CN114245334A - Ultra-wideband indoor positioning algorithm integrating error-calculable map and gray wolf optimization - Google Patents
Ultra-wideband indoor positioning algorithm integrating error-calculable map and gray wolf optimization Download PDFInfo
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Abstract
The invention relates to the field of wireless electromagnetic wave transmission and ultra wide band indoor positioning, in particular to an ultra wide band indoor positioning algorithm integrating calculable error maps and gray wolf optimization, which comprises the following steps: s1, dividing an indoor map to be positioned into a plurality of areas and fine-grained grids according to the wall-through quantity of UWB signals, and calculating a distance measurement error model between each UWB base station and the center coordinate of each grid according to a distance measurement error formula of each area, so as to form an error map of each UWB base station; and S2, setting the coordinates of the initial wolf based on the fine-grained grid and the gray wolf optimization algorithm, and accurately estimating the position of the UWB tag by using the improved gray wolf optimization algorithm. The invention effectively improves the positioning precision of the ultra-wideband indoor positioning technology in indoor complex environment.
Description
Technical Field
The invention relates to the field of wireless electromagnetic wave transmission and ultra-wideband indoor positioning, in particular to an ultra-wideband indoor positioning algorithm integrating a calculable error map and gray wolf optimization.
Background
With the continuous development of internet technology, location-based services are receiving wide attention and research, and how to improve the positioning accuracy of a positioning system in an indoor multi-wall environment is an urgent problem to be solved in practical applications such as indoor service robots for increasingly severe aging problems, indoor logistics carrying vehicles for rapid and efficient unmanned carrying, indoor worker trajectory analysis for manufacturers' cause analysis, and the like. Ultra-wideband technology is widely accepted and adopted because of its extremely large bandwidth and extremely low transmission power compared to other indoor positioning technologies.
However, the positioning accuracy of the existing ultra-wideband technology often depends on rough estimation of the initial position of the ultra-wideband tag, and in addition, even if the ultra-wideband signal has strong wall-penetrating capability, the ultra-wideband signal still has signal attenuation and distortion which are difficult to quantify when facing the shielding of multiple walls in an indoor positioning scene, so that a positioning error model in the scene is difficult to accurately estimate. Due to the above factors, limited ultra-wideband equipment is utilized, and the positioning system is not high in precision in the actual indoor positioning scene of multiple walls.
Meanwhile, the existing ultra-wideband indoor positioning algorithm for eliminating the shielding usually needs to know the initial position of the ultra-wideband tag, then calculates the shielding error of the ultra-wideband tag, and corrects the ranging value according to the shielding error, so as to calculate and obtain the final estimated position of the ultra-wideband tag. However, at present, the initial position of the ultra-wide band tag is calculated based on distance estimation under the shielding condition, and the estimated initial position contains obvious errors, which can cause obvious errors in calculating the shielding errors, so that research on an indoor positioning algorithm which does not need to know the initial position of the ultra-wide band tag is very important for improving the precision of an indoor positioning system.
Disclosure of Invention
The invention aims to provide an ultra-wideband indoor positioning algorithm integrating a calculable error map and a gray wolf optimization, which solves the problems that the precision of an indoor positioning system with a plurality of shelters is improved and the defect that the initial position of a UWB tag needs to be known when the problem is solved in the prior art.
The invention aims to realize the purpose by the following technical scheme, and integrates a calculable error map and a wolf optimized ultra-wideband indoor positioning algorithm, and is characterized by comprising the following steps: s1, dividing the indoor map to be positioned into a plurality of areas and fine-grained grids according to the wall-through quantity of UWB signals, and calculating a ranging error model between each UWB base station and the center coordinate of each grid according to the proposed ranging error formula of each area, so as to form an error map of each UWB base station; s2, setting the coordinates of the initial wolf based on the fine-grained grid and the gray wolf optimization algorithm, and accurately estimating the position of the UWB tag by using the improved gray wolf optimization algorithm objective function.
It should be noted that: this application adopts above-mentioned step can refine the positioning accuracy degree, refines the region of location, improves indoor positioning accuracy degree.
The S1 includes the following substeps: s11, known two-dimensional indoor positioning plane
Wherein R is a real number set, and
the maximum value of the Cartesian coordinates of the point in the middle is X in the horizontal axis direction and Y in the vertical axis direction, and the locating plane is
The number of the walls is W,
wherein
Is a natural number set; and, at the positioning plane
Has I fixed UWB base stations and a movable UWB tag deployed, wherein the coordinates of the UWB base stations are xi＝[xi,yi]TTrue coordinates of UWB tag are xp＝[x,y]T(ii) a Transmitting signals according to UWB base station and UWB tagThe indoor area is divided into a plurality of areas marked as U by the number combination of the walls which need to pass through indoorsi,jWherein the index i represents the ith base station and j represents the jth zone; s12, dividing all areas U of each base stationi,jDivided into fine-grained grids, denoted Gi,j,(x,y)Wherein, the subscript i represents the ith base station, j represents the jth area, and (x, y) represents the center coordinates of the fine-grained grid, wherein the size of the fine-grained grid can be divided into 10 centimeters multiplied by 10 centimeters to 100 centimeters multiplied by 100 centimeters according to the precision requirement; s13, according to Ui,jCalculating UWB base station and subdivision grid G by ranging error model of regioni,j,(x,y)Distance measurement error between the center coordinates, denoted as Ei,j,(x,y)(ii) a And storing the distance measurement error obtained by calculation into an NxXY three-dimensional matrix, wherein the three-dimensional matrix is the error map provided by the invention.
It should be noted that according to the error area division method and the error map calculation method based on the fine-grained grid, the approximate equivalent calculation of the UWB ranging error in the indoor positioning environment in the prior art can be effectively distinguished, a large amount of priori knowledge acquisition work in the fingerprint library establishment process in the prior art can be well distinguished, and the positioning accuracy and the actual construction efficiency of the ultra-wideband technology in the indoor multi-wall environment are obviously improved.
Locating planes in two dimensions indoors
In the method, a UWB base station is used as an end point to emit rays to the periphery, if the wall body penetrated by the two rays is the same, the two rays point to the same area, and the whole two-dimensional indoor positioning plane
Can be divided into at most
And a region, wherein w is the w-th wall.
It should be noted that, by adopting the multi-region refined positioning calculation, the positioning error can be refined from a plurality of large units to a small unit, and the positioning accuracy is improved.
The S2 includes the following substeps: s21, respectively measuring the distance between each UWB base station and UWB label according to the TOA distance measuring method
Record as
S22, setting a two-dimensional indoor positioning plane
In the k-th wolf, the initial coordinate is xk＝[xk,yk]TWhere K is equal to {1,2, 3., K }, where K denotes the total number of wolves, and the number of iterations t is set to 0, and 0 is equal to or less than t<T, T represents the maximum iteration number; s23, calculating the fitting degree of the kth wolf
Calculating to obtain a fitting degree set of K wolfs
Wherein the following formula set is followed:
wherein the content of the first and second substances,
and
indicating the Euclidean distance between the kth wolf and the ith base station and the modified distance between the kth wolf and the ith base station,
denotes the ranging error between the kth wolf and the ith base station, which can be derived from E in step S1.3i,j,(x,y)Reading; s24, integrating the fitting degrees of K wolfs
Sort, keep three wolves of least fitness, { xa,xb,xc}; s25, updating coordinates x of all wolfsk＝[xk,yk]TStopping until the iteration time T reaches the maximum iteration time T, wherein the following formula group is used:
wherein x isk(t +1) represents the coordinates of the kth wolf in the t +1 th iteration; s26, outputting coordinates when iteration is stopped
I.e. the estimated coordinates of the UWB tag.
It should be noted that, by adopting the above steps to estimate and determine the coordinates of the UWB tag, the positioning accuracy of the prior art can be prevented from being affected by the rough initial position estimation of the UWB tag, the reliability of the positioning system is effectively improved, and meanwhile, the improved sirius optimized algorithm can improve the accuracy of the coordinate estimation in the indoor positioning process, and improve the positioning accuracy of the system in the indoor multi-wall complex environment.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. by adopting the steps, the distance measurement error model of each indoor area can be accurately calculated on the premise of not increasing the field deployment workload, and the operability of indoor multi-wall complex environment positioning is improved;
2. the error area is further divided by adopting a fine-grained grid, and meanwhile, the error model of the center coordinate of the fine-grained grid is calculated by combining the error models of different indoor areas, so that an accurate error map is established, and the positioning precision is directly improved;
3. according to the error map calculation and the improved grey wolf optimization, the method can be effectively distinguished from the prior art that the approximate equivalent calculation of the UWB ranging error in the indoor positioning environment is simply carried out, the workload of acquiring a large amount of priori knowledge when the prior art obtains high precision is well avoided, the constraint and influence of the rough initial coordinate estimation of the label on the positioning result in the prior art are avoided, and the positioning precision of the ultra-wideband technology in the indoor multi-wall environment is remarkably improved.
Drawings
FIG. 1 is a flow chart of the algorithm calculation of the present invention;
FIG. 2 is a schematic diagram of a positioning system deployment of the present invention;
FIG. 3 is a schematic diagram of error zone division and fine-grained grid of UWB base station AN1 according to the present invention;
FIG. 4 is a schematic view of a positioning scenario of the present invention;
FIG. 5 is a graph of cumulative error distribution according to the present invention.
Detailed Description
Referring to the accompanying drawings 1-5, the embodiment provides an ultra-wideband indoor positioning algorithm with a calculable error map and a grayish wolf optimization, which is mainly used for solving the precision of a positioning system in an indoor environment with a plurality of shelters in the prior art, and overcoming the defects that the initial position of a UWB tag needs to be known and a large amount of prior knowledge needs to be acquired on site when the problem is solved in the prior art, and the positioning algorithm is already in the actual use stage.
The specific embodiment of the invention is as follows: an ultra-wideband indoor positioning algorithm integrating error-calculable maps and gray wolf optimization is characterized by comprising the following steps: s1, dividing the indoor map to be positioned into a plurality of areas and fine-grained grids according to the wall-through quantity of UWB signals, and calculating a ranging error model between each UWB base station and the center coordinate of each grid according to the proposed ranging error formula of each area, so as to form an error map of each UWB base station; s2, setting the coordinates of the initial wolf based on the fine-grained grid and the gray wolf optimization algorithm, and accurately estimating the position of the UWB tag by using the improved gray wolf optimization algorithm objective function. The S1 includes the following substeps: s11, known two-dimensional indoor positioning plane
Wherein R is a real number set, and
the maximum value of the Cartesian coordinates of the point in the middle is X in the horizontal axis direction and Y in the vertical axis direction, and the locating plane is
The number of the walls is W,
wherein
Is a natural number set; and, at the positioning plane
Has I fixed UWB base stations and a movable UWB tag deployed, wherein the coordinates of the UWB base stations are xi＝[xi,yi]TTrue coordinates of UWB tag are xp＝[x,y]T(ii) a Dividing an indoor area into a plurality of areas according to the number combination of walls which need to pass through the indoor space when the UWB base station and the UWB tag transmit signals, and marking the areas as Ui,jWherein the index i represents the ith base station and j represents the jth zone; s12, dividing all areas U of each base stationi,jDivided into fine-grained grids, denoted Gi,j,(x,y)Wherein, the subscript i represents the ith base station, j represents the jth area, and (x, y) represents the center coordinates of the fine-grained grid, wherein the size of the fine-grained grid can be divided into 10 centimeters multiplied by 10 centimeters to 100 centimeters multiplied by 100 centimeters according to the precision requirement; s13, according to Ui,jCalculating UWB base station and subdivision grid G by ranging error model of regioni,j,(x,y)Distance measurement error between the center coordinates, denoted as Ei,j,(x,y)(ii) a And storing the distance measurement error obtained by calculation into an NxXY three-dimensional matrix, wherein the three-dimensional matrix is the error map provided by the invention. Locating planes in two dimensions indoors
In the method, a UWB base station is used as an end point to emit rays to the periphery, if the wall body penetrated by the two rays is the same, the two rays point to the same area, and the whole two-dimensional indoor positioning plane
Can be divided into at most
And a region, wherein w is the w-th wall. The S2 includes the following substeps: s21, respectively measuring the distance between each UWB base station and UWB label according to the TOA distance measuring method
Record as
S22, setting a two-dimensional indoor positioning plane
In the k-th wolf, the initial coordinate is xk＝[xk,yk]TWhere K is equal to {1,2, 3., K }, where K denotes the total number of wolves, and the number of iterations t is set to 0, and 0 is equal to or less than t<T, T represents the maximum iteration number; s23, calculating the fitting degree of the kth wolf
Calculating to obtain a fitting degree set of K wolfs
Wherein the following formula set is followed:
wherein the content of the first and second substances,
and
indicating the Euclidean distance between the kth wolf and the ith base station and the modified distance between the kth wolf and the ith base station,
denotes the ranging error between the kth wolf and the ith base station, which can be derived from E in step S1.3i,j,(x,y)Reading; s24, integrating the fitting degrees of K wolfs
Sort, keep three wolves of least fitness, { xa,xb,xc}; s25, updating coordinates x of all wolfsk＝[xk,yk]TStopping until the iteration time T reaches the maximum iteration time T, wherein the following formula group is used:
wherein x isk(t +1) represents the coordinates of the kth wolf in the t +1 th iteration; s26, outputting coordinates when iteration is stopped
I.e. the estimated coordinates of the UWB tag.
The method specifically comprises the following steps: referring to fig. 2, in a common three-room one-hall type diagram, there are three fixed interior walls, and deployment of an indoor positioning system in such a scenario would require at least 3 fixed-location UWB base stations and 1 movable UWB tag. And the UWB base station and the UWB tag continuously carry out real-time ranging by using a bilateral ranging method of a UWB technology. However, there are a plurality of wall-shelters in UWB signal propagation between the UWB base station and the UWB tag, the ranging value at this time is inaccurate, and the ranging error is not easily quantized, resulting in a large error in the coordinate estimation of the UWB tag. Referring to fig. 3, in a generalized three-room one-hall indoor field scene, the whole indoor area is divided into 6 areas, which are respectively marked as 6 areas according to the number combination of the penetrating walls of the rays emitted by using the UWB base station 1 as an end point
And further divides the entire indoor area into a 10 x 10 cm grid where the inventors used the positioning error to evaluate the positioning performance. And the algorithm, the original trilateral localization algorithm and the unmodified wolf optimization algorithm are respectively adopted to carry out comparison experiments in the same scene, and as can be seen from a table, compared with other methods, the mean value, the standard deviation and the root mean square error of the algorithm provided by the invention are all minimum. The mean value of the algorithm provided by the invention is 22.28 centimeters, the error of the trilateral location algorithm is reduced by about 61.5%, and meanwhile, compared with the mean value 45.94 centimeters of the location error of the unmodified wolf optimization algorithm, the mean value of the location error of the algorithm provided by the invention is only 22.28 centimeters. In addition, the standard deviation of the positioning error of the algorithm is the lowest, and reaches 9.87 centimeters. The root mean square error represents the direct deviation of the calculated value and the true value, and the root mean square error is reduced to 17.23 centimeters by adopting the algorithm. Fig. 5 further shows the cumulative error distribution diagram of the three positioning algorithms, and it can be seen from the diagram that the performance of the algorithm of the present invention is superior to that of the trilateral positioning algorithm and also superior to that of the unmodified grayling optimization algorithm, and the cumulative error of the present invention is the smallest. Experimental results show that the method effectively reduces the positioning error in the indoor multi-wall positioning environment, namely, the positioning precision of the ultra-wideband system is improved, and the method is effective to the positioning performance.
Comparison of positioning error results of the three algorithms of table
It is clear from the above table that the root mean square error of the algorithm of the present invention is much lower than the trilateral localization and the unmodified wolf optimization algorithm of the prior art.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (4)
1. An ultra-wideband indoor positioning algorithm integrating error-calculable maps and gray wolf optimization is characterized by comprising the following steps:
s1, dividing the indoor map to be positioned into a plurality of areas and further into fine-grained grids according to the wall-through quantity and combination of UWB signals, and calculating a ranging error model between each UWB base station and the center coordinate of each grid according to the proposed ranging error formula of each area, so as to form an error map of each UWB base station;
s2, setting the coordinates of the initial wolf based on the fine-grained grid and the gray wolf optimization algorithm, and accurately estimating the position of the UWB tag by using the improved gray wolf optimization algorithm objective function under the condition that the initial position of the UWB tag is not required to be obtained.
2. The fused calculable error map and grayish optimized ultra-wideband indoor positioning algorithm as claimed in claim 1, wherein the S1 comprises the following sub-steps:
s11, known two-dimensional indoor positioning plane
Wherein R is a real number set, and
the maximum value of the Cartesian coordinates of the point in the middle is X in the horizontal axis direction and Y in the vertical axis direction, and the locating plane is
The number of the walls is W,
wherein
Is a natural number set; and, at the positioning plane
Has I fixed UWB base stations and a movable UWB tag deployed, wherein the coordinates of the UWB base stations are xi＝[xi,yi]TTrue coordinates of UWB tag are xp＝[x,y]T(ii) a Dividing an indoor area into a plurality of areas according to the number combination of walls which need to pass through the indoor space when the UWB base station and the UWB tag transmit signals, and marking the areas as Ui,jWherein the index i represents the ith base station and j represents the jth zone;
s12, dividing all areas U of each base stationi,jDivided into fine-grained grids, denoted Gi,j,(x,y)Wherein, the subscript i represents the ith base station, j represents the jth area, and (x, y) represents the center coordinates of the fine-grained grid, wherein the size of the fine-grained grid can be divided into 10 centimeters multiplied by 10 centimeters to 100 centimeters multiplied by 100 centimeters according to the precision requirement;
s13, according to Ui,jCalculating UWB base station and subdivision grid G by ranging error model of regioni,j,(x,y)Distance measurement error between the center coordinates, denoted as Ei,j,(x,y)(ii) a And storing the distance measurement error obtained by calculation into an NxXY three-dimensional matrix, wherein the three-dimensional matrix is the error map provided by the invention.
3. The fused calculable error map and grayish optimized ultra-wideband indoor positioning algorithm of claim 2, characterized by: locating planes in two dimensions indoors
In the method, a UWB base station is used as an end point to emit rays to the periphery, if the wall body penetrated by the two rays is the same, the two rays point to the same area, and the whole two-dimensional indoor positioning plane
Can be divided into at most
And a region, wherein w is the w-th wall.
4. The fused calculable error map and grayish optimized ultra-wideband indoor positioning algorithm as claimed in claim 1, wherein the S2 comprises the following sub-steps:
s21, respectively measuring the distance between each UWB base station and UWB label according to the TOA distance measuring method
Record as
S22, setting a two-dimensional indoor positioning plane
In the k-th wolf, the initial coordinate is xk＝[xk,yk]TWhere K is equal to {1,2, 3., K }, where K denotes the total number of wolves, and the number of iterations t is set to 0, and 0 is equal to or less than t<T, T represents the maximum iteration number;
s23, calculating the fitting degree of the kth wolf
Calculating to obtain a fitting degree set of K wolfs
Wherein the following formula set is followed:
wherein the content of the first and second substances,
and
indicating the Euclidean distance between the kth wolf and the ith base station and the modified distance between the kth wolf and the ith base station,
denotes the ranging error between the kth wolf and the ith base station, which can be derived from E in step S1.3i,j,(x,y)Reading;
s24, integrating the fitting degrees of K wolfs
Sort, keep three wolves of least fitness, { xa,xb,xc}；
S25, updating coordinates x of all wolfsk＝[xk,yk]TStopping until the iteration time T reaches the maximum iteration time T, wherein the following formula group is used:
wherein x isk(t +1) represents the coordinates of the kth wolf in the t +1 th iteration;
s26, outputting coordinates when iteration is stopped
I.e. the estimated coordinates of the UWB tag.
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| CN114245334B (en) | 2023-01-24 |
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