CN113701759A - Indoor synchronous positioning and map construction method and system based on reconfigurable metamaterial - Google Patents
Indoor synchronous positioning and map construction method and system based on reconfigurable metamaterial Download PDFInfo
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Abstract
The invention relates to an indoor synchronous positioning and map building method and system based on a reconfigurable metamaterial. The method comprises the following steps: the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period is taken as a target to obtain a reconfigurable metamaterial reflection coefficient in the current set time period; reconstructing a metamaterial reflection coefficient based on the current set time period to obtain a receiving signal of the current set period; and obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period. The invention can enhance the amplitude of the multipath component in the received signal, thereby improving the precision of positioning and mapping.
Description
Technical Field
The invention relates to the field of positioning and map construction, in particular to an indoor synchronous positioning and map construction method and system based on reconfigurable metamaterial.
Background
The future 6G network needs to provide accurate positioning service, and the synchronous positioning and mapping technology is an important solution for providing the service. In particular, the synchronized positioning and mapping technique uses sensors such as cameras, lasers or antennas to sense the surrounding environment and estimate the location of the mobile device carrying the sensors. In recent years, wireless synchronous positioning and mapping technology using antennas has attracted attention. Unlike the vision synchronous positioning and mapping technology which cannot work in dark areas, the wireless synchronous positioning and mapping technology is not sensitive to illumination conditions. In addition, because the cost of the antenna is low, the cost of the wireless synchronous positioning and mapping technology is also low relatively.
The accuracy of the wireless synchronous positioning and mapping system is influenced by the surrounding wireless environment and depends on high-quality multipath component signals, and the existing wireless synchronous positioning and mapping system can only passively accept the surrounding wireless environment. When the wireless environment is poor, the accuracy of positioning and mapping is poor. For example, when the multipath component in the environment is small, the environment information contained in the received signal is limited, which affects the richness of the map information. In addition, if the amplitude of the multipath component is not very large compared with noise, the estimation of the arrival time and the arrival angle of the multipath component will have relatively large errors due to the influence of noise, and the positioning and mapping accuracy will be reduced.
Disclosure of Invention
The invention aims to provide an indoor synchronous positioning and mapping method and system based on reconfigurable metamaterial, which can enhance the amplitude of multipath components in received signals, thereby improving the positioning and mapping accuracy.
In order to achieve the purpose, the invention provides the following scheme:
an indoor synchronous positioning and map building method based on reconfigurable metamaterial comprises the following steps:
the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period is taken as a target to obtain a reconfigurable metamaterial reflection coefficient in the current set time period;
reconstructing a metamaterial reflection coefficient based on the current set time period to obtain a receiving signal of the current set period;
and obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period.
Optionally, the obtaining, according to the received signal of the current setting period, the position of the mobile device in the current period, the speed of the mobile device in the current setting time period, and the map of the current setting time period by using a positioning and mapping algorithm specifically includes:
obtaining multipath components corresponding to landmark points in the current set time period according to the received signal in the current set time period; the landmark points comprise scattering points, virtual images formed by reflecting the scattering points, the reconfigurable metamaterial and virtual images formed by reflecting the reconfigurable metamaterial;
obtaining the speed of each equipment particle in the current set time period, the position of each equipment particle in the current set time period, the weight of each position in each landmark point set in the current set time period and the weight of each equipment particle in the current set time period according to all scheme sets in the previous set time period, the multipath components corresponding to each landmark point in the current set time period and the weights of each equipment particle in the previous set time period; one said solution set comprising the position and velocity of a device particle and all landmark point sets corresponding to said device particle, a landmark point set comprising all positions of a landmark point;
obtaining the position of the mobile equipment in the current set time period and the speed of the mobile equipment in the current set time period according to the weight of each equipment particle in the current set time period, the position of each equipment particle in the current set time period and the speed of each equipment particle in the current set time period;
and constructing a map of the current set time period according to the weight of each equipment particle of the current set time period and the weight of each position in the landmark point set of the current set time period.
Optionally, the obtaining, according to the received signal of the current set time period, the multipath components corresponding to each landmark point of the current set time period specifically includes:
obtaining all multipath components in the received signal of the current set time period according to the received signal of the current set time period;
inputting all multipath components in the received signal of the current set time period into a neural network respectively to obtain multipath components corresponding to the transmitter and multipath components corresponding to a virtual image reflected by the transmitter;
and calculating the arrival angle of each multipath component according to the received signal, and obtaining multipath components corresponding to scattering points in the environment, multipath components corresponding to virtual images formed by reflecting the scattering points, multipath components corresponding to reconfigurable metamaterials and multipath components corresponding to virtual images formed by reflecting the reconfigurable metamaterials according to the arrival angle of each multipath component.
Optionally, the obtaining, according to all the scheme sets in the previous set time period, the multipath components corresponding to the landmark points in the current set time period, and the weights of the device particles in the previous set time period, the speed of the device particles in the current set time period, the position of the device particles in the current set time period, the weights of the positions in the landmark point sets in the current set time period, and the weights of the device particles in the current set time period specifically includes:
obtaining the speed of each equipment particle in the current set time period and the position of each equipment particle in the current set time period according to the speed of each equipment particle in the previous set time period and the position of each equipment particle in the previous set time period;
calculating the weight of each position in each landmark point set in the current set time period according to each position in each landmark point set in the previous set time period and the multipath component corresponding to each landmark point in each landmark point set in the current set time period;
and obtaining the weight of each equipment particle in the current set time period according to the weight of each equipment particle in the last set time period.
Optionally, the obtaining the position of the mobile device in the current set time period and the speed of the mobile device in the current set time period according to the weight of each device particle in the current set time period, the position of each device particle in the current set time period, and the speed of each device particle in the current set time period specifically includes:
calculating the weight of each equipment particle in the current set time period and the weighted sum of the positions of each equipment particle in the current set time period to obtain the position of the mobile equipment in the current set time period;
and calculating the weighted sum of the weight of each equipment particle in the current set time period and the speed of each equipment particle in the current set time period to obtain the speed of the mobile equipment in the current set time period.
Optionally, the constructing a map of the current set time period according to the weight of each device particle of the current set time period and the weight of each position in the landmark point set of the current set time period specifically includes:
for any landmark point set, determining the product of the weight of each position in the landmark point set in the current setting period and a target device particle as a set product corresponding to the landmark point set, wherein the target device particle is a device particle corresponding to the landmark point set;
for any landmark point, determining the sum of the set products corresponding to all target sets as the position of the landmark point in the current set time period; the target set is a set of all landmark points corresponding to the landmark points;
and constructing a map of the current set time period according to the positions of all the landmark points of the current set time period.
An indoor synchronous positioning and mapping system based on reconfigurable metamaterial comprises:
the reconfigurable material is arranged in an area to be mapped and used for reflecting signals transmitted by the mobile equipment to landmark points and reflecting the signals reflected by the landmark points to the mobile equipment; the mobile device is used for positioning, mapping and configuring the reconfigurable material according to the received signals reflected by the landmark points.
Optionally, the mobile device includes:
the configuration module is used for obtaining the reconfigurable metamaterial reflection coefficient in the current set time period by taking the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period as a target;
the received signal determining module is used for reconstructing a metamaterial reflection coefficient based on the current set time period to obtain a received signal of the current set period;
and the positioning map determining module is used for obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention enhances the amplitude of the multipath component in the received signal by adjusting the reflection coefficient of the reconfigurable metamaterial, thereby improving the positioning and mapping accuracy.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described 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 without inventive exercise.
Fig. 1 is a flowchart of an indoor synchronous positioning and mapping method based on a reconfigurable metamaterial according to an embodiment of the present invention.
Detailed Description
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 derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Assuming that the mobile device moves in a room, the position and the speed of the mobile device may be constantly changed, so that the time line is divided into periods with the duration of δ seconds by the method for indoor synchronized localization and mapping based on reconfigurable metamaterial according to the embodiment, and in each period, the mobile device and the reconfigurable metamaterial cooperate to complete one location and map update, specifically, each period includes four steps: optimization, communication, measurement and updating. Optimization stage the mobile device optimizes the configure xi of the kth period metamaterial according to the previous informationkAnd positioning mapping algorithm fkThereby maximizing system performance. The communication stage is that the mobile equipment communicates with the metamaterial controller, and the xi is configured after the k period is optimizedkSent to the controller, which then sets the configuration of the metamaterial to XIk. In the measurement phase, the mobile device sends a signal s (t). The signal is scattered by obstacles and metamaterials in the environment and then received by a receiving antenna of the mobile device, and the received signal is represented as yk(t), (using the received signal for positioning and mapping). The update phase is that the mobile device will be based on the received signal y obtainedk(t) using a localization mapping algorithm fkTo update the position of the mobile device to obtain the k-th period
Velocity of mobile device
And map
The first step of the kth period requires optimizing the metamaterial configuration xi of the current periodkAnd f for positioning mapping algorithmkTo maximize system performance, the function of the location mapping algorithm is to utilize the received signal yk(t) configuration of xi with metamaterialkPosition of the mobile device in the previous cycle
Velocity of mobile device
And map
The information is updated to obtain the position of the mobile equipment in the period
Velocity of mobile device
And map
The optimization goal is to minimize the positioning error of the mobile device, which can be expressed as:
wherein
Refers to the true position of the mobile device during the k-th cycle. But because of xikAnd fkThe problem is difficult to solve because of mutual coupling, and an error minimization algorithm is provided for effectively solving the problem. This algorithm is divided into two phases. First-stage optimization of xi (xi) of metamaterial configurationkSecond stage optimization positioning mapping algorithm fk. The following are introduced separately:
and (3) metamaterial configuration optimization stage: since the true position of the mobile device is not known for the k-th cycle, it is difficult to directly optimize the objective function of the positioning error. We therefore use the cramer-circle to approximate the positioning error and then minimize the cramer-circle. Thus the original problem is converted into:
wherein
Indicating the device position paCramer-mero bound at the k-th cycle. Since the cramer-perot boundary is non-convex, it can be solved by non-convex algorithms, such as alternative optimization, genetic algorithms, etc.
And (3) positioning and mapping algorithm optimization stage: at this stage, we optimize the parameters of the location mapping algorithm based on the magnitude of the multipath component in the signal. The positioning and mapping algorithm comprises two steps: and data association and position and map estimation steps.
Data correlation this step correlates multipath components in the received signal with the transmitter (PT), the virtual image reflected by the transmitter (VT), scattering points in the environment (PS), the virtual image reflected by the scattering points (VS), the reconfigurable metamaterial (RIS) and the virtual image reflected by the reconfigurable metamaterial (VRIS).
A position and map estimation step, updating the mobile device and the map by using an algorithm based on particle filtering, wherein the parameters of the algorithm are based on the xi part configured after the last stage of optimizationkThe basic idea is to represent the position probability distribution of the mobile device and landmark points by a plurality of particles with different weights. The arrival angle and arrival time of the received multipath component (also can be based on y) in each roundk(t) to update the weights of the particles. Because the larger the amplitude of the multipath component is, the more accurate the estimation of the arrival angle and the arrival time is, the performance of the algorithm can be improved by optimizing the weight of the multipath component when the particle weight is updated.
Setting a total of NapA device particle. Each device particle represents one possible pose (including position and velocity) of the mobile device. Each device particle is subordinate to a plurality of landmark point sets, one set corresponds to one landmark point, one landmark point particle in one landmark point set corresponds to one possible position of the landmark point, and one landmark point set comprises a plurality of landmark point particles. At an initial time, the pose of each device particle is randomly generated, as is the position of the landmark particle. In each period, the weights of all the particles are updated.
As shown in fig. 1, a specific process of the indoor synchronous positioning and mapping method based on reconfigurable metamaterial according to the embodiment includes:
step 101: and obtaining the reconfigurable metamaterial reflection coefficient in the current set time period by taking the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period as a target.
Step 102: and reconstructing the metamaterial reflection coefficient based on the current set time period to obtain a receiving signal of the current set period.
Step 103: and obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period.
In practical application, in step 102, specifically, under the condition that the metamaterial reflection coefficient is reconfigurable in the current set period, the transmitting signal is reflected to obtain the receiving signal in the current set period.
step 1031: obtaining multipath components corresponding to landmark points in the current set time period according to the received signal in the current set time period; the landmark points comprise scattering points, virtual images formed by reflecting the scattering points, the reconfigurable metamaterial and virtual images formed by reflecting the reconfigurable metamaterial.
Step 1032: obtaining the speed of each equipment particle in the current set time period, the position of each equipment particle in the current set time period, the weight of each position in each landmark point set in the current set time period and the weight of each equipment particle in the current set time period according to all scheme sets in the previous set time period, the multipath components corresponding to each landmark point in the current set time period and the weights of each equipment particle in the previous set time period; one set of the solutions includes a position and a velocity of a device particle and all sets of landmark points corresponding to the device particle, one set of landmark points including all positions of one landmark point.
Step 1033: and obtaining the position of the mobile equipment in the current set time period and the speed of the mobile equipment in the current set time period according to the weight of each equipment particle in the current set time period, the position of each equipment particle in the current set time period and the speed of each equipment particle in the current set time period.
Step 1034: and constructing a map of the current set time period according to the weight of each equipment particle of the current set time period and the weight of each position in the landmark point set of the current set time period.
In practical applications, before step 1033, the method further includes:
normalization and resampling. The weights of all device particles and landmark points are normalized and, in addition, landmark points are resampled, the resampling rate being proportional to the weight of landmark points.
In practical application, step 1031 specifically includes:
and obtaining all multipath components in the received signal of the current set time period according to the received signal of the current set time period.
And respectively inputting all multipath components in the received signal of the current set time period into a neural network to obtain multipath components corresponding to the transmitter and multipath components corresponding to the virtual image reflected by the transmitter.
And calculating the arrival angle of each multipath component according to the received signal, and obtaining multipath components corresponding to scattering points in the environment, multipath components corresponding to virtual images formed by reflecting the scattering points, multipath components corresponding to reconfigurable metamaterials and multipath components corresponding to virtual images formed by reflecting the reconfigurable metamaterials according to the arrival angle of each multipath component.
In practical application, the step of inputting all multipath components in the received signal of the current set time period into the neural network respectively to obtain multipath components corresponding to the transmitter and multipath components corresponding to a virtual image reflected by the transmitter specifically includes:
the multipath components corresponding to PT and VT are first found out with one three-layer fully connected neural network and input into the neural network to obtain the multipath components corresponding to PT or VT, and these multipath components are eliminated. (because the corresponding relationship between multipath components and PS, VS, RIS, VRIS is very complex, so it can not be obtained by three-layer fully-connected neural network).
In practical application, the arrival angle of each multipath component is calculated according to the received signal, the multipath component corresponding to a scattering point in the environment, the multipath component corresponding to a virtual image formed by reflecting the scattering point, the multipath component corresponding to the reconfigurable metamaterial and the multipath component corresponding to a virtual image formed by reflecting the reconfigurable metamaterial are obtained according to the arrival angle of each multipath component, and the method specifically comprises the following steps:
according to the angle of arrival of the multipath component (which may be based on the received signal y for the currently set time period)k(t) grouping multipath components having similar angles of arrival into a group, and dividing the multipath components into L groups, each group corresponding to a PS, VS, RIS or VRIS. Since VS and VRIS are virtual images of PS and RIS, we can correlate them using conventional geometric methods. In this step, the RIS is treated as a normal PS. (the multipath components are divided into L groups according to the arrival angle, and by combining the map information and the arrival angle of the multipath components, we can know which one of PS, VS, RIS or VRIS the multipath components correspond to, and as for how to distinguish VS from VRIS, how to distinguish PS from RIS is the traditional geometric method used.) finally, we need to judge which one corresponds to RIS from a plurality of PS. The set of PS, VS, RIS and VRIS is referred to as landmark set.
In practical applications, the determining which one of the PS corresponds to the RIS specifically includes: let the probability that the ith landmark point is RIS in the kth set time period be
Based on Bayesian update, we can get
Wherein the content of the first and second substances,
indicates the probability that the ith landmark point is RIS in the k-1 set time period, alphakRepresenting the amplitude, L, of all multipath componentsiDenotes the ith landmark point, p (α)k|LiIs RIS) means that when the ith landmark point is RIS, α is receivedkThe probability of (c). In each of the set time periods, the time period is set,
the largest landmark point will be considered as the RIS, and at initialization, we set
Wherein N issIs the number of PS.
In practical application, step 1032 specifically includes:
and obtaining the speed of each device particle in the current set time period and the position of each device particle in the current set time period according to the speed of each device particle in the previous set time period and the position of each device particle in the previous set time period.
And calculating the weight of each position in each landmark point set in the current set time period according to each position in each landmark point set in the previous set time period and the multipath component corresponding to each landmark point in each landmark point set in the current set time period.
And obtaining the weight of each equipment particle in the current set time period according to the weight of each equipment particle in the last set time period.
In practical application, the obtaining of the weight of each device particle in the current set time period according to the weight of each device particle in the previous set time period specifically includes:
according to the formula
Calculating the weight of the device particles in the current set time period, wherein,
represents the weight of the ith device particle in the kth set time period,
represents the weight, N, of the ith device particle in the k-1 set time periodL,iRepresenting the number of landmark points in the landmark point set corresponding to the ith device particle, NIp,i,jAnd the number of particles in the jth landmark point set contained in the ith device particle is shown.
In practical applications, step 1033 specifically includes:
and calculating the weight of each equipment particle in the current set time period and the weighted sum of the positions of each equipment particle in the current set time period to obtain the position of the mobile equipment in the current set time period.
And calculating the weighted sum of the weight of each equipment particle in the current set time period and the speed of each equipment particle in the current set time period to obtain the speed of the mobile equipment in the current set time period.
In practical applications, step 1034 specifically includes:
for any landmark point set, determining the product of the weight of each position in the landmark point set in the current setting period and a target device particle as the set product corresponding to the landmark point set, wherein the target device particle is the device particle corresponding to the landmark point set.
For any landmark point, determining the sum of the set products corresponding to all target sets as the position of the landmark point in the current set time period; the target set is a set of all landmark points corresponding to the landmark points.
Constructing a map of the current set time period according to the positions of the landmark points of the current set time period (after obtaining the positions of all PS, RIS, VS, VRIS, the positions of the reflecting points can be reversely deduced by using the traditional geometric method, thereby obtaining the map
)。
In practical applications, the obtaining the speed of each device particle in the current set time period and the position of each device particle in the current set time period according to the speed of each device particle in the previous set time period and the position of each device particle in the previous set time period specifically includes:
and obtaining the speed of each equipment particle in the current set time period according to the speed of each equipment particle in the previous set time period (adding a tiny change eta to the speed of each equipment particle to obtain a new speed of the particle).
And obtaining the position of each equipment particle in the current set time period according to the speed of each equipment particle in the current set time period and the position of each equipment particle in the last set time period.
In practical application, the calculating the weight of each position in each landmark point set in the current set time period according to each position in each landmark point set in the previous set time period and the multipath component corresponding to each landmark point in each landmark point set in the current set time period specifically includes:
and calculating the arrival angle of each multipath component in the current set time period and the time delay of the multipath component in the current set time period according to each position in each landmark point set in the previous set time period.
Calculating the weight of the multipath component corresponding to each landmark point in the current set time period according to the multipath component corresponding to each landmark point in the current set time period; (let the average amplitude of all multipath components be αaveThen the weight of the ith multipath component is ρ i ═ αi/αave。αiRepresenting the magnitude of the ith multipath component, which may be derived from the received signal).
And calculating the weight of each position in the set of landmark points in the current set time period based on the weight of the multipath component corresponding to each landmark point in the current set time period, the arrival angle of each multipath component in the current set time period and the time delay of the multipath component in the current set time period.
In practical application, the calculation of the weight of each position in the set of landmark points in the current set time period based on the weight of the multipath component corresponding to each landmark point in the current set time period, the arrival angle of each multipath component in the current set time period, and the time delay of the multipath component in the current set time period is as follows:
according to the formula
The weight of the location is calculated, wherein,
a weight, rho, representing the mth position in the jth set of landmark points in the ith device particle associated with the nth multipath component for the kth set time periodnThe weight values representing the nth multipath component,
a weight, sigma, representing the mth position in the jth landmark point set in the ith device particle related to the nth multipath component in the set k-1 time periodφTo represent
The standard deviation of (a) is determined,
is the arrival angle of each multipath component in the kth set time period, which is calculated according to the position of the mth landmark point particle in the jth landmark point set of the ith device particle, phikRepresents the actual multipath component arrival angle, σ, of the kth set time periodτTo represent
The standard deviation of (a) is determined,
the time delay of multipath component in the kth set time period is calculated according to the mth position in the jth landmark point set in the ith equipment particle, and taukWhich represents the actual time delay of the multipath component for the kth set time period. SigmaφAnd στIs fixed by built-in programmeParameters, which do not change with the change of the input data.
The embodiment also provides an indoor synchronous positioning and mapping system based on the reconfigurable metamaterial, which corresponds to the method, and the system comprises:
the reconfigurable material is arranged in an area to be mapped and used for reflecting signals transmitted by the mobile equipment to landmark points and reflecting the signals reflected by the landmark points to the mobile equipment; the mobile device is used for positioning, mapping and configuring the reconfigurable material according to received signals reflected by landmark points, the reconfigurable metamaterial is a planar material and is formed by splicing a plurality of reflection units with sub-wavelength sizes, and the reflection coefficient of each reflection unit can be adjusted by applying different bias voltages, so that the reflection coefficient (hereinafter referred to as configuration) of the whole metamaterial can be controlled in a programming mode. Mobile devices are equipped with transmit and receive antennas that can transmit and receive electromagnetic waves. The mobile device can map the surrounding environment by analyzing the electromagnetic waves and locate itself.
As an alternative embodiment, the mobile device and the reconfigurable material may be connected wirelessly.
As an optional implementation, the indoor synchronized localization and mapping system based on reconfigurable metamaterial further comprises a controller, wherein the controller is used for configuring the reconfigurable material according to the configuration.
As an alternative embodiment, the reconfigurable metamaterial is arranged on a wall or ceiling in a room.
As an optional implementation, the mobile device includes:
the configuration module is used for obtaining the reconfigurable metamaterial reflection coefficient in the current set time period by taking the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period as a target;
the received signal determining module is used for reconstructing a metamaterial reflection coefficient based on the current set time period to obtain a received signal of the current set period;
and the positioning map determining module is used for obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period.
The invention has the following specific effects:
1. the reconfigurable metamaterial can change the reflectivity by changing the configuration of the reconfigurable metamaterial, and change the wireless environment by changing the reflectivity of the reconfigurable metamaterial, so that the amplitude of multipath components of received signals is enhanced, and the reconfigurable metamaterial can be used for changing the wireless environment to overcome the limitation of the traditional positioning and mapping algorithm.
2. The reconfigurable metamaterial can introduce a plurality of multipath components, enriches the environmental information contained in the received signals, regulates and controls a wireless channel by utilizing the reconfigurable metamaterial, and improves the quality of the multipath components, so that the estimation precision of the arrival time and the arrival angle of the multipath components can be improved, and the precision of the whole synchronous positioning and mapping system can be improved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. An indoor synchronous positioning and map building method based on reconfigurable metamaterial is characterized by comprising the following steps:
the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period is taken as a target to obtain a reconfigurable metamaterial reflection coefficient in the current set time period;
reconstructing a metamaterial reflection coefficient based on the current set time period to obtain a receiving signal of the current set period;
and obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period.
2. The indoor synchronous positioning and mapping method based on the reconfigurable metamaterial according to claim 1, wherein the map of the position of the mobile device in the current period, the speed of the mobile device in the current set time period and the current set time period is obtained by using a positioning and mapping algorithm according to the received signal in the current set period, and specifically comprises:
obtaining multipath components corresponding to landmark points in the current set time period according to the received signal in the current set time period; the landmark points comprise scattering points, virtual images formed by reflecting the scattering points, the reconfigurable metamaterial and virtual images formed by reflecting the reconfigurable metamaterial;
obtaining the speed of each equipment particle in the current set time period, the position of each equipment particle in the current set time period, the weight of each position in each landmark point set in the current set time period and the weight of each equipment particle in the current set time period according to all scheme sets in the previous set time period, the multipath components corresponding to each landmark point in the current set time period and the weights of each equipment particle in the previous set time period; one said solution set comprising the position and velocity of a device particle and all landmark point sets corresponding to said device particle, a landmark point set comprising all positions of a landmark point;
obtaining the position of the mobile equipment in the current set time period and the speed of the mobile equipment in the current set time period according to the weight of each equipment particle in the current set time period, the position of each equipment particle in the current set time period and the speed of each equipment particle in the current set time period;
and constructing a map of the current set time period according to the weight of each equipment particle of the current set time period and the weight of each position in the landmark point set of the current set time period.
3. The method according to claim 2, wherein the obtaining of the multipath components corresponding to the landmark points in the current set time period according to the received signal in the current set time period specifically comprises:
obtaining all multipath components in the received signal of the current set time period according to the received signal of the current set time period;
inputting all multipath components in the received signal of the current set time period into a neural network respectively to obtain multipath components corresponding to the transmitter and multipath components corresponding to a virtual image reflected by the transmitter;
and calculating the arrival angle of each multipath component according to the received signal, and obtaining multipath components corresponding to scattering points in the environment, multipath components corresponding to virtual images formed by reflecting the scattering points, multipath components corresponding to reconfigurable metamaterials and multipath components corresponding to virtual images formed by reflecting the reconfigurable metamaterials according to the arrival angle of each multipath component.
4. The method according to claim 2, wherein the obtaining of the speed of each device particle in the current set time period, the position of each device particle in the current set time period, the weight of each position in the set of landmark points in the current set time period, and the weight of each device particle in the current set time period according to all the solution sets in the previous set time period, the multipath components corresponding to the landmark points in the current set time period, and the weights of each device particle in the previous set time period specifically comprises:
obtaining the speed of each equipment particle in the current set time period and the position of each equipment particle in the current set time period according to the speed of each equipment particle in the previous set time period and the position of each equipment particle in the previous set time period;
calculating the weight of each position in each landmark point set in the current set time period according to each position in each landmark point set in the previous set time period and the multipath component corresponding to each landmark point in each landmark point set in the current set time period;
and obtaining the weight of each equipment particle in the current set time period according to the weight of each equipment particle in the last set time period.
5. The method according to claim 2, wherein the obtaining of the position of the mobile device in the current set time period and the speed of the mobile device in the current set time period according to the weight of each device particle in the current set time period, the position of each device particle in the current set time period, and the speed of each device particle in the current set time period specifically comprises:
calculating the weight of each equipment particle in the current set time period and the weighted sum of the positions of each equipment particle in the current set time period to obtain the position of the mobile equipment in the current set time period;
and calculating the weighted sum of the weight of each equipment particle in the current set time period and the speed of each equipment particle in the current set time period to obtain the speed of the mobile equipment in the current set time period.
6. The method according to claim 2, wherein the step of constructing the map of the current set time period according to the weight of each device particle of the current set time period and the weight of each position in the landmark point set of the current set time period specifically comprises:
for any landmark point set, determining the product of the weight of each position in the landmark point set in the current setting period and a target device particle as a set product corresponding to the landmark point set, wherein the target device particle is a device particle corresponding to the landmark point set;
for any landmark point, determining the sum of the set products corresponding to all target sets as the position of the landmark point in the current set time period; the target set is a set of all landmark points corresponding to the landmark points;
and constructing a map of the current set time period according to the positions of all the landmark points of the current set time period.
7. An indoor synchronous positioning and mapping system based on reconfigurable metamaterial is characterized by comprising:
the reconfigurable material is arranged in an area to be mapped and used for reflecting signals transmitted by the mobile equipment to landmark points and reflecting the signals reflected by the landmark points to the mobile equipment; the mobile device is used for positioning, mapping and configuring the reconfigurable material according to the received signals reflected by the landmark points.
8. The system of claim 7, wherein the mobile device comprises:
the configuration module is used for obtaining the reconfigurable metamaterial reflection coefficient in the current set time period by taking the minimum Clarmerelor boundary of the position of the mobile equipment in the current set time period as a target;
the received signal determining module is used for reconstructing a metamaterial reflection coefficient based on the current set time period to obtain a received signal of the current set period;
and the positioning map determining module is used for obtaining the position of the mobile equipment in the current period, the speed of the mobile equipment in the current set time period and a map of the current set time period by utilizing a positioning and mapping algorithm according to the received signal in the current set period.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015192745A1 (en) * | 2014-06-19 | 2015-12-23 | 无锡知谷网络科技有限公司 | Method and device for real-time target location and map creation |
| IL250382A0 (en) * | 2017-01-31 | 2017-03-30 | Arbe Robotics Ltd | A radar-based system and method for real-time simultaneous localization and mapping |
| CN106767828A (en) * | 2016-12-29 | 2017-05-31 | 南京邮电大学 | A kind of mobile phone indoor positioning solution |
| CN109239683A (en) * | 2018-08-28 | 2019-01-18 | 天津大学 | The Cramér-Rao lower bound analysis method of the passive MIMO radar in broadband |
| CN109798896A (en) * | 2019-01-21 | 2019-05-24 | 东南大学 | A kind of positioning of Indoor Robot with build drawing method and device |
| CN109978767A (en) * | 2019-03-27 | 2019-07-05 | 集美大学 | The ground laser SLAM drawing method based on multirobot collaboration |
| CN110290491A (en) * | 2019-05-17 | 2019-09-27 | 重庆邮电大学 | A kind of indoor objects localization method based on multipath auxiliary |
| KR20210092757A (en) * | 2018-11-19 | 2021-07-26 | 페이스북 테크놀로지스, 엘엘씨 | Systems and methods for maintaining directional wireless links of mobile devices |
| CN113225275A (en) * | 2021-04-25 | 2021-08-06 | 杭州电子科技大学 | Positioning information assistance-based channel estimation method and system |
-
2021
- 2021-08-27 CN CN202110994066.7A patent/CN113701759A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015192745A1 (en) * | 2014-06-19 | 2015-12-23 | 无锡知谷网络科技有限公司 | Method and device for real-time target location and map creation |
| CN106767828A (en) * | 2016-12-29 | 2017-05-31 | 南京邮电大学 | A kind of mobile phone indoor positioning solution |
| IL250382A0 (en) * | 2017-01-31 | 2017-03-30 | Arbe Robotics Ltd | A radar-based system and method for real-time simultaneous localization and mapping |
| CN109239683A (en) * | 2018-08-28 | 2019-01-18 | 天津大学 | The Cramér-Rao lower bound analysis method of the passive MIMO radar in broadband |
| KR20210092757A (en) * | 2018-11-19 | 2021-07-26 | 페이스북 테크놀로지스, 엘엘씨 | Systems and methods for maintaining directional wireless links of mobile devices |
| CN109798896A (en) * | 2019-01-21 | 2019-05-24 | 东南大学 | A kind of positioning of Indoor Robot with build drawing method and device |
| CN109978767A (en) * | 2019-03-27 | 2019-07-05 | 集美大学 | The ground laser SLAM drawing method based on multirobot collaboration |
| CN110290491A (en) * | 2019-05-17 | 2019-09-27 | 重庆邮电大学 | A kind of indoor objects localization method based on multipath auxiliary |
| CN113225275A (en) * | 2021-04-25 | 2021-08-06 | 杭州电子科技大学 | Positioning information assistance-based channel estimation method and system |
Non-Patent Citations (1)
| Title |
|---|
| HAOBO ZHANG等: "Towards Ubiquitous Positioning by Leveraging Reconfigurable Intelligent Surface", IEEE COMMUNICATIONS LETTERS, vol. 25, no. 1, 10 September 2020 (2020-09-10), pages 284 - 288, XP011829918, DOI: 10.1109/LCOMM.2020.3023130 * |
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