An Indoor Positioning Method Based on Bluetooth and Inertial Sensor Fusion

Abstract

This invention discloses an indoor positioning method based on the fusion of Bluetooth and inertial sensors, comprising the following steps: S1, in the offline stage, after collecting the signal strength of Bluetooth base stations at different distances, the distance formula is fitted by a piecewise function; in the online stage, the distance between the Bluetooth base station and the point to be located is calculated based on the signal strength of each Bluetooth base station; S2, the scanned Bluetooth base stations are filtered, removing those with signal strength below a threshold to obtain pre-selected Bluetooth base stations, and the positioning result is calculated based on the coordinates of the pre-selected Bluetooth base stations; S3, using the positioning result of step S2 as the starting point and the coordinates of the scanned base stations as the ending point, the vector deflection angle is calculated to obtain multiple sets of deflection angle data, and these vector deflection angles are restricted to the range of 0 to 1; S4, the angle difference between the vector deflection angle corresponding to each set of Bluetooth base stations and the heading angle of the inertial sensor is calculated, and the result is constrained to the range of 0 to 1; S5, signal compensation is performed on the Bluetooth signal value based on the angle difference; S6, a given trilateration equation is selected, and the position is calculated by combining the compensated signal value from step S5 to obtain the final positioning result.

Description

Technical Field

[0001] This invention relates to wireless sensor positioning technology, specifically an indoor positioning method based on the fusion of Bluetooth and inertial sensors. Background Technology

[0002] In the field of Bluetooth positioning, complex non-line-of-sight environments can significantly reduce positioning accuracy. In pedestrian positioning scenarios, occlusion by the human body is one of the main causes of non-line-of-sight issues.

[0003] Because the human body can obstruct the transmitter and receiver, the Bluetooth signal strength received by the receiver can vary significantly depending on the orientation of the human body at the same location. This difference makes it impossible for both distance-based and fingerprint-based Bluetooth positioning methods to obtain a relatively accurate positioning result.

[0004] Therefore, by using inertial sensors to obtain pedestrian heading information, and using pedestrian heading data to compensate for the signal strength value of the blocked Bluetooth base station, a more accurate positioning result can be obtained through the compensated signal strength data. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an indoor positioning method based on the fusion of Bluetooth and inertial sensors to solve the technical problem that the existing technology does not consider the influence of different human orientations on the Bluetooth signal strength, resulting in insufficient positioning accuracy.

[0006] To achieve the above objectives, the present invention provides an indoor positioning method based on the fusion of Bluetooth and inertial sensors, comprising the following steps:

[0007] S1. In the offline phase, after collecting the signal strength of Bluetooth base stations at different distances, the distance formula is fitted using a piecewise function. In the online phase, the distance between the Bluetooth base station and the point to be located is calculated based on the signal strength of each Bluetooth base station.

[0008] S2. Filter the scanned Bluetooth base stations, remove Bluetooth base stations with signal strength below the threshold, obtain the pre-selected Bluetooth base stations, and calculate the positioning result based on the coordinates of the pre-selected Bluetooth base stations.

[0009] S3. Using the positioning result from step S2 as the starting point and the scanned base station coordinates as the ending point, calculate the vector deviation angle to obtain multiple sets of deviation angle data, and limit these vector deviation angles to between 0 and... Within the range;

[0010] S4. Calculate the angle difference between the vector deflection angle and the inertial sensor heading angle for each group of base stations, and constrain the result to 0. between;

[0011] S5. Perform signal compensation based on the angle difference;

[0012] S6. Given the trilateration equation, use the compensated signal values ​​from S5 to calculate the position and obtain the final positioning result.

[0013] Furthermore, the specific method of S1 is as follows:

[0014] To describe the relationship between the distance d from the base station to the point to be located and the signal strength r received by the base station at the point to be located, the expression is as follows:

[0015] ;

[0016] in, , , and These are all parameters to be fitted, which can be obtained by observing the distance d and the Bluetooth signal strength r.

[0017] c and g are signal strength thresholds, d represents the distance from the base station to the location to be located, and r represents the signal strength.

[0018] Furthermore, the specific method of S2 is as follows:

[0019] If only one base station is selected, the coordinates of that base station will be used directly as the location result.

[0020] If there are two pre-selected base stations, the weighted average of the coordinates of the two Bluetooth base stations is calculated by weighting the reciprocal of the distance, and this average is used as the positioning result.

[0021] If there are 3 pre-selected base stations, the trilateration method is used to calculate the coordinates, and the calculated value is the result of one positioning.

[0022] If there are more than 3 pre-selected base stations, select the four base stations with the strongest signals from the scanned base stations and combine them in groups of 3. For each group, process it through the trilateration equation to obtain 4 sets of corresponding base stations and positioning coordinates. Calculate the sum of the Euclidean distances between each set of positioning coordinates and all other sets of positioning coordinates. Then remove the set of positioning coordinates with the longest Euclidean distance from the other sets of positioning coordinates. Keep the average value of the positioning coordinates corresponding to the remaining 3 sets of base stations as the positioning result.

[0023] Furthermore: the pre-selected base stations are defined according to their quantity as follows: , i∈{1,2,...,N}, where N is the total number of pre-selected base stations;

[0024] When the number of pre-selected base stations is 1, i.e., N=1 and i=1, the positioning result is:

[0025] ;

[0026] When the number of pre-selected base stations is 2, i.e., N=2, the positioning result is:

[0027] ;

[0028] in, The weight of the i-th base station is expressed mathematically as follows:

[0029] ;

[0030] in, The distance from the point to be located to the positioning base station;

[0031] When the number of pre-selected base stations is equal to 3, i.e., N=3, the basic positioning equation between the receiver and transmitter in trilateration mode is:

[0032] ;

[0033] Simplifying the above system of equations into matrix form, we get:

[0034] ;

[0035] ;

[0036] ;

[0037] Solving using the least squares method yields the following result:

[0038] ;

[0039] Therefore, the location result is:

[0040] ;

[0041] in, and They represent The first and second element values ​​in the array.

[0042] When the number of pre-selected base stations is greater than 3, the 4 base stations with the strongest signals are selected from the scanned base stations, i.e., N=4. These base stations are combined in groups of 3, denoted as P1, P2, P3, and P4, for a total of 4 groups. The basic positioning equation between the receiver and transmitter in the trilateration mode described above is applied to the 3 base stations in each group to obtain the 4 positioning results corresponding to P1, P2, P3, and P4. , , , ;

[0043] Then, calculate the sum of the distances from the k-th location result to the other three location results:

[0044] ;

[0045] in, This represents the sum of distances from the k-th location result to the other three location results. This is the location result for the k-th group, where k∈{1,2,3,4};

[0046] Compare the above four sets of distance sums, obtain the location result number m corresponding to the maximum value of the distance sum, and discard the m-th set of location results. ;

[0047] Therefore, the location result is:

[0048] .

[0049] Furthermore: the formula for calculating the vector deflection angle in S3 is as follows:

[0050] ;

[0051] Where B is the vector deflection angle, This indicates the modulo operation. Let (x, y) represent the arctangent function, where (x, y) is the positioning result obtained in step S2. These are the pre-selected base stations chosen in step S2.

[0052] Furthermore: In step S4, the formula for calculating the angle difference is as follows:

[0053] ;

[0054] in, Due to the angle difference, The current heading angle of the inertial sensor. The vector deflection angle. This indicates the modulo operation.

[0055] Furthermore, in S5, the specific method for implementing signal compensation for the angle difference is as follows:

[0056] When the angle difference is less than At this time, the human body's blocking effect on signals is relatively weak, so no additional compensation is made for signal strength within this range;

[0057] When the angle difference exceeds At this time, the degree of signal obstruction by the human body will significantly increase with the increase of the angular difference, until the angular difference reaches a certain level. When the human body is completely facing away from the base station at a 180-degree angle, the obstruction effect reaches its maximum, and the human body's obstruction of the signal is most severe at this time.

[0058] Angle difference greater than When the corresponding angle difference is applied, the signal compensation formula is as follows:

[0059] ;

[0060] in, To compensate for the signal strength, The original signal strength; The parameters to be fitted can be obtained by comparing the relationship between the angle difference and the signal intensity value under the same distance conditions; This is the difference in angle.

[0061] Furthermore, in step S6, the specific method for calculating the positioning result is as follows:

[0062] The distance is calculated using the compensated signal value in S5. After obtaining the distance, the location equation in S2 is selected based on the number of pre-selected base stations to calculate the location and obtain the final location result.

[0063] The beneficial effects of this invention are: This method addresses the problem of severe signal attenuation of base stations behind a person due to human occlusion. It compensates for the signal strength by judging the angular difference between the base station and the direction the person is facing, thereby improving the ranging accuracy; and uses the compensated signal value to calculate the distance and position to obtain a high-precision positioning solution; this method has low computational load and high positioning accuracy. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of the present invention and the prior art, the drawings used in the description of the embodiments and the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 This is a schematic diagram of the process of the present invention;

[0066] Figure 2 This is a performance comparison chart of the positioning method of the present invention. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments provided by this invention without inventive effort are within the scope of protection of this invention.

[0068] Obviously, the accompanying drawings described below are merely some examples or embodiments of the present invention. For those skilled in the art, the present invention can be applied to other similar scenarios based on these drawings without any creative effort.

[0069] Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art who are related to the content disclosed in this invention, some design, manufacturing or production changes based on the technical content disclosed in this invention are merely conventional technical means and should not be construed as insufficient disclosure of this invention.

[0070] Unless otherwise specified, all embodiments and optional embodiments of the present invention can be combined with each other to form new technical solutions.

[0071] Please see Figure 1 The system flowchart of the present invention includes the following steps:

[0072] S1. In the offline phase, after collecting the signal strength of Bluetooth base stations at different distances, the distance formula is fitted using a piecewise function. In the online phase, the distance between the base station and the point to be located is calculated based on the signal strength of each Bluetooth base station.

[0073] S2. Filter the scanned Bluetooth base stations, remove Bluetooth base stations with signal strength below the threshold, obtain the pre-selected Bluetooth base stations, and calculate the positioning result based on the coordinates of the pre-selected Bluetooth base stations.

[0074] S3. Using the positioning result from step S2 as the starting point and the scanned base station coordinates as the ending point, calculate the vector deviation angle to obtain multiple sets of deviation angle data, and limit these vector deviation angles to between 0 and... Within the range;

[0075] S4. Calculate the angle difference between the vector deflection angle and the inertial sensor heading angle for each group of base stations, and constrain the result to 0. between;

[0076] S5. Perform signal compensation based on the angle difference;

[0077] S6. Given the trilateration equation, use the signal value after compensation in S5 to calculate the position and obtain the final positioning result.

[0078] Specifically:

[0079] First, the collected Bluetooth signal strength data is converted into distance data; then, base stations that meet the criteria are selected based on a threshold and their coordinates are calculated accordingly; next, inertial sensor angle constraints are used to compensate for the Bluetooth signal strength; finally, the compensated Bluetooth base station is used to perform positioning again to obtain the final positioning result.

[0080] To describe the relationship between the distance d from the base station to the point to be located and the signal strength r received by the base station at the point to be located, the expression is as follows:

[0081] ;

[0082] in, , , and All of these are parameters to be fitted. The main method involves obtaining a piecewise function of signal strength versus distance using distance data d and signal strength data r. The specific operation process includes an offline positioning stage and a real-time positioning stage.

[0083] In the offline positioning phase, the signal strength of the target base station under line-of-sight conditions is collected at one-meter intervals to obtain a dataset, and a piecewise function of signal strength versus distance is obtained by fitting this dataset.

[0084] During the real-time positioning phase, the piecewise function of signal strength versus distance is obtained by fitting the signal strength of each base station with that of the offline phase. The distance between each base station and the point to be located can be calculated, which describes the relationship between the distance d from the base station to the point to be located and the base station signal strength r received by the point to be located.

[0085] c and g are signal strength thresholds, d represents the distance from the base station to the location to be located, and r represents the signal strength.

[0086] The specific method for S2 is as follows:

[0087] If only one base station is selected, the coordinates of that base station will be used directly as the location result.

[0088] If there are two pre-selected base stations, the weighted average of the coordinates of the two base stations is calculated using the reciprocal of the distance as the result of one positioning operation.

[0089] If there are 3 pre-selected base stations, the trilateration method is used to calculate the coordinates, and the calculated value is the result of one positioning.

[0090] If there are more than three pre-selected base stations, select the four base stations with the strongest signals from the scanned base stations and combine them in groups of three. For each group, process the trilateration equation to obtain four sets of corresponding base station coordinates. Calculate the sum of the Euclidean distances from each set of coordinates to all other sets. Then remove the set of coordinates with the longest Euclidean distance from the other sets, and retain the average of the remaining three sets of base station coordinates as the positioning result. The pre-selected base stations are defined according to their number. Let i ∈ {1,2,...,N}, where N is the total number of pre-selected base stations. The following cases are handled specifically:

[0091] When the number of pre-selected base stations is 1, i.e., N=1 and i=1, the positioning result is:

[0092] ;

[0093] When the number of pre-selected base stations is 2, i.e., N=2, the positioning result is:

[0094] ;

[0095] in, The weight of the i-th base station is expressed mathematically as follows:

[0096] ;

[0097] in, The distance from the point to be located to the positioning base station;

[0098] When the number of pre-selected base stations is equal to 3, i.e., N=3, the basic positioning equation between the receiver and transmitter in trilateration mode is:

[0099] ;

[0100] Simplifying the above system of equations into matrix form, we get:

[0101] ;

[0102] ;

[0103] ;

[0104] Solving using the least squares method yields the following result:

[0105] ;

[0106] Therefore, the location result is:

[0107] ;

[0108] in, and They represent The first and second element values ​​in the array.

[0109] When the number of pre-selected base stations is greater than 3, the 4 base stations with the strongest signals are selected from the scanned base stations, i.e., N=4. These base stations are combined in groups of 3, denoted as P1, P2, P3, and P4, for a total of 4 groups. The basic positioning equation between the receiver and transmitter in the trilateration mode described above is applied to the 3 base stations in each group to obtain the 4 positioning results corresponding to P1, P2, P3, and P4. , , , ;

[0110] Then, calculate the sum of the distances from each set of positioning results to the other three sets of positioning results:

[0111] ;

[0112] in, This represents the sum of distances from the k-th location result to the other three location results. This is the location result for the k-th group, where k∈{1,2,3,4};

[0113] Compare the above four sets of distance sums, obtain the location result number m corresponding to the maximum value of the distance sum, and discard the m-th set of location results. ;

[0114] Therefore, the location result is:

[0115] ;

[0116] The formula for calculating the vector deflection angle in S3 is as follows:

[0117] ;

[0118] in, The vector deflection angle. This indicates the modulo operation. Let (x, y) represent the arctangent function, where (x, y) is the positioning result obtained in step S2. These are the pre-selected base stations chosen in step S2.

[0119] In S4, the formula for calculating the angle difference is as follows:

[0120] ;

[0121] in, Due to the angle difference, The current heading angle of the inertial sensor. The vector deflection angle. This indicates the modulo operation.

[0122] In S5, the specific method for implementing signal compensation for angle differences is as follows:

[0123] When the angle difference is less than At this time, the human body's blocking effect on signals is relatively weak, and no additional compensation is made for signal strength within this range;

[0124] When the angle difference exceeds At this time, the degree of signal obstruction by the human body will significantly increase with the increase of the angular difference, until the angular difference reaches a certain level. When the human body is completely facing away from the base station at a 180-degree angle, the obstruction effect reaches its maximum, and the human body's obstruction of the signal is most severe at this time.

[0125] That is, only for angle differences greater than Under these conditions, the corresponding angle difference signal compensation formula is as follows:

[0126] ;

[0127] in, To compensate for the signal strength, The original signal strength; The parameters to be fitted can be obtained by comparing the relationship between the angle difference and the signal intensity value under the same distance conditions; This is the difference in angle.

[0128] In S6, the specific method for calculating the positioning results is as follows:

[0129] The distance is calculated using the compensated signal value in S5. After obtaining the distance, the location equation in S2 is selected based on the number of pre-selected base stations to calculate the location and obtain the final location result.

[0130] A specific embodiment provided by the present invention:

[0131] like Figure 2 As shown:

[0132] In this embodiment, four or more Bluetooth positioning base station coordinates are given. The tester holds a mobile phone and conducts the test at any location within the base station signal coverage area. Then, the mobile phone scans the signal strength of the Bluetooth positioning base station. The scanned signal strength is converted into the distance from the tester to the base station using a distance formula. The final positioning result can then be obtained by using the trilateration method and the signal compensation formula. In the results of 50 positioning attempts, the error of the traditional positioning method is 2.2 meters, while the positioning error of the method of this invention is 1.17 meters.

[0133] Numerical analysis shows that the method of the present invention has significant advantages in pedestrian navigation scenarios.

[0134] The foregoing has provided a very detailed description of one and more embodiments of the present invention. However, the description is merely a specific example of the present invention and should not be considered as limiting the scope of application of the present invention. All other methods and modifications proposed based on the content of this invention should fall within the scope of patent protection of this invention.

Claims

1. An indoor positioning method based on the fusion of Bluetooth and inertial sensors, characterized in that, Includes the following steps: S1. In the offline phase, after collecting the signal strength of Bluetooth base stations at different distances, the distance formula is fitted using a piecewise function. In the online phase, the distance between the Bluetooth base station and the point to be located is calculated based on the signal strength of each Bluetooth base station. S2. Filter the scanned Bluetooth base stations, remove Bluetooth base stations with signal strength below the threshold, obtain the pre-selected Bluetooth base stations, and calculate the positioning result based on the coordinates of the pre-selected Bluetooth base stations. S3. Using the positioning result from step S2 as the starting point and the scanned Bluetooth base station coordinates as the ending point, calculate the vector deviation angle to obtain multiple sets of deviation angle data, and limit these vector deviation angles to between 0 and... Within the range; S4. Calculate the angle difference between the vector deflection angle and the inertial sensor heading angle for each group of base stations, and constrain the result to 0. between; S5. Perform signal compensation based on the angle difference; S6. Using the given trilateration equation, combined with the compensated signal value from S5, the position is calculated to obtain the final positioning result. In step S5, the specific method for implementing signal compensation for the angle difference is as follows: When the angle difference is less than At this time, the human body's blocking effect on signals is relatively weak, and no additional compensation is made for signal strength within this range; When the angle difference exceeds At this time, the degree of signal obstruction by the human body will significantly increase with the increase of the angular difference, until the angular difference reaches a certain level. When the human body is completely facing away from the base station at a 180-degree angle, the obstruction effect reaches its maximum, and the human body's obstruction of the signal is most severe at this time. That is, only for angle differences greater than Under these conditions, the corresponding angle difference signal compensation formula is as follows: ； in, To compensate for the signal strength, The original signal strength; The parameters to be fitted can be obtained by comparing the relationship between the angle difference and the signal intensity value under the same distance conditions; This is the difference in angle.

2. The indoor positioning method based on Bluetooth and inertial sensor fusion according to claim 1, characterized in that, The specific method of S1 is as follows: To describe the relationship between the distance d from the Bluetooth base station to the point to be located and the signal strength r of the Bluetooth base station received by the point to be located, the expression is as follows: ； in, , , and All of these are parameters to be fitted, which can be obtained by observing the distance d and signal strength r data; c and g are signal strength thresholds, d represents the distance from the base station to the point to be located, and r represents the signal strength.

3. The indoor positioning method based on the fusion of Bluetooth and inertial sensors according to claim 1, characterized in that, The specific method of S2 is as follows: Pre-selected base stations are defined according to their numbers. , i∈{1,2,...,N}, where N is the total number of pre-selected base stations; When the number of pre-selected base stations is 1, i.e., N=1 and i=1, the positioning result is: ； When the number of pre-selected base stations is 2, i.e., N=2, the positioning result is: ； in, The weight of the i-th base station is expressed mathematically as follows: ； in, The distance from the point to be located to the positioning base station; When the number of pre-selected base stations is equal to 3, i.e., N=3, the basic positioning equation between the receiver and transmitter in trilateration mode is: ； Simplifying the above system of equations into matrix form, we get: ； ； ； Solving using the least squares method yields the following result: ； Therefore, the location result is: ； in, and They represent The first and second element values ​​in the array. When the number of pre-selected base stations is greater than 3, the 4 base stations with the strongest signals are selected from the scanned base stations, i.e., N=4. These base stations are combined in groups of 3, denoted as P1, P2, P3, and P4, for a total of 4 groups. The basic positioning equation between the receiver and transmitter in the trilateration mode described above is applied to the 3 base stations in each group to obtain the 4 positioning results corresponding to P1, P2, P3, and P4. , , , ; Then, calculate the sum of the distances from the Kth location result to the other 3 location results: ； in, This represents the sum of distances from the k-th location result to the other three location results. This is the location result for the k-th group, where k∈{1,2,3,4}; Compare the above four sets of distance sums, obtain the location result number m corresponding to the maximum value of the distance sum, and discard the m-th set of location results. ; Therefore, the location result is: 。 4. The indoor positioning method based on the fusion of Bluetooth and inertial sensors according to claim 1, characterized in that, The formula for calculating the vector deflection angle in S3 is as follows: ； in, The vector deflection angle. This indicates the modulo operation. Represents the arctangent function. The location result obtained in step S2 These are the pre-selected Bluetooth base stations filtered in step S2.

5. The indoor positioning method based on the fusion of Bluetooth and inertial sensors according to claim 1, characterized in that, In step S4, the formula for calculating the angle difference is as follows: ； in, The angle difference is h, the current inertial sensor heading angle is B, the vector deflection angle is mod, and mod indicates the remainder operation.

6. The indoor positioning method based on the fusion of Bluetooth and inertial sensors according to claim 1, characterized in that, In S6: The distance is calculated using the compensated signal value in S5. After obtaining the distance, the location equation in S2 is selected based on the number of pre-selected base stations to calculate the location and obtain the final location result.

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