A wireless positioning method for communication and perception integration

Abstract

The application discloses a wireless positioning method for communication and sensing integration, which comprises the following steps: a user equipment transmits a 5G NR signal to a base station; the base station estimates a channel state information matrix of a received signal by using a pilot carried in the transmitted signal; then, the base station estimates a DOA and an FTO of the received signal by using a MUSIC method; the base station takes the minimum FTO as a LOS path according to the estimated DOA and FTO; the base station suppresses signals of other directions of arrival by using a beam forming algorithm, calculates power of a signal in a LOS direction, and estimates a TOA according to the power and a path loss model, so as to perform rough positioning. The base station directs to transmit a sensing signal by using a beam forming technology according to the estimated DOA, receives an echo in a time window of the estimated rough TOA, and finally performs accurate time estimation and positioning by using the echo signal.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of communication sensing and wireless positioning, and particularly relates to a single base station TOA and DOA joint parameter estimation based on a 5G NR signal and a high-precision positioning technology assisted by a sensing signal probe. BACKGROUND

[0002] Existing TOA estimation mainly includes methods of using time stamp information interaction between a user mobile phone and a base station, and using phase differences caused by transmission time delay of different subcarriers. However, the method of using time stamp information needs strict synchronization between the user mobile phone and the base station, and is affected by processing delay; and the method of using phase differences caused by transmission time delay of different subcarriers has low estimation accuracy and is affected by different initial phases of carriers, and cannot meet actual application scenarios.

[0003] With the commercialization of 5G NR technology, the antenna scale is greatly increased, so the estimation accuracy of DOA is greatly improved, which is beneficial to the resolution of the arrival angle of the transmitted signal arriving at the base station through multiple paths; and large-scale multiple-input multiple-output provides conditions for the application of beamforming technology, which is beneficial to the estimation of TOA.

[0004] In addition, the communication and sensing system has great differences in duplex capability, frequency offset, phase noise, nonlinearity and other index requirements of radio frequency channels due to differences in system functions and specifications. Therefore, the system needs to balance the communication and sensing requirements, such as full duplex performance, at the beginning of design. SUMMARY

[0005] Technical problem: The purpose of the application is to solve the problems existing in the prior art, and to provide a wireless positioning method for communication and sensing integration. The positioning technology for communication and sensing integration can better solve the full duplex capability of the communication and sensing system, and can realize TOA estimation by using multi-antenna and beamforming technology.

[0006] Technical scheme: In order to achieve the above purpose, a wireless positioning method for communication and sensing integration adopted by the application includes the following steps:

[0007] Step 1: a user transmits a 5G NR signal to a base station;

[0008] Step 2: the base station estimates the channel state information matrix of the received signal, smooths the channel state information matrix, and then estimates the direction of arrival DOA and fractional symbol timing offset FTO of the received signal by using the multiple signal classification MUSIC method;

[0009] Step 3: The base station uses the DOA and FTO obtained in step 2 to take the FTO with the smallest FTO as the line-of-sight (LOS) path, uses beamforming to suppress signals from other directions of arrival, and calculates the power of the signal from the LOS direction;

[0010] Step 4: The base station estimates the rough time of arrival (TOA) according to the power of the signal from the LOS direction and different path loss models established for different scenarios.

[0011] Step 5: The base station uses beamforming to direct the transmission of a sensing signal according to the estimated DOA, receives echoes in a time window estimated for the rough TOA, and estimates the accurate TOA and position according to the time stamp and the time of detection of the sensing signal.

[0012] Step 6: The base station continuously adjusts the time window to perform real-time sensing and positioning according to the moving speed of the user.

[0013] Wherein:

[0014] In step 2, the step of estimating the DOA and FTO of the received signal using the channel state information matrix specifically includes: smoothing the channel state information matrix, i.e., selecting a matrix window on the channel state information matrix, taking the elements in the matrix window as a column of a new matrix, and sliding the matrix window from left to right and from top to bottom to obtain a new matrix to increase the number of snapshots and improve the resolution, and then using the MUSIC algorithm based on the orthogonality of the signal subspace and the noise subspace to divide the space to estimate the DOA and FTO of the signal.

[0015] The beamforming algorithm in step 3 uses the DOA of the LOS path obtained in step 2 as the expected signal direction as the constraint direction of the base station receiving beam to suppress the power of signals from other directions of arrival and keep the power of the LOS path signal unchanged; using the MVDR method, the "zero condition" of the beam is used to force the "zero point" of the receiving array beam pattern to point to all interference signal directions to obtain a constraint formula for the weight vector and calculate the weights of the base station antennas to combine the baseband signals received by each antenna, but it is not limited to the MVDR method. Any algorithm that can keep the power of the LOS path signal unchanged and suppress the power of signals from other directions can be used.

[0016] The path loss model in step 4 uses a log-distance path loss model that modifies the free space path loss model by introducing a path loss exponent n that changes with the environment.

[0017] In step 5, the base station can continue to provide communication or sensing services for other users after transmitting the sensing signal, and only needs to suspend the service in the time window estimated for the rough TOA and start the echo reception mode.

[0018] The sensing signal transmitted by the base station in step 5 is an OFDM signal or a radar signal.

[0019] Advantages: Compared with the prior art, the present application has the following advantages:

[0020] 1. The present application can realize TOA estimation by using multi-antenna and beamforming technology.

[0021] 2. The present application does not need strict time synchronization between user equipment and base station when performing TOA estimation.

[0022] 3. The present application can solve the duplex capability limitation of the communication and sensing system, and can still provide communication or sensing service for other users after transmitting sensing detection signal for a certain user, and only needs to suspend the service for a short time window of echo reception.

[0023] 4. The sensing signal of the present application is not limited to OFDM (Orthogonal Frequency Division Multiplexing) signal or radar signal, but can also be other forms of signals. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The scene area layout in embodiment one;

[0025] Figure 2 The schematic diagram of receiving signal of the uniform linear antenna array in embodiment one;

[0026] Figure 3 The simulation result diagram of MVDR beamforming algorithm in embodiment one;

[0027] Figure 4 The CDF diagram of TOA error of LOS path in embodiment one;

[0028] Figure 5 The echo reception time window diagram under the base station communication and sensing system in embodiment one. DETAILED DESCRIPTION

[0029] The present application will be further illustrated below in conjunction with the drawings and specific embodiments, and it should be understood that these examples are only used to illustrate the present application and not to limit the scope of the present application, and after reading the present application, those skilled in the art can make various equivalent modifications of the present application, which all fall within the scope defined by the appended claims.

[0030] The application provides a positioning method of communication and perception integration. A base station receives a 5G NR signal from a user, estimates a channel state information matrix, and estimates a DOA and an FTO by using a MUSIC algorithm. Then, the base station calculates a signal power of a LOS path by using beam forming, and estimates a TOA according to a logarithmic distance path loss model. The base station transmits a perception signal, receives an echo in a time window of the estimated rough TOA, estimates an accurate TOA and a position according to a time stamp and a perception signal detection time, and continuously adjusts and changes the time window according to a moving speed of the user to realize real-time perception positioning.

[0031] The wireless positioning method comprises the following steps:

[0032] Step 1: a user transmits a 5G NR signal to a base station.

[0033] Step 2: the base station estimates a channel state information matrix of a received signal, smoothes the channel state information matrix, and estimates a DOA and an FTO of the received signal by using a MUSIC method. Specifically, the channel state information matrix is smoothed, that is, a matrix window is selected on the channel state information matrix, elements in the matrix window are taken as a column of a new matrix, the matrix window is slid from left to right and from top to bottom to obtain the new matrix, so that the number of snapshots is increased and the resolution is improved, and then the MUSIC algorithm is used to estimate the DOA and the FTO of the signal based on the orthogonality of a signal subspace and a noise subspace.

[0034] Step 3: the base station takes the minimum FTO as a LOS path according to the DOA and the FTO obtained in step 2, suppresses signals of other directions of arrival by using a beam forming method, and calculates a power of a signal in the LOS direction. Specifically, the DOA of the LOS path obtained in step 2 is taken as an expected signal direction, which is used as a constraint direction of a receiving beam of the base station, so that the power of the signal in the LOS direction is kept unchanged and the powers of signals in other directions are suppressed. An MVDR method is used to force a “zero point” of a beam pattern of a receiving array to point to all directions of interference signals to obtain a constraint formula of a weight vector and calculate weights of antennas of the base station to combine baseband signals received by the antennas, but the method is not limited to the MVDR method, and any algorithm that can keep the power of the signal in the LOS direction unchanged and suppress the powers of signals in other directions can be used.

[0035] Step 4: the base station estimates a rough TOA according to a LOS direction signal power and different path loss models in different scenes. The path loss model is a logarithmic distance path loss model that is modified by introducing a path loss index n that changes with an environment to correct a free space path loss model.

[0036] Step 5: The base station uses beamforming technology to direct the transmission of the sensing signal according to the estimated DOA, and receives echoes in the time window of the estimated rough TOA, and estimates the accurate TOA and position according to the time stamp and sensing signal detection time. The base station can continue to provide communication or sensing services for other users after transmitting the sensing signal, and only needs to suspend the service and start the echo receiving mode in the time window of the estimated rough TOA. The sensing signal transmitted by the base station is an OFDM signal or a radar signal.

[0037] Step 6: The base station continuously adjusts and changes the time window for real-time sensing and positioning according to the moving speed of the user.

[0038] The method of the present application is specifically described based on the following examples.

[0039] Example 1:

[0040] In this embodiment, considering the case of multipath, the base station is configured with M antennas. The channel state information estimated by the base station can be represented as:

[0041]

[0042] where m represents the mth antenna, n represents the nth subcarrier, p represents the pth path, α p represents the channel attenuation of the pth path, f c represents the carrier frequency, τ p represents the TOA of the pth path, d represents the distance between adjacent antennas, θ p represents the DOA of the pth path, c represents the speed of light, Δf represents the subcarrier spacing, and Δ p represents the FTO of the pth path. Combined with multiple receiving antennas and multiple carriers, the channel state information matrix is defined as:

[0043]

[0044] where N is the number of subcarriers, H m,n represents the channel state information value corresponding to the mth antenna and the nth subcarrier.

[0045] In order to improve the estimation resolution of DOA and FTO, the channel state information matrix needs to be smoothed, and then θ p and Δ p are estimated according to the MUSIC algorithm. The θ p corresponding to the smallest Δ p is taken as the arrival direction of the LOS path.

[0046] The application has the characteristics that after the direction of arrival of the LOS path signal is estimated, the beam forming using the multi-antenna technology can extract the LOS path signal. The signals of multiple antennas are combined according to the beam forming, and the power of the combined signal is calculated, which is the power of the direct path signal. In this way, the path loss model can be well used without the influence of multipath fading, and the distance between the user equipment and the base station is calculated according to the power.

[0047] Another feature of the application is that the beam forming technology does not change the power of the LOS path signal, but only suppresses the power of other path signals.

[0048] A larger feature of the application is that the full duplex capability of the communication and sensing system can be well solved. After the direction and distance of the user equipment are obtained, the sensing signal is directed to the user equipment according to the beam forming technology, and during this period, communication or sensing services can still be provided for other users. According to the above power, the distance between the user equipment and the base station is calculated to determine a echo receiving window. During the time window, the service for other users is suspended for echo reception, and the accurate time of flight is estimated through the transmission and reception time of the sensing probe signal, so as to perform accurate positioning.

[0049] (1) The scene is an indoor environment of 20m x 10m, the user equipment transmits a 5G NR signal with a subcarrier spacing of 15 kHz, a bandwidth of 10 MHz for one time slot, and a carrier frequency of 5 GHz.

[0050] (2) It is assumed that 1 LOS path, 3 to 5 NLOS paths are generated each time, and the signal-to-noise ratio of the indoor environment is 20 dB.

[0051] (3) The base station receiving end is configured with 24 antennas to receive signals, the normalized carrier frequency deviation is 0.3, and the DOA and FTO are estimated using the MUSIC algorithm. The path with the smallest FTO is taken as the LOS path.

[0052] (4) The base station uses the MVDR algorithm for beam forming, and calculates the TOA according to the logarithmic distance path loss model.

[0053] (5) 5000 Monte Carlo experiments are performed on this embodiment, and the error CDF graph of the TOA of the LOS path is as shown in Figure 4

[0054] (6) The base station uses the beam forming technology to direct the sensing signal beam to the user equipment and transmit, and can continue to provide communication or sensing services before the echo receiving window arrives. When the echo receiving window arrives, echo reception is performed and the accurate signal time of flight is estimated for positioning.

[0055] ​(7) The base station continuously adjusts the change time window according to the moving speed of the user to realize real-time perception positioning.

[0056] The above merely describes the preferred embodiments of the present application, and it should be pointed out that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A wireless positioning method for communication and sensing integration, characterized in that, The wireless positioning method comprises the following steps: Step 1: the user transmits a 5G NR signal to the base station; Step 2: the base station estimates the channel state information matrix of the received signal, smoothes the channel state information matrix, and then estimates the DOA and FTO of the received signal by using the MUSIC method; Step 3: the base station takes the minimum FTO as the LOS path, uses the beam forming method to suppress the signals of other directions, and calculates the power of the LOS direction signal according to the DOA and FTO obtained in step 2; Step 4: the base station estimates the rough TOA according to the LOS direction signal power and different path loss models of different scenes; Step 5: the base station uses the beam forming technology to guide the transmission of the sensing signal according to the estimated DOA, receives the echo in the time window of the estimated rough TOA, and estimates the accurate TOA and position according to the time stamp and sensing signal detection time; Step 6: the base station continuously adjusts and changes the time window to realize real-time sensing positioning according to the moving speed of the user; In step 2, the steps of estimating the DOA and FTO of the received signal by using the channel state information matrix comprise the following steps: smoothing the channel state information matrix, i.e. selecting a matrix window on the channel state information matrix, taking the elements in the matrix window as a column of a new matrix, sliding the matrix window from left to right and from top to bottom to obtain a new matrix, increasing the number of snapshots, and improving the resolution, and then using the MUSIC algorithm to estimate the DOA and FTO of the signal based on the orthogonality of the signal subspace and the noise subspace; The beam forming algorithm in step 3 uses the DOA of the LOS path obtained in step 2 as the expected signal direction, uses it as the constraint direction of the base station receiving beam, suppresses the power of the signals of other directions, and keeps the power of the LOS path signal unchanged; uses the MVDR method to force the "zero point" of the receiving array beam pattern to point to all interference signal directions to obtain the constraint formula of the weight vector and calculate the weight of each antenna of the base station to combine the baseband signals received by each antenna, but it is not limited to the MVDR method, and any algorithm that can keep the power of the LOS path signal unchanged and suppress the power of the signals of other directions can be used; In step 5, the base station can continue to provide communication or sensing services for other users after transmitting the sensing signal, and only needs to suspend the service in the time window of the estimated rough TOA and start the echo receiving mode. The path loss model in step 4 uses a log-distance path loss model that corrects the free space path loss model by introducing a path loss exponent that varies with the environment n ​ In step 5, the sensing signal transmitted by the base station is an OFDM signal or a radar signal.

2. The communication-aware integrated oriented wireless positioning method according to claim 1, characterized in that: ​

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