TDOA positioning method and system

Abstract

The invention discloses a TDOA (Time Difference Of Arrival) positioning method and a TDOA positioning system, which are applied to the technical field of signal positioning, and the method comprises the following steps: processing uplink detection reference signal data received by a plurality of base stations to obtain discrete channel response data; performing interpolation processing on the discrete channel response data to obtain a frequency domain channel vector; performing frequency domain oversampling processing on the frequency domain channel vector to obtain an oversampled frequency domain vector; based on a fast Fourier transform technology, performing time domain conversion processing on the oversampling frequency domain vector to obtain time domain channel impulse response data; and performing peak search processing on the time domain channel impulse response data by using a peak detection technology, and inputting the obtained arrival time data into the positioning system for processing to obtain a TDOA positioning result. According to the method provided by the invention, the technical problems of time difference measurement error and positioning deviation caused by SRS detection peak deviation in TDOA positioning can be solved.

Description

Technical Field

[0001] This invention relates to the field of signal positioning technology, and in particular to a TDOA positioning method and system. Background Technology

[0002] In 5G NR systems, the uplink sounding reference signal (SRS) is widely used for physical layer functions such as channel state information acquisition, beamforming, and link adaptation. As 5G evolves towards integrated sensing and communication, SRS is gradually becoming a key signal resource for achieving high-precision positioning.

[0003] In existing technologies, the TDOA positioning method generally relies on the time difference of arrival of uplink probe reference signals to multiple base stations to calculate the location. However, during the positioning process, it will cause the detection peak of the probe reference signal to shift, resulting in the time difference measurement value deviating from the actual physical propagation delay, thus generating a systematic time estimation error, and consequently, a positioning deviation. Summary of the Invention

[0004] This invention provides a TDOA positioning method and system, which solves the technical problems of time difference measurement error and positioning deviation caused by SRS detection peak offset in TDOA positioning.

[0005] To address the aforementioned technical problems, this invention provides a TDOA positioning method, the method comprising: Channel estimation processing is performed on the uplink sounding reference signal data received by several base stations to obtain discrete channel response data; The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position. The frequency domain channel vector is subjected to frequency domain oversampling processing to obtain an oversampled frequency domain vector; Based on the Fast Fourier Transform technique, the oversampled frequency domain vector is transformed into time domain data to obtain time-domain channel impulse response data. Peak detection technology is used to perform peak search processing on the time-domain channel impulse response data, and the obtained arrival time data is input into the positioning system for processing to obtain the TDOA positioning result.

[0006] As one preferred embodiment, channel estimation processing is performed on the uplink sounding reference signal data received by the plurality of base stations to obtain discrete channel response data, including: Channel estimation processing is performed on the uplink detection reference signal data to obtain subcarrier channel estimation values; The subcarrier channel estimate is processed using frequency domain discretization techniques to obtain the discrete channel response data.

[0007] As one preferred embodiment, the discrete channel response data is interpolated using a position-adaptive piecewise filtering interpolation technique to obtain a frequency domain channel vector, including: The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain the interpolated frequency domain channel data. The interpolated frequency domain channel data is integrated to obtain the frequency domain channel vector.

[0008] As one preferred embodiment, based on the Fast Fourier Transform technique, the oversampled frequency domain vector is transformed into time-domain data to obtain time-domain channel impulse response data, including: The oversampled frequency domain vector is transformed into a complex time domain sequence using the Fast Fourier Transform technique. The complex time-domain sequence is processed by amplitude calculation to obtain the time-domain channel impulse response data.

[0009] As one preferred embodiment, peak detection technology is used to perform peak search processing on the time-domain channel impulse response data, and the obtained time-of-arrival data is input into the positioning system for processing to obtain the TDOA positioning result, including: The arrival time data is obtained by performing peak search processing on the time-domain channel impulse response data using peak detection technology. The arrival time data is processed using the TDOA calculation technology in the positioning system to obtain the TDOA positioning result.

[0010] The present invention also provides a TDOA positioning system, comprising: The estimation module is used to perform channel estimation processing on the uplink sounding reference signal data received by the base stations to obtain discrete channel response data; An interpolation module is used to interpolate the discrete channel response data using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position. The oversampling module is used to perform frequency domain oversampling processing on the frequency domain channel vector to obtain an oversampled frequency domain vector. The conversion module is used to perform time-domain conversion processing on the oversampled frequency domain vector based on the fast Fourier transform technique to obtain time-domain channel impulse response data; The processing module is used to perform peak search processing on the time-domain channel impulse response data using peak detection technology, input the obtained arrival time data into the positioning system for processing, and obtain the TDOA positioning result.

[0011] As one preferred embodiment, channel estimation processing is performed on the uplink sounding reference signal data received by the plurality of base stations to obtain discrete channel response data, including: Channel estimation processing is performed on the uplink detection reference signal data to obtain subcarrier channel estimation values; The subcarrier channel estimate is processed using frequency domain discretization techniques to obtain the discrete channel response data.

[0012] As one preferred embodiment, the discrete channel response data is interpolated using a position-adaptive piecewise filtering interpolation technique to obtain a frequency domain channel vector, including: The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain the interpolated frequency domain channel data. The interpolated frequency domain channel data is integrated to obtain the frequency domain channel vector.

[0013] As one preferred embodiment, based on the Fast Fourier Transform technique, the oversampled frequency domain vector is transformed into time-domain data to obtain time-domain channel impulse response data, including: The oversampled frequency domain vector is transformed into a complex time domain sequence using the Fast Fourier Transform technique. The complex time-domain sequence is processed by amplitude calculation to obtain the time-domain channel impulse response data.

[0014] As one preferred embodiment, peak detection technology is used to perform peak search processing on the time-domain channel impulse response data, and the obtained time-of-arrival data is input into the positioning system for processing to obtain the TDOA positioning result, including: The arrival time data is obtained by performing peak search processing on the time-domain channel impulse response data using peak detection technology. The arrival time data is processed using the TDOA calculation technology in the positioning system to obtain the TDOA positioning result.

[0015] The present invention also provides a TDOA positioning device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the TDOA positioning method as described above.

[0016] The present invention further provides a computer-readable storage medium storing a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the TDOA positioning method as described above.

[0017] Compared with the prior art, the beneficial effects of the present invention are at least one of the following: This invention obtains discrete channel response data by performing channel estimation processing on uplink sounding reference signal data received by several base stations; interpolating the discrete channel response data using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position; performing frequency domain oversampling processing on the frequency domain channel vector to obtain an oversampled frequency domain vector; performing time domain transformation processing on the oversampled frequency domain vector based on Fast Fourier Transform (FFT) technology to obtain time domain channel impulse response data; and performing peak search processing on the time domain channel impulse response data using peak detection technology. The obtained time of arrival (TOA) data is then input into the positioning system for processing to obtain a TDOA positioning result.

[0018] Compared with existing technologies, this invention addresses the problem of time difference measurement error and positioning deviation caused by SRS detection peak offset in traditional TDOA positioning in 5G NR systems. First, channel estimation is performed on the uplink SRS data received by the base station to obtain discrete channel response. Then, a high-fidelity frequency domain channel vector is obtained through position adaptive segmented filtering interpolation technology based on subcarrier position dynamic selection of filtering vector. After frequency domain oversampling to improve resolution, a time domain transformation is performed using fast Fourier transform technology to obtain accurate time domain channel impulse response. Finally, peak detection is used to obtain arrival time data without offset and systematic error, which is then used for TDOA positioning calculation. This eliminates the detection peak offset problem at its root, thereby solving the time measurement error and positioning deviation. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the TDOA positioning method in one embodiment of the present invention; Figure 2 This is a schematic diagram of the TDOA positioning system in one embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a TDOA positioning device in one embodiment of the present invention; Figure label: Among them, 11 is the estimation module; 12 is the interpolation module; 13 is the oversampling module; 14 is the conversion module; 15 is the processing module; 21 is the processor; and 22 is the memory. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0022] One embodiment of the present invention provides a TDOA positioning method. For details, please refer to [link to specific documentation]. Figure 1 , Figure 1 The diagram shown is a flowchart of a TDOA positioning method according to one embodiment of the present invention. The method includes: S1: Perform channel estimation processing on the uplink sounding reference signal data received by several base stations to obtain discrete channel response data; S2: The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position. S3: Perform frequency domain oversampling on the frequency domain channel vector to obtain an oversampled frequency domain vector; S4: Based on the Fast Fourier Transform technique, the oversampled frequency domain vector is converted to the time domain to obtain the time-domain channel impulse response data; S5: Use peak detection technology to perform peak search processing on the time-domain channel impulse response data, and input the obtained arrival time data into the positioning system for processing to obtain the TDOA positioning result.

[0023] The TDOA positioning method aims to achieve high-precision TDOA positioning by using uplink probe reference signal data received by multiple base stations (gNBs) in the positioning system.

[0024] Specifically, channel estimation processing is performed on the uplink sounding reference signal data received by several base stations to obtain discrete channel response data, including: performing channel estimation processing on the uplink sounding reference signal data to obtain subcarrier channel estimates; and processing the subcarrier channel estimates using frequency domain discretization techniques to obtain the discrete channel response data.

[0025] During processing, the base station first extracts the uplink sounding reference signal (SRS) received from the terminal. Based on the established SRS sequence format and time-frequency resource mapping rules of 5G NR, it uses the locally known standard SRS reference sequence to perform correlation matching, coherent demodulation, and channel decoupling operations with the actual received signal. It then calculates each subcarrier transmitting the SRS one by one, and finally outputs the channel amplitude, phase, and other characteristic parameters corresponding to each subcarrier, which is a one-to-one corresponding subcarrier channel estimate.

[0026] Based on the estimated values ​​of each subcarrier channel, and in accordance with the subcarrier frequency domain numbering order and time-frequency resource arrangement rules specified by the 5G NR system, all subcarrier channel estimates are arranged and integrated in an orderly manner. At the same time, data calibration and outlier removal are completed through frequency domain discretization processing, and the scattered subcarrier estimation results are encapsulated into a structured frequency domain data set that corresponds one-to-one with the subcarrier position.

[0027] Furthermore, the discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector. This includes: interpolating the discrete channel response data using the position-adaptive segmented filtering interpolation technique to obtain interpolated frequency domain channel data; and integrating the interpolated frequency domain channel data to obtain the frequency domain channel vector. The position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position.

[0028] Using the previously extracted discrete channel response data as the processing object, the frequency domain position of the subcarrier corresponding to each set of discrete data is first identified. Then, based on the position characteristics of different subcarriers, a matching filter vector is dynamically selected instead of using fixed filter parameters. Subsequently, using the adaptively selected filter vector as the core, segmented filtering interpolation is performed on the discrete channel response data to fill in the corresponding channel response values ​​in the frequency domain gaps between the original discrete subcarriers, and finally, continuous frequency domain channel data after point filling is generated.

[0029] In accordance with the frequency domain subcarrier arrangement order and resource mapping rules specified by the 5G NR system, the interpolated frequency domain channel data obtained in the first step is systematically spliced, regularized and calibrated. At the same time, abnormal values ​​that may be generated during the interpolation process are removed, and the scattered and segmented interpolation results are integrated into vector data with unified structure, regular dimensions and continuous arrangement in the frequency domain.

[0030] In this embodiment, to address the interpolation distortion problem of the symbol start and end subcarriers in the SRS comb configuration (Comb-2 / 4), an adaptive filtering mechanism is adopted to dynamically select the filtering vector based on the subcarrier position k. The subcarriers are divided into three segments: start, middle, and end, with different filtering vectors selected for each segment.

[0031] In the initial region, the initial filter vector V_first is used to compensate for the phase jump caused by the cyclic prefix truncation; in the middle region, the conventional filter vector V_medium is used for standard DFT interpolation; and in the final region, the final filter vector V_last is used to suppress spectral leakage and boundary oscillations.

[0032] The adaptive piecewise filtering interpolation process is represented as follows: in, It is the channel estimation output. , and It is a piecewise filtering vector. and These are the SRS comb configuration and the number of subcarriers on the OFDM symbol, respectively. , and This is achieved by introducing a linear phase correction term, using standard DFT interpolation, and sampling windowing functions, respectively.

[0033] By dynamically switching the optimal filter vector according to the subcarrier position, the spectral distortion and phase distortion caused by the discontinuity of OFDM symbol boundaries can be improved, thereby increasing the estimation accuracy without increasing the system complexity and reducing the estimation error.

[0034] The frequency domain channel vector is subjected to frequency domain oversampling processing to obtain an oversampled frequency domain vector.

[0035] In this step, the interpolated complete frequency domain channel vector is zero-paded to extend the sequence length, forming an oversampled frequency domain vector, thereby effectively increasing the sampling rate. Specifically, the vector is extended to L× Point, where L is the oversampling factor, This is the initial IFFT length.

[0036] Zero-padding involves inserting zero values ​​in the middle of the frequency domain.

[0037] Based on the Fast Fourier Transform (FFT) technique, the oversampled frequency domain vector is transformed into a time domain to obtain time-domain channel impulse response data. This includes: using the FFT technique to transform the oversampled frequency domain vector into a time domain to obtain a complex time-domain sequence; and performing amplitude calculation on the complex time-domain sequence to obtain the time-domain channel impulse response data.

[0038] Using the oversampled frequency domain vector after frequency domain oversampling as the processing object, the inverse fast Fourier transform (IFFT) is used to complete the conversion operation from frequency domain to time domain. According to the established transformation rules, the high-resolution frequency domain channel complex data after oversampling is converted point by point into a complex signal sequence in the time domain dimension. This sequence completely preserves the channel amplitude and phase information corresponding to different propagation delays.

[0039] For complex time-domain sequences, the amplitude (modulus) of the complex values ​​at each time-domain sampling point is calculated one by one. The amplitude information that represents the signal propagation intensity is retained, while the phase information is discarded. Finally, time-domain channel impulse response data with time delay as the index and signal amplitude as the value is formed.

[0040] In steps S3 and S4, there is another embodiment: to obtain a more accurate ToA estimate in the time domain, an L-fold oversampling IFFT method is employed. The core of this method lies in padding the frequency domain channel estimate before performing the IFFT, thereby effectively increasing the sampling rate.

[0041] After completing the above piecewise filtering and interpolation process, the system obtains a length of The full-frequency domain vector. Then, this vector is subjected to (L−1)× The zero-value padding operation expands it into a length L× The new sequence. The zero-padding position is located in the middle of the frequency domain to maintain conjugate symmetry.

[0042] The oversampling process is represented as follows: Among them, L and These are the oversampling factor and the number of IFFT points, respectively. Let be the number of points in the Fourier transform.

[0043] Subsequently, the extended frequency domain sequence Execute L× Point IFFT operation yields the time-domain channel impulse response. At this point, the time-domain sampling interval is reduced from the original T_s=1 / f_s to 1 / (L * f_s), and the equivalent sampling rate is increased by a factor of L.

[0044] The IFFT transformation process is represented as follows: in, It is a time-domain sequence.

[0045] By zero-padding in the frequency domain and performing an L-fold IFFT, the sampling density in the time domain can be effectively increased without increasing the actual physical sampling rate and hardware cost, thereby improving the accuracy of TOA estimation.

[0046] The peak search processing of the time-domain channel impulse response data is performed using peak detection technology, and the resulting time of arrival data is input into the positioning system for processing to obtain the TDOA positioning result. This includes: performing peak search processing of the time-domain channel impulse response data using peak detection technology to obtain the time of arrival data; and processing the time of arrival data using TDOA calculation technology in the positioning system to obtain the TDOA positioning result.

[0047] Taking the time-domain channel impulse response data after amplitude calculation as the object, a reasonable detection threshold (such as dynamic noise threshold or fixed threshold) is first set based on the noise level in the data. Then, the time-domain data is scanned point by point along the time delay axis to filter out signal points that exceed the threshold and meet the peak characteristics (such as local maximum value, slope change conforming to the signal rise and fall law). The main path signal peak and multipath interference peak are further distinguished. The time delay index corresponding to the main path peak is determined as the real time of signal arrival at the current base station. Finally, the arrival time data corresponding to each base station is output.

[0048] The positioning system first collects arrival time data from multiple base stations, calculates the time difference between the arrival of the terminal signal at different base stations, and then combines the known precise location coordinates of each base station with the preset TDOA positioning mathematical model (such as the hyperbolic positioning model). Multiple hyperbolic constraint equations are constructed through multiple sets of time differences, and the spatial location coordinates of the terminal are obtained by solving the equation system. Finally, the solution results are calibrated for error and verified for rationality, and the final TDOA positioning result is output.

[0049] Another embodiment of the present invention provides a TDOA positioning system; for details, please refer to [link to relevant documentation]. Figure 2 , Figure 2 The diagram shown is a structural schematic of a TDOA positioning system according to one embodiment of the present invention. The system includes: Estimation module 11 is used to perform channel estimation processing on uplink sounding reference signal data received by several base stations to obtain discrete channel response data; Interpolation module 12 is used to interpolate the discrete channel response data using position-adaptive segmented filtering interpolation technology to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technology dynamically selects the filtering vector based on the subcarrier position. The oversampling module 13 is used to perform frequency domain oversampling processing on the frequency domain channel vector to obtain an oversampled frequency domain vector; The conversion module 14 is used to perform time-domain conversion processing on the oversampled frequency domain vector based on the fast Fourier transform technique to obtain time-domain channel impulse response data; Processing module 15 is used to perform peak search processing on the time-domain channel impulse response data using peak detection technology, input the obtained arrival time data into the positioning system for processing, and obtain TDOA positioning results.

[0050] See Figure 3 This is a schematic diagram of the structure of a TDOA positioning device provided in an embodiment of the present invention. The TDOA positioning device provided in this embodiment includes a processor 21, a memory 22, and a computer program stored in the memory 22 and configured to be executed by the processor 21. When the processor 21 executes the computer program, it implements the steps described in the above-described TDOA positioning method embodiment, for example... Figure 1 The steps S1 to S5 described above; or, when the processor 21 executes the computer program, it implements the functions of each module in the above system embodiments, such as the estimation module 11.

[0051] For example, the computer program can be divided into one or more modules, which are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the TDOA positioning device. For example, the computer program can be divided into an estimation module 11, an interpolation module 12, an oversampling module 13, etc., with the specific functions of each module as follows: Estimation module 11 is used to perform channel estimation processing on uplink sounding reference signal data received by several base stations to obtain discrete channel response data; Interpolation module 12 is used to interpolate the discrete channel response data using position-adaptive segmented filtering interpolation technology to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technology dynamically selects the filtering vector based on the subcarrier position. The oversampling module 13 is used to perform frequency domain oversampling processing on the frequency domain channel vector to obtain an oversampled frequency domain vector; The conversion module 14 is used to perform time-domain conversion processing on the oversampled frequency domain vector based on the fast Fourier transform technique to obtain time-domain channel impulse response data; Processing module 15 is used to perform peak search processing on the time-domain channel impulse response data using peak detection technology, input the obtained arrival time data into the positioning system for processing, and obtain TDOA positioning results.

[0052] The TDOA positioning device may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will understand that the schematic diagram is merely an example of a TDOA positioning device and does not constitute a limitation on the TDOA positioning device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the TDOA positioning device may also include input / output devices, network access devices, buses, etc.

[0053] The processor 21 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 21 is the control center of the TDOA positioning device, connecting all parts of the TDOA positioning device via various interfaces and lines.

[0054] The memory 22 can be used to store the computer programs and / or modules. The processor 21 implements various functions of the TDOA positioning device by running or executing the computer programs and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0055] If the modules integrated into the TDOA positioning device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in 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. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0056] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0057] Accordingly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform steps in the TDOA positioning method of the above embodiments, for example... Figure 1 Steps S1 to S5 as described above.

[0058] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A TDOA positioning method, applied to a positioning system comprising at least a plurality of base stations, characterized in that, include: Channel estimation processing is performed on the uplink sounding reference signal data received by several base stations to obtain discrete channel response data; The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position. The frequency domain channel vector is subjected to frequency domain oversampling processing to obtain an oversampled frequency domain vector; Based on the Fast Fourier Transform technique, the oversampled frequency domain vector is transformed into time domain data to obtain time-domain channel impulse response data. Peak detection technology is used to perform peak search processing on the time-domain channel impulse response data, and the obtained arrival time data is input into the positioning system for processing to obtain the TDOA positioning result.

2. The TDOA positioning method as described in claim 1, characterized in that, The process of performing channel estimation on the uplink sounding reference signal data received by the plurality of base stations to obtain discrete channel response data includes: Channel estimation processing is performed on the uplink detection reference signal data to obtain subcarrier channel estimation values; The subcarrier channel estimate is processed using frequency domain discretization techniques to obtain the discrete channel response data.

3. The TDOA positioning method as described in claim 1, characterized in that, The step of interpolating the discrete channel response data using position-adaptive piecewise filtering interpolation technology to obtain a frequency domain channel vector includes: The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain the interpolated frequency domain channel data. The interpolated frequency domain channel data is integrated to obtain the frequency domain channel vector.

4. The TDOA positioning method as described in claim 1, characterized in that, The method based on Fast Fourier Transform (FFT) performs time-domain transformation on the oversampled frequency domain vector to obtain time-domain channel impulse response data, including: The oversampled frequency domain vector is transformed into a complex time domain sequence using the Fast Fourier Transform technique. The complex time-domain sequence is processed by amplitude calculation to obtain the time-domain channel impulse response data.

5. The TDOA positioning method as described in claim 1, characterized in that, The peak search processing of the time-domain channel impulse response data using peak detection technology, followed by inputting the obtained time-of-arrival data into the positioning system for processing, yields the TDOA positioning result, including: The arrival time data is obtained by performing peak search processing on the time-domain channel impulse response data using peak detection technology. The arrival time data is processed using the TDOA calculation technology in the positioning system to obtain the TDOA positioning result.

6. A TDOA positioning system, characterized in that, include: The estimation module is used to perform channel estimation processing on the uplink sounding reference signal data received by the base stations to obtain discrete channel response data; An interpolation module is used to interpolate the discrete channel response data using a position-adaptive segmented filtering interpolation technique to obtain a frequency domain channel vector, wherein the position-adaptive segmented filtering interpolation technique dynamically selects the filtering vector based on the subcarrier position. An oversampling module is used to perform frequency domain oversampling processing on the frequency domain channel vector to obtain an oversampled frequency domain vector; The conversion module is used to perform time-domain conversion processing on the oversampled frequency domain vector based on the fast Fourier transform technique to obtain time-domain channel impulse response data; The processing module is used to perform peak search processing on the time-domain channel impulse response data using peak detection technology, input the obtained arrival time data into the positioning system for processing, and obtain the TDOA positioning result.

7. The TDOA positioning system as described in claim 6, characterized in that, The process of performing channel estimation on the uplink sounding reference signal data received by the plurality of base stations to obtain discrete channel response data includes: Channel estimation processing is performed on the uplink detection reference signal data to obtain subcarrier channel estimation values; The subcarrier channel estimate is processed using frequency domain discretization techniques to obtain the discrete channel response data.

8. The TDOA positioning system as described in claim 6, characterized in that, The step of interpolating the discrete channel response data using position-adaptive piecewise filtering interpolation technology to obtain a frequency domain channel vector includes: The discrete channel response data is interpolated using a position-adaptive segmented filtering interpolation technique to obtain the interpolated frequency domain channel data. The interpolated frequency domain channel data is integrated to obtain the frequency domain channel vector.

9. The TDOA positioning system as described in claim 6, characterized in that, The method based on Fast Fourier Transform (FFT) performs time-domain transformation on the oversampled frequency domain vector to obtain time-domain channel impulse response data, including: The oversampled frequency domain vector is transformed into a complex time domain sequence using the Fast Fourier Transform technique. The complex time-domain sequence is processed by amplitude calculation to obtain the time-domain channel impulse response data.

10. The TDOA positioning system as described in claim 6, characterized in that, The peak search processing of the time-domain channel impulse response data using peak detection technology, followed by inputting the obtained time-of-arrival data into the positioning system for processing, yields the TDOA positioning result, including: The arrival time data is obtained by performing peak search processing on the time-domain channel impulse response data using peak detection technology. The arrival time data is processed using the TDOA calculation technology in the positioning system to obtain the TDOA positioning result.

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