A 5G Scenario Non-Line-of-Sight Positioning Method Based on Error Compensation

Abstract

The present invention provides a 5G scenario non-line-of-sight positioning method based on error compensation, including: Step S1, obtaining communication parameters of a base station, where 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 time of arrival TOA and received signal strength RSS; Step S3, performing positioning calculation based on the channel communication parameters and iteratively calculating non-line-of-sight errors; Step S4, if the positioning calculation result meets a first preset condition, outputting the positioning calculation result; otherwise, repeating Step S3. The non-line-of-sight positioning method provided by the present invention has low computational complexity, smaller errors, and high positioning accuracy.

Description

Technical Field

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

[0002] In existing positioning technologies, positioning methods such as UWB, Wi-Fi, and Bluetooth all have different advantages. For example, UWB has high positioning accuracy and strong anti-interference ability; Wi-Fi positioning has a wide coverage area and is not restricted 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 a high-precision, effective, reliable, and real-time positioning solution. Among them, 5G positioning technology exhibits significant advantages with its innovative features, such as ultra-dense network deployment, diverse access schemes, and a flexible SDN-based architecture. These advancements effectively improve the accuracy and reliability of positioning and can provide seamless high-precision indoor positioning services for end-users.

[0003] Currently, 5G positioning technology still faces many challenges in achieving high-precision indoor positioning. Due to the limitations of 5G indoor devices, it is difficult to obtain AOA information. There are also deficiencies in existing channel parameter estimation methods for obtaining key positioning parameters such as TOA and RSS. As Figure 1 shown, in a complex indoor environment, the signal propagation path is significantly affected by reflection, scattering, and attenuation, further increasing the difficulty of channel modeling and parameter extraction. In addition, obstacle occlusion leads to the frequent occurrence of the NLOS phenomenon, seriously interfering with the accuracy of the signal propagation path and the reliability of the measurement results, thereby reducing the overall accuracy of positioning.

[0004] Based on the above, the present 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 accuracy 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, including the following steps:

[0006] Step S1, obtaining communication parameters of a 5G base station, where the communication parameters at least include channel state information CSI;

[0007] Step S2, measuring channel communication parameters based on the CSI, where the channel communication parameters at least include time of arrival TOA and received signal strength RSS;

[0008] Step S3, performing positioning calculation based on the channel communication parameters and iteratively calculating the non-line-of-sight error;

[0009] Step S4. If the positioning solution result meets the first preset condition, output the positioning solution result; otherwise, repeat Step S3.

[0010] In a specific embodiment of the present invention, Step S3 includes:

[0011] Step S3.1. Establish a TOA-RSS joint model;

[0012] Step S3.2. Calculate the joint likelihood function of the TOA and the RSS;

[0013] Step S3.3. Solve the positioning result based on the linear least squares rough positioning solution algorithm and the nonlinear least squares positioning solution algorithm;

[0014] Step S3.4. Iteratively update the NLOS error.

[0015] In a specific embodiment of the present invention, Step S1 includes:

[0016] The subcarrier channel frequency response is:

[0017] ,

[0018] where is the total number of propagation paths, is the imaginary unit, and respectively represent the complex gain and TOA of the th path, is the additive white Gaussian noise in the measurement process, is the frequency of the th subcarrier, , is the carrier frequency, is the subcarrier spacing, , is the total number of subcarriers, is the Doppler frequency shift caused by the relative movement between the terminal and the base station BS.

[0019] In a specific embodiment of the present invention, Step S2 includes:

[0020] Subtract the estimated data of all paths except the th path from the received superimposed signal to obtain the complete data of the th path :

[0021] ,

[0022] where , representing the parameter value of the th path, representing the parameter estimate of the th path;

[0023] Based on the likelihood function, the parameter of the th path is obtained, and the objective function is:

[0024] ,

[0025] ,

[0026] where the function represents the loss function, represents minimization, representing the th path's estimated data, , representing 's squared norm, representing the conjugate transpose operation, representing the operation of taking the real part, representing the parameter estimate of the th path.

[0027] In a specific embodiment of the present invention, step S2 further includes updating communication parameters:

[0028] ,

[0029] ,

[0030] ,

[0031] where represents the TOA of the th updated path; represents the complex gain of the th updated path; represents the updated Doppler frequency shift.

[0032] In a specific embodiment of the present invention, step S3.1 includes:

[0033] Assume there are RRUs in total, and the RSS of the bth RRU is expressed as:

[0034] ,

[0035] The th RRU's TOA is expressed as:

[0036] ,

[0037] Among them, , and respectively represent the complex gain and TOA of the strongest path of the -th RRU. represents the speed of light, and respectively represent the unknown location of the terminal and the known location of the -th RRU. is the RSS at the reference distance . and represent the power error and distance error of NLOS propagation, represents the path loss exponent, represents the log-normal shadowing term, is a Gaussian random variable with a mean of 0 and a variance of . is the distance measurement noise, modeled as a Gaussian random variable with a mean of 0 and a variance of . is to take the Euclidean norm, represents the RSS received by the b -th RRU.

[0038] In a specific embodiment of the present invention, the step S3.2 includes:

[0039] The RSS is:

[0040] ,

[0041] When t approaches 0, applying the first-order Taylor expansion, , obtaining

[0042] ,

[0043] Combined with TOA, it can be obtained:

[0044] ,

[0045] ,

[0046] Among them, ;

[0047] Let , ,

[0048] The joint likelihood function is:

[0049] ,

[0050] ,

[0051] is the correlation coefficient matrix of TOA and RSS.

[0052] In a specific embodiment of the present invention, the linear least squares rough positioning algorithm is as follows:

[0053] ,

[0054] ,

[0055] ,

[0056] where represents the estimated terminal position;

[0057] The non-linear least squares th iteration algorithm is as follows:

[0058] ,

[0059] ,

[0060] where represents the result of the th iteration algorithm.

[0061] In a specific embodiment of the present invention, step S3.4 includes:

[0062] The NLOS errors of RSS and TOA are updated as:

[0063] ,

[0064] ,

[0065] and respectively represent the power error estimate value and distance error estimate value of NLOS propagation.

[0066] In a specific embodiment of the present invention, the first preset condition includes: the difference in distance between the front and back calculation results is less than the preset threshold or the number of iterations reaches the maximum number of iterations.

[0067] The present invention can bring at least one of the following beneficial effects: The present invention proposes a 5G scenario non-line-of-sight (NLOS) positioning method, which measures TOA and RSS based on the communication parameters of 5G base stations, performs least squares positioning calculation, iteratively calculates the NLOS error, and finally determines the positioning calculation result based on multiple iterations. Specifically, in terms of measuring TOA and RSS, the present invention divides and updates the multipath parameters successively, and estimates the multipath channel parameters of TOA and RSS alternately; moreover, the present invention considers the NLOS errors 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 non-linear least squares and adopts an alternating iterative estimation and compensation method. The NLOS positioning method proposed by the present invention is based on error compensation and least squares calculation, has low computational complexity and stronger anti-interference ability, can effectively cope with the problem of signal propagation path deviation caused by obstacles in the NLOS scenario, has a smaller error in the positioning calculation result, better positioning performance, and is more suitable for indoor positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The following will further illustrate the above characteristics, technical features, advantages and their implementation manners in a clear and understandable manner in combination with the drawings of the preferred embodiments.

[0069] Figure 1 It is a signal propagation schematic diagram of an indoor scenario;

[0070] Figure 2 It is 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;

[0071] Figure 3 It is a schematic diagram of the comparison of the cumulative distribution functions of the positioning result errors obtained by the positioning method proposed by the present invention and the positioning result errors obtained by other positioning methods. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] The following further details each aspect of the present invention.

[0073] Unless otherwise defined or described, all professional and scientific terms used herein have the same meaning as those familiar to those skilled in the art. In addition, any methods and materials similar or equivalent to the described content can be applied to the method of the present invention.

[0074] The following explains the terms.

[0075] Unless otherwise clearly specified and defined, the "or" described 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".

[0076] It will 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. Thus, a first element may be termed a second element without departing from the teachings of the inventive concept.

[0077] In the present invention, the terms "comprising", "including" or "containing" mean that various components can be applied together to the mixtures or compositions of the present invention. Thus, the term "consisting essentially of..." is included in the terms "comprising", "including" or "containing".

[0078] Unless otherwise expressly specified and defined, the terms "connected", "communicated with" and "coupled" of the present invention should be understood in a broad sense. For example, it may be a fixed connection, or may be connected through an intermediate medium, and may be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0079] For example, if an element (or component) is referred to as being on another element, coupled to or connected to another element, then said one element may be formed directly on, coupled to or connected to said other element, or there may be one or more intermediate elements therebetween. Conversely, if the expressions "directly on...", "directly coupled to..." and "directly connected to..." are used herein, then it means that there are no intermediate elements. Other words used to describe the relationship between elements should be interpreted similarly, such as "between..." and "directly between...", "attached" and "directly attached", "adjacent" and "directly adjacent", etc.

[0080] In addition, it should be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to the directions in the drawings. The words "inner" and "outer" respectively refer to the directions towards or away from the geometric center of a specific component. It will be understood that herein, these terms are used to describe the relationship of one element, layer or region to another element, layer or region as shown in the drawings. Except for the orientations described in the drawings, these terms should also include other orientations of the device.

[0081] Other aspects of the present invention will be apparent to those skilled in the art from the disclosure herein.

[0082] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation manners of the present invention will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings, and other implementation manners can also be obtained.

[0083] It should also be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present application in a schematic manner. The diagrams only show the components related to the present application, rather than being drawn according to the number, shape, and size of the components in actual implementation. The types, quantities, and proportions of the components in actual implementation can be arbitrarily changed, and the component layout type may also be more complex. For example, the thickness of the elements in the accompanying drawings can be exaggerated for clarity.

[0084] Embodiment

[0085] For the scenario of large non-line-of-sight positioning error and low accuracy in the 5G scenario in the prior art, refer to Figure 2 , the present invention provides a 5G scenario non-line-of-sight positioning method based on error compensation, including the following steps:

[0086] Step S1: Obtain the communication parameters of the 5G base station, and the communication parameters at least include the channel state information CSI;

[0087] Step S2: Measure the channel communication parameters based on the CSI, and the channel communication parameters at least include the time of arrival TOA and the received signal strength RSS;

[0088] Step S3: Perform positioning calculation based on the channel communication parameters, and iteratively calculate the non-line-of-sight error;

[0089] Step S4: If the positioning calculation result meets the first preset condition, output the positioning calculation result; otherwise, repeat step S3.

[0090] In a preferred embodiment of the present invention, step S1 includes:

[0091] The channel frequency response of the subcarrier is:

[0092] ,

[0093] where is the total number of propagation paths, is the imaginary unit, and respectively represent the complex gain and TOA of the th path, is the additive white Gaussian noise during the measurement process, is the frequency of the th sub - carrier, , is the carrier frequency, is the sub - carrier spacing, , is the total number of sub - carriers, is the Doppler frequency shift caused by the relative motion between the terminal and the base station BS.

[0094] Preferably, step S2 includes:

[0095] Subtracting the estimated data of all paths other than the th path from the received superimposed signal to obtain the complete data of the th path : :

[0096] ,

[0097] wherein, represents the parameter value of the th path, represents the parameter estimate of the th path;

[0098] Based on maximizing the likelihood function, obtain the parameters of the th path, and the objective function is:

[0099] ,

[0100] ,

[0101] wherein, the function represents the loss function, represents minimization, represents the estimated data of the th path, , represents the squared norm of, represents the conjugate transpose, represents the real - part operation, represents the parameter estimate of the th path.

[0102] Specifically, step S2 further includes updating communication parameters:

[0103] ,

[0104] ,

[0105] ,

[0106] Among them, represents the TOA of the th path after update; represents the complex gain of the th path after update; represents the Doppler frequency shift after update.

[0107] In a preferred embodiment, the step S3 includes:

[0108] Step S3.1, establish a TOA-RSS joint model;

[0109] Step S3.2, calculate the joint likelihood function of the TOA and the RSS;

[0110] Step S3.3, solve the positioning result based on the linear least squares rough positioning algorithm and the non-linear least squares positioning algorithm;

[0111] Step S3.4, iteratively update the non-line-of-sight error.

[0112] Among them, the step S3.1 includes:

[0113] Assume there are RRUs in total, and the RSS of the th RRU is expressed as:

[0114] ,

[0115] The TOA of the th RRU is expressed as:

[0116] ,

[0117] Among them, , and respectively represent the complex gain and TOA of the strongest path of the th RRU, represents the speed of light, and respectively represent the unknown position of the terminal and the known position of the th RRU, is the RSS at the reference distance , and represent the power error and distance error of NLOS propagation, represents the path loss exponent, represents the log-normal shadow term, is a Gaussian random variable with a mean of 0 and a variance of ​ is the distance measurement noise, modeled as a Gaussian random variable with a mean of 0 and a variance of and is the Euclidean norm, denotes the RSS received by the th RRU.

[0118] In a preferred embodiment of the present invention, step S3.2 includes:

[0119] The RSS is:

[0120] ,

[0121] When t approaches 0, especially when t < 0.1, apply the first-order Taylor expansion, , to obtain:

[0122] ,

[0123] Combined with TOA, we can obtain:

[0124] ,

[0125] ,

[0126] where ;

[0127] Let , ,

[0128] The joint likelihood function is:

[0129] ,

[0130] ,

[0131] is the correlation coefficient matrix of TOA and RSS.

[0132] The linear least squares coarse positioning algorithm in step S3.3 is:

[0133] ,

[0134] ,

[0135] ,

[0136] where denotes the estimated terminal position;

[0137] In the non - linear least - squares solution algorithm for the

[0138] th iteration described in step S3.3,

[0139] includes:

[0140] wherein, represents the result of the th iteration solution.

[0141] Preferably, step S3.4 includes:

[0142] The NLOS errors of RSS and TOA are updated as:

[0143] ,

[0144] ,

[0145] and represent the power error estimate and the distance error estimate of NLOS propagation respectively.

[0146] In a preferred embodiment of the present invention, the first preset condition includes: the difference between the distances of the front and rear solution results is less than a preset threshold or the number of iterations reaches the maximum number of iterations. Preferably, the preset threshold is 0.01 m and the maximum number of iterations is 100 times.

[0147] Figure 3 shows a comparison schematic diagram of the cumulative error distribution functions of the 5G scenario NLOS positioning method based on error compensation provided by the present invention and other positioning methods. It can be Figure 3 intuitively seen that the positioning error of the 5G scenario NLOS positioning method based on error compensation proposed by the present invention is significantly smaller than that of other positioning methods, and it can have better performance in the NLOS environment.

[0148] In summary, the present invention has obtained the following effects:

[0149] The present invention proposes a 5G scenario NLOS positioning method, which measures TOA and RSS based on the communication parameters of 5G base stations, performs least - squares positioning solution, iteratively calculates the NLOS error, and finally determines the positioning solution result based on multiple iterations. The NLOS positioning method proposed by the present invention is based on error compensation and least - squares solution, has low computational complexity, stronger anti - interference ability in positioning calculation, can effectively cope with the problem of signal propagation path deviation caused by obstacles in the NLOS scenario, has smaller errors in the positioning solution result, better positioning performance, and is more suitable for indoor positioning.

[0150] Based on the present application, those skilled in the art should understand 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 aspects described herein can be used to implement the device and / or practice the method. Additionally, this device and / or this method can be implemented using other structures and / or functionality in addition to one or more of the aspects described herein.

[0151] Those skilled in the art know that in addition to implementing the system provided by the present invention and its various devices, modules, and units in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system provided by the present invention and its various devices, modules, and units to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc., to achieve the same functions. Therefore, the system provided by the present invention and its various devices, modules, and units can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or structures within the hardware component.

[0152] It should be noted that the above embodiments can be freely combined as needed. The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

[0153] All the documents mentioned in the present invention are cited in this application as references, just as if each document is cited separately as a reference. 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 appended claims of 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; the 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; 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 b RSS received by each RRU; 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: Step S2 includes: The superimposed signal received Minus the l The estimated data of all paths except the first path are obtained. l Complete data for each path : ， in, , indicating the l 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 l Parameter estimates for the bar diameter.

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 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.

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: 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.

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 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.

6. A 5G scenario non-line-of-sight positioning method based on error compensation according to claim 5, 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.

7. A 5G scenario non-line-of-sight positioning method based on error compensation according to any one of claims 1-6, 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.

Images