CN114554395A

CN114554395A - Positioning accuracy prediction method and device, and signal source layout determination method and device

Info

Publication number: CN114554395A
Application number: CN202210202748.4A
Authority: CN
Inventors: 陶闯; 邱卫根; 赵康宁
Original assignee: Shanghai Weizhi Zhuoxin Information Technology Co ltd
Current assignee: Shanghai Weizhi Zhuoxin Information Technology Co ltd
Priority date: 2022-03-03
Filing date: 2022-03-03
Publication date: 2022-05-27

Abstract

The invention discloses a positioning accuracy prediction method, a positioning accuracy prediction device, a signal source layout determination method and a signal source layout determination device, wherein the positioning accuracy prediction method comprises the following steps: determining a signal source layout scheme in a target area; according to the signal source layout scheme and a signal propagation model, determining analog signal acquisition information corresponding to at least one sampling point in the target area; determining the analog positioning information of the sampling point according to the analog signal acquisition information and a signal positioning algorithm; and determining the corresponding predicted positioning precision of the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area. Therefore, the method and the device can determine the positioning effect corresponding to the signal source layout scheme in a simulation mode, provide data reference for subsequent operation of selecting the signal source layout scheme or adjusting the signal source layout scheme, and are also beneficial to improving the final area positioning effect.

Description

Positioning accuracy prediction method and device, and signal source layout determination method and device

Technical Field

The invention relates to the technical field of positioning algorithms, in particular to a positioning precision prediction method and device and a signal source layout determination method and device.

Background

The location capability of the geographic location of mobile terminals and internet of things devices is the technical basis for navigation and Location Based Service (LBS) applications. Various location-related services, such as emergency safety, smart warehousing, crowd monitoring, precision marketing, mobile health, virtual reality, human social interaction and the like, depend on the positioning capability of the mobile terminal and the internet of things device. Traditional positioning function mainly relies on satellite positioning system to accomplish, but to indoor environment or the more outdoor environment of obstacle, the topography is more complicated, and current all kinds of location demands are hardly satisfied to traditional satellite positioning technique.

To address the above situation, the conventional positioning technology starts to use the signal strength of the spatial clutter signal to determine the position of the terminal device. In such positioning technologies based on clutter signals, a specific signal source layout scheme is often required to build a signal positioning environment in a target area, and how to select a proper signal layout scheme becomes a key for success of such positioning technologies. However, in the prior art, the prediction of the positioning accuracy of the signal source layout scheme to be selected is not considered to help the screening and simulation of the signal source layout scheme to be selected, which obviously has defects and needs to be solved urgently.

Disclosure of Invention

The technical problem to be solved by the present invention is to provide a positioning accuracy prediction method, a positioning accuracy prediction device, a signal source layout determination method, and a signal source layout determination device, which can determine a positioning effect corresponding to a signal source layout scheme through a simulation mode, provide data reference for subsequent operations of selecting the signal source layout scheme or adjusting the signal source layout scheme, and also contribute to improving a final area positioning effect.

In order to solve the above technical problem, a first aspect of the present invention discloses a positioning accuracy prediction method, including:

determining a signal source layout scheme in a target area;

according to the signal source layout scheme and a signal propagation model, determining analog signal acquisition information corresponding to at least one sampling point in the target area;

determining the analog positioning information of the sampling point according to the analog signal acquisition information and a signal positioning algorithm;

and determining the corresponding predicted positioning precision of the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area.

The second aspect of the present invention discloses a signal source layout determining method, which includes:

determining a positioning precision requirement corresponding to a target area;

according to the positioning accuracy requirement and the positioning accuracy prediction method disclosed in the first aspect of the present invention, determining a target signal source layout scheme corresponding to the target area; the target signal source layout scheme is a signal source layout scheme which is calculated according to the positioning precision prediction method and can meet the positioning precision requirement according to the predicted positioning precision.

A third aspect of the present invention discloses a positioning accuracy prediction apparatus, including:

the scheme determining module is used for determining a signal source layout scheme in the target area;

the analog acquisition module is used for determining analog signal acquisition information corresponding to at least one sampling point in the target area according to the signal source layout scheme and the signal propagation model;

the analog positioning module is used for determining analog positioning information of the sampling point according to the analog signal acquisition information and a signal positioning algorithm;

and the accuracy determining module is used for determining the predicted positioning accuracy corresponding to the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area.

A fourth aspect of the present invention discloses a signal source layout determining apparatus, including:

the requirement determining module is used for determining a positioning precision requirement corresponding to the target area;

a scheme determining module, configured to determine a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement and the positioning accuracy prediction method disclosed in the first aspect of the present invention; the target signal source layout scheme is a signal source layout scheme which is calculated according to the positioning precision prediction method and can meet the positioning precision requirement according to the predicted positioning precision.

The fifth aspect of the present invention discloses another positioning accuracy prediction apparatus, including:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute part or all of the steps of the positioning accuracy prediction method disclosed by the first aspect of the invention.

A sixth aspect of the present invention discloses another signal source layout determining apparatus, including:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute part or all of the steps of the signal source layout determination method disclosed by the second aspect of the invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

the embodiment of the invention discloses a positioning precision prediction method, a positioning precision prediction device, a signal source layout determination method and a signal source layout determination device, wherein the positioning precision prediction method comprises the following steps: determining a signal source layout scheme in a target area; according to the signal source layout scheme and a signal propagation model, determining analog signal acquisition information corresponding to at least one sampling point in the target area; determining the analog positioning information of the sampling point according to the analog signal acquisition information and a signal positioning algorithm; and determining the corresponding predicted positioning accuracy of the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area. Therefore, the embodiment of the invention can determine the signal acquisition information of the sampling point in the specific signal source layout scheme through the signal propagation model, further determine the simulated positioning information of the sampling point through the positioning algorithm, and calculate the positioning precision through the simulated positioning information and the actual position information, thereby determining the positioning effect corresponding to the signal source layout scheme through a simulation mode, providing data reference for subsequent operation of selecting the signal source layout scheme or adjusting the signal source layout scheme, and being beneficial to improving the final area positioning effect.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic flow chart of a positioning accuracy prediction method according to an embodiment of the present invention.

Fig. 2 is a schematic flowchart of a signal source layout determining method according to an embodiment of the present invention.

Fig. 3 is a schematic structural diagram of a positioning accuracy prediction apparatus according to an embodiment of the present invention.

Fig. 4 is a schematic structural diagram of a signal source layout determining apparatus according to an embodiment of the present invention.

Fig. 5 is a schematic structural diagram of another positioning accuracy prediction apparatus according to an embodiment of the present invention.

Fig. 6 is a schematic structural diagram of another signal source layout determining apparatus according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or apparatus that comprises a list of steps or elements is not limited to those listed but may alternatively include other steps or elements not listed or inherent to such process, method, product, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The invention discloses a positioning precision prediction method, a positioning precision prediction device, a signal source layout determination method and a signal source layout determination device, which can determine signal acquisition information of sampling points in a specific signal source layout scheme through a signal propagation model, further determine simulated positioning information of the sampling points through a positioning algorithm, and calculate positioning precision through the simulated positioning information and actual position information, thereby determining a positioning effect corresponding to the signal source layout scheme through a simulation mode, providing data reference for subsequent operation of selecting the signal source layout scheme or adjusting the signal source layout scheme, and being beneficial to improving the final area positioning effect. The following are detailed below.

Example one

Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a positioning accuracy prediction method according to an embodiment of the present invention. The positioning accuracy prediction method described in fig. 1 is applied to a computing chip, a computing terminal, or a computing server (where the computing server may be a local server or a cloud server) of a positioning prediction system. As shown in fig. 1, the positioning accuracy prediction method may include the following operations:

101. and determining a signal source layout scheme in the target area.

Optionally, the signal source layout scheme may include a layout position of at least one signal source disposed in the target region and signal source information, where the layout position may be a two-dimensional position or a three-dimensional position, and the signal source information may include at least one of signal strength of the signal source, a type of the signal source, a name of the signal source, and signal source equipment information. Optionally, the signal source may be a WIFI signal source, a bluetooth signal source, or other signal transmitting devices that can transmit wireless signals.

Optionally, the method for determining the signal source layout scheme may be a signal source layout scheme for receiving external input, or may be automatically generating a signal source layout scheme according to preset rules and existing signal source layout requirements, where the signal source layout scheme may be determined by an operator or may be automatically generated by an algorithm model or a computer, and the present invention is not limited thereto.

102. And determining analog signal acquisition information corresponding to at least one sampling point in the target area according to the signal source layout scheme and the signal propagation model.

Optionally, the position information of at least one signal source arranged in the target area may be determined according to the signal source arrangement scheme, and then the signal strength of the signal from the signal source, which is simulatively acquired at the sampling point, is determined through the signal propagation model and the position of the sampling point, so as to obtain the simulated signal acquisition information. Optionally, the analog signal acquisition information may include at least one analog acquisition signal strength information for at least one signal source. Optionally, the position of any sampling point may be randomly generated by using a monte carlo method.

103. And determining the analog positioning information of the sampling point according to the analog signal acquisition information and a signal positioning algorithm.

Optionally, the signal localization algorithm may include at least one of a weight-based localization algorithm, a fingerprint-based localization algorithm, and a trilateral intersection-based localization method. Optionally, the basis for computing the weight-based positioning algorithm includes at least one of a distance weight, a signal accuracy weight, and a signal source weight. Optionally, the positioning concept of the fingerprint-based positioning algorithm at least includes: and establishing a fingerprint database of all signal sources of the signal source layout scheme, and determining the simulated positioning information of the sampling points through the matching calculation of the simulated signal acquisition information and the fingerprint database. Optionally, the analog positioning information may be two-dimensional position information or three-dimensional position information, which is not limited in the present invention.

104. And determining the corresponding predicted positioning precision of the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area.

Optionally, a positioning error may be calculated according to the simulated positioning information and the actual position information, and the predicted positioning accuracy corresponding to the target area may be determined according to the positioning errors of all the sampling points. Optionally, the predicted positioning accuracy corresponding to the target area may be determined according to a combination of one or more of the average value, the maximum value, the minimum value, the median value, the variance value and the standard deviation value of the positioning errors of all the sampling points, such as weighted summation or weighted averaging. In one particular arrangement, a sample point is assumed

The actual position information of

And the calculated analog positioning information of the sampling point is

Then the positioning error of the sampling point is:

。

therefore, the embodiment of the invention can determine the signal acquisition information of the sampling point in the specific signal source layout scheme through the signal propagation model, further determine the simulated positioning information of the sampling point through the positioning algorithm, and calculate the positioning precision through the simulated positioning information and the actual position information, thereby determining the positioning effect corresponding to the signal source layout scheme through a simulation mode, providing data reference for subsequent operation of selecting the signal source layout scheme or adjusting the signal source layout scheme, and being beneficial to improving the final area positioning effect.

As an optional implementation manner, in step 102, determining analog signal acquisition information corresponding to at least one sampling point in the target region according to the signal source layout scheme and the signal propagation model includes:

determining area structure information corresponding to a target area;

and determining analog signal acquisition information corresponding to at least one sampling point in the target area based on a signal propagation model according to the area structure information and the signal source layout scheme.

Alternatively, the area structure information may include at least one of floor information, barrier information, or other obstacle information in the target area. Optionally, the manner of determining the regional structure information may be determined by an operator after performing field measurement, or may be determined by performing data processing according to a regional map model of the target region. Optionally, the area map model may be a two-dimensional map model or a three-dimensional space model, which is not limited in the present invention.

Optionally, determining analog signal acquisition information corresponding to at least one sampling point in the target region based on the signal propagation model according to the region structure information and the signal source layout scheme, may include the following steps:

determining the signal characteristics of at least one signal source in a target area based on a signal propagation model according to the area structure information and the signal source layout scheme;

and determining analog signal acquisition information corresponding to the sampling point according to the signal characteristics of the signal source and the position of at least one sampling point in the target area.

Optionally, the signal propagation model includes at least one of a free space signal attenuation model, a signal attenuation model considering blocking, and a signal propagation model based on Helmholtz equation.

Optionally, the free space signal attenuation model may be adapted to an environment of a target area with less blockage, at this time, the area structure information may indicate that no wireless signal blockage exists in the target area, and according to a position of any signal source in the signal source layout scheme, the following free space attenuation model may be used to determine a signal characteristic of the signal source:

；

wherein,dis the distance of any sample point from the signal source,d ₀is a fixed distance, which is typically a distance value very close to the signal source, e.g. 1 meter. Wherein,PL(d) AndPL(d ₀) Respectively at a distance from the signal source ofdAndd ₀the signal strength at two points ofnIs the signal attenuation coefficient of the localization scenario corresponding to the target region, which may be determined from empirical or experimental values,x _σis a random error value.

Optionally, the signal attenuation model considering blocking may be suitable for blocking more target area environments, for example, the target area is provided with a plurality of partitions and spans a plurality of floors, at this time, according to the position of any signal source in the signal source layout scheme, the signal characteristics of the signal source may be determined by using the following signal attenuation model considering blocking, by using one or more of partition number information, partition position information, floor number information, and floor position information included in the area structure information:

；

wherein,FAF _ithe wireless signal representing the signal source passes throughiThe attenuation caused by the individual floors is such that,PAF _ithe wireless signal representing the signal source passes throughiThe attenuation generated by the individual compartments is such that,N _fandN _Prespectively the number of floors and the number of compartments of the target area.

Optionally, the signal propagation model based on the Helmholtz equation may be applicable to a target region environment in which the region structure information is relatively complete, at this time, the region structure information may be a relatively complete three-dimensional model of the target region, and for any signal source in the signal source layout scheme, the Helmholtz equation may be used to perform mapping modeling on the wireless signal, so as to determine the signal characteristics of the signal source.

Specifically, the Helmholtz equation can be expressed as:

；

here, thef(x) Is a signal source function of the signal source and E is the wireless signal distribution field. For a given signal sourcef(x) The Helmholtz equation can be solved through a grid method to obtain a wireless signal distribution field corresponding to the signal source, and then the signal intensity from the signal source corresponding to any sampling point in the target area is determined according to the position of the sampling point.

Optionally, according toThe signal characteristic of the signal source and the position of at least one sampling point in the target area determine the analog signal acquisition information corresponding to the sampling point, and the signal intensity from the signal source corresponding to the sampling point can be determined according to the position distance between the sampling point and the signal source and the signal characteristic of the signal source. Optionally, the signal characteristics of each AP of any signal source may be determined through the foregoing embodimentsPL(d) And determining the coordinates of any of the signal sourcesX _AP =(x _AP, y _AP) Then, at any sampling point, according to the known coordinates of the sampling pointX _i =(x _i, y _i) And calculating the distance from the sampling point to the signal source according to the following formula:

；

using the signal source obtained abovePL(d) The signal intensity from the signal source corresponding to the sampling point can be calculated.

Therefore, by implementing the optional implementation mode, the analog signal acquisition information corresponding to the sampling point in the target region can be determined based on the signal propagation model according to the region structure information and the signal source layout scheme, so that the accurate analog signal acquisition information can be determined, an accurate data base can be provided for subsequent analog positioning, and an accurate positioning prediction effect corresponding to the signal source layout scheme can be obtained through subsequent calculation.

As an optional implementation manner, in step 104, determining the predicted positioning accuracy corresponding to the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area includes:

for at least one sub-area in the target area, calculating a positioning error between simulated positioning information and actual position information of at least two sampling points in the sub-area;

determining sub-prediction positioning accuracy corresponding to the sub-region according to the positioning errors of all sampling points in the sub-region;

and determining the predicted positioning accuracy corresponding to the target area according to the sub-predicted positioning accuracy of all the sub-areas in the target area.

Optionally, the sub-regions may be determined by meshing the target region to obtain a plurality of sub-regions, where the meshing may be to divide the target region into a plurality of two-dimensional or three-dimensional mesh regions, or may be to divide the target region into a plurality of regions that are not equal but are physically or socially differentiated according to physical or sociological characteristics of the target region, for example, to divide a human living region into different spaces such as a bathroom, a kitchen, or a living room according to human living activity, or to divide the target region into different regions according to the setting of a partition or the setting of a floor.

Optionally, a manner of determining the sub-prediction positioning accuracy corresponding to the sub-region is similar to the manner of determining the prediction positioning accuracy in the foregoing embodiment, and is not described herein again. Optionally, one or more combinations of the average value, the maximum value, the minimum value, the median value, the variance value, and the standard deviation value of the sub-prediction positioning accuracies of all the sub-regions in the target region, such as weighted summation or weighted averaging, may be determined as the prediction positioning accuracy corresponding to the target region.

In a specific embodiment, the target area is first divided into a grid with a certain density, the positions of a plurality of signal sources in the signal source arrangement scheme in the target area are determined, and a plurality of random sampling points are generated by using a monte carlo method. Then, at the random sampling point in each grid, the signal strength of each signal source of any sampling point is calculated, and the positioning error of each random sampling point isr _iThen, the average positioning error of the grid is calculated:

wherein,Nis the number of random sampling points within the grid. After calculating the average error for all grids, forAccording to the specific signal source layout scheme, the positioning error (namely the positioning precision) of the target area at each position can be predicted, so that precision prediction is provided for the signal source layout scheme of the target area, the positioning precision which can be achieved by all the positions of the target area is known before engineering implementation, the trial and error process in the engineering implementation engineering is avoided, and the cost is saved.

Therefore, by implementing the optional implementation mode, the sub-prediction positioning accuracy corresponding to the sub-region can be determined according to the positioning errors of all the sampling points in the sub-region, and then the prediction positioning accuracy corresponding to the target region can be determined according to the sub-prediction positioning accuracy of all the sub-regions in the target region, so that more accurate prediction positioning accuracy can be determined, and further, data reference can be provided for subsequent operations of selecting a signal source layout scheme or adjusting the signal source layout scheme, and the final region positioning effect can be improved.

Example two

Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a signal source layout determining method according to an embodiment of the present invention. The signal source layout determining method described in fig. 2 is applied to a computing chip, a computing terminal, or a computing server (where the computing server may be a local server or a cloud server) of a signal source layout system. As shown in fig. 2, the signal source layout determining method may include the operations of:

201. and determining the positioning precision requirement corresponding to the target area.

Optionally, the positioning accuracy requirement corresponding to the target area may be a requirement for the positioning accuracy of the whole target area, or a requirement for the positioning accuracy of at least one sub-area of the target area. Alternatively, the positioning accuracy requirement may be that the positioning accuracy of the target area is required to be higher or the positioning error is required to be smaller than a specific threshold.

202. And determining a target signal source layout scheme corresponding to the target area according to the positioning precision requirement and a positioning precision prediction method.

Optionally, specific steps of the positioning accuracy prediction method described in the embodiment of the present invention may refer to technical details of the positioning accuracy prediction method disclosed in the first embodiment, and are not described in detail herein. Optionally, the target signal source layout scheme is a signal source layout scheme in which the predicted positioning accuracy calculated according to the positioning accuracy prediction method can meet the positioning accuracy requirement.

Therefore, the target signal source arrangement scheme corresponding to the target area can be determined according to the positioning precision requirement and the positioning precision prediction method, the preset positioning effect can be simulated by the aid of the positioning precision prediction method, the signal source arrangement scheme meeting the positioning precision requirement can be determined efficiently and accurately, the signal source arrangement efficiency can be improved, and the cost is reduced.

As an optional implementation manner, in step 202, determining a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement and the positioning accuracy prediction method includes:

and determining a target signal source layout scheme corresponding to the target area according to the positioning precision requirement, a dynamic programming algorithm and a positioning precision prediction method.

Optionally, the positioning accuracy requirement may be set as a planning target of a dynamic planning algorithm or an algorithm constraint, and through a combination of the dynamic planning algorithm and a positioning accuracy prediction method, it may be continuously determined whether the predicted positioning accuracy of the current scheme meets the requirement in iterative computation, so that iteration is continuously performed until a target signal source layout scheme meeting the positioning accuracy requirement is computed.

Therefore, by implementing the optional implementation mode, the target signal source layout scheme corresponding to the target area can be determined according to the dynamic programming algorithm and the positioning precision prediction method, so that the signal source layout scheme meeting the positioning precision requirement can be efficiently and accurately determined, the signal source layout efficiency can be improved, and the cost can be reduced.

and determining a target signal source layout scheme corresponding to the target area according to the positioning precision requirement, a neural network model algorithm and a positioning precision prediction method.

Optionally, the related information of the target area may be input into the trained scheme determination neural network model to obtain a plurality of candidate signal source layout schemes, then the predicted positioning accuracy corresponding to each candidate signal source layout scheme is determined according to the positioning accuracy prediction method, and finally the candidate signal source layout scheme whose predicted positioning accuracy meets the positioning accuracy requirement is determined as the target signal source layout scheme. Optionally, the information related to the target area may include one or more of area structure information of the target area, the positioning accuracy requirement information, and signal source number information. Optionally, when the predicted positioning accuracy meets the requirement of the positioning accuracy, a scheme with the minimum number of signal sources or the corresponding lowest laying cost may be selected to be determined as the target signal source laying scheme.

Optionally, the scheme-determining neural network model may be obtained by training a training data set including a plurality of training schemes, where each training scheme at least includes related information of a known region and a corresponding optimal signal source layout scheme.

Therefore, by implementing the optional implementation mode, the target signal source layout scheme corresponding to the target area can be determined by using a neural network model algorithm and a positioning precision prediction method, so that the signal source layout scheme meeting the positioning precision requirement can be efficiently and accurately determined, the signal source layout efficiency can be improved, and the cost can be reduced.

As an optional implementation manner, in the above step, determining a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement, the dynamic planning algorithm, and the positioning accuracy prediction method includes:

determining a cost function as the predicted positioning accuracy corresponding to the target area calculated according to a positioning accuracy prediction method;

and according to a dynamic programming algorithm, iteratively calculating a target signal source layout scheme corresponding to a target area by taking the cost function meeting the positioning precision requirement as a target.

Therefore, by implementing the optional implementation mode, the target signal source layout scheme corresponding to the target area can be iteratively calculated by taking the cost function meeting the positioning precision requirement as a target according to the dynamic programming algorithm, so that the signal source layout scheme meeting the positioning precision requirement can be efficiently and accurately determined, the signal source layout efficiency can be improved, and the cost can be reduced.

As an optional implementation manner, in the above step, according to a dynamic planning algorithm, with a cost function meeting the requirement of positioning accuracy as a target, iteratively calculating a target signal source layout scheme corresponding to a target area includes:

determining the number of a plurality of signal sources, and iteratively calculating an optimal signal source layout scheme and optimal positioning precision corresponding to each signal source number by taking cost function minimization as a target according to a dynamic programming algorithm;

and screening out the signal source layout scheme with the minimum signal source number and the optimal positioning precision meeting the positioning precision requirement from the optimal signal source layout schemes corresponding to all the signal source numbers, and determining the signal source layout scheme as a target signal source layout scheme.

In a specific embodiment, if a target area is required with a positioning accuracy, a dynamic planning algorithm is used to determine an optimal target signal source layout scheme, which can be performed by the following steps:

step 1, dividing a target area into grids with certain density

Step 2, for any signal source number K, assuming the position of each signal source to beP _i={x _i,y _i,i∈1,…K-constructing a cost function:

；

wherein,

is the firstjThe average error within the individual grids is,Mis the total number of meshes of the target area.

Step 3, utilizing a dynamic programming algorithm to iteratively calculate the optimal position of each signal sourceP _i={x _i,y _i,i∈1,…K-minimizing the cost function:

step 4, traversing 1 signal source to the upper limit N of the number of the signal sources according to the step 2-3, and recording the optimization result of the step 3 as two parameters of the traversal for any number k of the signal sources, namely recording the minimum errorf _{min k,}And grid distribution of beaconsP _k。

Step 5, after traversing 1 signal source to the upper limit N of the number of the signal sources, generatingf _{min k,}, k=1,…NAnd corresponding beacon location distributionP _k, k=1,…N。

Suppose that a given positioning accuracy requirement isr _EWe can choose T, where T e (1, … N), such thatf _min,T<∆r _EWhere T is the minimum number of beacons we seek to satisfy a given positioning accuracy, and corresponds toP _TIs the beacon deployment location that we seek to meet the positioning accuracy.

EXAMPLE III

Referring to fig. 3, fig. 3 is a schematic structural diagram of a positioning accuracy prediction apparatus according to an embodiment of the present invention. The positioning accuracy prediction apparatus described in fig. 3 is applied to a computing chip, a computing terminal, or a computing server (where the computing server may be a local server or a cloud server) of a positioning prediction system. As shown in fig. 3, the positioning accuracy prediction apparatus may include:

and the scheme determining module 301 is configured to determine a signal source layout scheme in the target area.

Optionally, the signal source layout scheme may include a layout position of at least one signal source disposed in the target region and signal source information, where the layout position may be a two-dimensional position or a three-dimensional position, and the signal source information may include at least one of signal strength of the signal source, a type of the signal source, a name of the signal source, and signal source equipment information. Optionally, the signal source may be a WIFI signal source, a bluetooth signal source, or other signal transmitting devices that can transmit a wireless signal.

And the analog acquisition module 302 is configured to determine analog signal acquisition information corresponding to at least one sampling point in the target region according to the signal source layout scheme and the signal propagation model.

Optionally, the signal strength of the signal from the signal source, which is acquired at the sampling point in a simulated manner, may be determined according to the signal source distribution scheme, and then the signal strength of the signal from the signal source, which is acquired at the sampling point in a simulated manner, is determined according to the signal propagation model and the position of the sampling point, so as to obtain the simulated signal acquisition information. Optionally, the analog signal acquisition information may include at least one analog acquisition signal strength information for at least one signal source. Optionally, the position of any sampling point may be randomly generated by using a monte carlo method.

And the analog positioning module 303 is configured to determine analog positioning information of the sampling point according to the analog signal acquisition information and a signal positioning algorithm.

And the accuracy determining module 304 is configured to determine the predicted positioning accuracy corresponding to the target area according to the simulated positioning information and the actual position information of at least one sampling point in the target area.

Optionally, the positioning error may be calculated according to the simulated positioning information and the actual position information, and the predicted positioning accuracy corresponding to the target area may be determined according to the positioning errors of all the sampling points. Optionally, the predicted positioning accuracy corresponding to the target area may be determined according to a combination of one or more of the average value, the maximum value, the minimum value, the median value, the variance value and the standard deviation value of the positioning errors of all the sampling points, such as weighted summation or weighted averaging. In one particular arrangement, a sample point is assumed

The actual position information of

And the calculated analog positioning information of the sampling point is

Then it is toThe positioning error of the sample points is:

。

As an optional implementation manner, the specific manner of determining the analog signal acquisition information corresponding to at least one sampling point in the target region by the analog acquisition module 302 according to the signal source layout scheme and the signal propagation model includes:

determining area structure information corresponding to a target area;

；

wherein,dis the distance of any sample point from the signal source,d ₀is a fixed distance which is typically a distance value very close to the signal source, e.g. 1 meter. Wherein,PL(d) AndPL(d ₀) Respectively at a distance from the signal source ofdAndd ₀the signal strength at two points ofnIs the signal attenuation coefficient of the localization scenario corresponding to the target region, which may be determined from empirical or experimental values,x _σis a random error value.

；

Specifically, the Helmholtz equation can be expressed as:

；

Optionally, according to the signal characteristic of the signal source and the position of at least one sampling point in the target region, analog signal acquisition information corresponding to the sampling point is determined, and the signal intensity from the signal source corresponding to the sampling point can be determined according to the position distance between the sampling point and the signal source and the signal characteristic of the signal source. Optionally, the signal characteristics of each AP of any signal source may be determined through the foregoing embodimentsPL(d) And determining the coordinates of any of the signal sourcesX _AP =(x _AP, y _AP) Then, at any sampling point, according to the known coordinates of the sampling pointX _i =(x _i, y _i) And calculating the distance from the sampling point to the signal source according to the following formula:

；

As an optional implementation manner, the specific manner of determining the predicted positioning accuracy corresponding to the target area by the accuracy determining module 304 according to the simulated positioning information and the actual position information of at least one sampling point in the target area includes:

Example four

Referring to fig. 4, fig. 4 is a schematic structural diagram of a signal source layout determining apparatus according to an embodiment of the present invention. The signal source layout determining apparatus depicted in fig. 4 is applied to a computing chip, a computing terminal, or a computing server (where the computing server may be a local server or a cloud server) of a signal source layout system. As shown in fig. 4, the signal source layout determining apparatus may include:

a requirement determining module 401, configured to determine a positioning accuracy requirement corresponding to the target area.

Optionally, the positioning accuracy requirement corresponding to the target region may be a positioning accuracy requirement for the whole target region, or a positioning accuracy requirement for at least one sub-region of the target region. Alternatively, the positioning accuracy requirement may be that the positioning accuracy of the target area is required to be higher or the positioning error is required to be smaller than a specific threshold.

And a scheme determining module 402, configured to determine a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement and the positioning accuracy prediction method.

As an optional implementation manner, the determining module 402 determines, according to the positioning accuracy requirement and the positioning accuracy prediction method, a specific manner of the target signal source arrangement scheme corresponding to the target area, including:

As an optional implementation manner, the specific manner of determining the target signal source layout scheme corresponding to the target area by the scheme determining module 402 according to the positioning accuracy requirement and the positioning accuracy prediction method includes:

Optionally, the related information of the target area may be input into the trained scheme determination neural network model to obtain a plurality of candidate signal source layout schemes, then the predicted positioning accuracy corresponding to each candidate signal source layout scheme is determined according to the positioning accuracy prediction method, and finally the candidate signal source layout scheme whose predicted positioning accuracy meets the positioning accuracy requirement is determined as the target signal source layout scheme. Optionally, the information related to the target area may include one or more of area structure information of the target area, the positioning accuracy requirement information, and signal source number information. Optionally, when the number of candidate signal source arrangement schemes with the predicted positioning accuracy meeting the positioning accuracy requirement is multiple, a scheme with the least number of signal sources or the lowest corresponding arrangement cost may be selected to be determined as the target signal source arrangement scheme.

As an optional implementation manner, the specific manner of determining the target signal source arrangement scheme corresponding to the target area by the scheme determining module 402 according to the positioning accuracy requirement, the dynamic planning algorithm, and the positioning accuracy prediction method includes:

As an optional implementation manner, the specific manner of iteratively calculating the target signal source layout scheme corresponding to the target area by using the cost function to meet the requirement of the positioning accuracy as a target according to the dynamic programming algorithm by the scheme determining module 402 includes:

EXAMPLE five

Referring to fig. 5, fig. 5 is a schematic diagram illustrating another positioning accuracy prediction apparatus according to an embodiment of the present invention. The positioning accuracy prediction apparatus described in fig. 3 is applied to a computing chip, a computing terminal, or a computing server (where the computing server may be a local server or a cloud server) of a positioning prediction system. As shown in fig. 5, the positioning accuracy prediction means may include:

a memory 501 in which executable program code is stored;

a processor 502 coupled to the memory 501;

the processor 502 calls the executable program code stored in the memory 501 for executing all or part of the steps of the positioning accuracy prediction method described in the first embodiment.

EXAMPLE six

Referring to fig. 6, fig. 6 is another signal source layout determining apparatus according to an embodiment of the disclosure. The signal source layout determining apparatus described in fig. 6 is applied to a computing chip, a computing terminal, or a computing server (where the computing server may be a local server or a cloud server) of a signal source layout system. As shown in fig. 6, the signal source layout determining apparatus may include:

a memory 601 in which executable program code is stored;

a processor 602 coupled to a memory 601;

the processor 602 calls the executable program code stored in the memory 601 for executing all or part of the steps of the signal source layout determining method described in the second embodiment.

EXAMPLE seven

The embodiment of the invention discloses a computer-readable storage medium which stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute all or part of the steps of the positioning precision prediction method described in the first embodiment.

Example eight

The embodiment of the invention discloses a computer-readable storage medium which stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute all or part of the steps of the signal source layout determination method described in the second embodiment.

Example nine

The embodiment of the invention discloses a computer program product, which comprises a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to make a computer execute all or part of the steps of the positioning accuracy prediction method described in the first embodiment.

Example ten

An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute all or part of the steps of the signal source layout determining method described in embodiment two.

While certain embodiments of the present disclosure have been described above, other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily have to be in the particular order shown or in sequential order to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus, device, and non-volatile computer-readable storage medium embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and in relation to the description, reference may be made to some portions of the description of the method embodiments.

The apparatus, the device, the nonvolatile computer readable storage medium, and the method provided in the embodiments of the present specification correspond to each other, and therefore, the apparatus, the device, and the nonvolatile computer storage medium also have similar advantageous technical effects to the corresponding method.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical blocks. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is an integrated circuit whose Logic functions are determined by a user programming the Device. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be conceived to be both a software module implementing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.

As will be appreciated by one skilled in the art, the present specification embodiments may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

All the embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

Finally, it should be noted that: the method and apparatus for locating ultrasound volume images of a biological structure disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used for illustrating the technical solutions of the present invention, not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting positioning accuracy, the method comprising:

determining a signal source layout scheme in a target area;

2. The method for predicting the positioning accuracy according to claim 1, wherein the determining the analog signal acquisition information corresponding to at least one sampling point in the target region according to the signal source layout scheme and the signal propagation model comprises:

determining area structure information corresponding to the target area;

and determining analog signal acquisition information corresponding to at least one sampling point in the target region based on a signal propagation model according to the region structure information and the signal source layout scheme.

3. The method of prediction of localization accuracy according to claim 1 or 2, characterized in that the signal propagation model comprises at least one of a free space signal attenuation model, a signal attenuation model taking into account blocking and a signal propagation model based on the Helmholtz equation, and/or the signal localization algorithm comprises at least one of a weight-based localization algorithm, a fingerprint-based localization algorithm and a trilateral intersection-based localization method.

4. The method for predicting the positioning accuracy according to claim 1, wherein the determining the predicted positioning accuracy corresponding to the target area according to the simulated positioning information and the actual position information of at least one of the sampling points in the target area comprises:

for at least one sub-region in the target region, calculating a positioning error between the simulated positioning information and actual position information of at least two sampling points in the sub-region;

determining sub-prediction positioning accuracy corresponding to the sub-region according to the positioning errors of all the sampling points in the sub-region;

5. A method for determining a signal source layout, the method comprising:

determining a positioning precision requirement corresponding to a target area;

determining a target signal source layout scheme corresponding to the target area according to the positioning precision requirement and the positioning precision prediction method according to any one of claims 1 to 4; the target signal source layout scheme is a signal source layout scheme which is calculated according to the positioning precision prediction method and can meet the positioning precision requirement according to the predicted positioning precision.

6. The signal source layout determining method according to claim 5, wherein the determining a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement and the positioning accuracy predicting method according to any one of claims 1 to 4 comprises:

determining a target signal source layout scheme corresponding to the target area according to the positioning precision requirement, a dynamic programming algorithm and the positioning precision prediction method according to any one of claims 1 to 4;

and/or the presence of a gas in the atmosphere,

determining a target signal source layout scheme corresponding to the target area according to the positioning precision requirement, a neural network model algorithm and the positioning precision prediction method according to any one of claims 1 to 4.

7. The signal source layout determining method according to claim 6, wherein the determining a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement, a dynamic planning algorithm, and the positioning accuracy predicting method according to any one of claims 1 to 4 comprises:

determining a cost function as the predicted positioning accuracy corresponding to the target area calculated according to the positioning accuracy prediction method of any one of claims 1 to 4;

and according to a dynamic programming algorithm, with the goal that the cost function meets the positioning precision requirement, iteratively calculating a target signal source layout scheme corresponding to the target area.

8. The signal source layout determining method according to claim 7, wherein the iteratively calculating, according to a dynamic programming algorithm, a target signal source layout scheme corresponding to the target area with the goal that the cost function satisfies the positioning accuracy requirement, includes:

determining the number of a plurality of signal sources, and iteratively calculating an optimal signal source layout scheme and optimal positioning precision corresponding to each signal source number by taking the minimization of the cost function as a target according to a dynamic programming algorithm;

and screening out the signal source layout scheme with the minimum signal source number and the optimal positioning precision meeting the positioning precision requirement from all the optimal signal source layout schemes corresponding to the signal source number, and determining the signal source layout scheme as a target signal source layout scheme.

9. A positioning accuracy prediction apparatus, characterized in that the apparatus comprises:

the scheme determining module is used for determining a signal source distribution scheme in the target area;

10. A signal source placement determination apparatus, the apparatus comprising:

a scheme determining module, configured to determine a target signal source layout scheme corresponding to the target area according to the positioning accuracy requirement and the positioning accuracy prediction method according to any one of claims 1 to 4; the target signal source layout scheme is a signal source layout scheme which is calculated according to the positioning precision prediction method and can meet the positioning precision requirement according to the predicted positioning precision.