A Single-Base Station Indoor UWB Optimized Positioning Method Based on Reflected Signals

Abstract

This invention relates to a single-base station indoor UWB optimized positioning method based on reflected signals, belonging to the field of indoor wireless positioning technology. The invention primarily utilizes reflected signals to achieve indoor positioning using a single base station. Based on an obtained indoor map, a model is created, a positioning base station is placed, and positioning tags are placed in the environment. Multipath signals are received, and the possible range of the positioning tags is narrowed down through processing of the actual received signals. The grid points of the constrained area are traversed, and a ray tracing model is used to simulate the received waveform. This simulation is compared with the actual received signal waveform to obtain the similarity probability of each grid point. Then, a similarity probability heatmap is fitted to the constrained area, and the point with the highest probability is the calculated positioning location. This scheme can optimize positioning accuracy in indoor scenarios, reduce costs, and improve base station utilization, providing a new approach to indoor UWB positioning and possessing certain reference value.

Description

Technical Field

[0001] This invention belongs to the field of indoor wireless positioning technology, specifically relating to a single-base station indoor UWB optimized positioning method based on reflected signals. Background Technology

[0002] With the development of wireless communication technology, people's demand for location services in daily life is constantly increasing. In outdoor scenarios, Global Navigation Satellite System (GNSS) technology is already very mature and can provide people with reliable outdoor positioning services. However, in indoor scenarios, due to the complex and changeable environment, satellite positioning errors are relatively large, and the TOA (Time of Arrival) positioning method is usually used.

[0003] When using the Time-of-Arrival (TOA) positioning method, the main approach is to measure the arrival time of the received signal between the base station and the mobile station, convert it into distance, and then find the intersection point by drawing a circle with the base station location as the center. This method requires at least three base stations to calculate the target's location.

[0004] When using ultra-wideband (UWB) signal antennas for TOA indoor positioning, the accuracy of UWB positioning is significantly affected by line-of-sight (LOS) and non-line-of-sight (NLOS) propagation. Positioning accuracy is high within the line-of-sight range but lower outside the line-of-sight range because the time-of-flight (TOF) is used to calculate the path distance, assuming the signal propagates only along a direct path. However, in the presence of obstacles, transmission and reflection occur, leading to lower positioning accuracy.

[0005] In the process of developing this invention, the inventors discovered that the existing technology has at least the following problems: When calculating the propagation time of a signal, it is assumed that the signal propagates only along a direct path. However, during the propagation process, the signal often encounters non-direct propagation due to interference from moving or stationary objects, such as reflection and diffraction. This results in low positioning accuracy for existing positioning methods. To improve accuracy, base stations need to be deployed as close to line of sight as possible, which leads to redundancy in the number of base stations and increases costs. The current solutions are as follows:

[0006] Application date: March 10, 2022; Application number: CN202210235302.1; Patent title: Indoor UWB Positioning Optimization Base Station Construction Method Based on Non-Line-of-Sight Environment Evaluation; This invention belongs to the field of indoor wireless positioning technology. It mainly utilizes the application of line-of-sight and non-line-of-sight areas of UWB signals in ranging to simulate the minimum non-line-of-sight weighted area layout of indoor base stations. Based on an obtained indoor map, a model is created. First, the approximate range of base stations is divided according to the map information. Then, a genetic algorithm is used to sequentially optimize the non-line-of-sight performance of each base station location. Compared with traditional base station construction methods, this invention can quickly obtain the optimal deployment location of base stations through modeling and simulation, reduce the impact of non-line-of-sight propagation on indoor UWB positioning, improve the usable range of base stations, and reduce the manpower and material resources consumed during actual testing. It has certain guiding significance for the deployment of actual UWB positioning base stations.

[0007] This method reduces the impact of non-line-of-sight propagation on indoor UWB positioning by rationally deploying base stations, aiming to guide actual base station construction without involving innovation in positioning methods. This paper describes a new positioning method: using a single base station, and based on prior information, constructing a virtual base station using reflected signals to achieve single-base station positioning. The aim is to improve positioning accuracy at the positioning method level, providing a new approach to indoor UWB positioning.

[0008] Application date: 2021 / 12 / 16, Application number: CN202111542767.3, Patent title: A distributed positioning algorithm based on a spatial environment error model. The algorithm is as follows: First, it acquires the spatial information of the positioning environment. Based on the error model of UWB signals in the spatial structure, it combines the known spatial information of the positioning environment to obtain a priori information map containing the distribution of line-of-sight base stations and non-line-of-sight error compensation functions within the positioning area. Based on the spatial prior information map, it selects and compensates for errors in UWB base stations during the positioning process. During the positioning process, it uses the heading information of the PDR to determine whether the base station is obstructed by pedestrians; if so, it corrects the ranging value. Finally, it combines the compensated multi-base station information with the PDR and achieves positioning through a distributed error state algorithm. This invention fully utilizes prior information such as spatial structure and the UWB non-line-of-sight error model to optimize base stations for accurate positioning, possessing the advantages of high accuracy and strong robustness.

[0009] This algorithm is an optimized localization method for pedestrians in complex indoor environments with human occlusion. It utilizes UWB multi-base station redundancy and combines it with PDR technology. The compensated multi-base station information is combined with PDR and a distributed error state algorithm to achieve localization, which is a fusion localization method. This paper describes a new standalone UWB technology localization method. It uses reflected signals to construct virtual base stations and combines them with a ray-tracking simulation model to achieve single-base station localization. The aim is to improve localization accuracy at the localization method level and provide a new approach to indoor UWB localization. Summary of the Invention

[0010] To address the problems existing in the prior art, this invention proposes a single-base station indoor UWB optimized positioning method based on reflected signals. Utilizing reflected signals, indoor positioning is achieved using a single base station. By setting up virtual base stations, not only is interference from reflected signals eliminated, but they are also utilized to form virtual direct signals, improving base station utilization. This reduces the number of base stations required while maintaining positioning accuracy, thus lowering costs.

[0011] This invention provides a single-base station indoor UWB optimized positioning method based on reflected signals, the method comprising the following steps:

[0012] (1) Scene modeling, determining environmental materials and electromagnetic parameters;

[0013] (2) Place a positioning base station, and its coordinates are considered as known quantities;

[0014] (3) The positioning tag is brought into the environment and receives the multipath signal sent to that point by the base station;

[0015] (4) Analyze the received waveform to determine whether the positioning tag is within the line of sight to the base station, and form corresponding positioning constraint areas for the two cases respectively;

[0016] The corresponding positioning constraint areas are formed for the two cases, namely, the line-of-sight case and the non-line-of-sight case.

[0017] When within line-of-sight range, the straight-line distance from the base station to the positioning tag can be calculated using the following formula:

[0018] d = c*(t1-t0)

[0019] Where d is the straight-line distance, c is the speed of light, t1 is the timestamp of the arrival of the first diameter, and t0 is the timestamp of the signal transmission;

[0020] The location tag constraint area is:

[0021] Z = L∩U

[0022] Where Z is the location tag constraint area, L is the arc drawn with the base station as the center and d as the radius, and U is the area in the spatial environment where the tag is placed;

[0023] When outside the line-of-sight range, a ray is emitted from the base station as the emission point, and then rotated around the base station's position. Based on the location of environmental obstacles, the area not swept by the ray is the location tag constraint area, calculated using the following formula:

[0024] Z=UR∩U

[0025] Where Z is the positioning tag constraint area, U is the area in the spatial environment where the tag can be placed, and R is the line-of-sight area swept by the ray.

[0026] The method for determining whether the location tag is within line-of-sight of the base station uses the difference between the first and second diameters for detection, and its steps include:

[0027] (4.1) Preprocess the received waveform, set the detection threshold, and filter out weak signals with secondary reflections or higher;

[0028] (4.2) Record the peak value and timestamp of the received multipath signal;

[0029] (4.3) Find the first waveform in a period by timestamp and regard it as the first path. Only when the signal strength of the first path is significantly greater than the signal strength of other signals is it considered that the base station and the positioning tag are within the line of sight and there are no obstacles blocking them. Otherwise, it is considered to be a waveform under non-line of sight influence.

[0030] (5) Use a ray tracing model in the positioning constraint area to obtain the simulated received signal waveform and obtain the probability value of the current grid point as the positioning point;

[0031] (6) Traverse all grid sampling points and repeat step (5) to obtain the probability value of each grid as a positioning point. Then fit a similar probability heat map within the constraint area. The position with the highest probability is the positioning solution position.

[0032] As a further improvement of the present invention, the threshold in step (4.1) is set according to the maximum value of the received waveform, and the calculation formula is as follows:

[0033] E threshold =E max *g

[0034] Where E threshold For the set threshold, E max The maximum intensity value of the received waveform is given by g, which is a threshold adjustment coefficient and is a positive number less than 1. The value is determined according to the actual situation.

[0035] As a further improvement to the present invention, the judgment condition for the first diameter signal strength being significantly greater than the other signal strengths in step (4.3) is as follows:

[0036] max{E i}≤E1*h, i=2,3,4,...

[0037] Where E i Let be the i-th peak signal in the waveform, and h be the judgment coefficient, which takes a value between 0 and 1 and is related to the reflection attenuation coefficient of the environmental material. When the condition formula is satisfied, it can be considered as a line-of-sight situation; otherwise, it is a non-line-of-sight situation.

[0038] As a further improvement of the present invention, step (5) uses a ray tracing method to obtain the positioning probability value, and the steps include:

[0039] (5.1) Divide the positioning label constraint area into a grid with a grid size of 30cm*30cm, for a total of M*N grids;

[0040] (5.2) Assuming one of the grid points is the positioning point, the ray tracing method is used to calculate the direct path and the first reflection path from all positioning base stations to the positioning tag. The time delay and power of the path are recorded, and the received signal waveform can be simulated.

[0041] (5.3) By comparing the simulated received waveform with the actual received waveform and matching them using a similarity algorithm, the waveform similarity probability can be obtained, which is the probability value P(x,y) used as the positioning point, where x and y are the coordinates of the sampling point of the grid.

[0042] As a further improvement of this invention, the ray tracing method described in step (5.2) is based on geometric optics and the theory of uniform geometric diffraction, and tracks the trajectory of electromagnetic waves transmitted from the source end to the receiver end through computer simulation. To simplify the model, this application only considers the paths of direct incidence, single reflection, and single transmission. The signal intensity attenuation satisfies the theory of geometric optics and is related to the electromagnetic parameters of the environmental materials; the time delay is obtained by dividing the path distance by the speed of light.

[0043] As a further improvement of the present invention, the position with the highest probability in step (6) is the location solution position, and the optimal coordinates are output, i.e., arg max{P(x,y)}.

[0044] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0045] This invention optimizes the positioning of indoor UWB base stations based on the influence of UWB reflection paths on the received signal waveform. After obtaining an indoor map, a model is created, positioning base stations are placed, and positioning tags are placed in the environment. Multipath signals are received, and the possible location range of the positioning tags is narrowed down by processing the actual received signals. The positioning constraint area is then gridded, and a ray tracing model is used to simulate the received waveform by traversing the grid points. This simulation is then compared with the actual received signal waveform to obtain the similarity probability of each grid point. Finally, a similarity probability heatmap is fitted to the constraint area, and the point with the highest probability is the calculated positioning location.

[0046] The single-base station indoor UWB optimized positioning method based on reflected signals of this invention improves the positioning accuracy in indoor non-line-of-sight environments, reduces the number of base stations while ensuring positioning accuracy, lowers costs, meets optimization objectives, and achieves the expected results. Attached Figure Description

[0047] Figure 1 This is a flowchart of the optimized method of the present invention;

[0048] Figure 2a This is a floor plan showing the indoor viewing distance of the specific plan;

[0049] Figure 2b The actual received waveform diagram for the specific scheme;

[0050] Figure 3a This is a floor plan of the indoor non-visual environment for the specific plan;

[0051] Figure 3b The actual received waveform diagram for the specific scheme;

[0052] Figure 4 This is a diagram showing the line-of-sight environmental labeling constraint area for a specific solution.

[0053] Figure 5a The simulation path diagram of the line-of-sight environmental ray tracing method at a sampling point is shown for a specific scheme.

[0054] Figure 5b For the specific scheme and simulation waveform diagram;

[0055] Figure 6 This is a diagram of the non-line-of-sight environment label constraint area for a specific solution;

[0056] Figure 7a The simulation path diagram of the non-line-of-sight environmental ray tracing method at a sampling point is shown for a specific scheme.

[0057] Figure 7b The waveform diagram is simulated for a specific scheme. Detailed Implementation

[0058] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0059] As a specific embodiment of the present invention, the present invention provides a single-base station indoor UWB optimized positioning method based on reflected signals, the flowchart of which is shown below. Figure 1 As shown, it includes the following steps:

[0060] (1) Scene modeling, determining environmental materials and electromagnetic parameters;

[0061] (2) Place a positioning base station, and its coordinates are considered as known quantities;

[0062] (3) The positioning tag is brought into the environment and receives the multipath signal sent to that point by the base station;

[0063] (4) Analyze the received waveform to determine whether the location tag is within line of sight to the base station, and form corresponding location constraint areas for the two cases respectively.

[0064] (5) Use a ray tracing model in the positioning constraint area to obtain the simulated received signal waveform and obtain the probability value of the current grid point as the positioning point.

[0065] (6) Traverse all grid sampling points and repeat step (5) to obtain the probability value of each grid as a positioning point. Then fit a similar probability heat map within the constraint area. The position with the highest probability is the positioning solution position.

[0066] by Figure 2a and Figure 2b The indoor viewing distance environment shown and Figure 3a and Figure 3b The method of the present invention will be specifically described using an indoor non-line-of-sight environment as an example:

[0067] First complete Figure 2a Indoor line-of-sight conditions, our actual received waveform is as follows: Figure 2b As shown, the waveform can be analyzed: the signal strength of the first path is significantly higher than that of the other multipaths, indicating that the first path is a line-of-sight path, and the threshold adjustment coefficient g is set to 0.2. Paths 2, 3, 4, and 5 are the second lowest paths and can be identified as primary reflection paths. Path 6 is significantly lower than the threshold and has a large time delay, so it can be considered a secondary reflection path. It can be eliminated in waveform preprocessing and is not included in the scope of consideration.

[0068] Because of the existence of the line-of-sight first path, in two-dimensional positioning, the tag position can be constrained by the distance radius and the base station position. Figure 4 On the arc, the arc region is divided into sampling points by angle. Then, the sampling points are traversed, and ray tracing is performed to obtain the simulated waveform. Figure 5a The path of the ray-traced reflection virtual base station at one sampling point is shown. Figure 5b This is a simulated waveform.

[0069] Then, a similarity matching process is performed with the actual signal waveform to obtain a similarity probability heatmap, and the location with the highest probability is used as the location solution position.

[0070] Then it is Figure 3a In indoor, non-line-of-sight situations, our actual received waveform is as follows: Figure 3b As shown, the waveform can be analyzed: due to the non-line-of-sight influence of obstacles, the intensity of the first path and some reflection paths is weakened or disappears, and the distinction is not obvious. Some paths are significantly lower than the threshold, which can be eliminated in waveform preprocessing and not included in the scope of consideration. Only three paths are left for base station waveform matching.

[0071] Since no path-first-path signal with a higher signal strength model than other paths can be found, it can be assumed that non-line-of-sight influences exist in the positioning process. Based on spatial environment information, the positioning area can be constrained to [specific location]. Figure 6 Within the green area, the green area is divided into a grid. Sampling points within the grid are traversed within the area, and a ray tracing model is used to obtain the simulated received waveform. Figure 7a The path of the ray-traced reflection virtual base station at one sampling point is shown. Figure 7b This is a simulated waveform.

[0072] Then, a similarity match is performed with the preprocessed simulated received waveform to obtain a similarity probability heatmap, and the location with the highest probability is used as the location solution position.

[0073] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any modifications or equivalent changes made based on the technical essence of the present invention shall still fall within the scope of protection claimed by the present invention.

Claims

1. A single-base station indoor UWB optimized positioning method based on reflected signals, characterized in that: The method includes the following steps: (1) Scene modeling, determining environmental materials and electromagnetic parameters; (2) Place a positioning base station, and consider its coordinates as known quantities; (3) The positioning tag is brought into the environment and receives the multipath signal sent to that point by the base station; (4) Analyze the received waveform to determine whether the location tag is within line of sight to the base station, and form corresponding location constraint areas for the two cases respectively; The corresponding positioning constraint areas are formed for the two cases, namely, the line-of-sight case and the non-line-of-sight case. When within line-of-sight range, the straight-line distance from the base station to the positioning tag can be calculated using the following formula: ； Where d is the straight-line distance, c is the speed of light, t1 is the timestamp of the arrival of the first diameter, and t0 is the timestamp of the signal transmission; The location tag constraint area is: ； Where Z is the location tag constraint area, L is the arc drawn with the base station as the center and d as the radius, and U is the area in the spatial environment where the tag is placed; When outside the line-of-sight range, a ray is emitted from the base station as the emission point, and then rotated around the base station's position. Based on the location of environmental obstacles, the area not swept by the ray is the location tag constraint area, calculated using the following formula: ； Where Z is the positioning tag constraint area, U is the area in the spatial environment where the tag can be placed, and R is the line-of-sight area swept by the ray. The method for determining whether the location tag is within line-of-sight of the base station uses the difference between the first and second diameters for detection, and its steps include: (4.1) Preprocess the received waveform, set the detection threshold, and filter out weak signals with secondary reflections or higher; (4.2) Record the peak value and timestamp of the received multipath signal; (4.3) Find the first waveform in a period by timestamp and regard it as the first path. Only when the signal strength of the first path is significantly greater than the signal strength of other signals is it considered that the base station and the positioning tag are within the line of sight and there are no obstacles blocking them. Otherwise, it is considered to be a waveform under non-line of sight influence. (5) Use a ray tracing model in the positioning constraint area to obtain the simulated received signal waveform and obtain the probability value of the current grid point as the positioning point; Step (5) uses ray tracing to obtain the positioning probability value, and the steps include: (5.1) Divide the positioning label constraint area into a grid with a grid size of 30cm*30cm, for a total of M*N grids; (5.2) Assuming one of the grid points is the positioning point, the ray tracing method is used to calculate the direct path and the first reflection path from all positioning base stations to the positioning tag. The time delay and power of the path are recorded, and the received signal waveform can be simulated. (5.3) By comparing the simulated received waveform with the actual received waveform and matching them using a similarity algorithm, the waveform similarity probability can be obtained, which is the probability value P(x,y) used as the location point, where x,y are the coordinates of the grid sampling point.

2. The single-base station indoor UWB optimized positioning method based on reflected signals according to claim 1, characterized in that, Step (4.1) The threshold is set based on the maximum value of the received waveform, and the calculation formula is: ； Where E threshold For the set threshold, E max The maximum intensity value of the received waveform is given by g, which is a threshold adjustment coefficient and is a positive number less than 1. The value is determined according to the actual situation.

3. The single-base station indoor UWB optimized positioning method based on reflected signals according to claim 1, characterized in that, The criterion for determining whether the initial diameter signal strength is significantly greater than other signal strengths in step (4.3) is: ； Where E i Let be the i-th peak signal in the waveform, and h be the judgment coefficient, which takes a value between 0 and 1 and is related to the reflection attenuation coefficient of the environmental material. When the condition formula is satisfied, it can be considered as a line-of-sight situation; otherwise, it is a non-line-of-sight situation.

4. The single-base station indoor UWB optimized positioning method based on reflected signals according to claim 1, characterized in that, The ray tracing method described in step (5.2) is based on geometric optics and uniform geometric diffraction theory, and uses computer simulation to track the trajectory of electromagnetic waves sent from the source end to the receiver end.

5. The single-base station indoor UWB optimized positioning method based on reflected signals according to claim 1, characterized in that, The location with the highest probability in step (6) is the location solution location, and the optimal coordinates are output. ; (6) Traverse all grid sampling points and repeat step (5) to obtain the probability value of each grid as a positioning point. Then fit a similar probability heat map within the constraint area. The position with the highest probability is the positioning solution position.

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