Methods, devices, computer equipment, and storage media for acquiring sensory information

Abstract

This invention relates to the field of network communication, and particularly to a method, apparatus, computer device, and storage medium for obtaining sensing information. By introducing frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristic constraints, an integrated waveform design is performed, enabling the obtained target sensing time-domain signal to utilize all frequency domain resources without the need for frequency domain division for communication and sensing detection. The signal shares the same spectrum to meet the needs of sensing and communication respectively, thereby mitigating the high bit error rate caused by frequency domain distortion, reducing the peak-to-average power ratio, and improving the efficiency of information sensing.

Description

Technical Field

[0001] This invention relates to the field of network communication, and in particular to a method, apparatus, computer device, and storage medium for obtaining sensing information. Background Technology

[0002] In recent years, with the surge in communication and sensing devices, the gap between huge business demands and limited spectrum resources has become increasingly apparent. Therefore, integrated communication and sensing technology has developed rapidly and become a focus of contemporary research. Waveform design, as a key component in realizing physical layer integrated communication and sensing, has received widespread attention.

[0003] Integrated waveforms must simultaneously meet two objectives: achieving a balance between theoretical performance in sensing and communication, and addressing engineering challenges such as hardware complexity and power efficiency. Existing integrated waveform designs can be categorized into three types: integrated waveforms based on communication waveforms, integrated waveforms based on radar waveforms, and integrated waveforms based on joint design. Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier modulation technique widely used in wireless communication systems such as LTE, Wi-Fi, and digital television broadcasting. OFDM offers numerous advantages, including high spectral efficiency, enhanced anti-fading capabilities through joint subcarrier coding, and ease of implementation.

[0004] However, a significant drawback of OFDM signals is their high peak-to-average power ratio (PAPR). A high PAPR means that in some situations, the peak power of an OFDM signal can significantly exceed its average power. This high PAPR leads to increased nonlinear distortion, low power, and quantization error. Specifically, in practical wireless communication systems, to mitigate nonlinear distortion, power amplifiers need to operate at power levels far below their maximum output power, resulting in decreased power efficiency. Moreover, during digital-to-analog conversion, a high PAPR increases quantization error, thereby degrading system performance. Therefore, high PAPR is a key factor limiting the performance of OFDM technology. To improve the efficiency of OFDM systems, effective PAPR reduction techniques must be employed. This is not only a key research topic in modern wireless communication but also an important direction for driving technological progress. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a method, apparatus, computer device, and storage medium for obtaining sensing information. By introducing frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristic constraints, an integrated waveform design is performed, enabling the obtained target sensing time domain signal to utilize all frequency domain resources without the need for communication and sensing detection frequency domain division. The same spectrum is shared to meet the needs of sensing and communication respectively, alleviating the high bit error rate caused by frequency domain distortion, reducing the peak-to-average power ratio, and improving the efficiency of information sensing.

[0006] In a first aspect, embodiments of this application provide a method for obtaining perceived information, comprising the following steps:

[0007] Obtain the sensing frequency domain signal, and construct an optimization problem function based on the sensing frequency domain signal, with frequency domain phase difference, peak-to-average power ratio and OFDM constant mode characteristics as constraints;

[0008] The optimization problem function is transformed into a first sub-optimization problem function regarding the sensed frequency domain signal and a second sub-optimization problem function regarding the time-frequency signal; the alternating direction multiplier algorithm is used to solve the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal to obtain the target sensed frequency domain signal and the target time-frequency signal;

[0009] The target time-frequency signal is sent to the receiving end, and the feedback signal sent by the receiving end is obtained. The receiving end's sensing information is obtained by analyzing the target sensing frequency domain signal and the feedback signal.

[0010] Secondly, embodiments of this application provide a sensing information acquisition device, comprising:

[0011] The first signal acquisition module is used to acquire the sensing frequency domain signal and, based on the sensing frequency domain signal, construct an optimization problem function with the frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristics as constraints.

[0012] The second signal acquisition module is used to transform the optimization problem function into a first sub-optimization problem function about the sensed frequency domain signal and a second sub-optimization problem function about the time-frequency signal; and to solve the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal using an alternating direction multiplier algorithm to obtain the target sensed frequency domain signal and the target time-frequency signal.

[0013] The information sensing module is used to send the target time-frequency signal to the receiving end, obtain the feedback signal sent by the receiving end, and analyze the target sensing frequency domain signal and the feedback signal to obtain the sensing information of the receiving end.

[0014] Thirdly, embodiments of this application provide a computer device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, it implements the steps of the perception information acquisition method as described in the first aspect.

[0015] Fourthly, embodiments of this application provide a storage medium storing a computer program that, when executed by a processor, implements the steps of the perception information acquisition method as described in the first aspect.

[0016] In this application embodiment, a method, apparatus, computer device, and storage medium for obtaining sensing information are provided. By introducing frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristic constraints, an integrated waveform design is performed, enabling the obtained target sensing time domain signal to utilize all frequency domain resources without the need for communication and sensing detection frequency domain division. The same spectrum is shared to meet the needs of sensing and communication respectively, alleviating the high bit error rate caused by frequency domain distortion, reducing the peak-to-average power ratio, and improving the efficiency of information sensing.

[0017] To better understand and implement this invention, the following detailed description is provided in conjunction with the accompanying drawings. Attached Figure Description

[0018] Figure 1 This is a schematic diagram illustrating an application scenario of the perception information acquisition method provided in one embodiment of this application;

[0019] Figure 2 A flowchart illustrating a method for obtaining perceived information according to an embodiment of this application;

[0020] Figure 3 This is a flowchart illustrating step S2 of a method for obtaining perception information according to an embodiment of this application.

[0021] Figure 4 This is a flowchart illustrating step S3 of a method for obtaining perception information according to an embodiment of this application.

[0022] Figure 5 A flowchart illustrating step S3 of a method for obtaining perception information provided in another embodiment of this application;

[0023] Figure 6 This is a schematic diagram of the structure of a sensing information acquisition device provided in one embodiment of this application;

[0024] Figure 7 This is a schematic diagram of the structure of a computer device provided in one embodiment of this application. Detailed Implementation

[0025] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0026] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0027] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0028] Please see Figure 1 , Figure 1 This is a schematic diagram of an application scenario for a perception information acquisition method provided in one embodiment of this application. The application scenario includes several vehicles. The OFDM-ISAC system integrates radar sensing capabilities. Vehicles can detect vehicles or obstacles in the surrounding environment through radar and avoid collisions. By utilizing ISAC technology, vehicles can detect paths through radar and automatically adjust speed and lanes based on the received perception data to achieve safe driving.

[0029] Please see Figure 2 , Figure 2 The following is a flowchart illustrating a method for obtaining perceived information according to an embodiment of this application. The method includes the following steps:

[0030] S1: Obtain the sensing frequency domain signal, and construct an optimization problem function based on the sensing frequency domain signal, with the frequency domain phase difference, peak-to-average power ratio and OFDM constant mode characteristics as constraints.

[0031] Vehicles can all serve as transmitters. In this embodiment, the transmitter obtains the sensing frequency domain signal. Specifically, the transmitter performs QPSK / QAM encoding based on the information to be sensed, mapping each two bits to a complex signal to obtain a modulated signal, which serves as the sensing frequency domain signal. The sensing frequency domain signal includes information vectors of several subcarriers.

[0032] In an OFDM (Orthogonal Frequency Division Multiplexing) system, an OFDM symbol consists of multiple subcarriers that are orthogonal to each other in the frequency domain. The number of subcarriers N represents the total number of subcarriers contained in an OFDM symbol. Each subcarrier carries a portion of data; therefore, the larger N is, the more data the system can transmit simultaneously.

[0033] In ISAC (Integrated Sensing and Communication) systems, the modulated signal typically represents a symbol transmitted in the frequency domain. This modulated signal can be represented as a vector x = [x0, x1, ..., x...]. N-1 ] T Where x0, x1, ..., x N-1 These are the modulation symbols of the system on different subcarriers.

[0034] Based on the sensed frequency domain signal, the transmitter constructs an optimization problem function with constraints including frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristics. The aim is to find the optimal sensed frequency domain signal and its corresponding sensed time domain signal within the distortion range that satisfy low PAPR and constant mode constraints. The expression for the optimization problem function is:

[0035] findx,s (1a)

[0036] stAx=s (1b)

[0037] arg(x i -c i )<θ (1c)

[0038]

[0039] |x i |=1,i=1,2,…,N(1e)

[0040] In the formula, x is the perceived frequency domain signal, s is the perceived time domain signal, and A is the discrete inverse Fourier transform matrix, wherein the discrete inverse Fourier transform matrix is:

[0041]

[0042] x i To sense the information vector of the i-th subcarrier in the frequency domain signal, c iLet be the information vector of the i-th subcarrier in the ideal sensing frequency domain signal. The scalable region in the interval (0,π) can be selected according to specific needs. θ is the phase threshold, which is used to limit the maximum allowable value of the frequency domain phase difference to ensure that the system can effectively process the signal and reduce errors. arg(·) is the function for finding the maximum and minimum values. PAPR(s) is the peak-to-average power ratio of the sensing time domain signal. α is the upper limit threshold of the peak-to-average power ratio. M is the number of subcarriers in the ideal sensing frequency domain signal. N is the number of subcarriers in the sensing frequency domain signal.

[0043] For constraint (1b), it means that the perceived frequency domain signal x is converted into the perceived time domain signal s through inverse Fourier transform; for constraint (1c), it means that the phase difference threshold between x and the preset ideal perceived frequency domain signal c is given; for constraint (1d), it means that the peak-to-average power ratio does not exceed the upper limit threshold α of the peak-to-average power ratio; for constraint (1e), it ensures that the perceived frequency domain signal x is a constant mode sequence.

[0044] S2: The optimization problem function is transformed into a first sub-optimization problem function with respect to the sensed frequency domain signal and a second sub-optimization problem function with respect to the time-frequency signal; the alternating direction multiplier algorithm is used to solve the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal to obtain the target sensed frequency domain signal and the target time-frequency signal.

[0045] In this embodiment, the transmitting end transforms the optimization problem function into a first sub-optimization problem function regarding the sensed frequency domain signal and a second sub-optimization problem function regarding the time-frequency signal, based on a preset augmented Lagrangian function. The augmented Lagrangian function is:

[0046]

[0047] In the formula, L ρ (x,s,r) is the augmented Lagrangian function, Re{·} is the x function, H is the conjugate transpose symbol, r is the Lagrangian operator, and ρ is the penalty parameter;

[0048] The first sub-optimization problem function:

[0049]

[0050] st|x n |=1,n=0,1,…,N-1

[0051] arg(x i -c i )<θ

[0052] In the formula, k is the number of iterations, and r (k)Let s be the Lagrange multiplier for the k-th iteration. (k) Let x be the time-domain signal of the k-th iteration. n The information vector of the nth subcarrier in the perceived frequency domain signal; ρ is the penalty parameter;

[0053] The second sub-optimization problem function is:

[0054]

[0055] To improve optimization efficiency, the transmitter employs the alternating direction multiplier algorithm (PAPR) to solve the first and second sub-optimization problem functions based on the sensed frequency domain signal, thereby obtaining the target sensed frequency domain signal and the target time-frequency signal. In the case of limited frequency domain resources, PAPR is balanced to reduce the contradiction between communication and sensing performance, maximize the utilization of frequency domain resources, and improve the phase degree of freedom, thereby improving the accuracy and efficiency of information sensing.

[0056] Please see Figure 3 , Figure 3 The flowchart of S2 in the method for obtaining perception information provided in one embodiment of this application is shown below, including steps S21 to S24, as follows:

[0057] S21: Obtain the initial sensing time-domain signal and the initial Lagrange multiplier. Based on the initial sensing time-domain signal, the initial Lagrange multiplier, and the first sub-optimization problem function, update the sensing frequency-domain signal to obtain the updated sensing frequency-domain signal, which will be used as the sensing frequency-domain signal for the next iteration.

[0058] In this embodiment, the transmitting end obtains the initial sensing time-domain signal and the initial Lagrange multiplier. Specifically, the initial sensing time-domain signal is generated by IDFT transformation of the sensing frequency-domain signal in the OFDM system, with an oversampling factor of 4, i.e., M = 4 * N. Each frequency subcarrier of the initial sensing time-domain signal s is oversampled by a factor of 4 in the time domain to ensure that the signal has higher temporal resolution. The sensing time-domain signal s is represented as s = [s0, s1, ..., s M-1 ] T Where s0, s1, ..., s M-1 This represents the sensing time-domain signal point after oversampling.

[0059] The transmitting end updates the sensing frequency domain signal based on the initial sensing time domain signal, the initial Lagrange multipliers, and the first sub-optimization problem function to obtain the updated sensing frequency domain signal, which serves as the sensing frequency domain signal for the next iteration. The updated sensing frequency domain signal is as follows:

[0060]

[0061] In the formula, k is the number of iterations. Let j be the information vector of the i-th subcarrier in the sensing frequency domain signal of the (k+1)-th iteration, and j be the amplitude. for The first N values ​​of y (k) Let ρ be the penalty parameter.

[0062] about There are three situations: when With c i The phase difference between them is within the threshold range, greater than the threshold, and less than the threshold. To minimize the error, if With c i If the phase difference between them is greater than the threshold, then The upper boundary should be taken; conversely, if the phase difference is less than the threshold, then... The boundary should be removed.

[0063] S22: Based on the updated sensing frequency domain signal, the initial Lagrange multipliers, and the second sub-optimization problem function, update the initial sensing time domain signal to obtain the updated sensing time domain signal, which will be used as the sensing time domain signal for the next iteration.

[0064] In this embodiment, the transmitting end updates the initial sensing time-domain signal based on the updated sensing frequency-domain signal, the initial Lagrange multipliers, and the second sub-optimization problem function to obtain an updated sensing time-domain signal, which serves as the sensing time-domain signal for the next iteration. The updated sensing time-domain signal is:

[0065] s (k+1) =max(Re{v (k+1)H q k},0)v (k+1)

[0066]

[0067] In the formula, s (k+1) Let v be the time-domain signal of the (k+1)th iteration. (k+1) This is the first auxiliary signal for the (k+1)th iteration. Let q be the information vector of the m-th subcarrier in the first auxiliary signal of the (k+1)-th iteration. k This is the second auxiliary signal for the k-th iteration. Let r be the information vector of the m-th subcarrier in the second auxiliary signal of the k-th iteration. (k) Let γ be the Lagrange multiplier for the k-th iteration, H be the conjugate transpose, and γ be the Lagrange multiplier. (k) The third auxiliary signal for the k-th iteration is obtained by performing a binary search based on a preset search interval. Specifically, the initial search interval is defined as follows: Ensure γ k Within this range, it can be... Set it to 0, and Set it to a sufficiently large value.

[0068] Repeat the following steps: First calculate To update v k+1 According to v k+1 The norm determines the next step:

[0069] if Then the left endpoint of the interval Update to the current γ k .

[0070] if Then the right endpoint of the interval Update to the current γ k .

[0071] Termination condition: when v k+1 Stop when the square of the norm is very close to 1, at which point γ is... k Set as

[0072] By following the steps above, the search range can be gradually narrowed down, and the location can be precisely pinpointed. γ close to 1 k The value of .

[0073] S23: Based on the updated sensing frequency domain signal, the updated sensing time domain signal, and the preset Lagrange multiplier update algorithm, update the initial Lagrange multiplier to obtain the updated Lagrange multiplier, which will be used as the Lagrange multiplier for the next iteration.

[0074] In this embodiment, the transmitting end updates the initial Lagrange multiplier based on the updated sensing frequency domain signal, the updated sensing time domain signal, and a preset Lagrange multiplier update algorithm to obtain the updated Lagrange multiplier, which serves as the Lagrange multiplier for the next iteration. The Lagrange multiplier update algorithm is as follows:

[0075] r (k+1) =r (k) +ρ(Ax (k+1) -s (k+1) )

[0076] In the formula, r (k+1) It is the Lagrange multiplier for the (k+1)th iteration.

[0077] S24: Based on the sensing frequency domain signal, sensing time domain signal, and Lagrange multipliers of the next iteration, repeat the update operation until the sensing frequency domain signal and sensing time domain signal converge to the optimal solution, and obtain the sensing frequency domain signal and sensing time domain signal of the last iteration as the target sensing frequency domain signal and target sensing time domain signal.

[0078] In this embodiment, the transmitting end repeatedly performs update operations based on the sensing frequency domain signal, sensing time domain signal, and Lagrange multipliers of the next iteration until the sensing frequency domain signal and sensing time domain signal converge to the optimal solution, and obtains the sensing frequency domain signal and sensing time domain signal of the last iteration as the target sensing frequency domain signal and target sensing time domain signal. While maintaining an acceptable bit error rate level, the PAPR of the target sensing time domain signal is significantly reduced, and better communication performance is achieved.

[0079] By introducing frequency domain phase difference, peak-to-average power ratio, and OFDM constant-mode characteristic constraints, an integrated waveform design is performed. This ensures that the autocorrelation function of the target sensing time-domain signal obtained based on the optimization problem function reaches its peak only at zero delay, and is zero at other delays. This characteristic helps improve the detection accuracy and sensing performance of the waveform. It can utilize all frequency domain resources without the need for frequency domain division between communication and sensing detection, sharing the same spectrum to meet the needs of sensing and communication respectively, thus mitigating the high bit error rate caused by frequency domain distortion. Secondly, for the sensing function, a constant-mode frequency domain sequence is used to ensure good time-domain periodic autocorrelation (PAC) characteristics, thereby improving the sensing performance of the OFDM-ISAC system. For communication, the frequency domain constellation points of the signal are limited to a preset phase threshold to ensure correct decoding at the communication receiver. At the same time, optimizing the frequency domain sequence within this phase threshold can reduce the peak-to-average power ratio (PAPR), improving the efficiency of information sensing.

[0080] S3: Send the target time-frequency signal to the receiving end, obtain the feedback signal sent by the receiving end, and analyze the target sensing frequency domain signal and the feedback signal to obtain the sensing information of the receiving end.

[0081] In this embodiment, the transmitting end sends the target time-frequency signal to the receiving end, obtains the feedback signal sent by the receiving end, and analyzes the target sensing frequency domain signal and the feedback signal to obtain the sensing information of the receiving end, wherein the sensing information includes distance information and speed information.

[0082] Please see Figure 4 , Figure 4 The flowchart of S3 in the method for obtaining perception information provided in one embodiment of this application is shown, including step S31, as follows:

[0083] S31: Insert the cyclic prefix into the target time-frequency signal to obtain the inserted target time-frequency signal, and send the inserted target time-frequency signal to the receiving end to obtain the feedback signal sent by the receiving end.

[0084] To prevent inter-symbol interference (ISI), in this embodiment, the transmitter inserts a cyclic prefix into the target time-frequency signal to obtain an inserted target time-frequency signal. This inserted target time-frequency signal is then sent to the receiver to obtain a feedback signal. The feedback signal is generated by the receiver removing the cyclic prefix from the inserted target time-frequency signal and transforming it into a sensing frequency domain signal Y using a DFT. This sensing frequency domain signal Y is then demodulated using QPSK to recover the original binary data, and the signal is generated based on this binary data.

[0085] Please see Figure 5 , Figure 5 The flowchart of S3 in the method for obtaining perception information provided in another embodiment of this application is shown, which also includes steps S32 to S34, as follows:

[0086] S32: Construct the frequency domain conjugate reference matrix of the target sensing frequency domain signal and the receiving matrix of the feedback signal, and perform Hadamard product operation based on the frequency domain conjugate reference matrix and the receiving matrix to obtain the Hadamard product result.

[0087] In this embodiment, the transmitting end constructs the frequency domain conjugate reference matrix of the target sensing frequency domain signal and the receiving matrix of the feedback signal, and performs a Hadamard product operation based on the frequency domain conjugate reference matrix and the receiving matrix to obtain the Hadamard product result.

[0088] S33: Perform inverse discrete Fourier transform based on the Hadamard product result to extract time delay information, and calculate the distance based on the time delay information to obtain the distance information.

[0089] In this embodiment, the transmitting end performs an inverse discrete Fourier transform based on the Hadamard product result to perform time delay analysis, extract time delay information, and calculate the distance based on the time delay information to obtain the distance information between the transmitting end and the receiving end, which is used as the distance information.

[0090] S34: Perform a discrete Fourier transform on the feedback signal to extract the spectral offset information, and calculate the speed based on the spectral offset information to obtain the speed information.

[0091] In this embodiment, the transmitting end performs a discrete Fourier transform on the sampling points on each subcarrier of the feedback signal to extract the spectral offset information caused by the Doppler frequency shift, and calculates the velocity based on the spectral offset information to obtain the velocity information.

[0092] Please refer to Figure 6 , Figure 6 This is a schematic diagram of a sensing information acquisition device according to an embodiment of this application. The device can be implemented entirely or partially through software, hardware, or a combination of both. The device 6 includes:

[0093] The first signal acquisition module 61 is used to acquire the sensing frequency domain signal and, based on the sensing frequency domain signal, construct an optimization problem function with the frequency domain phase difference, peak-to-average power ratio and OFDM constant mode characteristics as constraints.

[0094] The second signal acquisition module 62 is used to transform the optimization problem function into a first sub-optimization problem function about the sensed frequency domain signal and a second sub-optimization problem function about the time-frequency signal; and to solve the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal using an alternating direction multiplier algorithm to obtain the target sensed frequency domain signal and the target time-frequency signal.

[0095] The information sensing module 63 is used to send the target time-frequency signal to the receiving end, obtain the feedback signal sent by the receiving end, and analyze the target sensing frequency domain signal and the feedback signal to obtain the sensing information of the receiving end.

[0096] In this embodiment, a first signal acquisition module obtains a sensed frequency domain signal. Based on the sensed frequency domain signal, an optimization problem function is constructed using frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristics as constraints. A second signal acquisition module transforms the optimization problem function into a first sub-optimization problem function relating to the sensed frequency domain signal and a second sub-optimization problem function relating to the time-frequency signal. An alternating direction multiplier algorithm is used to solve the first and second sub-optimization problem functions based on the sensed frequency domain signal to obtain the target sensed frequency domain signal and the target time-frequency signal. An information sensing module transmits the target time-frequency signal to the receiving end to obtain a feedback signal from the receiving end. The receiving end's sensed information is obtained by analyzing the target sensed frequency domain signal and the feedback signal. By introducing frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristic constraints, an integrated waveform design is performed, enabling the obtained target sensing time domain signal to utilize all frequency domain resources without the need for communication and sensing detection frequency domain division. The same spectrum is shared to meet the needs of sensing and communication respectively, alleviating the high bit error rate caused by frequency domain distortion, reducing the peak-to-average power ratio, and improving the efficiency of information sensing.

[0097] Please refer to Figure 7 , Figure 7This is a schematic diagram of the structure of a computer device provided in one embodiment of this application. The computer device 7 includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. The computer device can store multiple instructions, which are adapted to be loaded and executed by the processor 71. Figures 1 to 5 The method steps shown can be found in the following document for detailed execution process. Figures 1 to 5 The specific details shown will not be repeated here.

[0098] The processor 71 may include one or more processing cores. The processor 71 connects to various parts of the server using various interfaces and lines, and executes various functions and processes data of the sensing information acquisition device 5 by running or executing instructions, programs, code sets, or instruction sets stored in the memory 72, and by calling data stored in the memory 72. Optionally, the processor 71 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 71 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU mainly handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required to be displayed on the touch screen; and the modem is used for wireless communication. It is understood that the modem may also not be integrated into the processor 71 and may be implemented as a separate chip.

[0099] The memory 72 may include random access memory (RAM) or read-only memory. Optionally, the memory 72 may include a non-transitory computer-readable storage medium. The memory 72 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 72 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch instructions), instructions for implementing the various method embodiments described above, etc.; the data storage area may store data involved in the various method embodiments described above, etc. Optionally, the memory 72 may also be at least one storage device located remotely from the aforementioned processor 71.

[0100] This application embodiment also provides a storage medium that can store multiple instructions, which are adapted to be loaded and executed by a processor as described above. Figures 1 to 5 The method steps shown can be found in the following document for detailed execution process. Figures 1 to 5 The specific details shown will not be repeated here.

[0101] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0102] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0103] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the algorithm. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0104] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / terminal devices and methods can be implemented in other ways. For example, the apparatus / terminal device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0105] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0106] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0107] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms.

[0108] This invention is not limited to the above-described embodiments. If any modifications or variations to this invention do not depart from the spirit and scope of this invention, and if such modifications and variations fall within the scope of the claims and equivalent technologies of this invention, then this invention also intends to include such modifications and variations.

Claims

1. A method for acquiring sensory information, characterized in that, Includes the following steps: Obtain the sensing frequency domain signal, and construct an optimization problem function based on the sensing frequency domain signal, with frequency domain phase difference, peak-to-average power ratio and OFDM constant mode characteristics as constraints; The optimization problem function is transformed into a first sub-optimization problem function regarding the sensed frequency domain signal and a second sub-optimization problem function regarding the time-frequency signal; the alternating direction multiplier algorithm is used to solve the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal to obtain the target sensed frequency domain signal and the target time-frequency signal; The target time-frequency signal is sent to the receiving end, and the feedback signal sent by the receiving end is obtained. The receiving end's sensing information is obtained by analyzing the target sensing frequency domain signal and the feedback signal.

2. The method for obtaining perceived information according to claim 1, characterized in that: The expression for the optimization problem function is: find x,s stAx=s arg(x i -c i )<θ |x i |=1,i=1,2,…,N In the formula, x is the perceived frequency domain signal, s is the perceived time domain signal, A is the discrete Fourier inverse transform matrix, and x i To sense the information vector of the i-th subcarrier in the frequency domain signal, c i Let be the information vector of the i-th subcarrier in the ideal sensing frequency domain signal, θ be the phase threshold, arg(·) be the function for finding the maximum and minimum values, PAPR(s) be the peak-to-average power ratio of the sensing time domain signal, α be the upper limit threshold of the peak-to-average power ratio, M be the number of subcarriers in the ideal sensing frequency domain signal, and N be the number of subcarriers in the sensing frequency domain signal.

3. The method for obtaining sensory information according to claim 2, characterized in that, The first sub-optimization problem function: s.t.|x n |=1,n=0,1,…,N-1 arg(x i -c i )<θ In the formula, k is the number of iterations, H is the conjugate transpose symbol, Re{·} is the x-function, and r (k) Let s be the Lagrange multiplier for the k-th iteration. (k) Let x be the time-domain signal of the k-th iteration. n The information vector of the nth subcarrier in the perceived frequency domain signal; ρ is the penalty parameter; The second sub-optimization problem function is:

4. The method for obtaining sensory information according to claim 3, characterized in that, The step of solving the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal to obtain the target sensed frequency domain signal and the target time-frequency signal includes the following steps: The initial sensing time-domain signal and the initial Lagrange multiplier are obtained. Based on the initial sensing time-domain signal, the initial Lagrange multiplier, and the first sub-optimization problem function, the sensing frequency-domain signal is updated to obtain the updated sensing frequency-domain signal, which is used as the sensing frequency-domain signal for the next iteration. Based on the updated sensing frequency domain signal, the initial Lagrange multipliers, and the second sub-optimization problem function, the initial sensing time domain signal is updated to obtain the updated sensing time domain signal, which is used as the sensing time domain signal for the next iteration. Based on the updated sensing frequency domain signal, the updated sensing time domain signal, and the preset Lagrange multiplier update algorithm, the initial Lagrange multiplier is updated to obtain the updated Lagrange multiplier, which is used as the Lagrange multiplier for the next iteration. Based on the sensing frequency domain signal, sensing time domain signal, and Lagrange multipliers of the next iteration, the update operation is repeated until the sensing frequency domain signal and sensing time domain signal converge to the optimal solution, and the sensing frequency domain signal and sensing time domain signal of the last iteration are obtained as the target sensing frequency domain signal and target sensing time domain signal.

5. The method for obtaining sensory information according to claim 4, characterized in that, The step of sending the target time-frequency signal to the receiving end and obtaining the feedback signal sent by the receiving end includes the following steps: A cyclic prefix is ​​inserted into the target time-frequency signal to obtain the inserted target time-frequency signal. The inserted target time-frequency signal is then sent to the receiving end to obtain the feedback signal sent by the receiving end.

6. The method for obtaining sensory information according to claim 5, characterized in that: The sensed information includes distance information and speed information; The step of parsing the target sensing frequency domain signal and the feedback signal to obtain the sensing information of the receiving end includes the following steps: Construct the frequency domain conjugate reference matrix of the target sensing frequency domain signal and the receiving matrix of the feedback signal, and perform a Hadamard product operation based on the frequency domain conjugate reference matrix and the receiving matrix to obtain the Hadamard product result. Perform an inverse discrete Fourier transform on the Hadamard product result to extract time delay information, and calculate the distance based on the time delay information to obtain the distance information; The feedback signal is subjected to a discrete Fourier transform to extract the spectral offset information, and the velocity is calculated based on the spectral offset information to obtain the velocity information.

7. A device for acquiring sensing information, characterized in that, include: The first signal acquisition module is used to acquire the sensing frequency domain signal and, based on the sensing frequency domain signal, construct an optimization problem function with the frequency domain phase difference, peak-to-average power ratio, and OFDM constant mode characteristics as constraints. The second signal acquisition module is used to transform the optimization problem function into a first sub-optimization problem function about the sensed frequency domain signal and a second sub-optimization problem function about the time-frequency signal; and to solve the first sub-optimization problem function and the second sub-optimization problem function based on the sensed frequency domain signal using an alternating direction multiplier algorithm to obtain the target sensed frequency domain signal and the target time-frequency signal. The information sensing module is used to send the target time-frequency signal to the receiving end, obtain the feedback signal sent by the receiving end, and analyze the target sensing frequency domain signal and the feedback signal to obtain the sensing information of the receiving end.

8. A computer device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and executable on the processor; the computer program, when executed by the processor, implements the steps of the method for obtaining perceptual information as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the perceptual information acquisition method as described in any one of claims 1 to 6.

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