CN108761391A - A kind of model class is without device target localization method - Google Patents
A kind of model class is without device target localization method Download PDFInfo
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- CN108761391A CN108761391A CN201810530928.9A CN201810530928A CN108761391A CN 108761391 A CN108761391 A CN 108761391A CN 201810530928 A CN201810530928 A CN 201810530928A CN 108761391 A CN108761391 A CN 108761391A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/12—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves by co-ordinating position lines of different shape, e.g. hyperbolic, circular, elliptical or radial
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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Abstract
The invention discloses a kind of model classes without device target localization method, the deficiency for the equal weights model of ellipse that this method is generally used for "current" model class without device target location technology, the spatial relationship influenced according to target on Radio Link proposes a kind of layering ellipse shade weight model to portray target to Radio Link effect, to reach more accurate description received signal strength（Received Signal Strength,RSS）The purpose of relationship between variation and target location, and model class is improved without device target positioning performance；Simultaneously when realizing positioning, using the autonomous selection target position of cross target automatic Searching, to improve the accuracy of positioning result, and the influence of ambient noise and pseudo- target image is overcome.
Description
Technical field
The present invention relates to a kind of improved model classes without device target localization method, belongs to wireless location technology field.
Background technology
Requiring positioning target that must carry the positioning device that matches with positioning system with traditional positioning method, (such as GPS connects
Receipts machine, mobile phone etc.) it is different, no device target positioning (Device-free localization, DFL) is without positioning target carrying
Any positioning device is actively engaged in position fixing process without positioning target, therefore DFL is in personnel's search and rescue, illegal invasion detection, spy
The positioning field that the conventional mapping methods such as old man's treatment in the case of different cannot achieve can play a significant role.Compared to existing
Based on camera, ULTRA-WIDEBAND RADAR, the technologies such as infrared and ultrasonic wave exempt from Portable device positioning, are based on wireless sensor network
DFL technologies because its is at low cost, versatility is good and wall can be penetrated, smog is positioned the advantages that, thus become current DFL
One research hotspot in field.
3 types, the i.e. DFL of fingerprint base, geometry are may be roughly divided into currently based on the DFL methods of wireless sensor network
The DFL of the base and DFL etc. of model base.The DFL of fingerprint base requires to establish fingerprint database in advance, and as the variation of environment needs
Library is updated the data, man power and material is put into more demanding.Link connection is expressed as straightway by the DFL of geometry base, is utilized
Geometrical relationship between link is positioned；Although such method is easy to be influenced by multipath etc. without establishing fingerprint database.
The DFL of model base establishes the relationship between target location and change in signal strength using shade weight model, and uses for reference medicine
The thought of CT is finally inversed by location drawing picture by regularization method, such method is also referred to as radio frequency tomography (Radio
Tomographic Imaging, RTI) technology.Due to the intuitive of RTI positioning, thus receive significant attention.Realize the pass of RTI
One of key is to need to establish the relationship between target location and change in signal strength using shade weight model.Initial
In RTI, this relationship is built using oval shade weight model, which provides using a pair of of radio node as elliptic focus
The weight of all lattice points at a distance from node with this to being inversely proportional in the ellipse of composition, and the weight of oval outer all lattice points is zero.
Although this model has certain reasonability, the weight of all lattice points is identical in ellipse and does not meet reality, and the model
Ellipse short shaft length by experience choose, be equally theoretically unsound.Therefore, the RTI imagings based on oval shade weight model
As a result often image quality is not high, is susceptible to pseudo- target, influences DFL precision.
Invention content
In order to solve the problems in the existing technology the present invention, provides a kind of accuracy that can improve positioning result, and
Overcome ambient noise and pseudo- target image influence without device target localization method.
In order to achieve the above object, technical solution proposed by the present invention is：A kind of model class without device target localization method,
Include the following steps：
Step 1: establishing wireless location system, the positioning system includes several wireless receiving and dispatching nodes, wireless receiving and dispatching section
Point communicates between any two, forms multi wireless links；
Step 2: establishing the oval weight model of layering to the spatial relationship that Radio Link influences according to no device target；
Step 3: measuring RSS value of the Radio Link in no target and when having target respectively；
Step 4: calculating radio frequency based on the oval weight model of layering chromatographs imaging results, image is obtained；
Step 5: obtaining target location on image using cross target automatic search method.
Above-mentioned technical proposal is further designed to：The positioning system includes M+1 wireless receiving and dispatching node, with wireless
Networking is carried out based on communication protocol, wherein M wireless receiving and dispatching node, which is constituted, measures network, is evenly distributed on positioning system institute
On the periphery of localization region, the M wireless receiving and dispatching node communicates between any two, forms L=M × (M-1)/2 wirelessly
Link；The M+1 node is data acquisition node, is responsible for collecting data；The region that positioning system is positioned is evenly dividing into N number of
Pixel.
Gradual change shade weight model i-th in the oval weight model of the layering corresponding to (i=1,2 ..., L) link
Formula is as follows：
Wherein, wijIt indicates when target is located at j-th of pixel on influencing corresponding weighted value produced by i-th link,
diFor i-th linkage length, dij1, dij2Respectively j-th of pixel to composition i-th two node of link distance, aiIndicate the
I link pair answers elliptical long axis length.For i-th article of link the corresponding maximum 1st
Fresnel region radius, wherein λ indicate the wavelength of electromagnetic wave.
The radio frequency tomography includes the following steps：
Step 4.1, the RSS variable quantities for calculating separately L active link, are as a result denoted as Δ Y, former according to radio frequency tomography
Reason, can obtain：
Δ Y=Wx+v
Wherein, x=[x1,x2,…,xN]TIndicate the pixel vector that localization region divides, xi, i=1,2 ..., N indicates each picture
Value on vegetarian refreshments, v indicate noise vector, and W is weight matrix；
Step 4.2 introduces regularization constraint item, and it is as follows to obtain object function：
Wherein, α indicates that regularization coefficient, Q indicate regular matrix, | | | | it indicates 2 norms, solves above formula, obtain：
X=(WTW+αQTQ)-1WTΔY。
The cross target automatic search method includes the following steps：
Step 5.1 eliminates the smaller noise spot of brightness value with averaging method；Flat is asked to the brightness of all pixels point on image
Mean value, sub-average pixel brightness value are set to 0；
Step 5.2, the brightness value for recalculating all pixels point on imaging figure calculate centered on each pixel,
Brachium is the product of the brightness value of all pixels point in the cross neighborhood of r, and calculation formula is as follows：
Wherein, Π indicates that multiplication operation, x (i, j) denotation coordination are the original luminance value of the pixel of (i, j),Table
Show that coordinate is that the pixel of (i, j) recalculates rear brightness value, as m=0, n=-r,-r+1 ... -1,1 ... r-1, r work as n
When=0, m=-r,-r-1 ... -1,1 ... r-1, r；R indicates cross arm lengths；
Non-zero pixels region, that is, target position in step 5.3, image, it is target to take wherein brightest pixel coordinate
Place coordinate.
What the present invention was reached has the beneficial effect that：
(1) method of the invention replaces the model of ellipse of existing fixed weights to go to realize radio frequency with the oval weight model of layering
Tomography, while the shortcomings that ellipse short shaft length is by experience value is overcome, model error can be effectively reduced, imaging is improved
Quality and positioning performance.
(2) method of the invention is overcome background and is made an uproar by the autonomous selection target position of cross target automatic Searching
The influence of sound and pseudo- target image, improves positioning accuracy and robustness.
Description of the drawings
Fig. 1 is the schematic diagram of positioning system of the present invention；
Fig. 2 is the oval weight model parameters relationship schematic diagram of layering；
Fig. 3 is cross neighborhood schematic diagram；
Fig. 4 is the imaging results figure based on oval weight model in the prior art in the embodiment of the present invention；
Fig. 5 is the imaging results figure based on the oval weight model of layering in the embodiment of the present invention；
Fig. 6 is the positioning result figure after target automatic search method in the embodiment of the present invention.
Specific implementation mode
Below in conjunction with the accompanying drawings and specific embodiment the present invention is described in detail.
The model class of a modification of the present invention includes the following steps without device target localization method：
Step 1: establishing positioning system；
The positioning system includes M+1 wireless receiving and dispatching node, based on the wireless communication protocol of IEEE802.15.4 into
Row networking, wherein M wireless receiving and dispatching node, which is constituted, measures network, is evenly distributed on the periphery of localization region, the M+1 section
Point is data acquisition node, is responsible for collecting data；The M wireless receiving and dispatching node communicates between any two, and composition L=M ×
(M-1)/2 wireless links；Localization region is evenly dividing into N number of pixel, and positioning system structure is as shown in Figure 1.
Step 2: the oval weight model of spatial relationship structure layering influenced on Radio Link according to no device target；
According to Fresnel theory, most energy are all propagated in first Fresnel zone.It is therefore contemplated that working as target
When sheltering from the first Fresnel zone of link, it is considered as and effectively blocks.And when target is in outside first Fresnel zone, it can recognize
For the influence very little to link measured value, weights are set as 0 as existing model of ellipse at this time.Simultaneously as closer to chain
The position on road is bigger on the influence of RSS values, should assign higher weights, result in new weight model.It is analyzed according to above,
Gradual change shade weight model formula corresponding to i-th (i=1,2 ..., L) link is as follows：
Wherein, wijIt indicates when target is located at j-th of pixel on influencing corresponding weighted value produced by i-th link,
diFor i-th linkage length, dij1, dij2Respectively j-th of pixel to composition i-th two node of link distance, aiIndicate the
I link pair answers elliptical long axis length.For i-th article of link the corresponding maximum 1st
Fresnel region radius, wherein λ indicate the wavelength of electromagnetic wave.The example of above each amount is as shown in Figure 2.
Step 3: RSS values when measuring Radio Link without target and when having a target；
According to communication theory, received signal strength (the Received Signal of receiving terminal in i-th link
Strength, RSS) value can be expressed as
yi(t)=Pi-Li-Si(t)-Fi(t)-vi(t) (2)
Wherein PiThe transmission power for indicating transmitting terminal, generally assumes that transmission power is fixed, LiIt indicates and transmission range, antenna
The relevant quiescent dissipation such as pattern, Si(t) shadow loss, F are indicatedi(t) fading loss, v are indicatedi(t) noise is represented.It surveys respectively
The RSS measured values of i-th link when measuring without target and having target, then in the RSS variation deltas y of i-th link of moment ti(t)
It can be expressed as
Wherein yi(0)=Pi-Li-Fi(0)-vi(0) the background RSS measured values of i-th link in the presence of no target are indicated,Due to noise compare with shadow fading it is much smaller, so Δ yi(t) mainly by t when
The shadow fading at quarter determines.Using same measurement method, the measured value of whole L links can use vector Y (t)=[y1(t)
y2(t)…yL(t)]TIt indicates, wherein []TIndicate transposition operation.Correspondingly, background, which measures vector, can use Y (0)=[y1(0)y2
(0)…yL(0)]TTo indicate.Calculate the difference for measuring vector Y (t) and background measurement vector Y (0), so that it may to obtain t moment RSS
Diverse vector Δ Y (t)=abs [Y (t)-Y (0)]=[Δ y1(t)Δy2(t)…ΔyL(t)], wherein abs [] indicates absolute value
Operation.
Step 4: radio frequency tomography, forms image；
Image-forming principle is chromatographed according to radio frequency, can be obtained：
Δ Y=Wx+v (4)
Wherein, x=[x1,x2,…,xN]TIndicate the pixel vector that localization region divides, xi, i=1,2 ..., N indicates each picture
Value on vegetarian refreshments, v indicate that noise vector, weight matrix W are calculated according to formula (1)；
Regularization constraint item is introduced, it is as follows to obtain object function：
Wherein, α indicates that regularization coefficient, Q indicate regular matrix, | | | | it indicates 2 norms, solves formula (5), obtain：
X=(WTW+αQTQ)-1WTΔY (6)
Step 5: determining target location based on cross target automatic search method；
Step 5.1 eliminates the smaller noise spot of brightness value with averaging method：Flat is asked to the brightness of all pixels point on image
Mean value, sub-average pixel brightness value are set to 0；
Step 5.2, averaging method eliminate background after remain be only high brightness noise pixel, due to noise with
Machine, thus surrounding pixel can not possibly all be necessarily high luminance pixel.According to this characteristic and calculation amount is considered, by as follows
Rule recalculates the brightness value of all pixels point on imaging figure：It calculates centered on each pixel, brachium is the cross of r
The product of the brightness value of all pixels point in shape neighborhood, calculation formula are as follows：
Wherein, Π indicates that multiplication operation, x (i, j) denotation coordination are the original luminance value of the pixel of (i, j),Table
Show that coordinate is that the pixel of (i, j) recalculates rear brightness value, as m=0, n=-r,-r+1 ... -1,1 ... r-1, r work as n
When=0, m=-r,-r-1 ... -1,1 ... r-1, r；R indicates half arm lengths of cross；As shown in Figure 3；
Step 5.3, due to averaging method eliminate background during the brightness value of a part of background has been set as 0, because
As long as the brightness value of pixel is 0 there are one in the cross neighborhood of this certain pixel, brightness value is changing to zero.And for target
Pixel is all the higher pixel of brightness value in cross neighborhood, zero is very unlikely to become after multiplication, therefore in this end of the step
Later, the non-zero pixels region left i.e. target position, it is coordinate where target to take wherein brightest pixel coordinate.
Embodiment
The present embodiment is based on the CC2530 chips for meeting Zigbee protocol, independent development wireless receiving and dispatching node.It is fixed
The square region that position region is one 5 meters × 5 meters, 1 wireless receiving and dispatching node is put every 1 meter, in total 20 wireless receiving and dispatching sections
Point composition positioning network, in addition 1 radio node is responsible that measurement data is transmitted to computer as data acquisition node.It is each fixed
Position node is placed on height as on 1 meter of holder.In terms of software protocol, the present embodiment is assisted with the wireless communication of IEEE802.15.4
Based on view, using Z-stack protocol stack sofewares, independent development poll measures and received signal strength value is read program generation
Code.20 positioning nodes compile ID number successively from 1 to 20, and different modules is distinguished by the difference of the ID number.One node hair
When sending location data, data packet can carry the ID number of sending module, after next node receives this ID number, will trigger the section
The transmission of the location data of point, such poll measurement are just set up.After a sending node sends location data,
His positioning node will produce an intensity value RSSI when receiving the data, and this data is preserved immediately, then successively
It is sent to data acquisition node, and computer is sent to by data acquisition node.Once collect data, using the above method into
Row imaging and Objective extraction.As shown in figure 4, being that RTI technologies are imaged using the existing single target for waiting weights model of ellipse to obtain
Experimental result picture is in (1,2) rice position by positioning target, and Fig. 4 is the present invention elliptical modes of use layering under the same conditions
The single target imaging experiment result figure that type obtains is similarly in (1,2) rice position by positioning target.Fig. 4 is due to using fixation
The model of ellipse of weight, target highlight is not clear enough on figure, and there are large stretch of background shadows, and uses Fig. 5 of layering model of ellipse
Target image becomes apparent, but background interference is still relatively strong, is easy by pseudo- target jamming.As shown in fig. 6, using present invention side
After the target automatic Searching of method, ambient noise is obviously inhibited, and pseudo- target also no longer occurs.
Technical scheme of the present invention is not limited to the various embodiments described above, all technical solutions obtained using equivalent replacement mode
It all falls in the scope of protection of present invention.
Claims (5)
1. a kind of model class is without device target localization method, which is characterized in that include the following steps：
Step 1: establishing wireless location system, the positioning system includes several wireless receiving and dispatching nodes, wireless receiving and dispatching node two
It is communicated between two, forms multi wireless links；
Step 2: establishing the oval weight model of layering to the spatial relationship that Radio Link influences according to no device target；
Step 3: measuring RSS value of the Radio Link in no target and when having target respectively；
Step 4: calculating radio frequency based on the oval weight model of layering chromatographs imaging results, image is obtained；
Step 5: obtaining target location using cross target automatic search method.
2. model class according to claim 1 is without device target localization method, it is characterised in that：The positioning system includes
M+1 wireless receiving and dispatching node, carries out networking based on wireless communication protocol, wherein M wireless receiving and dispatching node, which is constituted, measures net
Network is evenly distributed on the periphery of positioning system institute localization region, and the M wireless receiving and dispatching node communicates between any two,
Form L=M × (M-1)/2 wireless links；The M+1 node is data acquisition node, is responsible for collecting data；The positioning area
Domain is evenly dividing as N number of pixel.
3. the model class is without device target localization method according to claim 1, it is characterised in that：The layering is oval
Gradual change shade weight model formula i-th in weight model corresponding to (i=1,2 ..., L) link is as follows：
Wherein, wijIt indicates when target is located at j-th of pixel on influencing corresponding weighted value, d produced by i-th linkiFor
I-th linkage length, dij1, dij2Respectively j-th of pixel to composition i-th two node of link distance, aiIndicate i-th
Link pair answers elliptical long axis length. For the corresponding maximum 1st luxuriant and rich with fragrance alunite of i-th article of link
That area radius, wherein λ indicate the wavelength of electromagnetic wave.
4. model class according to claim 1 is without device target localization method, it is characterised in that：The radio frequency tomography
Include the following steps：
Step 4.1, the RSS variable quantities for calculating separately L active link, are as a result denoted as Δ Y, and image-forming principle is chromatographed according to radio frequency,
It can obtain：
Δ Y=Wx+v
Wherein, x=[x1,x2,…,xN]TIndicate the pixel vector that localization region divides, xi, i=1,2 ..., N indicates each pixel
On value, v indicate noise vector, W is weight matrix；
Step 4.2 introduces regularization constraint item, and it is as follows to obtain object function：
Wherein, α indicates that regularization coefficient, Q indicate regular matrix, | | | | it indicates 2 norms, solves above formula, obtain：
X=(WTW+αQTQ)-1WTΔY。
5. model class according to claim 1 is without device target localization method, it is characterised in that：The cross target is automatic
Searching method includes the following steps：
Step 5.1 eliminates the smaller noise spot of brightness value with averaging method；The brightness of all pixels point on image is averaging
Value, sub-average pixel brightness value are set to 0；
Step 5.2, the brightness value for recalculating all pixels point on imaging figure calculate centered on each pixel, brachium
For the product of the brightness value of all pixels point in the cross neighborhood of r, calculation formula is as follows：
Wherein, Π indicates that multiplication operation, x (i, j) denotation coordination are the original luminance value of the pixel of (i, j),It indicates to sit
The pixel for being designated as (i, j) recalculates rear brightness value, and as m=0, n=-r,-r+1 ... -1,1 ... r-1, r work as n=0
When, m=-r,-r-1 ... -1,1 ... r-1, r；R indicates cross arm lengths；
Non-zero pixels region, that is, target position in step 5.3, image, it is target place to take wherein brightest pixel coordinate
Coordinate.
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