 14.

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