Multiple measurement combination screening positioning method based on sx1280 ranging module

Abstract

The present invention proposes a multiple measurement combination screening positioning method based on the sx1280 ranging module, inputting the coordinates of N anchor points and the M-times ranging result matrix D from each anchor point to the point to be positioned; initializing the combination result matrix as M N ×N-dimensional zero matrix, obtain the combined result matrix through the combination algorithm, traverse the matrix row by row; use the distance equation group to calculate the coordinates of the point to be located X k And calculate the corresponding distance error F k ; Select the coordinates with the smallest distance error in the set P as the estimated value of the coordinates of the final point to be located. The present invention uses multiple measurements between the anchor point and the point to be measured and combines the arrangement and combination method to convert a small amount of samples into a large amount of samples. Under the same sample volume requirement, it takes less time to obtain samples, thereby improving the real-time performance of the positioning system. The distance measurement samples are screened by using the compatibility characteristics of the distance difference of the small error measurement data, and the large error measurements can be removed to improve the positioning accuracy.

Description

Technical Field

[0001] The invention belongs to the technical field of wireless positioning, and in particular relates to a multiple measurement combination screening positioning method based on an sx1280 ranging module. Background Art

[0002] The Global Navigation Satellite System (GNSS) has brought tremendous changes to people's lives and production, and has continuously reshaped their understanding of the need for location-based services. However, indoors, due to the obstruction of buildings and the rapid attenuation of satellite signal strength, GNSS struggles to obtain accurate location information. Therefore, providing precise and stable location services in the event of GNSS failure is a key issue in the positioning field.

[0003] Currently, wireless measurement and positioning technologies for GNSS failure scenarios or indoor positioning primarily include WiFi, ZigBee, Bluetooth, UWB, and LoRa. These utilize methods such as Time of Observation (TOA), Time-Delayed Observation (TDOA), and RSSI to obtain distance information between two nodes. Multilateration, Taylor iteration, and other algorithms can be used to determine the relative position of the target location and known nodes. However, due to the complexity of indoor buildings and physical structures, the reflection, refraction, and diffraction of ranging signals can lead to multipath effects or non-line-of-sight (NLOS) measurements. This can result in significant errors in distance measurement data, impacting positioning accuracy. Therefore, eliminating multipath effects and the influence of non-line-of-sight measurements during positioning is an effective way to improve positioning accuracy.

[0004] As a low-power, long-distance communication technology, LoRa has seen increasing adoption in recent years. Furthermore, the LoRasx1280 module adds ranging functionality to its communication capabilities. LoRa ranging also faces the multipath effect and non-line-of-sight issues encountered in indoor positioning. Furthermore, because LoRa uses an open frequency band, it is subject to interference from signals such as WiFi and Bluetooth in the same frequency band when used indoors, resulting in significant fluctuations in LoRa ranging data. The current LoRa ranging strategy involves performing multiple measurements on different channels and filtering the results to obtain more accurate ranging data. However, the effectiveness of filtering is affected by the sample size. While a larger sample size can improve measurement accuracy, it also results in prolonged positioning time, making it impossible to ensure real-time positioning. This patent proposes an algorithm that, utilizing the geometric compatibility constraints of the positioning model, can filter ranging information with large errors from a smaller number of ranging samples, thereby improving the system's positioning accuracy while ensuring real-time positioning. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a multiple measurement combination screening positioning method based on the sx1280 ranging module, comprising the following steps:

[0006] Step 1: Input the coordinates of N anchor points and the matrix D of M distance measurement results from each anchor point to the point to be located.

[0007] Step 2: Initialize the combination result matrix combination_matrix to M N ×N-dimensional zero matrix, obtain the combination result matrix combination_matrix through the combination algorithm combination, and traverse the matrix row by row;

[0008] Step 3: Use the distance equations to calculate the coordinates X of the point to be located k And calculate the corresponding distance error F k ;

[0009] Step 4: Select the coordinate with the smallest distance error in the set P as the estimated value (x, y) of the final coordinate of the point to be located.

[0010] Furthermore, the specific process of the combination algorithm is as follows:

[0011] a. Initialize an N-layer stack named combination_tmp, with the i-th layer of the stack corresponding to the measurement data of the i-th anchor point, and record the top of the stack pointer as top. Initialize an N-dimensional array num with all 1s, indicating that the num(i)th measurement data of the i-th anchor point is in the stack. Push the measurement data of each anchor point into the stack in order according to the array num.

[0012] b. Store the data in the stack combination_tmp into the first all-zero row of the combination result matrix combination_matrix; if the element values ​​in the array num are all M, the combination process ends;

[0013] c. The num element corresponding to the top element of the stack is incremented by 1, i.e., num(top) is incremented by 1, to prepare for the next measurement data combination;

[0014] d. Pop the top element of the stack and determine whether the value of the corresponding element in the num array is greater than M. If it is greater than M, the corresponding element in the num array is reset to 1, so that the next stacked data becomes the first measurement value again, and jump to step c;

[0015] e. The next measurement data of the corresponding anchor point in the measurement result matrix D is pushed into the stack,

[0016] That is, D(top+1,num(top+1)) is pushed onto the stack;

[0017] f. Determine whether the stack is full. If the stack is full, jump to step b; otherwise, jump to step e.

[0018] Furthermore, the step 3 specifically includes the following steps:

[0019] Calculate the coordinates of point X according to the distance equation group (1) where k = 1, 2, ..., M N ,

[0020]

[0021] Subtract the first equation from each equation in the equation group (1) and transpose the terms to obtain the linear equation group (2):

[0022] AX=B (2);

[0023] in,

[0024]

[0025] From this we can get the least squares solution of equation (2):

[0026] X=(A T A) -1 A T B (3);

[0027] definition To the known anchor point A m The distance is l km , where k = 1, 2, ..., M N , m=1,2,...,N; define the distance error of the kth calculated coordinate

[0028] M N The calculated coordinates are based on the corresponding distance error F k Sort from small to large to get a set of ordered positions

[0029] Furthermore, in step 1: Assume that in a two-dimensional space, there are N anchor points A with known coordinates. i (i=1,2,...,N), the coordinates are (x1,y1),(x2,y2),...,(x N ,y N ), the coordinates of the point X to be located in space are (x, y), and the distance measurement of the point X to be located is performed M times using the known N anchor points to obtain an N×M dimensional measurement data matrix D = {d ij}(i=1,2,...,N;j=1,2,...,M), where d ij is the i-th anchor point A i The jth measurement value of .

[0030] Beneficial effects of the present invention

[0031] 1. By using multiple measurements between the anchor point and the point to be measured and combining them with permutations and combinations, a small amount of samples can be converted into a large number of samples. Under the same sample volume requirement, it takes less time to obtain samples, thereby improving the real-time performance of the positioning system.

[0032] 2. By using the distance difference compatibility characteristics of small error measurement data to screen the ranging samples, large error measurements can be removed to improve positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Attachment Figure 1 A flow chart of the combined optimal positioning method of the present invention;

[0035] Attachment Figure 2 This is a schematic diagram of the positioning model;

[0036] Attachment Figure 3 This is the flow chart of the combination algorithm combination. DETAILED DESCRIPTION

[0037] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0038] like Figure 1 The flowchart of the combined optimal positioning method of the present invention is shown, which includes the following steps:

[0039] Step 1: Input the coordinates of N anchor points and the matrix D of M distance measurement results from each anchor point to the point to be located.

[0040] like Figure 2 In the positioning model shown, it is assumed that there are N anchor points A with known coordinates in a two-dimensional space.i (i=1,2,...,N), the coordinates are (x1,y1),(x2,y2),...,(x N ,y N ), the coordinates of the point X to be located in space are (x, y). Now, using the known N anchor points to measure the distance of the point X M times, we can get an N×M dimensional measurement data matrix D = {d ij}(i=1,2,...,N;j=1,2,...,M). ij is the i-th anchor point A i The jth measurement value of .

[0041] Step 2: Initialize the combination result matrix combination_matrix to M N ×N-dimensional zero matrix, obtain the combination result matrix combination_matrix through the combination algorithm combination, and traverse the matrix row by row.

[0042] Use the combination algorithm combination to extract an element from each row of the measurement data matrix D to form a set of measurement data for multilateration positioning, denoted as A total of M N Group data. Among them, j i =1,2,...,M(i=1,2,...,N).

[0043] like Figure 3 As shown, the specific process of the combination algorithm combination is as follows:

[0044] g. Initialize an N-layer stack called combination_tmp, with the i-th layer of the stack corresponding to the measurement data of the i-th anchor point, and record the top of the stack pointer as top. Initialize an N-dimensional array num with all 1s, indicating that the num(i)th measurement data of the i-th anchor point is in the stack. Push the measurement data of each anchor point into the stack in order according to the array num;

[0045] h. Store the data in the stack combination_tmp into the first all-zero row of the combination result matrix combination_matrix. If all the element values ​​in the array num are M, then the combination process ends; otherwise, proceed to the next step;

[0046] i. The num element corresponding to the top element of the stack is increased by 1, that is, num(top) is increased by 1, to prepare for the next measurement data combination;

[0047] j. Pop the top element of the stack and determine whether the value of the corresponding element in the num array of the popped element is greater than M. If it is greater than M, the corresponding element in the num array is reset to 1, so that the next data pushed into the stack becomes the first measurement value again, and jump to step c;

[0048] k. Push the next measurement data of the corresponding anchor point in the measurement result matrix D into the stack,

[0049] That is, D(top+1,num(top+1)) is pushed onto the stack;

[0050] l. Determine whether the stack is full. If the stack is full, jump to step b;

[0051] Otherwise, jump to step e.

[0052] Step 3: Use the distance equations to calculate the coordinates X of the point to be located k And calculate the corresponding distance error F k .

[0053] Each set of measurement data obtained in step 2 can be used to calculate the coordinates of point X according to the distance equation group (1) where k = 1, 2, ..., M N ,

[0054]

[0055] Subtract the first equation from each equation in the equation group (1) and shift the terms to obtain the linear equation group (2)

[0056] AX=B (2)

[0057] in,

[0058]

[0059] From this we can get the least squares solution of equation (2):

[0060] X=(A T A) -1 A T B (3)

[0061] Since the equation (3) is obtained from a set of measurement data is the least squares solution, which does not completely satisfy the equation system (1). To the known anchor point A m The distance is l km , where k = 1, 2, ..., M N , m=1,2,...,N; defines the distance error of the kth calculated coordinate Then M NThe calculated coordinates are based on the corresponding distance error F k Sort from small to large to get a set of ordered positions

[0062] Step 4: Select the coordinate with the smallest distance error in the set P as the estimated value of the final coordinate of the point to be located Right now

[0063]

[0064] The present invention is based on the sx1280 ranging module ranging engine. During positioning, multiple distance measurements are performed between each anchor point and the point to be measured in a short period of time. Using permutation and combination methods, multiple groups of distance measurement data between each anchor point and the point to be positioned are constructed. Each group is used to calculate the position of the point to be positioned. Compared with general methods, more groups of ranging data samples can be obtained with the same number of ranging measurements, making the final estimated result closer to the true value, while also saving the time of obtaining large samples.

[0065] The distance error index is used to sort the solution results, and multiple position solution results are optimized. The position solution with the smallest distance error is selected as the estimated value of the coordinates of the point to be located. The compatibility characteristics of each group of small error data are used to improve the positioning accuracy.

[0066] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0067] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A multiple measurement combination screening positioning method based on the sx1280 ranging module, characterized in that: The steps include: Step 1: Input the coordinates of N anchor points and the matrix D of M distance measurement results from each anchor point to the point to be located; Assume that in a two-dimensional space, there are N anchor points A with known coordinates. i (i=1,2,...,N), the coordinates are (x1,y1),(x2,y2),...,(x N ,y N ), the coordinates of the point X to be located in the space are (x, y), and the known N anchor points are used to perform M distance measurements on the point X to obtain an N×M dimensional measurement data matrix D = {d ij }(i=1,2,...,N;j=1,2,...,M), where d ij is the i-th anchor point A i The jth measurement value of Step 2: Initialize the combination result matrix combination_matrix to M N ×N-dimensional zero matrix, obtain the combination result matrix combination_matrix through the combination algorithm combination, and traverse the matrix row by row; The specific process of the combination algorithm combination is as follows: a. Initialize an N-layer stack combiantion_tmp, let the i-th layer of the stack correspond to the measurement data of the i-th anchor point, and record the stack top pointer as top; initialize an N-dimensional array num with all 1s, indicating that the num(i)th measurement data of the i-th anchor point is in the stack, and push the measurement data of each anchor point into the stack in sequence according to the array num; b. Store the data in the stack combination_tmp into the combination result matrix combination_ The first all-zero row of matrix; if the element values ​​in array num are all M, the combination process ends; c. The num element corresponding to the top element of the stack is increased by 1, that is, num(top) is increased by 1, to prepare for the next measurement data combination; d. Pop the top element of the stack and determine whether the value of the corresponding element in the num array is greater than M. If it is greater than M, the corresponding element in the num array is reset to 1, so that the next stacked data becomes the first measurement value again, and jump to step c; e. The next measurement data of the corresponding anchor point in the measurement result matrix D is pushed into the stack, That is, D(top+1,num(top+1)) is pushed into the stack; f. Determine whether the stack is full. If the stack is full, jump to step b; otherwise, jump to step e; Step 3: Use the distance equation group to calculate the coordinates X of the point to be located k And calculate the corresponding distance error F k ; Calculate the coordinates of point X according to the distance equation group (1) where k = 1, 2, ..., M N , Subtract the first equation from each equation in the equation group (1) and after transposing the terms, we can obtain the linear equation group (2): AX = B (2); in, From this we can get the least squares solution of equation (2): X=(A T A) -1 A T B (3); definition To known anchor point A m The distance is l km , where k = 1, 2, ..., M N , m=1,2,...,N; define the distance error of the kth calculated coordinate M N The calculated coordinates are based on the corresponding distance error F k Sort from small to large to get an ordered set of positions Step 4: Select the coordinate with the smallest distance error in the set P as the estimated value of the final coordinate of the point to be located.

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