CN105676179A - 433MHz signal based indoor positioning method and system - Google Patents

Abstract

The invention discloses a 433MHz signal based indoor positioning method and system. The method comprises that a positioning sensor network is disposed; a node to be positioned broadcasts a positioning request to a measurement space of the node; reference nodes which receive the positioning request detect whether the signal intensity in the surrounding reach the standard, and at least three effective reference nodes are selected; according to an RSSI value which is sent to the node to be positioned from certain reference node, the distance from the present reference node to the node to be positioned is calculated by utilizing a signal spreading model; according to the positions and distance information of the reference nodes, the position of the node to be positioned is calculated by using a trilateral model; and the positioning precision of the node to be positioned is improved by utilizing an algorithm in which the nodes share an error equally. According to the method and system of the invention, it is not required to establish an indoor offline signal intensity data set by much labor force and time, instead, accurate indoor positioning can be realized by fixing fewer reception nodes indoor, the cost of the indoor positioning system is effectively reduced, and both installation and use are easy.

Description

Indoor positioning method and system based on 433MHz signal

Technical Field

The invention relates to the technical field of indoor positioning, in particular to an indoor positioning method and system based on 433MHz signals.

Background

In recent years, with the development of wireless communication technology, people have an increasing demand for information to be ubiquitous and available at any time. Location services and mobility management are critical issues in order to provide a communication environment to mobile users anywhere and anytime. For outdoor environments, satellite positioning systems (e.g., the global positioning system GPS) are a viable, efficient and economical positioning system that has gained widespread use. However, in the indoor environment where human activities are most frequent, the satellite signals cannot penetrate due to the coverage of buildings, so that the signals transmitted by the satellites cannot be used for indoor positioning. Therefore, in the current wireless sensing research field, it has become a good research direction to provide a high-precision, convenient and feasible indoor positioning system with reasonable price.

As known to people, the working frequency bands of Wi-Fi, Bluetooth, ZigBee and wireless local area networks are all around 2.4GHz, and the signals of the frequency bands are characterized by weak anti-attenuation capacity, short communication distance, poor diffraction capacity and large influence of multipath effect indoors. In contrast, the radio frequency signal in the 433MHz frequency band can compensate for some of the disadvantages of the 2.4GHz signal to some extent, such as strong signal penetration, long transmission distance, and a communication distance of 14-28 km under a visible distance, etc. The excellent characteristic of the 433MHz frequency band can open up a new method for the positioning problem in the wireless sensing field.

Disclosure of Invention

The present invention aims to solve the problems mentioned in the background above by means of a method and system for indoor positioning based on 433MHz signals.

In order to achieve the purpose, the invention adopts the following technical scheme:

an indoor positioning method based on 433MHz signals comprises the following steps:

s1, deploying a positioning sensing network;

s2, broadcasting a positioning request to the measurement space by the node to be positioned;

s3, the reference node receiving the positioning request checks whether the signal intensity of the surrounding environment reaches the standard, and at least three effective reference nodes are selected;

s4, calculating the distance from the current reference node to the node to be positioned by using a signal propagation model according to the RSSI value sent to the node to be positioned by the reference node;

s5, calculating the position of the node to be positioned by using a trilateration model according to the position and distance information of the reference node;

and S6, improving the positioning precision of the node to be positioned by using a node shared error algorithm.

Specifically, the step S1 specifically includes: deploying reference nodes at different positions of a measured space, so that any position in the space is effectively covered by at least three reference nodes which are not on the same straight line, wherein the reference nodes are composed of signal receivers and signal transmitters; setting a measurement space plane on a two-dimensional coordinate system plane, and taking a fixed position as a coordinate origin to determine the position coordinate of a reference node; after the coordinates of the reference node are determined, the coordinate information of the reference node is added to a data packet sent by the reference node.

Specifically, the step S2 specifically includes: when a node to be positioned has a positioning requirement, the node to be positioned broadcasts a positioning request to a measurement space; when the reference node receives the positioning request packet, the reference node needs to perform ambient environment monitoring before sending an information packet to the node to be positioned so as to determine whether the reference node has a packet sending condition: the reference node firstly sends a command for inquiring the current environment, checks whether other reference nodes are sending packets in the surrounding environment, if so, the environment where the current reference node is located is greatly interfered, the reference node is not suitable for immediate sending, and repeats the inquiring process again after waiting for a random time within a specified range; if no interference signal exists, the data packet is immediately sent, after sending, the inquiry process is repeated after waiting for a certain range of random time until receiving a command of finishing sending the packet.

Specifically, the step S3 specifically includes: the reference node which receives the positioning request returns a signal with certain intensity and position information of the reference node to the transmitter, and the node to be positioned judges according to the received data packet of the reference node and selects at least three effective reference nodes; after receiving the positioning request, the reference nodes meeting the conditions, namely the effective reference nodes return a data packet containing RSSI (received signal strength indicator) information, self position information and CRC (cyclic redundancy check) codes to the transmitter; after receiving the data packet, the node to be positioned needs to check the correctness of the data packet: when a node to be positioned enters a monitoring state, judging whether a data packet is received, if so, firstly, carrying out primary verification to verify whether the length of the data packet and a packet header without an RSSI value are the same as the correct format, and if not, discarding the data packet; if the data packet is the same as the data packet, performing secondary check, namely removing the packet header, checking whether the data information of the data packet is correct by using CRC, if not, discarding the data packet, if so, storing the data packet data and recording a corresponding label value, and counting the number of the received nodes; and ending the process until the number of the nodes reaches the standard, otherwise, continuing to receive the data packet.

Specifically, the step S104 specifically includes: calculating the distance between the current reference node and the node to be positioned according to the RSSI value; the Received Signal Strength (RSSI) is a numerical value indicating the energy of electromagnetic waves in the current medium, and the electromagnetic waves have path loss in the transmission process, so that the RSSI value decreases with the increase of the distance, therefore, the distance corresponding to the node can be judged according to the signal strength, that is, the average path consumption is a function of the distance:

$\stackrel{\‾}{PL}\left(d\right)\∝{\left(\frac{d}{d_0}\right)}^n$

wherein,is the average path consumption; n is a path consumption index, which represents the speed of path consumption with increasing distance, in relation to the surroundings and obstacles; d₀Is a reference distance in meters; d is the distance between the transmitting end and the receiving end, and the unit is meter; taking logarithm on two sides of the equation of the formula, and converting the logarithm into a linear form; absolute average path consumption, defined as transmitter-to-reference distance d₀Plus the additional path consumption described in equation (a):

$\stackrel{\‾}{PL}\left(d\right)\[dB\]=\stackrel{\‾}{PL}\left(d_0\right)\[dB\]+10\×n\×\lg \left(\frac{d}{d_0}\right)$

selecting a reference distance d₀Is 1 meter and assumesThe average energy received when the transmitter reaches the reference distance in free space propagation is only expressed in the formula when the distance is d; however, when the distance is constant, due to the factors inherent in the environment, the signal value received at different times is a random quantity, the random quantity satisfies the lognormal distribution, and it satisfies the gaussian distribution in dB, that is, the complete wireless signal propagation attenuation model is:

$\stackrel{\‾}{PL}\left(d\right)\[dB\]=\stackrel{\‾}{PL}\left(d_0\right)\[dB\]+10\×n\×\lg \left(\frac{d}{d_0}\right)+X_{\mathrm{\δ}}$

wherein, X Is a gaussian distribution function with standard deviation σ, in dB, and σ depends on the current environment.

Specifically, the step S5 specifically includes: assuming that the coordinate position of the node to be positioned is (x)₀,y₀) The coordinate of the ith (i is more than or equal to 1 and less than or equal to n) reference node is (x)_i,y_i) D 'is the distance estimated value calculated between the node to be positioned and the reference node'_i(ii) a Let d_iIs the true euclidean distance to the ith reference node, i.e.:

$d_i=\sqrt{{(x_i-x_0)}^2+{(y_i-y_0)}^2}$

the error between the calculated distance and the true distance can be expressed as ρ_i＝d′_i-d_i(ii) a Due to errors in the calculation, in practical cases ρ_iTypically a non-zero value; to make it possible toMinimum, using least square method to solve the coordinate (x) of node to be positioned₀,y₀) (ii) a Therefore, the positioning problem can be converted into a numerical solution problem of an over-determined linear equation set, and the square sum of the above equation is reordered to obtain n equations similar to the following equation:

$2x_0{x}_i+2y_0{y}_i-(x_0^2+y_0^2)=x_i^2+y_i^2-d_i^2$

then, the other equations (1 ≦ i < n) are sequentially subtracted from the ith ≦ n equation of the above formula, which can give n-1 equations as shown in the following formula:

$\left\{\begin{array}{c}2(x_1-x_n)x_0+2(y_1-y_n)y_0=x_1^2+y_1^2-d_1^2-(x_n^2+y_n^2-d_n^2)\\ .\\ .\\ .\\ 2(x_i-x_n)x_0+2(y_i-y_n)y_0=x_i^2+y_i^2-d_i^2-(x_n^2+y_n^2-d_n^2)\\ .\\ .\\ .\\ 2(x_{n-1}-x_n)x_0+2(y_{n-1}-y_n)y_0=x_{n-1}^2+y_{i-1}^2-d_{i-1}^2-(x_n^2+y_n^2-d_n^2)\end{array}\right.$

wherein, the left side of the equation set is known quantity, and the right side of the equation set is only x₀And y₀Unknown, and others are known parameters, from which a linear relationship is derived:

Ax＝B

where A is the (n-1) × 2 matrix and the second of the matrixⁱThe row is [2 (x)_i-x_n)2(y_i-y_n)](ii) a B is an n-1 column vector whose i term isx is a column vector [ x ] of positioning node coordinates₀y₀]^T(ii) a Since the inter-node distance value d ' estimated from the signal attenuation model often deviates from the true distance value d to some extent, the estimated value d ' is used '_iInstead of d_iInstead of B, B ' is calculated such that the least squares method is used to solve for an estimated x such that | Ax ' -B ' | purple calculation²The minimum, i.e. solving for the column vector x' is formulated as:

x′＝(A^TA)^-1A^TB′。

specifically, the step S6 specifically includes: the criterion function of the robust M estimation isBy selecting a proper rho (), the influence of the gross error on the function can be made as much as possibleThe method can be small so as to eliminate the influence of the method, so that the solved unknown parameters are close to the true value as much as possible, and the unknown parameters cannot deviate from the true value too much due to the existence of gross errors; the multivariable function is obtained by taking an extreme value condition:

wherein, P is a weight coefficient matrix,the function is the derivative of ρ () with the final unknown parameter

$\hat{X}={\left(A^{T}PA\right)}^{-1}{A}^{T}PB$

Selecting Tukey double-whole method for robust estimation, wherein the method belongs to M estimation with elimination areas, and the criterion function is as follows:

$\mathrm{\&rho;}\left(e_i\right)=\left\{\begin{array}{cc}\&lsqb;1-{(1-{e_i}^2)}^3\&rsqb;/6,& \left|e_i\right|\&le;1\\ 1/6,& \left|e_i\right|>1\end{array}\right.$

wherein, $e_i=(b_i-a_i\hat{X})/(c\&times;MAD),MAD=\underset{i}{med}\left|b_i-a_i\hat{X}\right|,$ b_iis the ith element of B, a_iThe element in the ith row of A, c is a regression factor, a value between 6 and 12 is taken for balancing the resistance and the effect, and med represents the median; ordering the n statistics, wherein if n is an odd number, the median is the symmetric center of the ordering statistics; if n is an even number, the median is the average of the two middle ranking statistics; the median has the anti-error property that the magnitude of the ranking information only utilizes errors is only dependent on the magnitude of the middle one or two ranking statistics, and the gross error only influences the change of the median value in a small range around the symmetric center.

Corresponding to the indoor positioning method based on 433MHz signals, the invention also discloses an indoor positioning system based on 433MHz signals, which comprises:

the sensing positioning module is used for forming a sensing network by a receiver at a fixed place;

the checking module is used for checking whether the reference node in the environment meets the positioning requirement;

the trilateration positioning module is used for calculating the initial position of the node to be positioned by using a trilateration model;

and the error sharing module is used for improving the positioning precision of the node to be positioned by utilizing a node sharing error algorithm.

The indoor positioning method and system based on 433MHz signals provided by the invention do not need a large amount of manpower and much time to construct an indoor off-line signal intensity data set, can realize accurate indoor positioning only by fixing a few receiving nodes indoors, basically do not need manual intervention, not only effectively reduce the cost of the indoor positioning system, but also are easy to install and use.

Drawings

Fig. 1 is a flowchart of an indoor positioning method based on 433MHz signals according to an embodiment of the present invention;

fig. 2 is a packet format of a reference node according to an embodiment of the present invention;

FIG. 3 is a command format for detecting the surrounding environment according to an embodiment of the present invention;

fig. 4 is a report packet format according to an embodiment of the present invention;

fig. 5 is a flowchart of a packet protocol design of a reference node according to an embodiment of the present invention;

fig. 6 is a data packet format received by a node to be positioned according to an embodiment of the present invention;

fig. 7 is a flow chart of a packet receiving protocol design of a node to be positioned according to an embodiment of the present invention;

FIGS. 8a and 8b are schematic views of trilateral positioning according to embodiments of the present invention;

fig. 9 is a block diagram of an indoor positioning system based on 433MHz signals according to an embodiment of the present invention.

Detailed Description

To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

Referring to fig. 1, fig. 1 is a flowchart illustrating an indoor positioning method based on 433MHz signals according to an embodiment of the present invention.

The indoor positioning method based on 433MHz signal in this embodiment specifically includes the following steps:

and S1, deploying the positioning sensing network. Specifically, in this embodiment, reference nodes are deployed at different positions in the measured space, so that any position in the space is effectively covered by at least three reference nodes that are not on the same straight line, wherein the reference nodes are composed of signal receivers and signal transmitters; setting a measurement space plane on a two-dimensional coordinate system plane, and taking a fixed position as a coordinate origin to determine the position coordinate of a reference node; after the coordinates of the reference node are determined, the coordinate information of the reference node is added to a data packet sent by the reference node. The reference node packet format is shown in detail in fig. 2.

And S2, the node to be positioned broadcasts a positioning request to the measurement space. In this embodiment, when the node to be positioned has a positioning requirement, it will broadcast a positioning request to the measurement space where it is located; when the reference node receives the positioning request packet, the reference node needs to perform ambient environment monitoring before sending an information packet to the node to be positioned so as to determine whether the reference node has a packet sending condition, and a command for checking an ambient environment data packet is shown in fig. 3: firstly, a reference node sends a command for inquiring the current environment, checks whether other reference nodes in the surrounding environment send packets, namely, checks whether the RSSI value in an effective reported data packet (the format of the reported data packet is shown in figure 4) is higher than a specified threshold value, if the RSSI value is lower than the threshold value, the environment where the current reference node is located is greatly interfered, the reference node is not suitable for immediate sending, and repeats the inquiry process again after waiting for random time within a specified range; if the value is lower than the threshold value, the data packet is sent immediately, after sending, the inquiry process is repeated after waiting for a certain range of random time until receiving a command of finishing sending the packet. The flow chart of the packet protocol design of the reference node is shown in fig. 5.

And S3, the reference node receiving the positioning request checks whether the signal intensity of the surrounding environment reaches the standard, and at least three effective reference nodes are selected.

And the reference node receiving the positioning request returns a signal with certain strength and position information of the reference node to the transmitter, and the node to be positioned judges according to the received data packet of the reference node and selects at least three effective reference nodes. After receiving the positioning request, the reference nodes meeting the conditions, namely the effective reference nodes return a data packet containing RSSI (received signal strength indicator) information, self position information and CRC (cyclic redundancy check) codes to the transmitter; after receiving the data packet (the format of the data packet received by the node to be positioned is shown in fig. 6), the node to be positioned needs to check the correctness of the data packet: when a node to be positioned enters a monitoring state, judging whether a data packet is received, if so, firstly, carrying out primary verification to verify whether the length of the data packet and a packet header without an RSSI value are the same as the correct format, and if not, discarding the data packet; if the data packet is the same as the data packet, performing secondary check, namely removing the packet header, checking whether the data information of the data packet is correct by using CRC, if not, discarding the data packet, if so, storing the data packet data and recording a corresponding label value, and counting the number of the received nodes; and ending the process until the number of the nodes reaches the standard, otherwise, continuing to receive the data packet. The flow chart of the packet receiving protocol design of the node to be positioned is shown in figure 7.

And S4, calculating the distance from the current reference node to the node to be positioned by using a signal propagation model according to the RSSI value sent to the node to be positioned by the reference node.

In this embodiment, the distance between the current reference node and the node to be positioned is calculated according to the RSSI value; the Received Signal Strength (RSSI) is a numerical value indicating the energy of electromagnetic waves in the current medium, and the electromagnetic waves have path loss in the transmission process, so that the RSSI value decreases with the increase of the distance, therefore, the distance corresponding to the node can be judged according to the signal strength, that is, the average path consumption is a function of the distance:

$\stackrel{\&OverBar;}{PL}\left(d\right)\&Proportional;{\left(\frac{d}{d_0}\right)}^n$

wherein,is the average path consumption; n is a path consumption index, which represents the speed of path consumption with increasing distance, related to the surrounding environment and obstacles, and specific parameters are shown in table 1 below; d₀Is a reference distance in meters; d is the distance between the transmitting end and the receiving end, and the unit is meter; taking logarithm on two sides of the equation of the formula, and converting the logarithm into a linear form; absolute average path consumption, defined as transmitter-to-reference distance d₀Plus the additional path consumption described in equation (a):

$\stackrel{\&OverBar;}{PL}\left(d\right)\&lsqb;dB\&rsqb;=\stackrel{\&OverBar;}{PL}\left(d_0\right)\&lsqb;dB\&rsqb;+10\&times;n\&times;\lg \left(\frac{d}{d_0}\right)$

selecting a reference distance d₀Is 1 meter and assumesThe average energy received when the transmitter reaches the reference distance in free space propagation is only expressed in the formula when the distance is d; however, when the distance is constant, due to the factors inherent in the environment, the signal value received at different times is a random quantity, the random quantity satisfies the lognormal distribution, and it satisfies the gaussian distribution in dB, that is, the complete wireless signal propagation attenuation model is:

$\stackrel{\&OverBar;}{PL}\left(d\right)\&lsqb;dB\&rsqb;=\stackrel{\&OverBar;}{PL}\left(d_0\right)\&lsqb;dB\&rsqb;+10\&times;n\&times;\lg \left(\frac{d}{d_0}\right)+X_{\mathrm{\&delta;}}$

wherein, X Is a gaussian distribution function with standard deviation σ in dB, and σ depends on the current environment, see table 2 below for specific values.

TABLE 1

Environment(s)	σ
		Outdoor air conditioner	4～12
Office, hard-zone	7
		Office, soft zone	9.6
Factory environment, line of sight	3～66 -->
		Factory environment with shelters	6.8

TABLE 2

And S5, calculating the position of the node to be positioned by using a trilateration model according to the position and distance information of the reference node.

The distance of an unknown node relative to some reference nodes limits the position of the unknown node, and the positioning idea is called trilateral positioning. In fig. 8a, 8b, which is an example of trilateral localization, three reference nodes are precisely localized to one point, i.e., the localization node (node 0) is relative to the other three reference nodes (nodes 1, 2, 3) of known locations. Obviously, the position of the positioning node is at the intersection of three circles whose respective distances from the positioning node are radii centered on the three node positions.

Assuming that the coordinate position of the node to be positioned is (x)₀,y₀) The coordinate of the ith (i is more than or equal to 1 and less than or equal to n) reference node is (x)_i,y_i) D 'is the distance estimated value calculated between the node to be positioned and the reference node'_i(ii) a Let d_iIs the true euclidean distance to the ith reference node, i.e.:

$d_i=\sqrt{{(x_i-x_0)}^2+{(y_i-y_0)}^2}$

the error between the calculated distance and the true distance can be expressed as ρ_i＝d′_i-d_i(ii) a Due to errors in the calculation, in practical cases ρ_iTypically a non-zero value; to make it possible toMinimum, using least square method to solve the coordinate (x) of node to be positioned₀,y₀) (ii) a Therefore, the positioning problem can be converted into a numerical solution problem of an over-determined linear equation set, and the square sum of the above equation is reordered to obtain n equations similar to the following equation:

$2x_0{x}_i+2y_0{y}_i-(x_0^2+y_0^2)=x_i^2+y_i^2-d_i^2$

then, the other equations (1 ≦ i < n) are sequentially subtracted from the ith ≦ n equation of the above formula, which can give n-1 equations as shown in the following formula:

$\left\{\begin{array}{c}2(x_1-x_n)x_0+2(y_1-y_n)y_0=x_1^2+y_1^2-d_1^2-(x_n^2+y_n^2-d_n^2)\\ .\\ .\\ .\\ 2(x_i-x_n)x_0+2(y_i-y_n)y_0=x_i^2+y_i^2-d_i^2-(x_n^2+y_n^2-d_n^2)\\ .\\ .\\ .\\ 2(x_{n-1}-x_n)x_0+2(y_{n-1}-y_n)y_0=x_{n-1}^2+y_{i-1}^2-d_{i-1}^2-(x_n^2+y_n^2-d_n^2)\end{array}\right.$

wherein, the left side of the equation set is known quantity, and the right side of the equation set is only x₀And y₀Unknown, and others are known parameters, from which a linear relationship is derived:

Ax＝B

where A is an (n-1) × 2 matrix and the ith row of the matrix is [2 (x)_i-x_n)2(y_i-y_n)](ii) a B is an n-1 column vector whose i term isx is a column vector [ x ] of positioning node coordinates₀y₀]^T(ii) a Since the inter-node distance value d ' estimated from the signal attenuation model often deviates from the true distance value d to some extent, the estimated value d ' is used '_iInstead of d_iInstead of B, B ' is calculated such that the least squares method is used to solve for an estimated x such that | Ax ' -B ' | purple calculation²The minimum, i.e. solving for the column vector x' is formulated as:

x′＝(A^TA)^-1A^TB′。

and S6, improving the positioning precision of the node to be positioned by using a node shared error algorithm.

It should be noted that, the closer the reference node is to the positioning node, the smaller the error is, the closer the reflected distance is to the real distance, and therefore, the closer the position estimation value obtained by solving based on the error is to the real distance. However, once there is a large error in the nearest node, this assumption is no longer true and the work done before is also a torch. Thus, putting all trust at one point is not robust. The improvement method is that the risks are shared, and each node plays a certain role. Therefore, the node-shared error algorithm is used in step S6 to increase the positioning accuracy.

For strict normal distribution data, least square estimation has the characteristics of optimal consistency, unbiased performance and minimum variance. The signal intensity value does not strictly follow the normal distribution, and certain errors exist. This error is an outlier, i.e., gross, that does not belong to systematic and accidental errors. If the measurement result includes the part of the gross error information, the classical least square method does not have the capability of resisting the gross error, and the robust least square method is an improvement of the classical least square method for reducing the influence of the gross error on the parameter estimation.

The criterion function of the robust M estimation isBy selecting a proper rho (), the influence of the gross error on the function is reduced as much as possible so as to eliminate the influence, thus the solved unknown parameters are close to the true value as much as possible without deviating from the true value too much due to the existence of the gross error; the multivariable function is obtained by taking an extreme value condition:

wherein, P is a weight coefficient matrix,the function is the derivative of ρ () with the final unknown parameter

$\hat{X}={\left(A^{T}PA\right)}^{-1}{A}^{T}PB$

In this embodiment, a Tukey double-total method is selected for robust estimation, the method belongs to M estimation with a culled area, and the criterion function is as follows:

$\mathrm{\&rho;}\left(e_i\right)=\left\{\begin{array}{cc}\&lsqb;1-{(1-{e_i}^2)}^3\&rsqb;/6,& \left|e_i\right|\&le;1\\ 1/6,& \left|e_i\right|>1\end{array}\right.$

wherein, $e_i=(b_i-a_i\hat{X})/(c\&times;MAD),MAD=\underset{i}{med}\left|b_i-a_i\hat{X}\right|,$ b_iis the ith element of B, a_iThe element in the ith row of A, c is a regression factor, a value between 6 and 12 is taken for balancing the resistance and the effect, and med represents the median; ordering the n statistics, wherein if n is an odd number, the median is the symmetric center of the ordering statistics; if n is an even number, the median is the average of the two middle ranking statistics; the median has an anti-propertyThe difference property only uses the sorting information of errors, the size of the difference property only depends on the size of the middle one or two sorting statistics, and the gross difference only influences the change of median values in a small range around the symmetrical center.

Corresponding to the indoor positioning method based on 433MHz signal, as shown in fig. 9, this embodiment further discloses an indoor positioning system based on 433MHz signal, and the system includes:

the sensing positioning module is used for forming a sensing network by a receiver at a fixed place;

the checking module is used for checking whether the reference node in the environment meets the positioning requirement;

the trilateration positioning module is used for calculating the initial position of the node to be positioned by using a trilateration model;

and the error sharing module is used for improving the positioning precision of the node to be positioned by utilizing a node sharing error algorithm.

It should be noted that the indoor positioning system based on the 433MHz signal further includes modules, sub-modules, units, and sub-units for implementing the steps of the indoor positioning method based on the 433MHz signal, and details are not repeated herein in order to avoid repeated descriptions.

According to the technical scheme, a large amount of manpower and a long time are not needed for constructing the indoor offline signal intensity data set, accurate indoor positioning can be achieved only by fixing a few receiving nodes indoors, manual intervention is basically not needed, the cost of the indoor positioning system is effectively reduced, and the indoor positioning system is easy to install and use.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (8)

1. An indoor positioning method based on 433MHz signals is characterized by comprising the following steps:

s1, deploying a positioning sensing network;

s2, broadcasting a positioning request to the measurement space by the node to be positioned;

s3, the reference node receiving the positioning request checks whether the signal intensity of the surrounding environment reaches the standard, and at least three effective reference nodes are selected;

s4, calculating the distance from the current reference node to the node to be positioned by using a signal propagation model according to the RSSI value sent to the node to be positioned by the reference node;

s5, calculating the position of the node to be positioned by using a trilateration model according to the position and distance information of the reference node;

and S6, improving the positioning precision of the node to be positioned by using a node shared error algorithm.

2. The indoor positioning method based on 433MHz signal of claim 1, wherein the step S1 specifically comprises: deploying reference nodes at different positions of a measured space, so that any position in the space is effectively covered by at least three reference nodes which are not on the same straight line, wherein the reference nodes are composed of signal receivers and signal transmitters; setting a measurement space plane on a two-dimensional coordinate system plane, and taking a fixed position as a coordinate origin to determine the position coordinate of a reference node; after the coordinates of the reference node are determined, the coordinate information of the reference node is added to a data packet sent by the reference node.

3. The indoor positioning method based on 433MHz signal of claim 2, wherein the step S2 specifically comprises: when a node to be positioned has a positioning requirement, the node to be positioned broadcasts a positioning request to a measurement space; when the reference node receives the positioning request packet, the reference node needs to perform ambient environment monitoring before sending an information packet to the node to be positioned so as to determine whether the reference node has a packet sending condition: the reference node firstly sends a command for inquiring the current environment, checks whether other reference nodes are sending packets in the surrounding environment, if so, the environment where the current reference node is located is greatly interfered, the reference node is not suitable for immediate sending, and repeats the inquiring process again after waiting for a random time within a specified range; if no interference signal exists, the data packet is immediately sent, after sending, the inquiry process is repeated after waiting for a certain range of random time until receiving a command of finishing sending the packet.

4. The indoor positioning method based on 433MHz signals as claimed in claim 3, wherein said step S3 specifically comprises: the reference node which receives the positioning request returns a signal with certain intensity and position information of the reference node to the transmitter, and the node to be positioned judges according to the received data packet of the reference node and selects at least three effective reference nodes; after receiving the positioning request, the reference nodes meeting the conditions, namely the effective reference nodes return a data packet containing RSSI (received signal strength indicator) information, self position information and CRC (cyclic redundancy check) codes to the transmitter; after receiving the data packet, the node to be positioned needs to check the correctness of the data packet: when a node to be positioned enters a monitoring state, judging whether a data packet is received, if so, firstly, carrying out primary verification to verify whether the length of the data packet and a packet header without an RSSI value are the same as the correct format, and if not, discarding the data packet; if the data packet is the same as the data packet, performing secondary check, namely removing the packet header, checking whether the data information of the data packet is correct by using CRC, if not, discarding the data packet, if so, storing the data packet data and recording a corresponding label value, and counting the number of the received nodes; and ending the process until the number of the nodes reaches the standard, otherwise, continuing to receive the data packet.

5. The indoor positioning method based on 433MHz signals of claim 4, wherein the step S104 specifically comprises: calculating the distance between the current reference node and the node to be positioned according to the RSSI value; the Received Signal Strength (RSSI) is a numerical value indicating the energy of electromagnetic waves in the current medium, and the electromagnetic waves have path loss in the transmission process, so that the RSSI value decreases with the increase of the distance, therefore, the distance corresponding to the node can be judged according to the signal strength, that is, the average path consumption is a function of the distance:

$\stackrel{\&OverBar;}{PL}\left(d\right)\&Proportional;{\left(\frac{d}{d_0}\right)}^n$

wherein,is the average path consumption; n is a path consumption index, which represents the speed of path consumption with increasing distance, in relation to the surroundings and obstacles; d₀Is a reference distance in meters; d is the distance between the transmitting end and the receiving end, and the unit is meter; taking logarithm on two sides of the equation of the formula, and converting the logarithm into a linear form; absolute average path consumption, defined as transmitter-to-reference distance d₀Plus the additional path consumption described in equation (a):

$\stackrel{\&OverBar;}{PL}\left(d\right)\&lsqb;dB\&rsqb;=\stackrel{\&OverBar;}{PL}\left(d_0\right)\&lsqb;dB\&rsqb;+10\&times;n\&times;\lg \left(\frac{d}{d_0}\right)$

selecting a reference distance d₀Is 1 meter and assumesThe average energy received when the transmitter reaches the reference distance in free space propagation is only expressed in the formula when the distance is d; however, when the distance is constant, due to the factors inherent in the environment, the signal value received at different times is a random quantity, the random quantity satisfies the lognormal distribution, and it satisfies the gaussian distribution in dB, that is, the complete wireless signal propagation attenuation model is:

$\stackrel{\&OverBar;}{PL}\left(d\right)\&lsqb;dB\&rsqb;=\stackrel{\&OverBar;}{PL}\left(d_0\right)\&lsqb;dB\&rsqb;+10\&times;n\&times;\lg \left(\frac{d}{d_0}\right)+X_{\mathrm{\&delta;}}$

wherein, X Is a gaussian distribution function with standard deviation σ, in dB, and σ depends on the current environment.

6. The indoor positioning method based on 433MHz signals of claim 5, wherein the step S5 specifically comprises: assuming that the coordinate position of the node to be positioned is (x)₀,y₀) The coordinate of the ith (i is more than or equal to 1 and less than or equal to n) reference node is (x)_i,y_i) Calculation between the node to be positioned and the reference nodeThe obtained distance estimation value is d'_i(ii) a Let d_iIs the true euclidean distance to the ith reference node, i.e.:

$d_i=\sqrt{{(x_i-x_0)}^2+{(y_i-y_0)}^2}$

the error between the calculated distance and the true distance can be expressed as ρ_i＝d′_i-d_i(ii) a Due to errors in the calculation, in practical cases ρ_iTypically a non-zero value; to make it possible toMinimum, using least square method to solve the coordinate (x) of node to be positioned₀,y₀) (ii) a Therefore, the positioning problem can be converted into a numerical solution problem of an over-determined linear equation set, and the square sum of the above equation is reordered to obtain n equations similar to the following equation:

$2x_0{x}_i+2y_0{y}_i-(x_0^2+y_0^2)=x_i^2+y_i^2-d_i^2$

then, the other equations (1 ≦ i < n) are sequentially subtracted from the ith ≦ n equation of the above formula, which can give n-1 equations as shown in the following formula:

$\left\{\begin{array}{c}2(x_1-x_n)x_0+2(y_1-y_n)y_0=x_1^2+y_1^2-d_1^2-(x_n^2+y_n^2-d_n^2)\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ 2(x_i-x_n)x_0+2(y_i-y_n)y_0=x_i^2+y_i^2-d_i^2-(x_n^2+y_n^2-d_n^2)\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ 2(x_{n-1}-x_n)x_0+2(y_{n-1}-y_n)y_0=x_{n-1}^2+y_{i-1}^2-d_{i-1}^2-(x_n^2+y_n^2-d_n^2)\end{array}\right.$

wherein, the left side of the equation set is known quantity, and the right side of the equation set is only x₀And y₀Unknown, and others are known parameters, from which a linear relationship is derived:

Ax＝B

where A is an (n-1) × 2 matrix and the ith row of the matrix is [2 (x)_i-x_n)2(y_i-y_n)](ii) a B is an n-1 column vector whose i term isx is a column vector [ x ] of positioning node coordinates₀y₀]^T(ii) a Since the inter-node distance value d ' estimated from the signal attenuation model often deviates from the true distance value d to some extent, the estimated value d ' is used '_iInstead of d_iInstead of B, B ' is calculated such that the least squares method is used to solve for an estimated x such that | Ax ' -B ' | purple calculation²The minimum, i.e. solving for the column vector x' is formulated as:

x′＝(A^TA)^-1A^TB′。

7. the indoor positioning method based on 433MHz signals as claimed in claim 6, wherein said step S6 specifically comprises: the criterion function of the robust M estimation isBy selecting a proper rho (), the influence of the gross error on the function is reduced as much as possible so as to eliminate the influence, thus the solved unknown parameters are close to the true value as much as possible without deviating from the true value too much due to the existence of the gross error; the multivariable function is obtained by taking an extreme value condition:

wherein, P is a weight coefficient matrix,the function is the derivative of ρ () with the final unknown parameter

$\hat{X}={\left(A^{T}PA\right)}^{-1}{A}^{T}PB$

Selecting Tukey double-whole method for robust estimation, wherein the method belongs to M estimation with elimination areas, and the criterion function is as follows:

$\mathrm{\&rho;}\left(e_i\right)=\left\{\begin{array}{cc}\&lsqb;1-{(1-{e_i}^2)}^3\&rsqb;/6,& \left|e_i\right|\&le;1\\ 1/6,& \left|e_i\right|>1\end{array}\right.$

wherein, $e_i=(b_i-a_i\hat{X})/(c\&times;MAD),MAD=\underset{i}{med}|b_i-a_i\hat{X}|,$ b_iis the ith element of B, a_iThe element in the ith row of A, c is a regression factor, a value between 6 and 12 is taken for balancing the resistance and the effect, and med represents the median; ordering the n statistics, wherein if n is an odd number, the median is the symmetric center of the ordering statistics; if n is an even number, the median is the average of the two middle ranking statistics; the median has the anti-error property that the magnitude of the ranking information only utilizes errors is only dependent on the magnitude of the middle one or two ranking statistics, and the gross error only influences the change of the median value in a small range around the symmetric center.

8. An indoor positioning system based on 433MHz signal, comprising:

the sensing positioning module is used for forming a sensing network by a receiver at a fixed place;

the checking module is used for checking whether the reference node in the environment meets the positioning requirement;

the trilateration positioning module is used for calculating the initial position of the node to be positioned by using a trilateration model;

and the error sharing module is used for improving the positioning precision of the node to be positioned by utilizing a node sharing error algorithm.