CN101553029A - Positioning method and positioning device of signal intensity rate in wireless sensor network - Google Patents

Abstract

The invention relates to a position method of the signal intensity rate in a wireless sensor network, comprising the following steps: 1) initializing and formatting each node in the network; 2) using a reference node for regulating a transceiving module and a write register thereof and broadcasting the position thereof; 3) using an unknown node j for regulating the transceiving module, receiving coordinate information and storing the coordinate information in a data module; 4) the unknown node using a micro-processing module thereof for calculating the weight of each received reference node; 5) if the received reference nodes are bigger than 3, using micro-processing module thereof for calculating the coordinates of the position node by the right formula; and 6) realizing the communication among nodes. The micro-processing module of the positioning device achieves the control of nodes and data processing; the memorizing module thereof memorizes the data; the transceiving module thereof receives and transmits the wireless signals; the system starts the firmware and achieves the initialization work, the memory stores the related data; and the invention has high anti-interference capacity, low error rate, low power consumption, high reliability and a better positioning effect.

Description

Signal intensity rate localization method and positioner in the wireless sensor network

Technical field

The present invention belongs to the wireless sensor network technology field, is specifically related to the signal intensity rate localization method among the wireless sensor network WSN.

Background technology

Wireless sensor network has that finite energy, communication distance are short, the node scale is big and characteristics such as random arrangement, and localization method is had special requirement.Existing localization method can be divided into based on the localization method of distance and with the localization method of range-independence, the former needs absolute distance or the angle information between the measured node to determine the position, the latter then need not absolute distance and the angle between measured node, but estimates the unknown node position by relevant informations such as internodal relative position, network topology, network-in-dialings.

Based on the localization method positioning accuracy height of distance, but higher, do not meet the characteristics such as low-power consumption, small size of wireless sensor node to the hardware requirement of node.Though and bigger with the localization method position error of range-independence, realization is simple, algorithm complex is low, it is low that environmental factor is relied on, and is applicable to wireless sensor network.Main following several with the localization method of range-independence: centroid algorithm, this algorithm at first determines to comprise the zone of unknown node, calculates this regional barycenter then and with its position as unknown node; Distance vector (DV-Hop Distance Vector-Hop) algorithm, unknown node in this algorithm is at first calculated the minimum hop count of itself and reference node, estimate average every hop distance, use minimum hop count to multiply by average every hop distance then, re-use the maximum likelihood estimation technique and calculate the unknown node coordinate as the estimated distance between unknown node and reference node; Point method of testing (APIT Approxamate Point-in-triangulation Test) in subtriangular, this method determines to comprise the delta-shaped region of unknown node earlier, the common factor of these delta-shaped regions is polygons, calculates this polygonal barycenter then and with its position as unknown node.

Prior art

Centroid algorithm is a localization method a kind of and range-independence, rough estimation, low expense, is proposed by N.Bulusu and J.Heidemann in 2000.Reference node is at first broadcasted the positional information (x of oneself in centroid algorithm _j, y _j), if unknown node collects the information that n reference node sent, when n 〉=3 then the unknown node coordinate just the mean value of the reference node coordinate that received of use determine.

Have than mistake according to the determined unknown node coordinate of above method and its physical location, when reference node density was higher, relative error reduced, so it is applicable to the position of rough estimate unknown node in large-scale network.Because this method is based on the hypothesis of ideal signal propagation model, thus with actual environment in the circulation way of signal have greater difference.Its advantage is to calculate simply, in to the not high application scenarios of precision certain practical value is arranged.

Consider in the actual wireless sensor network, the reference node nearer apart from unknown node should have big weight at the estimation coordinate time that calculates unknown node, and Jan Blumenthal etc. has proposed weighted mass center algorithm (WCL Weight Centroid Localization).

The weighted mass center algorithm has been introduced weighted value w at calculating unknown node coordinate time _Ij, be illustrated in the shared proportion of coordinate time reference node i that calculates unknown node j.w _Ij=1/ (d _Ij) ^g, d wherein _IjDistance between expression reference node i and the unknown node j, g represents the number of degrees.

d _IjCan draw by correlation technique such as received signal intensity (RSSI Received Signal StrengthIndicator), quality of connection (LQI Link Quality Indicator).But because the value of RSSI and LQI is not linear with distance, be subjected to the influence of factors such as environment, interference, therefore apart from d _IjBe the distance of rough estimation, the not actual distance between the representation node.Number of degrees g is relevant with distance estimation technique that is adopted and environment, is an empirical value.Generally g gets 1.Calculating unknown node coordinate time, w _IjRepresent the weighted value of different reference nodes, the reference node nearer apart from unknown node has bigger weighted value usually.Therefore the coordinate that calculates is more close apart from its nearer reference node, has improved positioning accuracy.

Weighted mass center method based on ratio has improved positioning accuracy, but its weights to use are bigger if pass through the method errors of calculation such as RSSI, LOI, and comparatively relies on for environment.RSSI under the varying environment and LQI value are come in and gone out very big, cause the localization method reliability not high.Have in the document and point out in experimental result, plant at reference node grid branch, when the inter-node communication distance was reference node spacing 95%, this method can obtain optimum efficiency, and maximum positioning error is 18% of a communication distance.

The structure of the hardware node of wireless sensor network is made up of power management module, radio receiving transmitting module, micro treatment module and data storage module at present.In order to meet the characteristics of wireless sensor network, its power module adopts comparatively stable pressurizer and power supply; Radio receiving transmitting module adopts better quality, the radio transmitting and receiving chip that the error rate is low; Computing module adopts the chip of taking into account operational capability and energy consumption.Overall the design of node of wireless sensor network will be taken into account all multifactor of performance, power consumption and cost.

Summary of the invention

At in the prior art in the wireless sensor network, based on the localization method positioning accuracy height of distance, but also high to the hardware requirement of node; Have than mistake according to the determined unknown node coordinate of centroid algorithm and its physical location, when reference node density is higher, the technical problem that relative error reduces, the present invention proposes the signal intensity rate localization method in a kind of wireless sensor network.

Signal intensity rate localization method in a kind of wireless sensor network comprises the steps:

1) initialization and format: node carries out initialization respectively in the network, and processor module operation start-up routine, transceiver module are write register, is set to resting state, storage module formats the storage area;

2) broadcast transmission signal: reference node i adjusts its transceiver module respectively, writes the wireless receiving and dispatching register, state is changed into the co-ordinate position information (x of emission state and broadcasting oneself _i, y _i);

3) acknowledge(ment) signal: unknown node j adjusts its transceiver module, writes the wireless receiving and dispatching register, changes state into accepting state, and the signal strength signal intensity of the reference node of j received signal intensity maximum is designated as P _MaxjAnd be stored in the data module (d);

4) weighted: unknown node uses its micro treatment module to pass through formula

$w_{\mathrm{ij}}=\frac{d_{\max }}{d_i}\≈{10}^{\left|P_{\max j}\left(d\right)\right|-\left|P_{\mathrm{ij}}\left(d\right)\right|}$

For each reference node that receives calculates weight w _Ij

5) determine node location: if the weights of the reference node that receives are greater than certain thresholding r _MinAnd receive the reference node number greater than 3 o'clock, just use its micro treatment module to pass through formula

$(x_{\mathrm{est}\_j},y_{\mathrm{est}\_j})=(\frac{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}\·x_i}{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}},\frac{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}\·y_i}{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}})$

Coordinate (the x of calculating location node _{Est_j}, y _{Est_j}), determined concrete node location;

6) realize inter-node communication: the various information that transducer is collected and the coordinate (x of estimation _{Est_j}, y _{Est_j}) write packet, be sent to reference node, realize its internodal communication.

Signal intensity rate positioner in a kind of wireless sensor network, for reference node and unknown node, positioner is all by constituting with lower module:

Micro treatment module is that internal memory constitutes with S3C44B0X processor and HY57V641602, finishes the control of node and the processing capacity of data;

Data storage module makes node can preserve the data of collecting with the file system of K9F2808U0C construction system;

Radio receiving transmitting module is responsible for the transmitting/receiving wireless signal with the CC1000 chip, plays the transmitting effect of wireless data;

Power management module provides stable electric energy for whole system.

The burned system start-up firmware of SST39VF1601 chip is finished the initial work of system;

Its signal flow separately is to being:

Reference node uses its micro treatment module to read positional information from data memory module, forms packet with node serial number, by transceiver module packet is sent again.

Unknown node receives the packet that reference node sends, in the data memory module that node serial number in the use micro treatment module sense data bag and positional information are stored in unknown node, the micro treatment module of unknown node is again according to the position of this information calculations self, as shown in Figure 6.

We have contrasted the positioning accuracy of centroid algorithm and ratio weighting location algorithm under different reference node communication radius, quantity and the distribution form by the MATLAB emulation experiment.Also contrasted simultaneously as path attenuation index n _pDuring with environmental change, the error of ratio weighting location algorithm and weighted mass center algorithm.Through the mean error contrast situation of 50 independent experiments, under the situation of reference node random distribution, the average positioning accuracy error of barycenter method is 39.8%, and the average positioning accuracy error of RRWCL method is 34.4%.The RRWCL method improves precision 13.5% than barycenter method; Under the situation that grid distributes, the average positioning accuracy error of barycenter method is 21.4%, and the average positioning accuracy error of RRWCL method is 7.84%, and the RRWCL method improves precision 63.36% than barycenter method; Plant at the equilateral triangle branch, the average positioning accuracy error of barycenter method is 20.27%, and the average positioning accuracy error of RRWCL method is 7.7%, and the RRWCL method improves precision 62.01% than barycenter method.

Description of drawings

Fig. 1 is the FB(flow block) of the middle reference node of signal intensity rate localization method of the present invention

Fig. 2 is the FB(flow block) of unknown node in the signal intensity rate localization method of the present invention;

Fig. 3 is reference node and a unknown node schematic diagram in the wireless sensor network;

Fig. 4 is a weight w under the varying environment _IjContrast;

Fig. 5 is the error contrast of signal intensity rate localization method of the present invention and barycenter method;

Fig. 6 is the sensor node system structured flowchart;

Embodiment

Signal intensity rate localization method in a kind of wireless sensor network comprises the steps:

1) node carries out initialization respectively in the network, and processor module operation start-up routine, transceiver module are write register, is set to resting state, storage module formats the storage area;

2) reference node i adjusts its transceiver module respectively, writes the wireless receiving and dispatching register, state is changed into the positional information (x of emission state and broadcasting oneself _i, y _i);

3) unknown node j adjusts its transceiver module, writes the wireless receiving and dispatching register, changes state into accepting state, and j receives the positional information (x of reference node i _i, y _i), the signal strength signal intensity of the reference node of received signal intensity maximum is designated as P _MaxjAnd be stored in the data module (d);

4) unknown node uses its micro treatment module to pass through formula

$w_{\mathrm{ij}}=\frac{d_{\max }}{d_i}\≈{10}^{\left|P_{\max j}\left(d\right)\right|-\left|P_{\mathrm{ij}}\left(d\right)\right|}$

For each reference node that receives calculates weight w _Ij

5) if the weights of the reference node that receives greater than certain thresholding r _MinAnd receive the reference node number greater than 3 o'clock, just use its micro treatment module to pass through formula

$(x_{\mathrm{est}\_j},y_{\mathrm{est}\_j})=(\frac{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}\·x_i}{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}},\frac{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}\·y_i}{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\Σ}}{w}_{\mathrm{ij}}})$

Coordinate (the x of calculating location node _{Est_j}, y _{Est_j});

6) realize inter-node communication, the various information that transducer is collected and the coordinate (x of estimation _{Est_j}, y _{Est_j}) write packet, be sent to reference node.

The FB(flow block) of this method as depicted in figs. 1 and 2.

This localization method is a weight with the relative ratio of the signal strength signal intensity between unknown node and each reference node, determines the unknown node coordinate with this, has improved positioning accuracy.Owing to introduced the signal strength signal intensity relative ratio, this method has also reduced the influence of environment to positioning accuracy, has higher reliability.

In the weighted mass center localization method, the levels of precision of weights is the deciding factors that influence the positioning accuracy performance.In the localization method of traditional barycenter class, its weights often inadequately accurately and to be subjected to such environmental effects bigger.

Signal intensity rate localization method in the wireless sensor network of the present invention, the signal attenuation model that generally uses in signals transmission is logarithm normality model, can be formulated as: P (d)=P ₀-10n _pLog d/d ₀The signal strength signal intensity unit that it calculated is dBm (decibelmilliwatts), and this is the value of an expression signal strength signal intensity absolute size.The signal strength signal intensity of considering the reference node i that two unknown node m and n receive is respectively P _m(d) and P _n(d), its difference is

$P_m\left(d\right)-P_n\left(d\right)=(P_0-{10n}_p\log \frac{d_m}{d_0})-({\mathrm{<figure-callout\; id="0"\; label="P"\; filenames="A20091002249300152.png,A20091002249300161.png"\; state="\{\{state\}\}">P</figure-callout>}}_0+{10n}_p\log \frac{d_n}{d_0})$

The relative ratio relation of 2 signal strength signal intensities of this value representation.

As shown in Figure 3, RN _iReference node for random distribution.1. unknown node j can receive reference node RN _1-4Positional information, suppose from reference node RN ₁The signal strength signal intensity maximum that receives is designated as RN _MaxIts signal strength signal intensity is designated as P _Maxj(d), the signal strength signal intensity that 2. receives from other reference nodes i and its are got ratio respectively:

$\left|P_{\max j}\left(d\right)\right|-\left|P_{\mathrm{ij}}\left(d\right)\right|=(P_0-10n_p\log \frac{d_i}{d_0})-({\mathrm{<figure-callout\; id="0"\; label="P"\; filenames="A20091002249300152.png,A20091002249300161.png"\; state="\{\{state\}\}">P</figure-callout>}}_0+10n_p\log \frac{d_{\max }}{d_0})$

To be unknown node receive the relative ratio of signal strength signal intensity and its maximum signal that receives from the i reference node to this value, and we get w in order to make weighted value meet the centroid algorithm requirement _IjFor:

$w_{\mathrm{ij}}=\frac{d_{\max }}{d_i}\&ap;{10}^{\left|P_{\max j}\left(d\right)\right|-\left|P_{\mathrm{ij}}\left(d\right)\right|}$

D wherein _MaxThe reference node of expression signal strength signal intensity maximum is apart from the distance of unknown node.

w _IjBe one about d _iFunction, w under the perfect condition _Ij=d _Max/ d _iIt is subjected to acknowledge(ment) signal intensity error, n _pInfluence with factors such as environmental changes.Fig. 4 shows that these factors are to w _IjInfluence less, w _IjCurve approach ideally curve.

Hardware platform mainly consists of the following components: micro treatment module is that finish the control of node and the processing capacity of data at the center with the S3C44B0X processor; The burned system start-up firmware of SST39VF1601 chip is finished the initial work of system; HY57V641602 is an internal memory, the operating related data of saved system; Data storage module makes node can preserve the data of collecting with the file system of K9F2808U0C construction system; Radio receiving transmitting module is responsible for the transmitting/receiving wireless signal with the CC1000 chip, plays the transmitting effect of wireless data.

The structured flowchart of hardware platform as shown in Figure 6, navigation system in the frame of broken lines among the figure is a virtual navigation system, calculation procedure in the localization method just of the present invention constitutes, and its result of calculation sends to reference node by micro treatment module notice radio receiving transmitting module.

The signal flow of the signal intensity rate positioner in the wireless sensor network of the present invention is to being:

Reference node uses its micro treatment module to read positional information from data memory module, forms packet with node serial number, by transceiver module packet is sent again.

Unknown node receives the packet that reference node sends, and uses in the data memory module that node serial number in the micro treatment module sense data bag and positional information be stored in unknown node, and the micro treatment module of unknown node is again according to the position of this information calculations self.

Hardware system of the present invention is consistent with the hardware system of prior art.Wherein microcontroller circuit adopts the S3C44B0X microcontroller of Samsung in the major part processor module, it adopts the Low-Power CMOS explained hereafter, based on risc architecture, program storage (Flash), the data storage (SRAM) of 4KB and the EEPROM of 4KB with 128KB in the sheet, 8 10 ADC passages, 28 and 2 16 hardware Timer, 8 PWM passages are arranged, have on programmable watchdog timer and the sheet interfaces such as analog comparator, JTAG, UART, SPI, I2C bus on oscillator, the sheet.S3C44B0X can work under multiple different mode, except normal manipulation mode, also have the low energy consumption operator scheme of six kinds of different brackets, so this microcontroller is suitable for the application scenario of low energy consumption.Modes such as external crystal-controlled oscillation, outside RC oscillator, inner RC oscillator, external clock can be chosen in the work clock source of S3C44B0X.The selection of work clock designs by the internal fuse position of S3C44B0X, and modes such as fuse bit can be programmed by JTAG, ISP programming are provided with.S3C44B0X adopts two external crystal-controlled oscillation among the present invention: the 14.3728MHz crystal oscillator is as the work clock of S3C44B0X, and the 32.768kHz crystal oscillator is as realtime clock source.

Wireless communication module adopts less radio-frequency CC1000 module.It is the radio receiving transmitting module of Chipcon company in a standard of release in the end of the year 2003, SmartRF03 technology based on Chipcon company, use the CMOS explained hereafter, operating voltage is low, energy consumption is low, volume is little, has characteristics such as output intensity and transmitting-receiving frequency be able to programme.This chip only needs crystal oscillator and outer members seldom such as load capacitance, I/O matching element and power supply coupling capacitor to get final product operate as normal, can guarantee the validity and the reliability of short haul connection, and its maximum transmitting-receiving speed is 250kbps.

CC1000 has the reception FIFO buffer area of 33 16 configuration registers, 15 command strobes registers, the transmission FIFO buffer area of 1 128 byte, 1 128 byte, the secure information storage device of 1 112 byte.CC1000 is easier with being connected of processor, and it uses SFD, FIFO, FIFOP and four pins of CCA to represent the state of transceive data; Processor is by SPI interface (CSn, SO, SI, SCLK) and CC1000 swap data, transmission order, use the RESETn pin chip that resets, use the voltage adjuster of VREG EN pin enabled CC1000, make it produce the required 1.8V voltage of CC1000, thereby make CC1000 enter the state of operate as normal, CC1000 communicates by unipole antenna or PCB antenna.

This hardware platform has the micropower emission; High anti-jamming capacity and low error rate; Low-power consumption, High reliability, volume are little, in light weight; The characteristics such as wireless transmission device modularization meet wireless biography The sensor network is conducive to the realization of location algorithm for the requirement of hardware node.

Claims (2)

1. the signal intensity rate localization method in the wireless sensor network is characterized in that, comprises the steps:

1) each node carries out initialization respectively in the network, in each node apparatus processor module operation start-up routine, transceiver module write register and be set to resting state, storage module formats the storage area;

2) reference node i adjusts its transceiver module respectively, writes the wireless receiving and dispatching register, state is changed into the position coordinates (x of emission state and broadcasting oneself _i, y _i);

3) unknown node j adjusts its transceiver module, writes the wireless receiving and dispatching register, changes state into accepting state, and j receives the coordinate information (x of reference node i _i, y _i), the signal strength signal intensity of the reference node of received signal intensity maximum is designated as P _MaxjAnd be stored in the data module (d);

4) unknown node uses its micro treatment module to pass through formula

$w_{\mathrm{ij}}=\frac{d_{\max }}{d_i}\&ap;{10}^{\left|P_{\max j}\left(d\right)\right|-\left|P_{\mathrm{ij}}\left(d\right)\right|}$

For each reference node that receives calculates weight w _Ij

5) if the weights of the reference node that receives greater than certain thresholding r _MinAnd receive the reference node number greater than 3 o'clock, just use its micro treatment module to pass through formula

$(x_{\mathrm{est}\_j},y_{\mathrm{est}\_j})=(\frac{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\&Sigma;}}{w}_{\mathrm{ij}}\&CenterDot;x_i}{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\&Sigma;}}{w}_{\mathrm{ij}}},\frac{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\&Sigma;}}{w}_{\mathrm{ij}}\&CenterDot;y_i}{\underset{w_{\mathrm{ij}}>r_{\min }}{\mathrm{\&Sigma;}}{w}_{\mathrm{ij}}})$

Coordinate (the x of calculating location node _{Est_j}, y _{Est_j});

6) realize inter-node communication, the various information that transducer is collected and the coordinate (x of estimation _{Est_j}, y _{Est_j}) write packet, be sent to reference node.

2. the signal intensity rate positioner in the wireless sensor network is characterized in that:

For reference node and unknown node, positioner is all by constituting with lower module:

Micro treatment module is that internal memory constitutes with S3C44B0X processor and HY57V641602, finishes the control of node and the processing capacity of data;

Data storage module makes node can preserve the data of collecting with the file system of K9F2808U0C construction system;

Radio receiving transmitting module is responsible for the transmitting/receiving wireless signal with the CC1000 chip, plays the transmitting effect of wireless data;

Power management module provides stable electric energy for whole system;

The burned system start-up firmware of SST39VF1601 chip is finished the initial work of system;

Its signal flow separately is to being:

Reference node uses its micro treatment module to read positional information from data memory module, forms packet with node serial number, by transceiver module packet is sent again;

Unknown node receives the packet that reference node sends, and uses in the data memory module that node serial number in the micro treatment module sense data bag and positional information be stored in unknown node, and the micro treatment module of unknown node is again according to the position of this information calculations self.

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