Multi-information fusion direction-finding positioning system suitable for indoor 5G frequency band

Abstract

The invention discloses a multi-information fusion direction-finding positioning system suitable for an indoor 5G frequency band, and the system comprises an actual measurement module which is responsible for building a test environment, collecting 5G-RSS (Received Signal Strength) data, and carrying out the preprocessing of the data, thereby guaranteeing the accuracy of effective data; and the distance measurement module is used for establishing a relation model between the 5G-RSS data and the distance based on a basic path loss model and by considering indoor environment factors, so that accurate distance calculation is provided. The direction finding module performs sum-difference beam processing on the received 5G-RSS data, classifies signals, performs normalization, and constructs an angle discrimination curve to extract target angle information; and the information fusion module combines the angle information and the distance information to realize target positioning. Experiments show that in the indoor 5G environment, the multi-information fusion direction-finding positioning system is excellent in performance, the positioning precision is remarkably improved, the positioning range is effectively expanded, stable operation in the complex indoor environment can be achieved, and a new view angle is provided for subsequent 5G radio positioning research.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication and positioning technology, and in particular to but not limited to a multi-information fusion direction-finding and positioning system suitable for indoor 5G frequency bands. Background Art

[0002] With the rapid development of 5G technology, the demand for indoor positioning systems in smart homes, industrial automation, warehouse management and other fields is growing. However, traditional indoor positioning methods usually rely on a single source of signal information, such as received signal strength (RSS) or time difference of arrival (TDOA), which have certain limitations in accuracy and range. Especially in complex indoor environments, the multipath effect and interference of signals make the positioning method of a single signal source challenging. In addition, the traditional amplitude comparison direction finding method also has shortcomings in distance calculation and is difficult to provide accurate location information. In order to solve these problems, a more efficient and flexible positioning technology is needed. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides a multi-information fusion direction-finding and positioning system suitable for indoor 5G frequency bands, which at least solves the problem of low accuracy of existing indoor single signal source positioning methods.

[0004] The technical solution of the embodiment of the present invention is achieved as follows:

[0005] The embodiment of the present invention provides a multi-information fusion direction finding and positioning system applicable to indoor 5G frequency band, including:

[0006] The actual measurement module is responsible for building the test system and collecting 5G-RSS data;

[0007] A distance measurement module, for preprocessing the 5G-RSS data, and establishing a relationship model between the 5G-RSS data and the distance based on a basic path loss model to calculate the distance information of the target to be measured; the basic path loss model characterizes the relationship between RSS power attenuation and distance;

[0008] A direction finding module is used to perform sum and difference beam processing on the 5G-RSS data, classify the signal type and perform signal strength normalization, and construct an angle detection curve to extract the angle information of the target to be measured; wherein the angle detection curve is used to represent the signal strength change in different directions;

[0009] The information fusion module is used to combine the angle information and the distance information and use the triangulation positioning principle or geometric relationship to determine the positioning result of the target to be measured.

[0010] Furthermore, in the actual measurement module, a 5G base station is used as a signal source, a receiving terminal installed with a road test software is used as the target to be tested, the test system is built, and parameter configuration and equipment calibration are completed; multi-point data is collected in the target area by slowly moving the target to be tested; measurements are performed at a preset position to be tested, and the RSS value at each position coordinate is recorded.

[0011] Furthermore, the basic path loss model is expressed by the following formula:

[0012] RSS(d)=A-10×n×log(d);

[0013] Wherein, RSS(d) represents the relationship between the RSS value of the measuring point where the target to be measured is located and the distance d; A represents the signal strength when the measuring point and the signal source are 1 meter apart; n is the environmental attenuation factor;

[0014] On the basis of the basic path loss model, environmental factors are introduced, and the model is optimized by fitting simulation, and A is -60.24, n is 0.69, and the relationship model between 5G-RSS data and distance is established as follows:

[0015] RSS(d)=-60.24-10×0.69×log(d);

[0016] Then the distance information of the target to be measured is calculated by the following formula:

[0017]

[0018] Furthermore, the angle discrimination curve is represented by the following formula:

[0019]

[0020] In the formula, ∑ sum represents and channel beam, represent the difference channel beams in azimuth and elevation respectively, Respectively represent the difference in output signal strength in azimuth and elevation, K x , K z are the normalized curve slopes of azimuth and elevation, respectively, Δθ are the relative positions to the target θ0, deviation.

[0021] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:

[0022] 1. Information fusion: The present invention combines 5G received signal strength (5G-RSS) and differential beam positioning technology. By integrating multiple information sources, it improves the accuracy and reliability of positioning and overcomes the limitations that may be brought about by a single information source.

[0023] 2. High-precision ranging: The ranging module is optimized based on actual environmental factors, taking into account wall materials and occlusion distribution, and establishing a more accurate RSS and distance relationship model, thereby significantly improving the accuracy of ranging and adapting to complex indoor environments.

[0024] 3. Fast direction finding capability: The direction finding module realizes fast and accurate target direction identification by processing the sum and difference beam signals. The normalization processing and the construction of angle identification curve enable the system to achieve positioning in dynamic environments.

[0025] 4. Excellent environmental adaptability: The present invention fully considers the complexity of the indoor environment, can operate stably under various interference conditions, adapts to the influence of different materials and layouts on signal propagation, and improves the stability of positioning.

[0026] 5. Strong real-time performance: The present invention can respond quickly to environmental changes and is suitable for application scenarios that require instant feedback.

[0027] 6. Scalability and compatibility: This system has good scalability and can be used in combination with other positioning technologies, such as visual positioning or inertial navigation, to further improve the overall performance of the system. At the same time, it is compatible with existing 5G infrastructure and is easy to deploy and integrate. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0029] Figure 1 A schematic diagram of the system architecture of a multi-information fusion direction finding and positioning system applicable to indoor 5G frequency bands provided by an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of a test system constructed in a multi-information fusion direction finding and positioning system provided in an embodiment of the present invention;

[0031] Figure 3 A schematic diagram of a drive test software interface installed in a receiving terminal in a test system provided by an embodiment of the present invention;

[0032] Figure 4 A schematic diagram of an RSS-distance fitting curve provided in an embodiment of the present invention;

[0033] Figure 5 A schematic diagram of two basic beams of 5G-RSS and differential direction finding provided in an embodiment of the present invention;

[0034] Figure 6 A schematic diagram of comparing errors of different positioning methods provided by an embodiment of the present invention;

[0035] Figure 7 A schematic diagram of comparing the effective ranges of different positioning methods provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0037] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0038] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present invention are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present invention described here can be implemented in an order other than that illustrated or described here.

[0039] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the field to which the embodiments of the present invention belong. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with those in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0040] Figure 1 A multi-information fusion direction finding and positioning system suitable for indoor 5G frequency band is provided in an embodiment of the present invention, such as Figure 1 As shown, the system includes:

[0041] The actual measurement module 11 is responsible for setting up the test system and collecting 5G-RSS data;

[0042] The ranging module 12 is used to establish a relationship model between the 5G-RSS data and the distance based on a basic path loss model after preprocessing the 5G-RSS data, so as to calculate the distance information of the target to be measured; the basic path loss model characterizes the relationship between RSS power attenuation and distance;

[0043] A direction finding module 13 is used to perform sum and difference beam processing on the 5G-RSS data, classify the signal type and perform signal strength normalization, and construct an angle detection curve to extract the angle information of the target to be measured; wherein the angle detection curve is used to represent the signal strength change in different directions;

[0044] The information fusion module 14 is used to combine the angle information and the distance information and use the triangulation positioning principle or geometric relationship to determine the positioning result of the target to be measured.

[0045] Here, the actual measurement module 11 is responsible for setting up the test system for actual measurement, establishing a test system with the terminal and the four base stations around it (base station 1, base station 2, base station 3, base station 4), and after 5G base station configuration and terminal configuration, data collection is performed to obtain 5G-RSS data. This module processes the collected RSS data to ensure that valid data is input into the subsequent ranging module 12 and direction finding module 13.

[0046] In the ranging module 12, data sorting and fitting are first performed, and the collected RSS data is preliminarily cleaned to remove noise and outliers. Combined with the collected real data, based on the basic path loss model, considering environmental factors such as wall materials and occlusion distribution, the real data is analyzed, and the basic path loss model is optimized through fitting simulation, thereby establishing a relationship model between 5G-RSS data and distance, improving the accuracy of distance calculation and model applicability, and providing reliable support for subsequent positioning. Preferably, a machine learning algorithm is used to train and optimize the model to improve the accuracy of distance estimation.

[0047] In the direction finding module 13, the sum and difference direction finding technology is used, such as Figure 1As shown, the received 5G-RSS data is divided into sum beam and difference beam according to different subarrays (subarray 1, subarray 2), and the signal strength is normalized to eliminate the influence under different measurement conditions. Then an angle discrimination curve is constructed, which can reflect the relationship between the phase difference of the signal and the angle estimation under different incident angles. By comparing the phase difference between the actual signal and the reference signal, the resolution ability of the system can be evaluated to obtain more accurate angle information. In summary, the distance information obtained by the ranging module 12 and the angle information obtained by the direction finding module 13 are combined by the information fusion module 14, and the triangulation positioning principle or geometric relationship is used. The system can accurately determine the target position to obtain the positioning result. Preferably, multiple positioning is performed to improve the reliability of position determination and ensure the consistency of the results. The design of this module helps to quickly and accurately identify the target direction in a complex environment, and improves the real-time performance of the overall system.

[0048] The multi-information fusion direction-finding and positioning system proposed in the present invention combines 5G-RSS with difference beam technology, and provides a high-precision positioning solution by integrating signal strength and angle information. The main working process is as follows: First, build a test system, perform actual measurements through the test system, and collect 5G-RSS data. Secondly, the collected 5G-RSS data is processed by the ranging module, and environmental factors are introduced to establish a relationship model between 5G-RSS data and distance. The received 5G-RSS data is then processed by the direction-finding module, the signal is classified, the signal strength is normalized, and an angle detection curve is constructed to extract angle information. Finally, the system combines the distance information obtained by the ranging module with the angle information obtained by the direction-finding module, and uses the triangulation positioning principle or geometric relationship to accurately determine the target position. At the same time, the multi-information fusion direction-finding and positioning system has real-time data processing capabilities, can quickly respond to environmental changes, and adapt to complex scenarios.

[0049] In some embodiments, in the actual measurement module, a 5G base station is used as a signal source, a receiving terminal installed with a road test software is used as the target to be tested, the test system is built, and parameter configuration and equipment calibration are completed; multi-point data is collected in the target area by slowly moving the target to be tested; measurements are performed at a preset position to be tested, and the RSS data at each position coordinate is recorded.

[0050] Here, if Figure 2 As shown in the figure, a 5G commercial base station, a HUAWEI Mate 30Pro 5G smartphone and the drive test software Pilot Pioneer are used to measure the actual RSS data. The target 21 uses the HUAWEI Mate 30Pro as the receiving terminal to receive the 5G signal, and the pRRU5931 as the base station to provide RF signal processing. Due to the shooting angle, Figure 2Only base stations 1 and 2 are displayed. Base stations 3 and 4 cannot be marked due to the obstruction of buildings. Figure 3 shown.

[0051] During the test, the position of base station 1 is first selected as the origin and a coordinate system is established. Then, multiple measurement points are marked at fixed intervals in the indoor environment, and the coordinates of each point and its corresponding RSS value are recorded.

[0052] Preferably, multiple measurements are performed at different positions and heights to obtain sufficient sample data to ensure the representativeness and accuracy of the data.

[0053] In some embodiments, the basic path loss model is represented by the following formula:

[0054] RSS(d)=A-10×n×log(d) Formula (1);

[0055] Wherein, RSS(d) represents the relationship between the RSS value of the measuring point where the target to be measured is located and the distance d; A represents the signal strength when the measuring point and the signal source are 1 meter apart; n is the environmental attenuation factor;

[0056] On the basis of the basic path loss model, environmental factors are introduced, and the model is optimized by fitting simulation, and A is -60.24, n is 0.69, and the relationship model between 5G-RSS data and distance is established as follows:

[0057] RSS(d)=-60.24-10×0.69×log(d) Formula (2);

[0058] Then the distance information of the target to be measured is calculated by the following formula:

[0059]

[0060] Here, by analyzing the 100 sets of data collected (Table 1 shows part of the collected data), the relationship model between 5G-RSS data and distance can be obtained as shown in formula (1).

[0061] Table 1 Part of the collected data of actual measurement

[0062]

[0063] After considering environmental factors, recalculation can get A = -60.24, n = 0.69, and modify formula (1) to get formula (2), and get the RSS-distance fitting curve as follows Figure 4 shown.

[0064] In the direction finding module, the present invention proposes a sum and difference direction finding algorithm based on 5G-RSS for indoor environments. The algorithm uses the RSS value as a reference factor, and generates an angle detection curve by performing sum, difference and normalization processing on the RSS values ​​of different beams received by the receiving terminal. Specifically, the algorithm first forms two basic beams that cover each other (generally intersecting at around 3dB), and then performs sum and difference processing on the output signal strength modulus values ​​of the two basic beams to form a sum and difference beam. In order to improve the direction finding accuracy, a two-dimensional uniform array is used as the receiving signal array array. The number of array elements is M×N, and the array element spacing is d'. Figure 5 As shown, assuming that the direction of the target to be measured is The direction of the steering angle is θ and θ0 represent the azimuth dimension, and represents the pitch dimension, the origin is the reference point, and the directions of the two basic beams generated by the azimuth dimension and the pitch dimension are Among them, Δθ, is the basic beam deviation and the beam deflection angle.

[0065] Then the directions of the four basic beams generated by the uniform surface array with M×N array elements are as follows: The corresponding output signal F i (i=1,2,3,4) The steering vector can be expressed as:

[0066]

[0067] Among them, μ xi , μ zi are the cosine differences of the x-axis and z-axis directions of the four beams, θ i , are the pointing directions of the four beams in the xoz plane and xoy plane, i.e., the azimuth dimension and the elevation dimension, i=1,2,3,4 are the corresponding indexes of the four basic beams generated by the uniform surface array, (m,n) are any array elements that can be selected in the M×N uniform surface array, j is the signal vector, which is an imaginary number expression, d' is the array element spacing, x, z are the coordinate positions of the array element on the x-axis and z-axis, respectively, and λ is the beam wavelength. After simplification, we have:

[0068]

[0069] By taking the RSS measurement modulo we can get:

[0070]

[0071] Expand to get:

[0072]

[0073] Perform sum and difference processing on the RSS values ​​of the four echo signals:

[0074] RSS(F sum )=RSS(|F1|+|F2|+|F3|+|F4|) Formula (8);

[0075]

[0076] In the formula, RSS(F sum ) represents the sum of the signal strengths of the channel outputs. Represents the difference in output signal strength in azimuth and elevation dimensions respectively.

[0077] The final constructed angle detection curve is expressed by the following formula:

[0078]

[0079] In the formula, ∑ sum represents and channel beam, represent the difference channel beams in azimuth and elevation respectively, Respectively represent the difference in output signal strength in azimuth and elevation, K x , K z are the normalized curve slopes of azimuth and elevation, respectively, Δθ are the relative positions to the target θ0, deviation.

[0080] The multi-information fusion direction finding and positioning system applicable to the indoor 5G frequency band is described below in conjunction with a specific embodiment. However, it is worth noting that this specific embodiment is only for better illustrating the present invention and does not constitute an improper limitation to the present invention.

[0081] In order to verify the effectiveness of the multi-information fusion direction finding and positioning system for the 5G frequency band proposed in the present invention, the present invention will use the hardware environment and combine it with semi-physical simulation data to verify the indoor 5G wireless positioning method based on the multi-information fusion direction finding and positioning system. The semi-physical simulation data collection steps are as follows:

[0082] 1. Test system preparation: To build an indoor 5G test environment, the present invention uses a pRRU59315G micro base station with a transmission frequency of 2675MHz as the signal source, which is installed on a bracket about 3.35 meters high. At the same time, the equipment is calibrated to ensure the stability and accuracy of the 5G signal.

[0083] As for the receiving terminal (i.e., the target to be tested), the embodiment of the present invention requires the installation of the drive test software in advance and the preparation of a test phone compatible with the hardware. The test phone is placed at a height of 1.5 meters and regarded as the target to be tested in order to accurately receive the 5G signal from the signal source.

[0084] 2. Data collection: After setting up the test system and determining the target area for direction finding and positioning, environmental features (such as walls and obstacles, etc.) should be considered, and then multi-point data should be collected by slowly moving the receiving terminal (target to be measured) in the target area. Measure at the preset position to be measured and record the RSS value at each position coordinate.

[0085] 3. Data processing: The collected 5G-RSS data is preliminarily cleaned through the ranging module to remove noise and outliers. The relationship between the known distance and signal strength is used to establish a relationship model between 5G-RSS data and distance to obtain accurate distance information.

[0086] 4. Signal processing: The direction finding module first normalizes the processed 5G-RSS data to eliminate environmental interference and differences between devices. Then, the processed data is used to generate angle detection curves, which can reflect the changes in signal strength in different directions, thus providing a basis for calculating the azimuth of the target to be measured.

[0087] 5. Target position calculation: After combining the distance information obtained by the ranging module with the angle information of the direction finding module, the precise position of the target to be measured is calculated based on the geometric relationship of triangulation positioning.

[0088] 6. Experiment and verification: The simulation experiment of the present invention in indoor environment demonstrates its excellent positioning accuracy. Figure 6 and Figure 7 As shown, compared with the traditional positioning method, the method of the present invention improves the positioning accuracy by 31%, significantly reduces the large error in long-distance target positioning, and expands the measurement range. The test results show that the positioning ability of the system in complex environments is better than that of traditional methods, effectively improving the detection range and flexibility.

[0089] In summary, the present invention focuses on the method of indoor 5G wireless positioning. By improving the traditional amplitude comparison direction finding method, the sum difference method is used to solve the problem of direction detection range limitation caused by antenna gain loss. At the same time, by actually measuring 5G-RSS data and fitting modeling, the basic path loss model is corrected, and a relationship model between 5G-RSS data and distance suitable for indoor scenarios is established. The simulation results can be seen in Table 2.

[0090] Table 25G-RSS positioning results

[0091]

[0092] like Figure 6 As shown in FIG. 1 , the multi-information fusion direction-finding and positioning system proposed in the present invention achieves a vectorization accuracy of 0.01 radians (±0.5°) in the azimuth and elevation dimensions, and the angle deviation error is 0.001 radians (±0.05°). Figure 7 It is shown that compared with the traditional direction detection positioning algorithm (including TDOA method and amplitude comparison direction finding method), the scheme of the present invention shows higher stability in long-distance target positioning.

[0093] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present invention, the size of the serial number of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. The serial numbers of the above-mentioned embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0094] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0095] In the several embodiments provided by the present invention, it should be understood that the disclosed methods can be implemented in other ways. The methods disclosed in the several method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments. The features disclosed in the several method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0096] The above is only an embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A multi-information fusion direction finding and positioning system suitable for indoor 5G frequency band, characterized in that: include: The actual measurement module is responsible for building the test system and collecting 5G-RSS data; A distance measurement module, used to establish a relationship model between 5G-RSS data and distance based on a basic path loss model after preprocessing the 5G-RSS data, so as to calculate the distance information of the target to be measured; The basic path loss model characterizes the relationship between RSS power attenuation and distance; A direction finding module is used to perform sum and difference beam processing on the 5G-RSS data, classify the signal type and normalize the signal strength, and construct an angle detection curve to extract the angle information of the target to be measured; wherein the angle detection curve is used to represent the change of signal strength in different directions; The information fusion module is used to combine the angle information and the distance information and use the triangulation positioning principle or geometric relationship to determine the positioning result of the target to be measured.

2. The multi-information fusion direction finding and positioning system according to claim 1, characterized in that: In the actual measurement module, a 5G base station is used as a signal source, a receiving terminal with the drive test software installed is used as the target to be tested, the test system is built, and parameter configuration and equipment calibration are completed; In the target area, multi-point data is collected by slowly moving the target to be measured; measurements are performed at preset positions to be measured, and the RSS value at each position coordinate is recorded.

3. The multi-information fusion direction finding and positioning system according to claim 1, characterized in that: The basic path loss model is expressed by the following formula: RSS(d)=A-10×n×log(d); Wherein, RSS(d) represents the relationship between the RSS value of the measuring point where the target to be measured is located and the distance d; A represents the signal strength when the measuring point and the signal source are 1 meter apart; n is the environmental attenuation factor; On the basis of the basic path loss model, environmental factors are introduced, and the model is optimized by fitting simulation, and A is -60.24, n is 0.69, and the relationship model between 5G-RSS data and distance is established as follows: RSS(d)=-60.24-10×0.69×log(d); Then the distance information of the target to be measured is calculated by the following formula:

4. The multi-information fusion direction finding and positioning system according to any one of claims 1 to 3, characterized in that: The angle discrimination curve is expressed by the following formula: In the formula, ∑ sum represents and channel beam, represent the difference channel beams in azimuth and elevation respectively, Respectively represent the difference in output signal strength in azimuth and elevation, K x , K z are the normalized curve slopes of azimuth and elevation, respectively, Δθ are the relative positions to the target θ0, deviation.

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