CN104333903A - Indoor multi-object positioning system and method based on RSSI (receiver signal strength indicator) and inertia measurement - Google Patents

Abstract

The invention discloses an indoor multi-object positioning system and method based on an RSSI (receiver signal strength indicator) and inertia measurement. The system is provided with three components: a positioning server, positioning anchor anodes and positioners, integrates positioning data of an RSSI method and the positioning data of an inertia measurement method, and then executes dynamic correction on the positions of the positioning anchor nodes and the positioners so as to reduce system positioning errors, improve system positioning precision and enhance system positioning stability. According to the invention, by use of a characteristic that anchor node positions are relatively fixed in a progressive maximum positioning process, through increasing measuring time and reducing the influence of environment accidental factors on the RSSI, the RSSI measuring precision of the anchor nodes is improved. During a positioning measuring process, period correction is performed on the positions of each stage of anchor nodes by use of new range finding signal values so that the stability and the accuracy of the positioning system are improved. Besides, the two methods of a RSSI propagation model and the inertia measurement are utilized for data fusion and positioning, so that the strengths of the two can be integrated, and the positioning precision is higher.

Description

Indoor multi-target positioning system and method based on RSSI and inertial measurement

technical field

The present invention relates to a positioning technology for solving indoor environment, to be precise, relates to an indoor multi-target positioning system and method based on RSSI and inertial measurement, and belongs to the technical field of indoor positioning. the

Background technique

Wireless indoor positioning technology has broad application prospects in indoor navigation, trajectory tracking, mobile office, emergency location reporting, etc., and has become the strategy of Internet service providers such as Google and Foursquare and mobile operators such as China Mobile and China Telecom. Focus on development and become an essential part of today's mobile Internet business. Due to its high cost, slow satellite search speed, and the inability to locate due to obstacles, GPS is not suitable for direct use in indoor positioning, and other alternative methods must be found. The research on indoor positioning originated in the 1990s. The current indoor positioning research includes GSM positioning, infrared positioning (Active Badge), ultrasonic positioning (Cricket System and Active Bat), ultra-wideband (UWB) positioning, radio frequency identification (RFID) positioning (LANDMARK) and so on. The positioning technology used in the present invention includes: RSSI (Receive Signal Strength Indicator) propagation model positioning technology and inertial measurement positioning technology. Below, first introduce the two technical backgrounds:

(1) RSSI propagation model positioning is a classic positioning algorithm, because of its simple calculation, it is still widely used in current wireless positioning systems. This method obtains the distance between the signal sending point and the receiving point indirectly through the propagation model, and then uses the geometric relationship to determine the position of the target. the

The relationship between the received signal strength RSSI of the wireless signal and the transmission distance of the signal can be simply expressed as: RSSI=-(A+10nlgd)+pt; wherein, A is the RSSI value when the signal propagates 1m, n is the path attenuation factor, and d is The distance between the sending end and the receiving end, pt is an influencing factor that obeys a Gaussian distribution with a mean value of 0. According to the above formula, ignoring the pt item, the distance d between the receiving end and the sending end can be calculated from the RSSI value of the receiving end. the

The positioning process in the three-dimensional space of the RSSI propagation model method is described below. the

In three-dimensional space, an unknown node can determine its own coordinates according to the distance information between it and four non-coplanar neighbor reference nodes. Suppose the unknown node E(x,y,z) is based on the reference nodes A(x ₁ ,y ₁ ,z ₁ ), B(x ₂ ,y ₂ ,z ₂ ), C(x ₃ ,y ₃ ,z ₃ ) and D(x ₄ ,y ₄ ,z ₄ ) are respectively d ₁ , d ₂ , d ₃ , d ₄ . Right now: $\begin{array}{c}{d}_1^2={(x-x_1)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_1)}^2+(z-z_1^2)\\ d_2^2={(x-x_2)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_2)}^2+(z-z_2^2)\\ d_3^2={(x-x_3)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_3)}^2+(z-z_3^2)\\ d_4^2={(x-x_4)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_4)}^2+(z-z_4^2)\end{array};$ Then set: $r_i^2=d_i^2-x_i^2-{\mathrm{the\; y}}_i^2-z_i^2{r}_i^2=d_i^2-x_i^2-{\mathrm{the\; y}}_i^2,$ And i=1,2,3,4, then subtract the 4th equation from the first 3 equations respectively, we can get: $\left[\begin{array}{ccc}2x_4-2x_1& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_1& 2z_4-2z_1\\ 2x_4-2x_2& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_2& 2z_4-2z_2\\ 2x_4-2x_3& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_3& 2z_4-2z_3\end{array}\right]\left[\begin{array}{c}x\\ \mathrm{the\; y}\\ z\end{array}\right]=\left[\begin{array}{c}{r}_1^2-r_4^2\\ r_2^2-r_4^2\\ r_3^2-r_4^2\end{array}\right].$ Then set: $Q=\left[\begin{array}{ccc}2x_4-2x_1& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_1& 2z_4-2z_1\\ 2x_4-2x_2& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_2& 2z_4-2z_2\\ 2x_4-2x_3& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_3& 2z_4-2z_3\end{array}\right],$ $\mathrm{\θ}=\left[\begin{array}{c}x\\ \mathrm{the\; y}\\ z\end{array}\right],$ $b=\left[\begin{array}{c}{r}_1^2-r_4^2\\ r_2^2-r_4^2\\ r_3^2-r_4^2\end{array}\right];$ Then the above formula can be converted into: Qθ=b, and the least squares solution is obtained: In the formula, It is the position coordinate of the unknown node E(x, y, z) calculated by the least square method.

From the above analysis, it can be seen that when the RSSI measurement accuracy is higher, the distance calculation between nodes will be more accurate, and the positioning accuracy of the propagation model method will be higher. the

However, RSSI measurements are more closely related to the indoor environment. Compared with the outdoors, the indoor space is small and the layout is complex. Various accidental factors such as walls, doors and windows, electrical appliances, and people's walking will affect signal propagation and cause phenomena such as reflection, refraction, diffraction, and scattering, which in turn lead to wireless transmission. The multipath propagation effect of the signal, therefore, the jitter of the real-time measurement value of RSSI is very large, which makes the error of the real-time positioning method of the RSSI propagation model large. the

However, if the effective sample of RSSI is large enough, the measurement error of RSSI can be reduced through parameter optimization and filtering. Therefore, the longer the sampling time is, the more effective RSSI samples are obtained, the more stable the RSSI propagation model positioning method is, and the higher the accuracy will be. the

(2) Inertial measurement and positioning technology is an autonomous positioning technology that does not depend on external information. By measuring the acceleration and direction of the carrier in the inertial reference system and integrating it with time, the positioning target in the reference coordinate system can be obtained. information such as speed, yaw angle and position. With the popularization of inertial measurement equipment, inertial measurement positioning technology is also increasingly used for indoor positioning. the

Pedestrian dead reckoning algorithm is a commonly used inertial measurement positioning algorithm. The basic principle of this algorithm is to use the original position, displacement and direction to estimate the position of pedestrians. The specific method is: use the product of the number of steps and the step length as the walking distance, and then combine the walking direction to calculate the walking displacement, and then calculate the pedestrian's position after the pedestrian's movement based on the initial position of the pedestrian. the

The process of dead reckoning algorithm can be expressed as: In the formula, (x _n , y _n , z _n ) is the initial position, (x _n+1 , y _n+1 , z _n+1 ) is the position at the next moment, k, l are the number of moving steps, step size, is the moving direction vector in three-dimensional space.

The dead reckoning algorithm of the inertial sensor has the advantages of completely autonomous positioning, only relying on the sensor without being affected by external signals and the environment, and can be very flexible in a short period of time, providing position information to users anytime and anywhere. the

In the dead reckoning algorithm, the number of steps, direction and step length are the three main factors affecting the positioning accuracy. Among them, the number of steps is obtained by analyzing the data collected by the acceleration sensor, the direction can be obtained by the electronic compass, and the step length depends on the It cannot be measured directly, and empirical estimates are generally used. Since the user's step size is very random and variable, and there are errors in the number of steps and direction information obtained from sensor data, the positioning error of the pedestrian dead reckoning algorithm will continue to increase as time increases. increase. the

Contents of the invention

In view of this, the object of the present invention is to provide an indoor multi-target positioning system and method based on RSSI and inertial measurement for solving multi-target positioning in an indoor environment. The present invention combines the characteristics of RSSI long-term positioning stability And inertial navigation positioning technology has the advantages of high short-term positioning accuracy and good continuity, and has better positioning accuracy. the

In order to achieve the above object, the present invention provides an indoor multi-target positioning system based on RSSI (Receive Signal Strength Indicator) and inertial measurement, characterized in that: the system is a combination of RSSI and inertial measurement The positioning data of the method, and dynamically correct the position of the positioning anchor node and the locator, so that the system positioning error is reduced and the stability of the system positioning is increased; the system has three components: a positioning server, a positioning anchor node and a locator ,in:

The positioning server is responsible for calculating the position of the positioning anchor node and the locator according to the positioning measurement information sent by the positioning anchor node and the locator, and sending the positioning result to the locator through the positioning anchor node; it has four components: communication interface , system positioning module, data storage module and data display module;

The positioning anchor node, as the relay node of the two-way communication path between the positioning server and the locator, is not only responsible for sending the operation instructions of the positioning server to the locator; at the same time, it is also used to provide position reference data for the locator to perform measurement operations, And forward the positioning result data to the positioning server; the positioning anchor nodes are divided into multiple levels of anchor nodes according to the order in which they are placed: the positioning anchor nodes with known positions are the initial anchor nodes, the first-level anchor nodes, the second-level anchor nodes and the subsequent Anchor nodes of the corresponding level; the positioning system calculates and determines the position of the next-level anchor node according to the position of the upper-level anchor node: first calculates the position of the first-level anchor node according to the position of the initial anchor node, and then calculates the position of the first-level anchor node according to the position of the first-level anchor node Calculate the position of the second-level anchor node, and so on, to form a multi-level anchor node; each positioning anchor node has three components: communication interface, data storage module and RSSI measurement module;

The locator is responsible for collecting RSSI data and inertial measurement data, sending them to the positioning server, and receiving and displaying the positioning results of the positioning server; it has four components: communication interface, data storage module, sensor module and display module. the

In order to achieve the above object, the present invention also provides a multi-target positioning method using the indoor multi-target positioning system of the present invention, which is characterized in that the positioning data of the two measurement methods of RSSI and inertial measurement are fused , and then dynamically modify the positions of the positioning anchor nodes and locators to improve the positioning accuracy of the system and increase the stability of system positioning; the method includes the following steps:

Step 1. Set the initial position of the positioning anchor node: when starting positioning, first set the initial position of the positioning anchor node in the positioning server, and then input the known position coordinates of the starting anchor node to the positioning server before starting the positioning , and according to the position of the initial anchor node, the position of the positioning anchor node of the following levels is calculated step by step;

Step 2, locate the moving target: when the target moves a certain distance, the locator placed on the target sends the received RSSI value and its own inertial measurement parameters to the positioning server, and the positioning server uses the RSSI value received by the locator The largest top k anchor nodes in , are used as reference nodes, combined with inertial measurement data, to perform data fusion positioning on the locator; among them, the natural number k should be greater than or equal to 4. the

The advantages of the present invention's indoor multi-target positioning system and method based on RSSI and inertial measurement are:

The invention utilizes the feature that the position of the anchor node is relatively fixed in the incremental positioning process, increases the measurement time and reduces the impact of environmental accidental factors on the RSSI, and improves the RSSI measurement accuracy of the anchor node. the

In the positioning measurement process, the present invention uses the new ranging signal value to periodically correct the position of each level of anchor nodes, thereby increasing the stability and accuracy of the positioning system. the

The present invention uses two methods of RSSI propagation model and inertial measurement to perform data fusion positioning, and has better positioning accuracy compared with single RSSI positioning or inertial navigation positioning. the

The innovative key technology of the present invention includes: using the feature that the positions of anchor nodes at all levels are relatively fixed in the incremental positioning process, by increasing the measurement time, reducing the impact of environmental accidental factors on RSSI, and improving the RSSI measurement accuracy of anchor nodes. In the process of positioning measurement, the new ranging signal value is used to periodically correct the position of each level of anchor nodes to increase the stability and accuracy of the positioning system. In a word, the present invention uses the data obtained by the RSSI propagation model and the inertial measurement method to perform fusion positioning, which has better and more stable positioning accuracy than using RSSI positioning or inertial navigation positioning alone. the

Description of drawings

FIG. 1 is a schematic diagram of network structure composition of an indoor multi-target positioning system based on RSSI and inertial measurement according to the present invention. the

Fig. 2 is a schematic diagram of the structural composition of the positioning server in the indoor multi-target positioning system of the present invention. the

Fig. 3 is a schematic diagram of the structural composition of the positioning anchor node in the indoor multi-target positioning system of the present invention. the

Fig. 4 is a schematic diagram of the structural composition of the locator in the indoor multi-target positioning system of the present invention. the

FIG. 5 is a flowchart of the operation steps of the positioning method of the indoor multi-target positioning system based on RSSI and inertial measurement according to the present invention. the

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. the

The invention combines two indoor positioning methods of RSSI propagation model positioning method and inertial measurement, and proposes an indoor multi-target positioning system based on RSSI and inertial measurement. The core idea of the system is to integrate the positioning data of RSSI and inertial measurement methods, and dynamically correct the positions of the positioning anchor node and the locator, so as to reduce the system positioning error and increase the stability of the system positioning. the

Referring to Figures 1 to 4, three parts of the system of the present invention are introduced: a positioning server, a positioning anchor node, and a locator, wherein the positioning anchor nodes can be divided into initial anchor nodes, first-level anchor nodes, and second-level anchor nodes according to the order in which they are placed. Anchor nodes and more. The block diagram of the system is shown in Figure 1. The three components are described below:

(1) Positioning server: responsible for calculating the positions of the positioning anchor node and the locator according to the positioning measurement information sent by the positioning anchor node and the locator, and sending the positioning result to the locator through the positioning anchor node. There are four component modules (see Figure 2): communication interface, system positioning module, data storage module and data display module. The functions of each module of the positioning server are as follows:

The communication interface, as the communication interface for receiving and sending data of the positioning server, uses the WLAN communication protocol to maintain interactive communication with the locator and the positioning anchor node, and completes the sending and receiving function of positioning data. The two-way communication path between the positioning server and the locator uses the positioning anchor node as a relay node. the

The data storage module is used to store the location information received by the network communication module and the location information of each node calculated and generated by the system location module for calling by other modules. the

The system positioning module is used to run a positioning algorithm according to the positioning information of the data storage module, calculate and obtain the position information of each node, and then transmit it to the data storage module. the

The information display module is responsible for reading location information from the data storage module and displaying it to the user. the

(2) Positioning anchor node: As the relay node of the two-way communication path between the positioning server and the locator, it is not only responsible for sending the operation instructions of the positioning server to the locator; it is also used to provide position reference data for the locator to perform positioning. Measurement operation, and forward the positioning result data to the positioning server. Positioning anchor nodes are divided into multiple levels of anchor nodes according to the order in which they are placed: positioning anchor nodes with known positions are initial anchor nodes, first-level anchor nodes, second-level anchor nodes, and subsequent anchor nodes of corresponding levels. The positioning system determines the position of the next-level anchor node based on the position of the upper-level anchor node: first calculate the position of the first-level anchor node according to the position of the initial anchor node, and then calculate the second-level anchor node according to the position of the first-level anchor node. The position of the anchor node, and so on, form a multi-level anchor node. Each positioning anchor node is respectively equipped with three constituent modules (see FIG. 3 ): a communication interface, a data storage module and an RSSI measurement module. The functions of the three modules are introduced as follows:

The communication interface is used as the communication interface for receiving and sending the data of the positioning anchor node, and uses the WLAN communication protocol to maintain the communication interaction with the positioning server and the locator respectively, and complete the sending and receiving function of positioning information. the

The data storage module is used to store the positioning information received by the network communication module and the RSSI measurement position information of each node calculated and generated by the RSSI measurement module, for calling by other modules. the

The RSSI measurement module is responsible for collecting and counting the received RSSI information from other positioning anchor nodes. the

(3) Locator: Responsible for collecting RSSI data and inertial measurement data, sending them to the positioning server, and receiving and displaying the positioning results of the positioning server. There are four component modules (see Figure 4): communication interface, data storage module, sensor module and display module. The functions of the four modules are introduced as follows:

The communication interface is used as the communication interface for data receiving and sending of the locator, and uses the WLAN communication protocol to respectively communicate with the positioning server and the positioning anchor node to complete the sending and receiving function of positioning information. the

The data storage module is used to store the positioning information received by the network communication module and the RSSI measurement information of each node calculated and generated by the RSSI measurement module. the

The sensor has two components: the RSSI measurement unit and the inertial measurement unit, which respectively collect the corresponding position information of the locator: the RSSI measurement unit is responsible for collecting and counting the RSSI information received from other positioning anchor nodes; the inertial measurement module is responsible for collecting the locator The self-measured information includes: moving step length, moving steps, and moving direction angle. the

The information display module is used to read the positioning information from the data storage module, and display the current position and movement track of the locator to the user. the

The multi-target positioning method of the indoor multi-target positioning system based on RSSI and inertial measurement of the present invention, its core idea is mainly: to fuse the positioning data of the two measurement methods of RSSI and inertial measurement, and then locate the anchor node And the position of the locator is dynamically corrected to improve the positioning accuracy of the system and increase the stability of the system positioning. the

Referring to Fig. 5, the following operating steps of the multi-target positioning method of the present invention are introduced:

Step 1. Set the initial position of the positioning anchor node: when starting positioning, first set the initial position of the positioning anchor node in the positioning server, and then input the known position coordinates of the starting anchor node to the positioning server before starting the positioning , and according to the position of the initial anchor node, the position of the positioning anchor node of the subsequent levels is calculated step by step. the

Step 2, locate the moving target: when the target moves a certain distance, the locator placed on the target sends the received RSSI value and its own inertial measurement parameters to the positioning server, and the positioning server uses the RSSI value received by the locator The largest top k anchor nodes in , are used as reference nodes, combined with inertial measurement data, to perform data fusion positioning on the locator; among them, the natural number k should be greater than or equal to 4. the

In this step, using the largest first k anchor nodes in the RSSI values received by the locator as reference nodes, combined with inertial measurement data, the method of data fusion positioning for the locator is weighted by coefficients, according to the following formula: (x ,y,z)=λ ₀ (x _I ,y _I ,z _I )+(1-λ ₀ )(x _R ,y _R ,z _R ) to calculate the position coordinates (x,y, z); Among them, (x _I , y _I , z _I ) is the three-dimensional space position of the node calculated by the pedestrian dead reckoning algorithm according to the inertial navigation measurement, and (x _R , y _R , z _R ) is the positioning calculation using the RSSI propagation model The obtained three-dimensional space position of the node, λ ₀ is the fixed weight coefficient of the inertial navigation measurement position coordinates (x _I , y _I , z _I ).

In this step, combining the inertial measurement data, the method for data fusion positioning of the locator includes the following operations:

(21) Because in the three-dimensional space, the unknown node E(x,y,z) is based on its neighbor reference nodes A(x ₁ ,y ₁ ,z ₁ ), B(x ₂ ,y ₂ , z ₂ ), C(x ₃ ,y ₃ ,z ₃ ) and D(x ₄ ,y ₄ ,z ₄ ) to determine the three-dimensional space coordinates of the formula: Let the four non-coplanar neighbors The distance between the nodes ( _xi , _y , zi ₎ and the unknown node E(x, y, z) is d _i : $\begin{array}{c}{d}_1^2={(x-x_1)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_1)}^2+(z-z_1^2)\\ d_2^2={(x-x_2)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_2)}^2+(z-z_2^2)\\ d_3^2={(x-x_3)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_3)}^2+(z-z_3^2)\\ d_4^2={(x-x_4)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_4)}^2+(z-z_4^2)\end{array};$ Then set: $r_i^2=d_i^2-x_i^2-{\mathrm{the\; y}}_i^2-z_i^2,$ Then subtract the fourth equation from the first three equations to get: $\left[\begin{array}{ccc}2x_4-2x_1& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_1& 2z_4-2z_1\\ 2x_4-2x_2& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_2& 2z_4-2z_2\\ 2x_4-2x_3& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_3& 2z_4-2z_3\end{array}\right]\left[\begin{array}{c}x\\ \mathrm{the\; y}\\ z\end{array}\right]=\left[\begin{array}{c}{r}_1^2-r_4^2\\ r_2^2-r_4^2\\ r_3^2-r_4^2\end{array}\right];$ In the formula, the natural number i is the sequence number of four neighbor nodes that are not coplanar, so its values are: 1, 2, 3 and 4, respectively.

(22) Settings: $Q=\left[\begin{array}{ccc}2x_4-2x_1& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_1& 2z_4-2z_1\\ 2x_4-2x_2& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_2& 2z_4-2z_2\\ 2x_4-2x_3& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_3& 2z_4-2z_3\end{array}\right],$ $\mathrm{\θ}=\left[\begin{array}{c}x\\ \mathrm{the\; y}\\ z\end{array}\right],$ $b=\left[\begin{array}{c}{r}_1^2-r_4^2\\ r_2^2-r_4^2\\ r_3^2-r_4^2\end{array}\right];$ Then the formula on the left can be transformed into: Qθ=b, and the least squares solution can be obtained: Among them, r _i , Q, and b are all intermediate variables in the calculation and derivation process of the formula, is the position coordinates of the unknown node E(x, y, z) calculated by the least square method; and when the RSSI measurement accuracy is higher, the distance calculation between nodes will be more accurate, and the positioning accuracy of the propagation model method will also be higher. higher.

(23) Add and record the position of the new anchor node: if the total number of anchor nodes is less than the maximum value S allowed by the system, set a new anchor node at the current location of the measurement target, and record the newly added anchor node position, The number of anchor nodes is increased by 1. the

(24) Correct the RSSI measurement value of the anchor node: starting from the first-level anchor node, the median value filtering algorithm is used to correct the node RSSI value of each level to locate the anchor node step by step. Among them, the median algorithm filtering algorithm is to collect N effective RSSI values, arrange the N RSSI values in numerical order, and select the RSSI value in the middle as the filtering output, that is: the nth RSSI of the anchor node The median value obtained during correction RSSI _medn =Med(RSSI ₁ , RSSI ₂ , RSSI ₃ ,..., RSSI _N ); wherein, the natural number N is an odd number. If the number of samples collected is larger, the median filtering method can effectively overcome the fluctuation interference caused by accidental factors.

(25) Correcting the position of the anchor node: using the corrected RSSI value in step (24), the positions of the anchor nodes at all levels are corrected step by step according to the anchor node position correction algorithm. Among them, the calculation formula of the anchor node position correction algorithm is: through coefficient weighting, the three-dimensional space coordinates of the anchor node z _n after the nth correction (x _n , y _n , z _n ) = (λ ₀ +ε(n)) (x _I ,y _I ,z _I )+(1-λ ₀ -ε(n))(x _Rn ,y _Rn ,z _Rn ); where (x _I ,y _I ,z _I ) is the used track The calculated three-dimensional space position coordinates of the anchor node, (x _Rn , y _Rn , z _Rn ) is the three-dimensional space position coordinates of the anchor node calculated according to the received signal strength value RSSI _medn after the nth correction and the propagation model method, λ ₀ is the fixed weight coefficient of the inertial navigation measurement coordinates (x _I , y _I , z _I ), and the additional weight coefficient function ε(n) is a decreasing function of the RSSI measurement times n as a variable, and ε(n)<1- λ ₀ ,

(26) The positioning server judges whether an instruction to terminate the positioning measurement is received, and if so, exits the positioning and ends the entire positioning process. Otherwise, return to step 2 and continue to perform the next round of positioning operations. the

The present invention has carried out many implementation tests, and the result of test is successful, has realized the purpose of the invention. the

Claims (9)

1. A positioning system based on RSSI (Receive Signal Strength Indicator) and inertial measurement indoor multi-target positioning system, characterized in that: said system is to fuse the positioning data of RSSI and inertial measurement two measurement methods, and to The position of the positioning anchor node and the locator is dynamically corrected, so that the system positioning error is reduced and the stability of the system positioning is increased; the system has three components: a positioning server, a positioning anchor node and a locator, of which: The positioning server is responsible for calculating the position of the positioning anchor node and the locator according to the positioning measurement information sent by the positioning anchor node and the locator, and sending the positioning result to the locator through the positioning anchor node; it has four components: communication interface , system positioning module, data storage module and data display module; The positioning anchor node, as the relay node of the two-way communication path between the positioning server and the locator, is not only responsible for sending the operation instructions of the positioning server to the locator; at the same time, it is also used to provide position reference data for the locator to perform measurement operations, And forward the positioning result data to the positioning server; the positioning anchor nodes are divided into multiple levels of anchor nodes according to the order in which they are placed: the positioning anchor nodes with known positions are the initial anchor nodes, the first-level anchor nodes, the second-level anchor nodes and the subsequent Anchor nodes of the corresponding level; the positioning system calculates and determines the position of the next-level anchor node according to the position of the upper-level anchor node: first calculates the position of the first-level anchor node according to the position of the initial anchor node, and then calculates the position of the first-level anchor node according to the position of the first-level anchor node Calculate the position of the second-level anchor node, and so on, to form a multi-level anchor node; each positioning anchor node is equipped with three components: communication interface, data storage module and RSSI measurement module; The locator is responsible for collecting RSSI data and inertial measurement data, sending them to the positioning server, and receiving and displaying the positioning results of the positioning server; it has four components: communication interface, data storage module, sensor module and display module. 2. The system according to claim 1, wherein the functions of each component of the positioning server are as follows: The communication interface, as the communication interface for receiving and sending data of the positioning server, uses the WLAN communication protocol to maintain interactive communication with the locator and the positioning anchor node, and completes the function of sending and receiving positioning data; the two-way communication path between the positioning server and the locator is based on Locating anchor nodes as relay nodes; The data storage module is used to store the location information received by the network communication module and the location information of each node calculated and generated by the system location module for calling by other modules; The system positioning module is used to run a positioning algorithm according to the positioning information of the data storage module, calculate and obtain the position information of each node, and then pass it to the data storage module; The information display module is responsible for reading location information from the data storage module and displaying it to the user. 3. The system according to claim 1, wherein the functions of the three components of the positioning anchor node are as follows: The communication interface is used as the communication interface for receiving and sending the data of the positioning anchor node, using the WLAN communication protocol to maintain the communication interaction with the positioning server and the locator respectively, and complete the sending and receiving function of positioning information; The data storage module is used to store the location information received by the network communication module and the RSSI measurement position information of each node calculated and generated by the RSSI measurement module, so as to be called by other modules; The RSSI measurement module is responsible for collecting and counting the received RSSI information from other positioning anchor nodes. 4. The system according to claim 1, characterized in that: the functions of the four components of the locator are as follows: The communication interface is used as the communication interface for data receiving and sending of the locator, and uses the WLAN communication protocol to communicate with the positioning server and the positioning anchor node respectively to complete the sending and receiving function of positioning information; The data storage module is used to store the positioning information received by the network communication module and the RSSI measurement information of each node calculated and generated by the RSSI measurement module; The sensor has two components: the RSSI measurement unit and the inertial measurement unit, which respectively collect the corresponding position information of the locator: the RSSI measurement unit is responsible for collecting and counting the RSSI information received from other positioning anchor nodes; the inertial measurement module is responsible for collecting the locator The self-measured information includes: moving step length, number of moving steps, and moving direction angle; The information display module is used to read the positioning information from the data storage module, and display the current position and movement track of the locator to the user. 5. A multi-target positioning method adopting the indoor multi-target positioning system of claim 1, characterized in that: the positioning data of the two measurement methods of received signal strength indication (RSSI) and inertial measurement are fused, and then the positioning anchor The positions of the nodes and the locator are dynamically corrected to improve the positioning accuracy of the system and increase the stability of the system positioning; the method includes the following steps: Step 1. Set the initial position of the positioning anchor node: when starting positioning, first set the initial position of the positioning anchor node in the positioning server, and then input the known position coordinates of the starting anchor node to the positioning server before starting the positioning , and according to the position of the initial anchor node, the positions of the positioning anchor nodes of the following levels are calculated step by step; Step 2, locate the moving target: when the target moves a certain distance, the locator placed on the target sends the received RSSI value and its own inertial measurement parameters to the positioning server, and the positioning server uses the RSSI value received by the locator The largest top k anchor nodes in , are used as reference nodes, combined with inertial measurement data, to perform data fusion positioning on the locator; among them, the natural number k should be greater than or equal to 4. 6. The method according to claim 5, characterized in that: in the step 2, using the largest first k anchor nodes in the RSSI value received by the locator as reference nodes, combined with the inertial measurement data, the locator is The method of data fusion positioning is weighted by coefficients, according to the following formula: (x,y,z)=λ ₀ (x _I ,y _I ,z _I )+(1-λ ₀ )(x _R ,y _R ,z _R ) calculate the position coordinates (x, y, z); among them, (x _I , y _I , z _I ) is the three-dimensional space position of the node calculated by the dead reckoning algorithm based on the inertial navigation measurement, and (x _R , y _R , z _R ) is the RSSI propagation model The three-dimensional space position of the node obtained by positioning calculation, λ ₀ is the fixed weight coefficient of the inertial navigation measurement position coordinates (x _I , y _I , z _I ). 7. The method according to claim 6, characterized in that: combining the inertial measurement data in the step 2, the method for performing data fusion positioning on the locator includes the following operations: (21) Because in the three-dimensional space, the unknown node E(x,y,z) is based on its neighbor reference nodes A(x ₁ ,y ₁ ,z ₁ ), B(x ₂ ,y ₂ , z ₂ ), C(x ₃ ,y ₃ ,z ₃ ) and D(x ₄ ,y ₄ ,z ₄ ) to determine the three-dimensional space coordinates of the formula: Let the four non-coplanar neighbors The distance between the nodes ( _xi , _y , zi ₎ and the unknown node E(x, y, z) is d _i : $\begin{array}{c}{d}_1^2={(x-x_1)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_1)}^2+(z-z_1^2)\\ d_2^2={(x-x_2)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_2)}^2+(z-z_2^2)\\ d_3^2={(x-x_3)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_3)}^2+(z-z_3^2)\\ d_4^2={(x-x_4)}^2+{(\mathrm{the\; y}-{\mathrm{the\; y}}_4)}^2+(z-z_4^2)\end{array};$ Then set: $r_i^2=d_i^2-x_i^2-{\mathrm{the\; y}}_i^2-z_i^2,$ Then subtract the fourth equation from the first three equations to get: $\left[\begin{array}{ccc}2x_4-2x_1& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_1& 2z_4-2z_1\\ 2x_4-2x_2& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_2& 2z_4-2z_2\\ 2x_4-2x_3& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_3& 2z_4-2z_3\end{array}\right]\left[\begin{array}{c}x\\ \mathrm{the\; y}\\ z\end{array}\right]=\left[\begin{array}{c}{r}_1^2-r_4^2\\ r_2^2-r_4^2\\ r_3^2-r_4^2\end{array}\right];$ In the formula, the natural number i is the serial number of four neighbor nodes that are not coplanar, so its values are: 1, 2, 3 and 4; (22) Settings: $Q=\left[\begin{array}{ccc}2x_4-2x_1& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_1& 2z_4-2z_1\\ 2x_4-2x_2& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_2& 2z_4-2z_2\\ 2x_4-2x_3& 2{\mathrm{the\; y}}_4-2{\mathrm{the\; y}}_3& 2z_4-2z_3\end{array}\right],$ $\mathrm{\&theta;}=\left[\begin{array}{c}x\\ \mathrm{the\; y}\\ z\end{array}\right],$ $b=\left[\begin{array}{c}{r}_1^2-r_4^2\\ r_2^2-r_4^2\\ r_3^2-r_4^2\end{array}\right];$ Then the formula on the left can be transformed into: Qθ=b, and the least squares solution can be obtained: Among them, r _i , Q, and b are all intermediate variables in the calculation and derivation process of the formula, is the position coordinates of the unknown node E(x, y, z) calculated by the least square method; and when the RSSI measurement accuracy is higher, the distance calculation between nodes will be more accurate, and the positioning accuracy of the propagation model method will also be higher. higher; (23) Add and record the position of the new anchor node: if the total number of anchor nodes is less than the maximum value S allowed by the system, set a new anchor node at the current location of the measurement target, and record the newly added anchor node position, Add 1 to the number of anchor nodes; (24) Correcting the anchor node RSSI measurement value: starting from the first-level anchor node, using the median filter algorithm to correct the node RSSI value of the anchor node at each level step by step; (25) Correct the anchor node position: use the RSSI value after step (24) correction, according to the anchor node position correction algorithm, the positions of the anchor nodes at all levels are corrected step by step; (26) The positioning server judges whether an instruction to terminate the positioning measurement is received, and if so, exits the positioning and ends the entire positioning process; otherwise, returns to step 2 and continues to execute the next round of positioning operations. 8. The method according to claim 5, characterized in that: in the step (24), the median algorithm filter algorithm is after collecting N effective RSSI values, and then arranges the N RSSI values according to numerical order, Select the RSSI value in the middle as the filter output, that is, the median value RSSI _medn ＝Med(RSSI ₁ ,RSSI ₂ ,RSSI ₃ ,....,RSSI _N ) obtained during the nth RSSI correction of the anchor node ; Among them, the natural number N is an odd number; if the number of samples collected is larger, the median filtering method can effectively overcome the fluctuation interference caused by accidental factors. 9. The method according to claim 5, characterized in that: in the step (25), the calculation formula of the anchor node position correction algorithm is: by coefficient weighting, the position three-dimensional space of the anchor node z _n after the nth correction Coordinates (x _n ,y _n ,z _n )=(λ ₀ +ε(n))(x _I ,y _I ,z _I )+(1-λ ₀ -ε(n))(x _Rn ,y _Rn , z _Rn ); in the formula, (x _I , y _I , z _I ) are the three-dimensional space position coordinates of the anchor node obtained by using the track calculation, and (x _Rn , y _Rn , z _Rn ) are the The received signal strength value RSSI _medn and the three-dimensional spatial position coordinates of the anchor node calculated by the propagation model method, λ ₀ is the fixed weight coefficient of the inertial navigation measurement coordinates (x _I , y _I , z _I ), and the additional weight coefficient function ε(n ) is a decreasing function about the number of RSSI measurements n as a variable, and ε(n)<1-λ ₀ ,