CN104640203A - Mine moving object positioning accuracy enhancement method assisted by non-special node - Google Patents

Abstract

A non-special node-assisted method for enhancing the positioning accuracy of a moving target in a mine belongs to the underground target positioning method of a coal mine. The positioning accuracy enhancement method is divided into two stages. In the first stage, the moving target is positioned using the existing positioning system during the roadway, and the preliminary positioning result lp(i) is obtained; in the second stage, the moving target The node communicates with other types of sensing nodes within the communication range, that is, non-specialized nodes, and receives the coordinate sensor(n) and signal strength strength(n) sent by it, corrects the obtained initial positioning results, and obtains the final result of the moving target. The present invention makes full use of the existing underground positioning system and other types of nodes used for disaster or equipment perception, does not need to rearrange equipment, is simple to deploy, low in cost, and can be enhanced as much as possible on the basis of ensuring existing equipment and systems The positioning accuracy is suitable for the seamless upgrade of the mine positioning system, especially the upgrade of the positioning system under the Internet of Things architecture.

Description

A non-specialized node-assisted method for enhancing the positioning accuracy of mine moving targets

technical field

The invention relates to a coal mine underground target positioning method, in particular to a non-special node-assisted mine mobile target positioning accuracy enhancement method.

Background technique

The underground environment of coal mines is complex, there are many equipments, and many unfavorable factors such as non-line-of-sight and multipath fading bring various difficulties to underground target positioning. However, the accurate positioning of underground targets is closely related to coal mine safety production, disaster warning and post-disaster rescue. Therefore, improving the positioning accuracy of targets is the most important thing in building an underground personnel positioning system.

At present, the downhole target positioning mainly uses ranging-based algorithms, including signal strength (RSSI), signal angle of arrival (AOA), time of arrival (TOA), time difference of arrival (TDOA), etc. The influence of various factors reduces the positioning accuracy. Due to the particularity of the coal mine environment, the underground signal attenuation model is very different from that on the ground, resulting in low accuracy of the positioning algorithm based on RSSI, and the error even reaches tens of meters; while the algorithm based on the signal angle of arrival requires high-precision angle measurement , once the angle measurement is inaccurate, it may cause the positioning result to be quite different from the actual coordinates; the algorithm based on the time of arrival and time difference needs the cooperation of a high-precision time synchronization algorithm, and the impact of the measurement time error on the positioning result can be said to be less than a hair. thousands of miles. In the absence of a very accurate target positioning algorithm in coal mines, correcting the positioning results calculated by existing positioning algorithms has become an effective way to improve the target positioning accuracy.

At present, the construction of the Internet of Things in mines is the general trend. Under the framework of the mine Internet of Things, it is necessary to deploy a large number of different types of sensor nodes to realize the perception of environmental information, disaster information, and equipment health information, such as gas monitoring sensors, roof pressure sensors, and equipment vibration sensors. Generally speaking, these sensor nodes perform their own duties and specialize in their own information perception and reporting tasks. In fact, the process of these sensor nodes reporting the sensing results to the ground is the process of sending radio signals to the surrounding nodes. When the unknown nodes carried by the moving target enter the communication range of these non-specialized sensor nodes, they can also receive these radio signals. Signal. If these radio signals can be used as auxiliary signals to correct the positioning results of the existing positioning system, it will bring new opportunities for improving the positioning accuracy of unknown nodes. Compared with the positioning system, these sensor nodes are not dedicated to positioning, so they are called non-specialized nodes.

Contents of the invention

Technical problem: The purpose of the present invention is to provide a non-specialized node-assisted mine mobile target positioning accuracy enhancement method that is simple, effective, flexible to use, and fully utilizes underground non-specialized positioning node equipment resources. On the basis of this, the positioning accuracy is improved, and the problem of low positioning accuracy existing in the existing coal mine underground positioning algorithm is solved.

Technical solution: the purpose of the present invention is achieved in this way: the positioning accuracy enhancement method: in the process of advancing in the roadway, the unknown node broadcasts mobile radio signals with time t as a period, and the existing positioning system locates it, and obtains the preliminary result lp (i); Subsequently, the unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point, and the scope of the broadcast is the laneway area within the communication radius of the unknown node; the non-specialized node in the communication range is in After receiving the search information, send a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node; after the unknown node receives the confirmation message, Calculate the distance d _n between the non-specialized node and the unknown node, and then use the position correction algorithm to obtain the final positioning result p(i) of the unknown node; the specific steps are as follows:

(1) The unknown node travels in the roadway, during which the mobile radio signal is broadcast periodically; the existing positioning system locates the unknown node once every _t , and the initial positioning coordinate point is recorded as lp(i);

(2) The unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point. The scope of the broadcast is the roadway area within the communication radius of the unknown node; After receiving the message, send a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node; after receiving the confirmation message, the unknown node calculates the non-specialized node The distance d _n between the specialized node and the unknown node, the formula is as follows:

$\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 10</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&delta;</span>}$

In the formula, P(d ₀ ) is the signal strength of the node at d ₀ position, the value of P(d _n ) is strength(n), β is the attenuation factor, which is determined by specific environmental factors, and δ is random noise;

(3) Use the position correction algorithm to obtain the coordinate point p(i) obtained after the position correction of the unknown node;

The steps of the position correction algorithm are as follows:

a. Calculate the weighted centroid ave of all non-specialized nodes, the formula is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; sensor</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}}{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; sensor</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}}{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}\end{array}\right.<span\; class="notranslate">\; ;</span>$

where w _n is the reciprocal of d _n , N is the number of non-specialized nodes;

b. Find the weighted centroid ave and the preliminary correction point p'(i) of the preliminary positioning point lp(i), the formula is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}^{<span\; class="notranslate">\; ,</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; lp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; bx</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}^{<span\; class="notranslate">\; ,</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; lp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; b</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}\end{array}\right.$

In the formula, a and b are weight factors and satisfy a+b=1, 0≤a≤1, 0≤b≤1, and their values can be adjusted according to the actual situation to find the optimal solution of p'(i);

c. Make a straight line perpendicular to the roadway through p'(i), and the intersection point with the center line of the roadway is the final correction point p(i).

Beneficial effect, owing to adopting above-mentioned technical scheme, the non-specific node-assisted method for enhancing the positioning accuracy of mine mobile targets of the present invention advances in the roadway through unknown nodes, broadcasts mobile radio signals with time t as a period, and uses existing arbitrary positioning algorithms to It performs positioning and obtains the preliminary result lp(i); then, the unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point, and the broadcast range is the laneway area within the communication radius of the unknown node; After receiving the search information, the non-specialized node in the communication range sends a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node; unknown After the node receives the confirmation information, it calculates the distance d _n between the non-specialized node and the unknown node, and then uses the position correction algorithm to obtain the final positioning result p(i) of the unknown node. Using the simple communication between the mobile node and these non-specialized positioning nodes, the positioning results of the existing positioning system are corrected, thereby improving the positioning accuracy to the greatest extent.

Advantages: The present invention makes full use of the existing underground positioning system and other types of nodes used for disaster or equipment perception, does not need to rearrange equipment, is simple to deploy, and has low cost. It may enhance the positioning accuracy and is suitable for the seamless upgrade of the mine positioning system, especially the positioning system upgrade under the Internet of Things architecture.

Description of drawings:

Fig. 1 is the overall flowchart of the present invention.

Fig. 2 is a flow chart of the position correction algorithm of the present invention.

Fig. 3 is a schematic diagram of the position correction algorithm of the present invention.

In the figure, 1. sensor node; 2. preliminary positioning point; 3. weighted centroid; 4. preliminary correction point p'(i); 5. final correction point p(i).

Detailed ways

An embodiment of the present invention will be further described below in conjunction with accompanying drawing:

The non-specialized node-assisted mine mobile target positioning accuracy enhancement method of the present invention, the positioning accuracy enhancement method: the unknown node broadcasts mobile radio signals with time t as a period during the travel process in the roadway, and the existing positioning system locates it, The preliminary result lp(i) is obtained; then, the unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point, and the scope of the broadcast is the laneway area within the communication radius of the unknown node; After receiving the search information, the non-specialized node sends a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node; the unknown node receives the After confirming the information, calculate the distance d _n between the non-specialized node and the unknown node, and then use the position correction algorithm to obtain the final positioning result p(i) of the unknown node; the specific steps are as follows:

(1) The unknown node travels in the roadway, during which the mobile radio signal is broadcast periodically; the existing positioning system locates the unknown node once every _t , and the initial positioning coordinate point is recorded as lp(i);

(2) The unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point. The scope of the broadcast is the roadway area within the communication radius of the unknown node; After receiving the message, send a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node; after receiving the confirmation message, the unknown node calculates the non-specialized node The distance d _n between the specialized node and the unknown node, the formula is as follows:

$\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 10</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&delta;</span>}$

In the formula, P(d ₀ ) is the signal strength of the node at d ₀ position, the value of P(d _n ) is strength(n), β is the attenuation factor, determined by specific environmental factors, and δ is random noise;

(3) Use the position correction method to obtain the coordinate point p(i) obtained after the position correction of the unknown node;

The steps of the position correction algorithm are as follows:

a. Calculate the weighted centroid ave of all non-specialized nodes, the formula is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; sensor</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}}{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; sensor</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}}{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}\end{array}\right.<span\; class="notranslate">\; ;</span>$

where w _n is the reciprocal of d _n , N is the number of non-specialized nodes;

b. Find the weighted centroid ave and the preliminary correction point p'(i) of the preliminary positioning point lp(i), the formula is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}^{<span\; class="notranslate">\; ,</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; lp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; bx</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}^{<span\; class="notranslate">\; ,</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; lp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; b</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}\end{array}\right.$

In the formula, a and b are weight factors and satisfy a+b=1, 0≤a≤1, 0≤b≤1, and their values can be adjusted according to the actual situation to find the optimal solution of p'(i);

c. Make a straight line perpendicular to the roadway through p'(i), and the intersection point with the center line of the roadway is the final correction point p(i).

Embodiment 1: The positioning accuracy enhancement method is divided into two stages. In the first stage, the moving target is positioned using the existing positioning system while it is moving in the roadway, and the preliminary positioning result lp(i) is obtained; In the second stage, the mobile node communicates with other types of sensing nodes within the communication range, that is, non-specialized nodes, receives the coordinate sensor(n) and signal strength strength(n) sent by it, corrects the obtained initial positioning results, and obtains the mobile target of the final result.

The unknown node travels in the roadway and broadcasts mobile radio signals with time t as the period. The existing positioning system locates it and obtains the preliminary result lp(i). Subsequently, the unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point, and the broadcast range is the laneway area within the communication radius of the unknown node. After receiving the search information, the non-specialized node in the communication range sends a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node. After receiving the confirmation message, the unknown node calculates the distance d _n between the non-specialized node and the unknown node, and then uses the position correction algorithm to obtain the final positioning result p(i) of the unknown node. Specific steps are as follows:

(1) The unknown node travels in the roadway, during which it periodically broadcasts mobile radio signals. The existing positioning system locates the unknown node once every _t , and the initial positioning coordinate point is recorded as lp(i);

(2) The unknown node broadcasts a non-specialized node search information to search for non-specialized nodes near the preliminary positioning result point, and the scope of the broadcast is the roadway area within the communication radius of the unknown node. After receiving the search information, the non-specialized node in the communication range sends a radio message to the unknown node as a confirmation, which includes the coordinate sensor(n) and signal strength information strength(n) of the non-specialized node. After receiving the confirmation message, the unknown node calculates the distance d _n between the non-specialized node and the unknown node, the formula is as follows:

$\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 10</span>}\mathrm{<span\; class="notranslate">\; \&beta;</span>}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&delta;</span>}$

In the formula, P(d ₀ ) is the signal strength of non-specialized nodes at d ₀ position, the value of P(d _n ) is strength(n), β is the attenuation factor, determined by specific environmental factors, and δ is random noise.

(3) Calculate the weighted centroid ave of all non-specialized nodes, the formula is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; sensor</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}}{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; sensor</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span>}}{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}\end{array}\right.<span\; class="notranslate">\; ;</span>$

where w _n is the reciprocal of d _n , N is the number of non-specialized nodes;

(4) Find the weighted centroid ave and the preliminary correction point p'(i) of the preliminary positioning point lp(i), the formula is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}^{<span\; class="notranslate">\; ,</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; lp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; bx</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}^{<span\; class="notranslate">\; ,</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; lp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; b</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; ave</span>}}\end{array}\right.$

In the formula, a and b are weight factors and satisfy a+b=1, 0≤a≤1, 0≤b≤1, and their values can be adjusted according to the actual situation to find the optimal solution of p'(i). Here, a=0.5 and b=0.5 can be taken, then p'(i) is the midpoint between the weighted centroid ave and the preliminary positioning point lp(i).

(5) Make a straight line perpendicular to the roadway through p'(i), and the intersection point with the center line of the roadway is the final correction point p(i), as shown in Figure 3.

Claims (1)

1. the mine movable target location accuracy Enhancement Method that a non-expert node is auxiliary, it is characterized in that: this Positioning Precision Improvement method: unknown node is in tunnel in traveling process, with time t for periodic broadcasting mobile radio signal, existing navigation system positions it, obtains PRELIMINARY RESULTS lp (i); Subsequently, unknown node broadcasts a non-expert node searching information, and in order to search for the non-expert node near Primary Location result points, the scope of broadcast is the region, tunnel in unknown node communication radius; Be in the non-expert node of communication range after receiving search information, send a RI radio intelligence as confirmation to unknown node, in this confirmation, contain coordinate sensor (n) and signal strength information strength (n) of this non-expert node; After unknown node receives this confirmation, calculate the distance d between non-expert node and unknown node _n, then utilize position correction algorithm, try to achieve final positioning result p (i) of unknown node; Concrete steps are as follows:

(1) unknown node is advanced in tunnel, the broadcast mobile radio signal of period; Every t to unknown node location once, Primary Location coordinate points is designated as lp (i) to existing navigation system;

(2) unknown node broadcasts a non-expert node searching information, and in order to search for the non-expert node near Primary Location result points, the scope of broadcast is the region, tunnel in unknown node communication radius; Be in the non-expert node of communication range after receiving search information, send a RI radio intelligence as confirmation to unknown node, in this confirmation, contain coordinate sensor (n) and signal strength information strength (n) of this non-expert node; After unknown node receives this confirmation, calculate the distance d between non-expert node and unknown node _n, formula is as follows:

$P\left(d_n\right)=P\left(d_0\right)-10\mathrm{\&beta;}\left(\frac{d_n}{d_0}\right)+\mathrm{\&delta;}$

In formula, P (d ₀) be that node is at d ₀the signal strength signal intensity of position, P (d _n) value and strength (n), β be decay factor, determined by specific environment factor, δ is random noise;

(3) utilize position correcting method, try to achieve the coordinate points p (i) that unknown node obtains after position correction;

Described position correcting method step is as follows:

A. calculate the weighted mass center ave of whole non-expert node, formula is as follows:

$\left\{\begin{array}{c}{x}_{\mathrm{ave}}=\frac{\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_n{x}_{\mathrm{sensor}}\left(n\right)}{\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_n}\\ y_{\mathrm{ave}}=\frac{\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_n{y}_{\mathrm{sensor}\left(n\right)}}{\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_n}\end{array}\right.;$

W in formula _nfor d _ninverse, n is non-expert interstitial content;

B. the preliminary adjusting point p'(i of weighted mass center ave and Primary Location point lp (i) is asked), formula is as follows:

$\left\{\begin{array}{c}{x}_{p^{,}\left(i\right)}={\mathrm{ax}}_{\mathrm{lp}\left(i\right)}+{\mathrm{bx}}_{\mathrm{ave}}\\ y_{p^{,}\left(i\right)}={\mathrm{ay}}_{\mathrm{lp}\left(i\right)}+{\mathrm{by}}_{\mathrm{ave}}\end{array}\right.$

In formula, a, b are weight and meet a+b=1,0≤a≤1,0≤b≤1, can adjust its numerical value, seek p'(i according to actual conditions) optimal solution;

C. p'(i is crossed) make the straight line of vertical working, be final adjusting point p (i) with the intersection point of laneway midline.