5G scene non-line-of-sight positioning method based on error compensation

Abstract

The invention provides a 5G scene non-line-of-sight positioning method based on error compensation, and the method comprises the steps: S1, obtaining a communication parameter of a base station, the communication parameter at least comprising channel state information (CSI); s2, measuring channel communication parameters based on the CSI, wherein the channel communication parameters at least comprise time of arrival (TOA) and received signal strength (RSS); s3, performing positioning calculation based on the channel communication parameters, and iteratively calculating a non-line-of-sight error; s4, if the positioning calculation result meets a first preset condition, outputting the positioning calculation result; otherwise, repeating the step S3. The non-line-of-sight positioning method provided by the invention is low in calculation complexity, smaller in error and high in positioning precision.

Description

Technical Field

[0001] The present invention belongs to the field of positioning, and in particular relates to a 5G scenario non-line-of-sight positioning method based on error compensation. Background Art

[0002] Among the existing positioning technologies, UWB, Wi-Fi and Bluetooth all have different advantages. For example, UWB positioning has high accuracy and strong anti-interference ability; WiFi positioning has a wide coverage range and is not limited by GPS signals; Bluetooth positioning has low cost and is conducive to large-scale promotion. However, due to the complexity of the indoor environment, it is still challenging to achieve high-precision, effective, reliable and real-time positioning solutions. Among them, 5G positioning technology has shown significant advantages with its innovative features, such as ultra-dense network deployment, diversified access solutions, and flexible architecture based on SDN. These advances have effectively improved the accuracy and reliability of positioning and can provide end users with seamless high-precision indoor positioning services.

[0003] At present, 5G positioning technology still faces many challenges in achieving high-precision indoor positioning. Due to the limitations of 5G indoor equipment, it is difficult to obtain AOA information. In terms of obtaining key positioning parameters such as TOA and RSS, the existing channel parameter estimation methods are also insufficient. Figure 1 As shown in Figure 1, in complex indoor environments, the signal propagation path is significantly affected by reflection, scattering, and attenuation, which further increases the difficulty of channel modeling and parameter extraction. In addition, obstacle occlusion will lead to the frequent occurrence of NLOS phenomenon, which seriously interferes with the accuracy of the signal propagation path and the reliability of the measurement results, thereby reducing the overall positioning accuracy.

[0004] Based on the above, this application provides a technical solution to solve the above technical problems. Summary of the invention

[0005] In view of the large positioning error and low precision in the 5G non-line-of-sight scenario in the prior art, the present invention provides a 5G scenario non-line-of-sight positioning method based on error compensation, comprising the following steps: Step S1, obtaining communication parameters of a 5G base station, wherein the communication parameters at least include channel state information CSI; Step S2: measuring channel communication parameters based on the CSI, where the channel communication parameters at least include arrival time TOA and received signal strength RSS; Step S3, performing positioning solution based on the channel communication parameters, and iteratively calculating the non-line-of-sight error; Step S4: If the positioning solution result meets the first preset condition, output the positioning solution result; otherwise, repeat step S3.

[0006] In a specific embodiment of the present invention, step S3 includes: Step S3.1, establishing a TOA-RSS joint model; Step S3.2, calculating the joint likelihood function of the TOA and the RSS; Step S3.3, calculating the positioning result based on the linear least squares rough positioning solution algorithm and the nonlinear least squares positioning solution algorithm; Step S3.4, iteratively update the non-line-of-sight error.

[0007] In a specific embodiment of the present invention, step S1 includes: No. The channel frequency response of subcarriers is: , in, is the total number of propagation paths, is the imaginary unit, and Respectively represent The complex gain and TOA of each path, is the additive white Gaussian noise in the measurement process, For the The subcarrier frequency, , is the carrier frequency, is the subcarrier spacing, , is the total number of subcarriers, It is the Doppler frequency shift caused by the relative motion between the terminal and the base station BS.

[0008] In a specific embodiment of the present invention, step S2 includes: The superimposed signal received Minus the The estimated data of all paths except the first path are obtained. Complete data for each path : , in, , indicating the The parameter value of the strip diameter, Indicates Parameter estimates for each path; Based on the likelihood function, we get path parameters, the objective function is: , , Among them, the function represents the loss function, represents minimization, Indicates Estimated data for each path, , express The square norm of represents the conjugate transpose operation, represents real number operation, Indicates Parameter estimates for the bar diameter.

[0009] In a specific embodiment of the present invention, step S2 further includes updating communication parameters: , , , in, Indicates the updated TOA of the strip diameter; Indicates the updated Complex gain of the strip diameter; Represents the updated Doppler shift.

[0010] In a specific embodiment of the present invention, step S3.1 comprises: Assume that there is a RRUs, the RSS of the bth RRU is expressed as: , No. The TOA of an RRU is expressed as: , in, , and Respectively represent The complex gain and TOA of the strongest path of each RRU, represents the speed of light, and Respectively represent the unknown location of the terminal and the The known locations of the RRUs, is the reference distance RSS at and represents the power error and distance error of NLOS propagation, represents the path loss exponent, represents the lognormal shadow term, The mean is 0 and the variance is A Gaussian random variable, is the distance measurement noise, Modeled as having a mean of 0 and a variance of A Gaussian random variable, To obtain the Euclidean norm, Indicates b The RSS received by each RRU.

[0011] In a specific embodiment of the present invention, step S3.2 includes: The RSS is: , When t approaches 0, the first-order Taylor expansion is applied, ,get , Combined with TOA, you can get: , , in, ; make , , The joint likelihood function is: , , is the correlation coefficient matrix of TOA and RSS.

[0012] In a specific embodiment of the present invention, the linear least squares rough positioning solution algorithm is: , , , in, represents the estimated terminal position; Nonlinear least squares The iterative solution algorithm is: , , in, Indicates The result of the iterative solution.

[0013] In a specific embodiment of the present invention, step S3.4 includes: The NLOS errors of RSS and TOA are updated as: , , and They represent the power error estimate and distance error estimate of NLOS propagation respectively.

[0014] In a specific implementation of the present invention, the first preset condition includes: the difference between the distances of the previous and next solution results is less than a preset threshold or the number of iterations reaches a maximum number of iterations.

[0015] The present invention can bring at least one of the following beneficial effects: The present invention proposes a non-line-of-sight positioning method for 5G scenarios, measures TOA and RSS based on the communication parameters of the 5G base station, performs least squares positioning solution, iteratively calculates the non-line-of-sight error, and finally determines the positioning solution result based on multiple iterations. Specifically, in terms of the measurement and acquisition of TOA and RSS, the present invention divides and updates the multipath parameters one by one, and estimates the multipath channel parameters of TOA and RSS alternately; and the present invention considers the NLOS error of TOA and RSS and the correlation between TOA and RSS, and obtains a joint likelihood function; in addition, in solving the influence of the NLOS error of TOA and RSS information, the present invention combines linear and nonlinear least squares and adopts an alternating iterative estimation and compensation method. The non-line-of-sight positioning method proposed by the present invention is based on error compensation and least squares solution, has low computational complexity, stronger anti-interference ability, can effectively deal with the problem of signal propagation path deviation caused by obstacles in non-line-of-sight scenarios, has smaller positioning solution results, better positioning performance, and is more suitable for indoor positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The preferred implementation scheme will be described below in a clear and understandable manner with reference to the accompanying drawings to further illustrate the above-mentioned characteristics, technical features, advantages and their implementation methods.

[0017] Figure 1 Schematic diagram of signal propagation in indoor scenes; Figure 2 A schematic diagram of the steps of a 5G scenario non-line-of-sight positioning method based on error compensation proposed in an embodiment of the present invention; Figure 3 This is a schematic diagram comparing the cumulative distribution function of the positioning result error obtained by the positioning method proposed in the present invention and the positioning result error obtained by other positioning methods. DETAILED DESCRIPTION

[0018] Various aspects of the present invention are described in further detail below.

[0019] Unless otherwise defined or indicated, all professional and scientific terms used herein have the same meanings as those familiar to those skilled in the art. In addition, any methods and materials similar or equivalent to those described herein can be applied to the method of the present invention.

[0020] The following is an explanation of the terms.

[0021] Unless otherwise clearly specified and limited, the "or" mentioned in the present invention includes the relationship of "and". The "and" is equivalent to the Boolean logic operator "AND", the "or" is equivalent to the Boolean logic operator "OR", and "AND" is a subset of "OR".

[0022] It is to be understood that although the terms "first", "second", etc. may be used herein to describe different elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. Therefore, the first element may be referred to as the second element without departing from the teachings of the present invention.

[0023] In the present invention, the terms "comprising", "including" or "comprising" indicate that various components can be applied together in the mixture or composition of the present invention. Therefore, the term "consisting mainly of..." is included in the terms "comprising", "including" or "comprising".

[0024] Unless otherwise clearly specified and limited, the terms "connected", "connected" and "connection" in the present invention should be understood in a broad sense, for example, it can be a fixed connection, or it can be connected through an intermediary medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0025] For example, if an element (or component) is referred to as being on, coupled to, or connected to another element, the element may be directly formed on, coupled to, or connected to the other element, or there may be one or more intervening elements between them. In contrast, if the expressions "directly on," "directly coupled to," and "directly connected to" are used herein, then no intervening elements are indicated. Other words used to describe the relationship between elements should be similarly interpreted, such as "between" and "directly between," "attached" and "directly attached," "adjacent" and "directly adjacent," etc.

[0026] It should also be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to directions in the drawings. The words "inner" and "outer" used refer to directions toward or away from the geometric center of a particular component, respectively. It can be understood that these terms are used here to describe the relationship of one element, layer or region relative to another element, layer or region as shown in the drawings. In addition to the orientations described in the drawings, these terms should also include other orientations of the device.

[0027] Other aspects of the present invention will be apparent to those skilled in the art in view of the disclosure herein.

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings and other implementation methods can be obtained based on these drawings without creative work.

[0029] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. The drawings only show the components related to the present application and are not drawn according to the number, shape and size of the components in actual implementation. The type, quantity and proportion of each component in actual implementation may be changed arbitrarily, and the component layout may also be more complicated. For example, the thickness of the components in the drawings may be exaggerated for the sake of clarity.

[0030] Example

[0031] For the existing technology of 5G scenarios with large non-line-of-sight positioning errors and low accuracy, see Figure 2 The present invention provides a 5G scenario non-line-of-sight positioning method based on error compensation, comprising the following steps: Step S1, obtaining communication parameters of a 5G base station, wherein the communication parameters at least include channel state information CSI; Step S2: measuring channel communication parameters based on the CSI, where the channel communication parameters at least include arrival time TOA and received signal strength RSS; Step S3, performing positioning solution based on the channel communication parameters, and iteratively calculating the non-line-of-sight error; Step S4: If the positioning solution result meets the first preset condition, output the positioning solution result; otherwise, repeat step S3.

[0032] In a preferred embodiment of the present invention, step S1 comprises: No. The channel frequency response of subcarriers is: , in, is the total number of propagation paths, is the imaginary unit, and Respectively represent The complex gain and TOA of each path, is the additive white Gaussian noise in the measurement process, For the The subcarrier frequency, , is the carrier frequency, is the subcarrier spacing, , is the total number of subcarriers, It is the Doppler frequency shift caused by the relative motion between the terminal and the base station BS.

[0033] Preferably, step S2 comprises: The superimposed signal received Minus the The estimated data of all paths except the first path are obtained. Complete data for each path : , in, , indicating the The parameter value of the strip diameter, Indicates Parameter estimates for each path; Based on maximizing the likelihood function, we get path parameters, the objective function is: , , Among them, the function represents the loss function, represents minimization, Indicates Estimated data for each path, , express The square norm of represents the conjugate transpose, represents real number operation, Indicates Parameter estimates for the bar diameter.

[0034] Specifically, step S2 also includes updating communication parameters: , , , in, Indicates the updated TOA of the strip diameter; Indicates the updated Complex gain of the strip diameter; Represents the updated Doppler shift.

[0035] In a preferred embodiment, step S3 includes: Step S3.1, establishing a TOA-RSS joint model; Step S3.2, calculating the joint likelihood function of the TOA and the RSS; Step S3.3, calculating the positioning result based on the linear least squares rough positioning solution algorithm and the nonlinear least squares positioning solution algorithm; Step S3.4, iteratively update the non-line-of-sight error.

[0036] Wherein, the step S3.1 comprises: Assume that there is a RRU, The RSS of an RRU is expressed as: , No. The TOA of an RRU is expressed as: , in, , and Respectively represent The complex gain and TOA of the strongest path of each RRU, represents the speed of light, and Respectively represent the unknown location of the terminal and the The known locations of the RRUs, is the reference distance RSS at and represents the power error and distance error of NLOS propagation, represents the path loss exponent, represents the lognormal shadow term, The mean is 0 and the variance is A Gaussian random variable, is the distance measurement noise, Modeled as having a mean of 0 and a variance of A Gaussian random variable, To obtain the Euclidean norm, Indicates The RSS received by each RRU.

[0037] In a preferred embodiment of the present invention, step S3.2 comprises: The RSS is: , When t approaches 0, especially when t < 0.1, the first-order Taylor expansion is applied. ,get: , Combined with TOA, you can get: , , in, ; make , , The joint likelihood function is: , , is the correlation coefficient matrix of TOA and RSS.

[0038] The linear least squares rough positioning solution algorithm described in step S3.3 is: , , , in, represents the estimated terminal position; The nonlinear least squares method described in step S3.3 The iterative solution algorithm includes: , , in, Indicates The result of the iterative solution.

[0039] Preferably, step S3.4 comprises: The NLOS errors of RSS and TOA are updated as: , , and They represent the power error estimate and distance error estimate of NLOS propagation respectively.

[0040] In a preferred embodiment of the present invention, the first preset condition includes: the difference between the distances of the previous and next solution results is less than a preset threshold or the number of iterations reaches a maximum number of iterations. Preferably, the preset threshold is 0.01 m and the maximum number of iterations is 100 times.

[0041] Figure 3 A schematic diagram showing a comparison of the cumulative error distribution function of the 5G scenario non-line-of-sight positioning method based on error compensation provided by the present invention and other positioning methods is shown. Figure 3 It can be seen intuitively that the positioning error of the 5G scenario non-line-of-sight positioning method based on error compensation proposed in the present invention is significantly smaller than that of other positioning methods, and can perform better in non-line-of-sight environments.

[0042] In summary, the present invention has achieved the following effects: The present invention proposes a non-line-of-sight positioning method for 5G scenarios, which measures TOA and RSS based on the communication parameters of the 5G base station, performs least squares positioning solution, iteratively calculates the non-line-of-sight error, and finally determines the positioning solution result based on multiple iterations. The non-line-of-sight positioning method proposed in the present invention is based on error compensation and least squares solution, with low computational complexity and stronger anti-interference ability of positioning calculation. It can effectively deal with the problem of signal propagation path deviation caused by obstacles in non-line-of-sight scenarios, and the positioning solution result has smaller error, better positioning performance, and is more suitable for indoor positioning.

[0043] Based on this application, it should be understood by those skilled in the art that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspect described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0044] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0045] It should be noted that the above embodiments can be freely combined as needed. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention.

[0046] All documents mentioned in the present invention are cited as references in this application, just as each document is cited as reference separately. In addition, it should be understood that after reading the above content of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the claims attached to this application.

Claims

1. A 5G scenario non-line-of-sight positioning method based on error compensation, characterized in that: The following steps are involved: Step S1: Acquire the communication parameters of the 5G base station, wherein the communication parameters at least include the channel state information CSI, wherein The channel frequency response of subcarriers is: ， in, is the total number of propagation paths, is the imaginary unit, and Respectively represent The complex gain and TOA of each path, is the additive white Gaussian noise in the measurement process, For the The subcarrier frequency, , is the carrier frequency, is the subcarrier spacing, , is the total number of subcarriers, The Doppler frequency shift caused by the relative motion between the terminal and the base station BS; Step S2: measuring channel communication parameters based on the CSI, where the channel communication parameters include at least arrival time TOA and received signal strength RSS; Step S3, performing positioning solution based on the channel communication parameters, and iteratively calculating the non-line-of-sight error; Step S4: If the positioning solution result meets the first preset condition, output the positioning solution result; otherwise, repeat step S3.

2. According to a 5G scenario non-line-of-sight positioning method based on error compensation according to claim 1, it is characterized in that: The step S3 comprises: Step S3.1, establishing a TOA-RSS joint model; Step S3.2, calculating the joint likelihood function of the TOA and the RSS; Step S3.3, calculating the positioning result based on the linear least squares rough positioning solution algorithm and the nonlinear least squares positioning solution algorithm; Step S3.4, iteratively update the non-line-of-sight error.

3. According to a 5G scenario non-line-of-sight positioning method based on error compensation according to claim 2, it is characterized in that: Step S2 includes: The superimposed signal received Minus the The estimated data of all paths except the first path are obtained. Complete data for each path : ， in, , indicating the The parameter value of the strip diameter, Indicates The parameter estimates of the paths are obtained based on the likelihood function. path parameters, the objective function is: ， ， Among them, the function represents the loss function, represents minimization, Indicates Estimated data for each path, , express The square norm of represents the conjugate transpose operation, represents real number operation, Indicates Parameter estimates for the bar diameter.

4. According to the 5G scenario non-line-of-sight positioning method based on error compensation according to claim 3, it is characterized in that: Step S2 also includes updating the communication parameters: ， ， ， in, Indicates the updated TOA of the strip diameter; Indicates the updated Complex gain of the strip diameter; Represents the updated Doppler shift.

5. According to the 5G scenario non-line-of-sight positioning method based on error compensation according to claim 4, it is characterized in that: The step S3.1 comprises: Assume that there is a RRU, b The RSS of an RRU is expressed as: ， No. The TOA of an RRU is expressed as: ， in, , and Respectively represent The complex gain and TOA of the strongest path of each RRU, represents the speed of light, and Respectively represent the unknown location of the terminal and the The known locations of the RRUs, is the reference distance RSS at and represents the power error and distance error of NLOS propagation, represents the path loss exponent, represents the lognormal shadow term, The mean is 0 and the variance is A Gaussian random variable, is the distance measurement noise, Modeled as having a mean of 0 and a variance of A Gaussian random variable, To obtain the Euclidean norm, Indicates b The RSS received by each RRU.

6. A 5G scenario non-line-of-sight positioning method based on error compensation according to claim 5, characterized in that: The step S3.2 comprises: The RSS is: ， When t approaches 0, the first-order Taylor expansion is applied, ,get: ， Combined with TOA, you can get: ， ， in, ; make , , The joint likelihood function is: ， ， is the correlation coefficient matrix of TOA and RSS.

7. A 5G scenario non-line-of-sight positioning method based on error compensation according to claim 6, characterized in that: The linear least squares rough positioning solution algorithm is: ， ， ， in, represents the estimated terminal position; Nonlinear least squares The iterative solution algorithm includes: ， ， in, Indicates The result of the iterative solution.

8. The 5G scenario non-line-of-sight positioning method based on error compensation according to claim 7 is characterized in that: Step S3.4 includes: The NLOS errors of RSS and TOA are updated as: ， ， and They represent the power error estimate and distance error estimate of NLOS propagation respectively.

9. A 5G scenario non-line-of-sight positioning method based on error compensation according to any one of claims 1-8, characterized in that: The first preset condition includes: the difference between the distances of the previous and next solution results is less than a preset threshold or the number of iterations reaches a maximum number of iterations.

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