CN116761254B

CN116761254B - Indoor positioning method, device, communication equipment and storage medium

Info

Publication number: CN116761254B
Application number: CN202311035100.3A
Authority: CN
Inventors: 陈梓荣; 庞涛; 朱先飞; 梁宇杰; 牛思杰
Original assignee: China Telecom Corp Ltd
Current assignee: China Telecom Corp Ltd
Priority date: 2023-08-17
Filing date: 2023-08-17
Publication date: 2023-11-07
Anticipated expiration: 2043-08-17
Also published as: CN116761254A

Abstract

The present application relates to an indoor positioning method, an indoor positioning device, a communication apparatus, a storage medium, a chip and a computer program product. The method comprises the following steps: receiving a transmitting message sent by a base station, wherein the transmitting message comprises initial coordinates of the base station and various base station parameter information of the base station; establishing a first coordinate system according to initial coordinates of a base station; determining the distance between the target object and the base station under the condition that the target object is detected to move; determining signal quality factors of the base station according to various base station parameter information of the base station; determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy; and determining a first coordinate of the target object in a first coordinate system according to the particle filtering strategy and the distance between the target object and the base station. By adopting the method, the particle filtering strategy matched with the basic parameters of the base station can be obtained, and the positioning accuracy is improved.

Description

Indoor positioning method, device, communication equipment and storage medium

Technical Field

The present application relates to the field of wireless communication and terminal technologies, and in particular, to an indoor positioning method, an indoor positioning device, a communication apparatus, a storage medium, a chip, and a computer program product.

Background

With the development of wireless communication and terminal technology, location-based services have emerged. Currently, in an outdoor environment, technologies for performing positioning navigation based on a global positioning system (GPS, global Positioning System) or a cellular network are mature. However, because of more shielding and obstruction to the indoor environment, the signals of the GPS and the cellular network are fragile, so that indoor positioning cannot be realized through the GPS or the cellular network technology.

The conventional algorithm for indoor fusion positioning mostly adopts a particle filtering algorithm, and states of particles in a particle set are predicted to correct the states of the particles in the particle set, so that the particle state with the best state is obtained, and the position of a target object is determined.

However, in the NLOS (Non Line of Sight, non-line-of-sight transmission) scenario, the existing particle filtering technology needs to perform positioning processing on the target object according to the UWB (Ultra-wide band) base station to obtain positioning data of the target object relative to the base station, but due to the many shielding objects in the NLOS scenario, the transmitting signal of the UWB base station may generate refraction, resulting in inaccurate positioning data and poor positioning accuracy.

Disclosure of Invention

The embodiment of the application provides an indoor positioning method, an indoor positioning device, communication equipment, a storage medium and a computer program product, which can improve the accuracy of indoor positioning.

An indoor positioning method, the method comprising:

receiving a transmitting message sent by a base station, wherein the transmitting message comprises initial coordinates of the base station and various base station parameter information of the base station;

establishing a first coordinate system according to the initial coordinates of the base station;

determining a distance between a target object and the base station when movement of the target object is detected;

determining a signal quality factor of the base station according to each base station parameter information of the base station;

determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy;

and determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station.

In one embodiment, before the receiving the downlink message sent by the base station, the method further includes:

acquiring initial coordinates of a target object, and establishing a second coordinate system according to the initial coordinates of the target object;

Determining a second coordinate of the target object in the second coordinate system according to the initial coordinate of the target object and the motion parameter of the target object;

the determining the distance between the target object and the base station comprises:

and determining the distance between the target object and the base station according to the distance noise vector and the second coordinate.

In one embodiment, the base station parameter information includes a first base station parameter, a second base station parameter, a third base station parameter, and a fourth base station parameter, where the first base station parameter is used to characterize a base time slot, the second base station parameter is used to characterize a data frame number, the third base station parameter is used to characterize a frame time, the fourth base station parameter is used to characterize a transmission rate of a data frame,

the determining the signal quality factor of the base station according to the parameter information of each base station of the base station comprises the following steps:

determining a quality factor parameter according to the second base station parameter, the third base station parameter and the fourth base station parameter, wherein the quality factor parameter is positively correlated with the second base station parameter, the third base station parameter and the fourth base station parameter respectively;

And determining a signal quality factor according to the first base station parameter and the quality factor parameter, wherein the signal quality factor is inversely related to the quality factor parameter, and the signal quality factor is positively related to the first base station parameter.

In one embodiment, the determining a particle state correction strategy according to the signal quality factor includes:

determining a signal quality factor threshold interval to which the signal quality factor belongs;

and taking the particle state correction strategy corresponding to the signal quality factor threshold interval as the particle state correction strategy corresponding to the signal quality factor.

In one embodiment, the taking the particle state correction policy corresponding to the signal quality factor threshold interval as the particle state correction policy corresponding to the signal quality factor includes:

when the signal quality factor is in a first threshold interval or a second threshold interval, a first particle state correction strategy is used as a particle state correction strategy corresponding to the signal quality factor, and the first particle state correction strategy is obtained based on a gamma distribution function with a constant;

when the signal quality factor is in a third threshold interval, a second particle state correction strategy is used as a particle state correction strategy corresponding to the signal quality factor, and the second particle state correction strategy is obtained based on a gamma distribution function with a constant and a Gaussian function;

The lower limit value of the third threshold interval is a first signal quality factor, the upper limit value of the third threshold interval is a second signal quality factor, the upper limit value of the first threshold interval is smaller than the first signal quality factor, and the lower limit value of the second threshold interval is larger than the second signal quality factor.

In one embodiment, the determining the distance between the target object and the base station according to the distance noise vector and the second coordinate includes:

obtaining a distance noise vector, wherein the distance noise vector is obtained based on first Gaussian noise;

determining a distance parameter based on the x-axis coordinate, the y-axis coordinate, and the z-axis coordinate in the second coordinate; the distance parameter is positively correlated with an x-axis coordinate, a y-axis coordinate and a z-axis coordinate in the second coordinate respectively;

and determining the distance between the target object and the base station according to the distance noise vector and the distance parameter, wherein the distance is positively correlated with the distance noise vector and the distance parameter.

In one embodiment, the determining the second coordinate of the target object in the second coordinate system according to the initial coordinate of the target object and the motion parameter of the target object includes:

Acquiring a first noise vector corresponding to an x axis in the second coordinate system, a second noise vector corresponding to a y axis in the second coordinate system and the height of the target object, wherein the first noise vector is obtained based on second Gaussian noise, and the second noise vector is obtained based on third Gaussian noise;

determining a target included angle according to the initial coordinate of the target object and the x-axis of the first coordinate system;

determining the step length of the target object through an inertial navigation module;

inputting the first noise vector, the step length of the target object, the x-axis coordinate in the initial coordinate of the target object and the target included angle into an x-axis coordinate prediction model to obtain a predicted x-axis coordinate of the target object in the second coordinate system;

inputting the second noise vector, the step length of the target object, the y-axis coordinate in the initial coordinate of the target object and the target included angle into a y-axis coordinate prediction model to obtain a predicted y-axis coordinate of the target object in the second coordinate system;

and determining a second coordinate of the target object in the second coordinate system according to the predicted x-axis coordinate, the predicted y-axis coordinate and the height of the target object.

An indoor positioning device, the device comprising:

the receiving module is used for receiving a down-sending message sent by a base station, wherein the down-sending message comprises initial coordinates of the base station and various base station parameter information of the base station;

the establishing module is used for establishing a first coordinate system according to the initial coordinates of the base station;

a first determining module, configured to determine a distance between a target object and the base station when movement of the target object is detected;

the second determining module is used for determining the signal quality factor of the base station according to the parameter information of each base station of the base station;

the construction module is used for determining a particle state correction strategy according to the signal quality factor and constructing a particle filtering strategy according to the particle state correction strategy;

and the third determining module is used for determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station.

In one embodiment, the apparatus further comprises:

the first acquisition module is used for acquiring initial coordinates of a target object and establishing a second coordinate system according to the initial coordinates of the target object;

A fourth determining module, configured to determine a second coordinate of the target object in the second coordinate system according to the initial coordinate of the target object and the motion parameter of the target object;

and a fifth determining module, configured to determine a distance between the target object and the base station according to the distance noise vector and the second coordinate.

In one embodiment, each piece of base station parameter information of the base station includes a first base station parameter, a second base station parameter, a third base station parameter and a fourth base station parameter, where the first base station parameter is used to characterize a basic time slot, the second base station parameter is used to characterize a data frame number, the third base station parameter is used to characterize a frame time, the fourth base station parameter is used to characterize a transmission rate of the data frame, and the second determining module 908 is specifically configured to:

In one embodiment, the second determining module is specifically configured to:

In one embodiment, the first determining module is specifically configured to:

In one embodiment, the apparatus further comprises:

the second acquisition module is used for acquiring a first noise vector corresponding to an x axis in the second coordinate system, a second noise vector corresponding to a y axis in the second coordinate system and the height of the target object, wherein the first noise vector is obtained based on second Gaussian noise, and the second noise vector is obtained based on third Gaussian noise;

a sixth determining module, configured to determine a target included angle according to an initial coordinate of the target object and an x-axis of the first coordinate system;

a seventh determining module, configured to determine, by using an inertial navigation module, a step size of the target object;

The first input module is used for inputting the first noise vector, the step length of the target object, the x-axis coordinate in the initial coordinate of the target object and the target included angle into an x-axis coordinate prediction model to obtain a predicted x-axis coordinate of the target object in the second coordinate system;

the second input module is used for inputting the second noise vector, the step length of the target object, the y-axis coordinate in the initial coordinate of the target object and the target included angle into a y-axis coordinate prediction model to obtain a predicted y-axis coordinate of the target object in the second coordinate system;

and an eighth determining module, configured to determine a second coordinate of the target object in the second coordinate system according to the predicted x-axis coordinate, the predicted y-axis coordinate, and the height of the target object.

A communication device, comprising: a receiver and a processor;

the receiver is configured to receive a downlink message sent by a base station, where the downlink message includes initial coordinates of the base station and parameter information of each base station of the base station;

the processor establishes a first coordinate system according to the initial coordinates of the base station; determining a distance between a target object and the base station when movement of the target object is detected; determining a signal quality factor of the base station according to each base station parameter information of the base station; determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy; and determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station.

A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the indoor positioning methods described above.

A chip comprising programmable logic circuitry and/or program instructions capable of performing the steps of any of the indoor positioning methods described above when the chip is in operation.

A computer program product comprising a computer program, characterized in that the computer program when executed by a processor implements the steps of any of the indoor positioning methods described above.

The indoor positioning method, the indoor positioning device, the communication equipment, the storage medium and the computer program product are characterized in that the method, the device, the storage medium and the computer program product are used for receiving a downlink message sent by a base station, wherein the downlink message comprises initial coordinates of the base station and various base station parameter information of the base station; establishing a first coordinate system according to the initial coordinates of the base station; determining a distance between a target object and the base station when movement of the target object is detected; determining a signal quality factor of the base station according to each base station parameter information of the base station; determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy; and determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station. By adopting the method, the particle filtering strategy is adjusted through the signal quality factor of the base station when the transmitted signal of the base station is refracted, and the target object is positioned according to the adjusted particle filtering strategy and the distance between the target object and the base station.

Drawings

FIG. 1 is an application environment diagram of an indoor positioning method in one embodiment;

FIG. 2 is a flow chart of an indoor positioning method according to an embodiment;

FIG. 3 is a flow chart of determining a distance between a target object and a base station in one embodiment;

FIG. 4 is a flow chart of determining a signal quality factor in one embodiment;

FIG. 5 is a flow diagram of determining a particle status correction policy in one embodiment;

FIG. 6 is a flow chart of determining a particle status correction strategy according to another embodiment;

FIG. 7 is a flowchart illustrating a method for determining a distance between a target object and a base station according to another embodiment;

FIG. 8 is a flow diagram of determining a second coordinate of a target object in a second coordinate system in one embodiment;

FIG. 9 is a flowchart illustrating an example of a process of the indoor positioning method according to another embodiment;

FIG. 10 is a block diagram of an indoor positioning device in one embodiment;

fig. 11 is an internal structural diagram of a communication device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

Fig. 1 is a schematic view of an application scenario of an indoor positioning method according to an embodiment of the present application. As shown in fig. 1, this scenario includes a UWB (ultra wide band) base station 100 and a terminal 102. Wherein data transmission is performed between the UWB base station 100 and the terminal 102 via a network.

The terminal 100 may be a wireless terminal, which may be a device that provides voice and/or other traffic data connectivity to a user, or a handheld device with wireless connectivity, or other processing device connected to a wireless modem. A wireless terminal may communicate with one or more core networks via a radio access network (Radio Access Network, RAN for short), which may be mobile terminals such as mobile phones (or "cellular" phones) and computers with mobile terminals, e.g., portable, pocket, hand-held, computer-built-in or vehicle-mounted mobile devices that exchange voice and/or data with the radio access network. A wireless Terminal may also be referred to as a system, subscriber Unit (Subscriber Unit), subscriber Station (Subscriber Station), mobile Station (Mobile Station), mobile Station (Mobile), remote Station (Remote Station), remote Terminal (Remote Terminal), access Terminal (Access Terminal), user Terminal (User Terminal), user Agent (User Agent), user equipment (User Device or User Equipment), without limitation.

The embodiment of the invention can be applied to a wireless local area network (Wireless Local Area Network, WLAN for short), wherein the wireless local area network can comprise a plurality of basic service sets (BSS for short, english: basic Service Set), network nodes in the basic service sets are stations (STA for short), and the stations comprise stations (AP for short, access Point) of Access points and stations (None Access PointStation for short, non-AP STA) of Non-Access points. Each basic service set may include an AP and a plurality of Non-AP stas associated with the AP.

An Access Point class station (AP, english) is also called a wireless Access Point or a hotspot. The AP is an access point for mobile users to enter a wired network, and is mainly deployed in families, buildings and parks, and typically has a coverage radius of several tens meters to hundreds meters, although it may also be deployed outdoors. The AP acts as a bridge connecting the wired network and the wireless network, and is mainly used to connect the wireless network clients together and then access the wireless network to the ethernet. The standard currently adopted by the AP is the IEEE (English: institute of Electrical and Electronics Engineers, chinese: institute of Electrical and electronics Engineers) 802.11 series. Specifically, the AP may be a terminal device or a network device with a WiFi (english: wireless Fidelity, chinese: wireless fidelity) chip. Optionally, the AP may be a device supporting an 802.11ax standard, and further optionally, the AP may be a device supporting multiple WLAN standards such as 802.11ac, 802.11n, 802.11g, 802.11b, and 802.11 a.

The Non-access point type station (None Access Point Station, referred to as Non-AP STA) may be a wireless communication chip, a wireless sensor or a wireless communication terminal. For example: the mobile phone supporting the WiFi communication function, the tablet personal computer supporting the WiFi communication function, the set top box supporting the WiFi communication function, the smart television supporting the WiFi communication function, the smart wearable device supporting the WiFi communication function and the computer supporting the WiFi communication function. Optionally, the station may support 802.11ax, and further optionally, the station supports multiple WLAN systems such as 802.11ac, 802.11n, 802.11g, 802.11b, and 802.11 a.

The STA is typically a client in a WLAN. The STA may be mobile or fixed, and is the most basic component of a wireless local area network. The AP is an access point for mobile users to enter a wired network, and is mainly deployed in families, buildings and parks, and typically has a coverage radius of several tens meters to hundreds meters, although it may also be deployed outdoors. The AP acts as a bridge connecting the wired network and the wireless network, and is mainly used to connect the wireless network clients together and then access the wireless network to the ethernet. In particular, the AP may be a terminal device or a network device with a wireless fidelity (Wireless Fidelity, wiFi) chip. Optionally, the AP may be a device supporting an 802.11ax standard, and further optionally, the AP may be a device supporting multiple WLAN standards such as 802.11ac, 802.11n, 802.11g, 802.11b, and 802.11 a.

Before describing the embodiments of the present application, the technical terms involved in the present application will be explained:

UWB (Ultra-Wideband) base station: the UWB technology is an emerging positioning technology and is characterized by high precision, high reliability, strong anti-interference performance and the like, and is widely applied to the fields of indoor positioning, internet of things, intelligent transportation and the like. The ranging principle of the UWB technology is that a UWB base station is utilized to send radio frequency signals to a target, and receive signals reflected by the target, and the distance between the target and the base station is calculated by measuring the propagation time of the signals. Meanwhile, the distance between the target and the base station is measured by utilizing multiple base stations at the same time, so that the three-dimensional positioning of the target can be realized.

And the inertial navigation module is used for: inertial navigation is an autonomous navigation that does not resort to external forces (receiving signals outside the body). The inertial navigation module is a sensor module applied to a terminal in an inertial navigation system, such as a direction sensor, a gyroscope sensor, an acceleration sensor, a gravity sensor and the like.

The following describes the technical scheme of the present application and how the technical scheme of the present application solves the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

In one embodiment, as shown in fig. 2, an indoor positioning method is provided, and the method is applied to the terminal 102 in fig. 1 for illustration, and includes the following steps:

step 202, receiving a down-sending message sent by the base station.

The message comprises initial coordinates of the base station and various base station parameter information of the base station. The issued message may be a radio frequency signal that is continuously transmitted by the UWB base station based on a certain frequency.

In the embodiment of the application, the terminal can be pre-installed with the positioning application program, and when the positioning application program is started, the terminal receives the issuing information which is sent by the UWB base station and comprises the initial coordinates of the base station and the parameter information of each base station of the base station under the condition that the terminal is positioned in the coverage area of the UWB base station.

It will be appreciated that when the positioning application is started, if the terminal is not within the coverage area of the UWB base station, the terminal will not be able to receive the downlink message sent by the UWB base station.

Step 204, a first coordinate system is established according to the initial coordinates of the base station.

In the embodiment of the application, the terminal obtains the initial coordinates of the base station and each base station parameter information of the base station according to the issued message sent by the base station. Then, the terminal establishes a first coordinate system by taking the initial coordinates of the base station as a first coordinate origin.

In step 206, in case that movement of the target object is detected, a distance between the target object and the base station is determined.

In the embodiment of the application, the terminal acquires the motion state of the target object according to the inertial navigation module. The inertial navigation module comprises hardware modules such as a gyroscope and an accelerometer in the terminal. For the inertial navigation module, any hardware module or algorithm with motion state detection in the terminal can be applied to the inertial navigation module, and the inertial navigation module is not particularly limited in the embodiment of the application.

Then, the terminal determines the distance between the target object and the base station according to the coordinates of the target object before the movement and the initial coordinates of the base station when the movement state of the target object is that the target object moves.

For example, the terminal may determine that the motion state of the target object generates movement for the target object according to the accelerometer, detecting that the acceleration of the target object is not zero.

Step 208, determining the signal quality factor of the base station according to the base station parameter information of the base station.

In the embodiment of the application, the terminal calculates the signal quality factor of the base station according to each basic parameter in the issued message sent by the base station and the signal quality factor calculation strategy under the condition that the motion state of the target object is that the target object moves.

The signal quality factor characterizes the signal intensity of the radio frequency signal sent by the base station, and the refraction condition generated by the radio frequency signal sent by the base station can be determined based on the signal quality factor. For example, the greater the signal quality factor, the greater the signal strength characterizing the radio frequency signal and the less refraction the radio frequency signal emitted by the base station produces.

Step 210, determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy.

In the embodiment of the application, the terminal determines the particle state correction strategy according to the signal quality factor threshold value to which the signal quality factor belongs, and constructs the particle filtering strategy according to the particle state correction strategy.

The particle state correction strategy is used for performing weight correction processing on the particles, for example, correcting the initial weight of the particles according to the initial weight of the particles and the particle state correction strategy.

Step 212, determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station.

In the embodiment of the application, the terminal determines the coordinate information of the target object in the first coordinate system according to the distance between the target object and the base station and the particle filtering strategy, and takes the coordinate information as the first coordinate of the target object in the first coordinate system.

The terminal determines, according to the distance between the target object and the base station and the particle filtering algorithm, one exemplary implementation of the coordinate information of the target object in the first coordinate system as follows:

the terminal generates an initialized particle set comprising a plurality of particles, each particle having an initial coordinate and an initial weight in a first coordinate system. The initial coordinates of each particle may be coordinate information uniformly distributed in the first coordinate system, and the initial weights of each particle are the same.

Illustratively, the particle set is initialized to. The particle group P0 comprises i particles, each particle +>All including the initial coordinates in the first coordinate system (+.>）。

The terminal determines, for each particle in the set of particles, a predicted coordinate of the particle in the first coordinate system based on an initial coordinate of the particle in the first coordinate system and a motion parameter of the target object. Then, the terminal determines the predicted distance between each particle and the base station based on the predicted coordinates of each particle and the distance noise vector.

The terminal takes the distance between the target object and the base station as a reference, assigns a larger weight for particles with a predicted distance between the base station and the target object which is closer to the distance between the base station and the base station according to the distance between the target object and the base station and the predicted distance between each particle and the base station, assigns a smaller weight for particles with a larger difference between the predicted distance between the base station and the target object and the base station, so as to determine the weight of each particle, and performs weighted average processing according to the weight of each particle and the predicted coordinates of each particle in the first coordinate system to obtain a final coordinate, and takes the coordinate as the coordinate of the target object in the first coordinate system.

For example, the terminal may determine a probability density of a predicted distance of each particle from the base station according to a particle state correction policy, and determine a first weight of each particle according to an initial weight of each particle and the probability density of each particle. And then, the terminal performs weight normalization processing on each particle to obtain a second weight after the normalization processing of each particle. For example, for the implementation process of determining the first weight of each particle according to the initial weight of each particle and the probability density of each particle, the following formula may be referred to, and the specific process is as follows:

wherein,first weight representing the ith particle, < ->Represents the initial weight of the ith particle, d (t) represents the distance between the target object and the base station，/>Representing the probability density of the ith particle determined based on the distance between the target object and the base station,/->To initialize the ith particle in the particle set.

Any algorithm capable of determining the probability density according to the distance between the target object and the base station may be applied to the method for determining the probability density according to the distance between the target object and the base station, which is not limited in the embodiment of the present application.

And the terminal carries out resampling processing on each particle according to the second weight of each particle and a system resampling method to obtain a new particle set corresponding to each particle, wherein the new particle set P1 comprises i particles, and each particle comprises a new initial coordinate and a second weight in a first coordinate system. The terminal performs weighted average processing according to the new initial coordinates of each particle in the first coordinate system and the second weight of each particle to obtain a final coordinate, and the final coordinate is taken as the first coordinate of the target object in the first coordinate system. It can be appreciated that the terminal may perform the next resampling process according to the second weight of each particle in the new particle set P1 and the new initial coordinate of each particle in the first coordinate system, so as to improve the obtained final coordinate precision.

In the indoor positioning method, the issuing message sent by the base station is received, wherein the issuing message comprises the initial coordinates of the base station and various base station parameter information of the base station; establishing a first coordinate system according to initial coordinates of a base station; determining the distance between the target object and the base station under the condition that the target object is detected to move; determining signal quality factors of the base station according to various base station parameter information of the base station; determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy; and determining a first coordinate of the target object in a first coordinate system according to the particle filtering strategy and the distance between the target object and the base station. By adopting the method, the particle filtering strategy is adjusted through the signal quality factor of the base station when the transmitted signal of the base station is refracted, and the target object is positioned according to the adjusted particle filtering strategy and the distance between the target object and the base station.

In one embodiment, as shown in fig. 3, before step 202, the method further includes:

Step 302, obtaining initial coordinates of the target object, and establishing a second coordinate system according to the initial coordinates of the target object.

In the embodiment of the application, the terminal obtains the initial coordinates of the target object according to the initial coordinate acquisition strategy, and establishes a second coordinate system by taking the initial coordinates of the target object as the origin of coordinates.

In an exemplary embodiment, when the positioning application is started, the terminal may send positioning request messages to a plurality of surrounding base stations, where each base station may be capable of receiving the positioning request message sent by the terminal, and generate a corresponding positioning feedback message according to the time when the positioning request message is received. And then, the terminal obtains the time difference of the positioning request message sent to each base station by the terminal according to the received positioning feedback messages. The terminal obtains initial coordinates of the terminal according to a UTDOA (uplink time difference of arrival) method, a plurality of time differences and initial coordinates of the base station corresponding to the time differences, and takes the initial coordinates of the terminal as initial coordinates of a target object.

The terminal may also determine the initial coordinates of the terminal, and thus the initial coordinates of the target object, based on the GPS signal or the bluetooth beacon, for example.

The method for determining the initial coordinates of the target object may be obtained by adopting the manner provided in the above exemplary embodiment, and any method capable of performing the initial coordinate assignment or positioning function of the target object may be applied to the present application, which is not specifically limited in the embodiment of the present application.

Step 304, determining the second coordinates of the target object in the second coordinate system according to the initial coordinates of the target object and the motion parameters of the target object.

In the embodiment of the application, the terminal determines the motion parameters of the target object through the inertial navigation module. The motion parameters of the target object may include a step length, a speed, an acceleration, and the like of the target object.

And then, the terminal inputs the initial coordinates of the target object and the motion parameters of the target object into the prediction model to obtain the second coordinates of the target object in the second coordinate system.

Step 212 includes:

step 306, determining the distance between the target object and the base station according to the distance noise vector and the second coordinate.

In the embodiment of the application, the terminal firstly aligns the coordinate axes of the first coordinate system and the second coordinate system, and then calculates the distance between the target object and the base station according to a preset distance calculation strategy, a distance noise vector and the second coordinate.

The distance noise vector is used for correcting the distance between the target object and the base station to obtain the distance between the target object and the base station which is closer to reality.

In this embodiment, the terminal can predict and obtain the second coordinate of the target object in the second coordinate system at the current moment through the initial coordinate of the target object and the motion parameter of the target object, and obtain the distance between the target object and the base station according to the second coordinate and the distance noise vector. Because only one base station is needed to provide initial coordinates in the distance calculation and the distance between the target object and the base station is corrected according to the distance noise vector, the distance between the target object and the base station which is more consistent with reality and more accurate at the current moment can be obtained. The method is convenient for realizing the positioning of the target object based on the distance between the target object and the base station.

In one embodiment, as shown in fig. 4, each piece of base station parameter information of the base station includes a first base station parameter, a second base station parameter, a third base station parameter and a fourth base station parameter, where the first base station parameter is used to characterize a base time slot, the second base station parameter is used to characterize a data frame number, the third base station parameter is used to characterize a frame time, and the fourth base station parameter is used to characterize a transmission rate of the data frame, and step 208 includes:

step 402, determining a quality factor parameter according to the second base station parameter, the third base station parameter and the fourth base station parameter.

Wherein the quality factor parameter is positively correlated with the second base station parameter, the third base station parameter, and the fourth base station parameter, respectively.

In the embodiment of the present application, the implementation manner of determining the quality factor parameter by the terminal according to the second base station parameter, the third base station parameter and the fourth base station parameter may refer to formula (1), and the specific calculation process is as follows:

where J represents a quality factor parameter, F1 represents a second base station parameter, F2 represents a third base station parameter, and F3 represents a fourth base station parameter.

Step 404, determining a signal quality factor according to the first base station parameter and the quality factor parameter.

Wherein the signal quality factor is inversely related to the quality factor parameter. The signal quality factor is positively correlated with the first base station parameter.

In the embodiment of the present application, a terminal determines a signal quality factor according to a first base station parameter and a quality factor parameter by referring to a formula (2), and the specific calculation process is as follows:

wherein Q represents a signal quality factor, C represents a first base station parameter, J represents a quality factor parameter, and log represents a log function.

In this embodiment, the terminal may determine a signal quality factor of the base station based on a base parameter of the base station included in the downlink message sent by the base station, and determine a refraction condition of the radio frequency signal sent by the base station according to the signal quality factor, so as to implement a subsequent particle state correction policy corresponding to the signal quality factor, construct a particle filtering policy, and implement an effect of accurately positioning the target object at the current moment.

In one embodiment, as shown in FIG. 5, step 210 includes:

step 502, determining a signal quality factor threshold interval to which the signal quality factor belongs.

In the embodiment of the application, the terminal can prestore the mapping relation between the signal quality factor threshold interval and the particle state correction strategy. And the terminal determines the signal quality factor threshold interval to which the signal quality factor belongs according to the signal quality factor and each signal quality factor threshold interval.

Illustratively, the first threshold interval is 6dB to 8dB, and the signal quality factor is 6.7dB, the signal quality factor belongs to the first threshold interval.

Step 504, taking the particle state correction strategy corresponding to the threshold interval of the signal quality factor as the particle state correction strategy corresponding to the signal quality factor.

In the embodiment of the application, the terminal uses the particle state correction strategy corresponding to the signal quality factor threshold interval as the particle state correction strategy corresponding to the signal quality factor according to the mapping relation between the pre-stored signal quality factor threshold interval and the particle state correction strategy and the signal quality factor threshold interval to which the signal quality factor belongs.

In this embodiment, the terminal may determine, according to the particle state correction policy corresponding to the signal quality factor, the particle state correction policy corresponding to the refraction condition of the radio frequency signal sent by the base station, so as to facilitate the subsequent accurate positioning of the target object at the current moment according to the refraction condition of the radio frequency signal sent by the base station.

In one embodiment, as shown in FIG. 6, step 504 includes:

step 602, when the signal quality factor is in the first threshold interval or the second threshold interval, using the first particle state correction strategy as the particle state correction strategy corresponding to the signal quality factor.

Wherein the first particle state modification strategy is based on a constant-carrying gamma distribution function.

In the embodiment of the application, when the signal quality factor is in the first threshold interval or the second threshold interval, the terminal takes the first particle state correction strategy as the particle state correction strategy corresponding to the signal quality factor.

For example, the first threshold interval is an interval in which the signal quality factor is smaller than the first signal quality factor, for example, an interval in which the signal quality factor is smaller than 6dB, the second threshold interval is an interval in which the signal quality factor is larger than the second signal quality factor, for example, an interval in which the signal quality factor is larger than 10dB, and the first particle state correction policy corresponding to the first threshold interval and the second threshold interval may refer to formula (3), where the first particle state correction policy is specifically as follows:

formula (3)

Wherein,represents the probability density of the ith particle, +.>The gamma distribution function is represented, x represents the distance noise vector, and c represents a constant. Any function satisfying the gamma distribution can be used instead of the gamma distribution function, and the application is not particularly limited. For the value of c, fine adjustment can be performed according to the positioning accuracy when the embodiment of the application is applied, and the application is not particularly limited to the constant c.

Step 604, when the signal quality factor is in the third threshold interval, the second particle state correction strategy is used as the particle state correction strategy corresponding to the signal quality factor.

The second particle state correction strategy is obtained based on a gamma distribution function with a constant and a Gaussian function.

In the embodiment of the application, when the signal quality factor is in the third threshold interval, the terminal takes the second particle state correction strategy as the particle state correction strategy corresponding to the signal quality factor.

For example, the third threshold interval is an interval in which the signal quality factor is greater than or equal to the first signal quality factor and less than or equal to the second signal factor, for example, an interval in which the signal quality factor is greater than or equal to 6dB and less than or equal to 10dB, and the second particle state correction policy corresponding to the third threshold interval may refer to formula (4), where the second particle state correction policy is specifically as follows:

formula (4)

Wherein,represents the probability density of the ith particle, +.>Representing the Galenic distribution function, < >>Representing a gaussian function, c representing a constant, and x representing a distance noise vector. Any function satisfying the gamma distribution can be used instead of the gamma distribution function, and the application is not particularly limited. For the value of c, fine adjustment can be performed according to the positioning accuracy when the embodiment of the application is applied, and the application is not particularly limited to the constant c.

In this embodiment, the particle state correction policy corresponding to the refraction condition of the radio frequency signal sent by the base station can be determined according to the particle state correction policy corresponding to the threshold to which the signal quality factor belongs, so that the effect of accurately positioning the target object at the current moment can be achieved according to the refraction condition of the radio frequency signal sent by the base station.

In one embodiment, as shown in FIG. 7, step 306 includes:

step 702, a distance noise vector is obtained.

Wherein the distance noise vector is derived based on the first gaussian noise.

In the embodiment of the present application, the terminal acquires a distance noise vector preset in the positioning application program, for example, the distance noise vector may be a first gaussian noise compliant with N (0,0.05).

Wherein N (0,0.05) represents a normal distribution having a mean value of 0 and a standard deviation of 0.05.

In step 704, a distance parameter is determined based on the x-axis coordinate, the y-axis coordinate, and the z-axis coordinate in the second coordinate.

Wherein the distance parameter is positively correlated with the x-axis coordinate, the y-axis coordinate, and the z-axis coordinate, respectively, in the second coordinates.

In the embodiment of the application, the terminal determines the coordinates of the second coordinate of the target object in the first coordinate system according to the x-axis coordinate, the y-axis coordinate, the z-axis coordinate and the initial coordinate of the base station in the second coordinate. The terminal determines the distance parameter according to the coordinate of the second coordinate of the target object in the first coordinate system, and the implementation process of determining the distance parameter can refer to the formula (5), and the specific process is as follows:

wherein D0 represents a distance parameter, x (t) represents an x-axis coordinate of the second coordinate in the first coordinate system, y (t) represents a y-axis coordinate of the second coordinate in the first coordinate system, and z (t) represents a z-axis coordinate of the second coordinate in the first coordinate system.

Step 706, determining the distance between the target object and the base station according to the distance noise vector and the distance parameter.

Wherein, the distance is positively correlated with the distance noise vector and the parameters in the distance.

In the embodiment of the present application, the implementation process of determining the distance between the target object and the base station by the terminal according to the distance noise vector and the distance parameter may refer to formula (6), and the specific process is as follows:

d (t) =d0+v (t) formula (6)

Where D (t) represents the distance between the target object and the base station, D0 represents the distance parameter, and v (t) represents the distance noise vector.

In this embodiment, the terminal is more in accordance with the real environment according to the distance noise vector conforming to the gaussian distribution and the coordinates of the target object at the current moment, and on this basis, the terminal can obtain a more accurate distance between the target object and the base station.

In one embodiment, as shown in FIG. 8, step 304 includes:

step 802, acquiring a first noise vector corresponding to an x axis in a second coordinate system, a second noise vector corresponding to a y axis in the second coordinate system, and a height of a target object.

Wherein the first noise vector is derived based on the second gaussian noise and the second noise vector is derived based on the third gaussian noise.

In the embodiment of the application, the terminal acquires a first noise vector corresponding to an x axis in a preset second coordinate system in the positioning application program, a second noise vector corresponding to a y axis in the preset second coordinate system and the height of a preset target object according to the positioning application program.

Illustratively, the first noise vector may be a second gaussian noise compliant with N (0,0.01), and the second noise vector may be a second gaussian noise compliant with N (0,0.01). The specific values of the first gaussian noise and the second gaussian noise may be set according to practical application by a technician, and the specific values of the first gaussian noise and the second gaussian noise may be the same or different, which is not specifically limited in the embodiment of the present application. The height of the preset target object may be 1.7 meters.

Preferably, for the height of the target object, a specific value of each target object can be obtained according to the height sensor, so that the positioning accuracy is improved.

In step 804, a target angle is determined according to the initial coordinates of the target object and the x-axis of the first coordinate system.

In the embodiment of the application, the terminal determines the target included angle between the initial coordinate of the target object and the x-axis of the first coordinate system according to the initial coordinate of the target object and the x-axis of the first coordinate system and according to an angle calculation strategy.

Any formula capable of calculating the included angle between the point and the straight line can be applied to the angle calculation strategy, the terminal can obtain the target included angle according to the angle data returned by the gyroscope sensor of the terminal, and the embodiment of the application is not particularly limited.

Step 806, determining, by the inertial navigation module, a step size of the target object.

In the embodiment of the application, the terminal can calculate the step length of the target object according to the inertial navigation module, so as to determine the step length of the target object.

For example, the terminal may determine the step size of the target object according to the acceleration in the inertial navigation module and the movement time of the target object to generate movement.

The step size of the target object may be determined in real time at the current time or may be predetermined before indoor positioning is performed. The step length of the target object can be determined by calculating a plurality of sensor groups by adopting other sensors in the inertial navigation module, and the step length of the target object can be calculated before the target object is positioned according to the deep neural network, so that the step length of the target object can be determined. The method for acquiring the step length of the target object is not particularly limited in the embodiment of the application.

And 808, inputting the first noise vector, the step length of the target object, the x-axis coordinate in the initial coordinate of the target object and the target included angle into an x-axis coordinate prediction model to obtain the predicted x-axis coordinate of the target object in the second coordinate system.

In the embodiment of the application, a terminal acquires an x-axis coordinate prediction model. The x-axis coordinate prediction model can be obtained by referring to the formula (7), and is specifically as follows:

formula (7)

Where x (t+1) represents the predicted x-axis coordinate at the current time, x (t) represents the x-axis coordinate in the previous time coordinate of the target object, L represents the step size of the target object,and Wx (t) represents a first noise vector, wherein the first noise vector represents a target included angle between a coordinate of a target object at a previous moment and a first coordinate system.

And then, the terminal inputs the first noise vector, the step length of the target object, the x-axis coordinate in the initial coordinate of the target object and the target included angle into an x-axis coordinate prediction model to obtain the predicted x-axis coordinate of the target object at the current moment, and takes the predicted x-axis coordinate of the target object at the current moment as the predicted x-axis coordinate of the target object in a second coordinate system.

And step 810, inputting the second noise vector, the step length of the target object, the y-axis coordinate in the initial coordinate of the target object and the target included angle into a y-axis coordinate prediction model to obtain the predicted y-axis coordinate of the target object in the second coordinate system.

In the embodiment of the application, a terminal acquires a y-axis coordinate prediction model. The y-axis coordinate prediction model can be obtained by referring to the formula (8), and is specifically as follows:

formula (8)

Where y (t+1) represents the predicted y-axis coordinate at the current time, y (t) represents the y-axis coordinate in the previous time coordinate of the target object, L represents the step size of the target object,and Wy (t) represents a second noise vector, wherein the target included angle between the coordinate of the target object at the previous moment and the first coordinate system is represented.

And then, the terminal inputs the second noise vector, the step length of the target object, the y-axis coordinate in the initial coordinate of the target object and the target included angle into a y-axis coordinate prediction model to obtain the predicted y-axis coordinate of the target object at the current moment, and takes the predicted y-axis coordinate of the target object at the current moment as the predicted y-axis coordinate of the target object in a second coordinate system.

Step 812, determining a second coordinate of the target object in a second coordinate system based on the predicted x-axis coordinate, the predicted y-axis coordinate, and the height of the target object.

In the embodiment of the application, the terminal determines the second coordinate of the target object in the second coordinate system at the current moment according to the predicted x-axis coordinate, the predicted y-axis coordinate and the height of the target object.

Illustratively, the terminal determines that the predicted x-axis coordinate is 70.3, the predicted y-axis coordinate is 13.4, and the height of the target object is 1.7, and then the terminal determines that the second coordinate of the target object in the second coordinate system is (70.3, 13.4,1.7).

It can be understood that, in the case that the target object moves at the next time of the current time, the terminal determines the second coordinate of the target object in the second coordinate system at the next time of the current time according to the second coordinate of the target object in the second coordinate system at the current time and the motion parameter of the target object, and performs the subsequent positioning process based on the second coordinate of the target object in the second coordinate system at the next time of the current time. For the process of performing the subsequent positioning processing according to the second coordinate of the target object in the second coordinate system, in the foregoing embodiment, the defining of the second coordinate of the target object in the second coordinate system at the current moment according to the initial coordinate of the target object and the motion parameter of the target object may be determined, which is not described herein.

After the target object leaves the coverage area of the first base station and enters the coverage area of the second base station, the terminal acquires the initial coordinate of the second base station and establishes a first coordinate system of the second base station.

Similarly, the whole-course positioning processing of the target object can be realized under the environment containing the UWB base station.

The specific implementation process of obtaining the initial coordinates of the second base station and establishing the first coordinate system of the second base station is described in the foregoing embodiment, and is not repeated herein.

In this embodiment, the terminal may determine the coordinates of the target object in the second coordinate system at the current time according to the coordinates of the target object in the second coordinate system at the previous time, the step length of the target object, the first noise vector and the second noise vector. Because the noise vector conforming to Gaussian distribution is introduced, the noise modeling is more conforming to the real environment, and the obtained coordinates of the target object at the current moment in the second coordinate system are more accurate.

In one embodiment, as shown in fig. 9, an example of a processing procedure of the indoor positioning method is further provided, and specific contents include:

in step 901, when a terminal (i.e., a target object) enters the coverage area of a UWB base station, a coordinate axis alignment is performed between a first coordinate system of the UWB base station and a second coordinate system of the terminal.

And step 902, reading output data (namely motion parameters of a target object) of an inertial navigation module of the terminal, and obtaining target included angles between an abscissa and an ordinate of the terminal in a second coordinate system and an x-axis of the first coordinate system.

In step 903, a first noise vector and a second noise vector are obtained, and a prediction model is built based on the first noise vector, the second noise vector, and the motion parameters of the target object.

Step 904, obtaining a distance noise vector, and establishing an observation model according to the distance noise vector and coordinates of the target object in a second coordinate system at the previous moment.

Step 905, calculating a signal quality factor according to each basic parameter of the base station.

Step 906, determining coordinates of the target object in the first coordinate system according to the particle filtering strategy corresponding to the signal quality factor.

The specific limitation in this embodiment is described in detail in the foregoing embodiments, and will not be repeated here.

It should be understood that, although the steps in the flowcharts of fig. 2-8 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-8 may include multiple steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the steps or stages in other steps or other steps.

In one embodiment, as shown in fig. 10, there is provided an indoor positioning device, comprising: a receiving module 1002, a building module 1004, a first determining module 1006, a second determining module 1008, a building module 1010, and a third determining module 1012, wherein:

the receiving module 1002 is configured to receive a downlink message sent by a base station, where the downlink message includes initial coordinates of the base station and information of various base station parameters of the base station.

The establishing module 1004 is configured to establish a first coordinate system according to the initial coordinates of the base station.

A first determining module 1006 is configured to determine a distance between the target object and the base station when movement of the target object is detected.

A second determining module 1008 is configured to determine a signal quality factor of the base station according to each piece of base station parameter information of the base station.

A construction module 1010, configured to determine a particle status modification policy according to the signal quality factor, and construct a particle filtering policy according to the particle status modification policy.

A third determining module 1012 is configured to determine a first coordinate of the target object in the first coordinate system according to the particle filtering policy and a distance between the target object and the base station.

By adopting the indoor positioning device provided by the embodiment of the application, the particle filtering strategy is adjusted through the signal quality factor of the base station when the transmitted signal of the base station is refracted, and the positioning of the target object is performed according to the adjusted particle filtering strategy and the distance between the target object and the base station, and the particle filtering strategy obtained based on the signal quality factor of the base station is more adaptive to the base station, so that the positioning accuracy can be greatly improved.

In one embodiment, the apparatus further comprises:

In one embodiment, each piece of base station parameter information of the base station includes a first base station parameter, a second base station parameter, a third base station parameter and a fourth base station parameter, where the first base station parameter is used to characterize a basic time slot, the second base station parameter is used to characterize a data frame number, the third base station parameter is used to characterize a frame time, the fourth base station parameter is used to characterize a transmission rate of the data frame, and the second determining module 1008 is specifically configured to:

In one embodiment, the second determining module 1008 is specifically configured to:

In one embodiment, the first determining module 1006 is specifically configured to:

In one embodiment, the apparatus further comprises:

For specific limitations of the indoor positioning device, reference may be made to the above limitation of the indoor positioning method, and the description thereof will not be repeated here. The modules in the indoor positioning device can be realized in whole or in part by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a communication device is provided, see fig. 11. Fig. 11 is a schematic structural diagram of a terminal device according to an embodiment of the present invention. The terminal apparatus 1100 shown in fig. 11 includes: at least one processor 1101, memory 1102, at least one network interface 1104, and a user interface 1103. The various components in terminal device 1100 are coupled together by bus system 1105. It is appreciated that bus system 1105 is used to implement the connected communications between these components. The bus system 1105 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration, the various buses are labeled as bus system 1105 in fig. 11. In addition, in embodiments of the present invention, a transceiver 1106 is also included, which may be a plurality of elements, i.e., a transmitter and a receiver, providing a means for communicating with various other apparatus over a transmission medium.

The user interface 1103 may include, among other things, a display, keyboard, or pointing device (e.g., mouse, trackball, touch pad, or touch screen, etc.).

It will be appreciated that memory 1102 in embodiments of the invention can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a Read-only memory (ROM), a programmable Read-only memory (ProgrammableROM, PROM), an erasable programmable Read-only memory (ErasablePROM, EPROM), an electrically erasable programmable Read-only memory (ElectricallyEPROM, EEPROM), or a flash memory, among others. The volatile memory may be a random access memory (RandomAccessMemory, RAM) that acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic random access memory (DynamicRAM, DRAM), synchronous dynamic random access memory (SynchronousDRAM, SDRAM), double data rate synchronous dynamic random access memory (ddr SDRAM), enhanced Synchronous Dynamic Random Access Memory (ESDRAM), synchronous link dynamic random access memory (SynchlinkDRAM, SLDRAM), and direct memory bus random access memory (DirectRambusRAM, DRRAM). The memory 1102 of the systems and methods described in embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.

In some implementations, the memory 1102 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof: an operating system 11021 and application programs 11022.

The operating system 11021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application programs 11022 include various application programs such as a media player (MediaPlayer), a Browser (Browser), and the like for implementing various application services. A program for implementing the method of the embodiment of the present invention may be included in the application program 11022.

In the embodiment of the present invention, by calling a program or an instruction stored in the memory 1102, specifically, a program or an instruction stored in the application program 11022, where the receiver is configured to receive a downlink message sent by a base station, where the downlink message includes initial coordinates of the base station and various base station parameter information of the base station; the processor is used for establishing a first coordinate system according to the initial coordinates of the base station; determining a distance between a target object and the base station when movement of the target object is detected; determining a signal quality factor of the base station according to each base station parameter information of the base station; determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy; and determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station.

Some or all of the methods disclosed in the embodiments of the present invention may also be applied to the processor 1101, or implemented by the processor 1101 in conjunction with other elements (e.g., a transceiver). The processor 1101 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware in the processor 1101 or instructions in software. The processor 1101 described above may be a general purpose processor, a digital signal processor (DigitalSignalProcessor, DSP), an application specific integrated circuit (application specific IntegratedCircuit, ASIC), an off-the-shelf programmable gate array (FieldProgrammableGateArray, FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 1102, and the processor 1101 reads information in the memory 1102 and performs the steps of the method in combination with its hardware.

It is to be understood that the embodiments of the application described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For a hardware implementation, the processing units may be implemented within one or more application specific integrated circuits (ApplicationSpecificIntegratedCircuits, ASIC), digital signal processors (DigitalSignalProcessing, DSP), digital signal processing devices (dspev), programmable logic devices (ProgrammableLogicDevice, PLD), field programmable gate arrays (Field-ProgrammableGateArray, FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.

For a software implementation, the techniques described in embodiments of the present application may be implemented by modules (e.g., procedures, functions, and so on) that perform the functions described in embodiments of the present application. The software codes may be stored in a memory and executed by the processor 1101. The memory may be implemented within the processor 1101 or external to the processor 1101.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.

In one embodiment, a chip is provided that includes programmable logic and/or program instructions that when executed perform the steps of the method embodiments described above.

Embodiments of the present application also provide a computer program product comprising instructions which, when run on a computer, cause the computer to perform the steps of the method embodiments described above.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims

1. An indoor positioning method, comprising:

Determining a signal quality factor of the base station according to each base station parameter information of the base station, wherein the signal quality factor characterizes the signal strength of a radio frequency signal sent by the base station;

determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy, wherein the particle state correction strategy is used for carrying out weight correction processing on particles;

2. The method of claim 1, wherein prior to receiving the downlink message sent by the base station, further comprising:

3. The method of claim 1, wherein the base station parameter information comprises a first base station parameter, a second base station parameter, a third base station parameter, and a fourth base station parameter, wherein the first base station parameter is used for characterizing a base time slot, the second base station parameter is used for characterizing a data frame number, the third base station parameter is used for characterizing a frame time, the fourth base station parameter is used for characterizing a transmission rate of the data frame,

4. A method according to any one of claims 1 to 3, wherein said determining a particle state correction strategy based on said signal quality factor comprises:

5. The method according to claim 4, wherein the step of using the particle state correction strategy corresponding to the signal quality factor threshold interval as the particle state correction strategy corresponding to the signal quality factor comprises:

6. The method of claim 2, wherein determining the distance between the target object and the base station based on the distance noise vector and the second coordinate comprises:

7. The method of claim 2, wherein determining the second coordinates of the target object in the second coordinate system based on the initial coordinates of the target object and the motion parameters of the target object comprises:

8. An indoor positioning device, the device comprising:

the second determining module is used for determining a signal quality factor of the base station according to each base station parameter information of the base station, wherein the signal quality factor characterizes the signal strength of a radio frequency signal sent by the base station;

the construction module is used for determining a particle state correction strategy according to the signal quality factor, constructing a particle filtering strategy according to the particle state correction strategy, and carrying out weight correction processing on particles by the particle state correction strategy;

9. A communication device, comprising: a receiver and a processor;

the processor establishes a first coordinate system according to the initial coordinates of the base station; determining a distance between a target object and the base station when movement of the target object is detected; determining a signal quality factor of the base station according to each base station parameter information of the base station, wherein the signal quality factor characterizes the signal strength of a radio frequency signal sent by the base station; determining a particle state correction strategy according to the signal quality factor, and constructing a particle filtering strategy according to the particle state correction strategy, wherein the particle state correction strategy is used for carrying out weight correction processing on particles; and determining a first coordinate of the target object in the first coordinate system according to the particle filtering strategy and the distance between the target object and the base station.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.