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Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment

Authors:
  • ELEDIA Research Center (ELEDIA@UniTN, University of Trento, Italy)

Abstract

In this paper, an innovative strategy for the passive localization of transceiver-free objects is presented. The localization is yielded by processing the received signal strength data measured in an infrastructured environment. The problem is reformulated in terms of an inverse source one, where the probability map of the presence of an equivalent source modeling the moving target is looked for. Toward this end, a customized classification procedure based on a support vector machine is exploited. Selected, but representative, experimental results are reported to assess the feasibility of the proposed approach and to show the potentialities and applicability of this passive and unsupervised technique.
UNIVERSITY
OF TRENTO
DIPARTIMENTO DI INGEGNERIA E SCIENZA DELL’INFORMAZIONE
38123 Povo – Trento (Italy), Via Sommarive 14
http://www.disi.unitn.it
ELECTROMAGNETIC PASSIVE LOCALIZATION AND TRACKING
OF MOVING TARGETS IN A WSN-INFRASTRUCTURED
ENVIRONMENT
F. Viani, P. Rocca, M. Benedetti, G. Oliveri, and A. Massa
January 2011
Technical Report # DISI-11-100
.
W SN
RF
W SN
T OA DOA
RSS
RSS
W SN
RF
W SN
LBE SV M
SV M
W SN
2D
D
τh(r) = εh(r)1jσh(r)
ωε0ω
r= (x, y)εhσh
τo(r)rDo
W SN S rss= 1, ..., S s
ξinc
s(r)(1)
S1
ξtot
s(rm) = ξinc
s(rm) + ZD
J(r)G0(r, rm)dr
G0rmm m =
1, ..., S 1D
J(r) = τ(r)ξtot (r)rD
τ(r) = τo(r)rDoτ(r) = τh(r)
rDh=DDoDoDh
ˆ
J(r)
ξtot
s(rm) = ˆ
ξinc
s(rm) + ZDo
ˆ
J(r)G1(r, rm)dr
ˆ
ξinc
s(rm) = ξinc
s(rm) + ZD
τh(r)ξtot
s,u (r)G0(r, rm)dr
ˆ
J(r) = ˆτ(r)ξtot
s,p (r) ˆτ(r) = τ(r)τh(r)
ξtot
s,u ξinc
s
(1)
G1
G1(r, r) = G0(r, r) + ZD
τh(r)G0(r, r”) G1(r, r)dr.
G1
ˆ
J
Do
D
ξtot (rm)m= 1, ..., S 1W S N
RSS RSS m
s ξinc
s(rm)
D ξtot
s(rm)
ξsct
m,s =ξtot
s(rm)ˆ
ξinc
s(rm)
W SN
W N S
D
ξsct
m,s s= 1, ..., S m = 1, ..., S m 6=s
SV M
D
C rcc= 1, ..., C
c χcχc=1
χc= 1
c
αc=P r {χc= 1|, c)}
αc=1
1 + exp npHhϕ, c)i+qo, c = 1, ..., C
Γ = nξsct
m,s;s= 1, ..., S;m= 1, ..., S;m6=nop q
ϕ(·)
Γ
H
H
TΓt= 1, ..., T
χt={χc,t;c= 1, ..., C }t= 1, ..., T
Hhϕ, c)i=w·ϕ, c) + b, c = 1, ..., C
w b
Ψ (w) = kwk2
2+λ
PT
t=1 C(t)
+
T
X
t=1
C(t)
+
X
c=1
η(t)
c++λ
PT
t=1 C(t)
T
X
t=1
C(t)
X
c=1
η(t)
c
w·ϕ, c) + b1η(t)
c+, c = 1, ..., C
w·ϕ, c) + bη(t)
c1, c = 1, ..., C
λ
η(t)
c+η(t)
c
rs= (xs, ys)s= 1, ..., S
D D
20λx20λ12λy12λ
λ
f= 2.4GHz S = 6
D
SV M
T
Hλ C
SV M
T[100,700] ∆T= 100 λ= 10ii={0,1,2,3}C[15,960]
C= 5 ×3 4λ×4λ
C= 40 ×24 λ×λ
ρ=rxact
jxest
j2+yact
jyest
j2
ρmax
ract
j=xact
j, yact
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j=xest
j, yest
j
ρmax
ρmax =qX2
D+Y2
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j
xest
j=PC
c=1 αcxc
PC
c=1 αc
yest
j=PC
c=1 αcyc
PC
c=1 αc
.
Topt = 500 λopt = 100 Copt = 60
SV M
ˆτ(r) = 0 ξsct
m,s = 0 m, s = 1, ..., S
m6=s RSS RSSm,s (t)m, s = 1, ..., S
m6=s t = 1, ..., T T
rj= (xj, yj)j= 1, .., T D
D3×102[s]T= 100 C= 15
104[s]T= 700 C= 960
SV M J = 1 J= 2
RSS 5×102[s]
RSS
S1 2 [s]
αcc= 1, ..., C 0.1 [s] 3 GHz
2GB
D ract
1= (16λ, 8λ)
SV M
D
RSS 6
SV M
T1J= 1
T2J= 2 T=T1+T2
T1T2
T1< T2
T1= 150
T2= 350
J= 2
j= 1 D j = 2
ρ1= 0.070 ρ2= 0.061 ρ1= 0.101 ρ2= 0.070
RSS W SN
W SN
SV M
(a)
(b)
XD
YD
x
y
(xc, yc)
(xs, ys)
D
W SN node
(a)
(xs, ys)
(xact
j, yact
j)
W SN node
(b)
W SN
2
4
6
8
10
12
14
16
18
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Localization Error, ρ [x102]
Normalized Parameter Value
T/Tmax - [Tmax=700]
λ/λmax - [λmax=1000]
C/Cmax - [Cmax=960]
SV M
T λ = 100 C= 60 λ T = 500 C= 60 C T = 500 λ= 100
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
(a)
(b)
D
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
(a)
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
(b)
D
-12
-8
-4
0
4
8
12
-20 -16 -12 -8 -4 0 4 8 12 16 20
y/λ
x/λ
Real
Estimated
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
(a) (b)
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
(c) (d)
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
(e) (f)
D
-12
-8
-4
0
4
8
12
-20 -16 -12 -8 -4 0 4 8 12 16 20
y/λ
x/λ
Real
Estimated
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
T1[0,500] T2[0,500]
λ= 100 C= 60 D
100 T10T280 T120 T260 T140 T240 T160 T2
20 T180 T20T1100 T2
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
−20 20
12
0.0 1.0
−12
λ
λ
{χΓ}
T1[0,500] T2[0,500]
λ= 100 C= 60 D
100 T10T280 T120 T260 T140 T240 T160 T2
20 T180 T20T1100 T2
-12
-8
-4
0
4
8
12
-20 -16 -12 -8 -4 0 4 8 12 16 20
y/λ
x/λ
Target 1 - Real
Target 1 - Estimated
Target 2 - Real
Target 2 - Estimated
-12
-8
-4
0
4
8
12
-20 -16 -12 -8 -4 0 4 8 12 16 20
y/λ
x/λ
Target 1 - Real
Target 1 - Estimated
Target 2 - Real
Target 2 - Estimated
Outdoor I ndoor
T ime I nstant ρ ρ ×ρmax [λ]ρ ρ ×ρmax [λ]
1 0.071 3.32 0.209 9.76
2 0.070 3.30 0.131 6.09
3 0.060 2.78 0.115 5.38
4 0.057 2.67 0.048 2.23
5 0.045 2.09 0.089 4.15
6 0.074 3.46 0.140 6.53
Average Error :ρ0.063 2.94 0.122 5.69
Sing le T arg et Multiple T arget
j= 1 j= 1 j= 2
ρ ρ ×ρmax [λ]ρ ρ ×ρmax [λ]ρ ρ ×ρmax [λ]
(a) 0.044 2.07 0.217 10.12 0.158 7.37
(b) 0.059 2.77 0.196 9.14 0.135 6.31
(c) 0.093 4.34 0.151 7.02 0.074 3.44
(d) 0.150 6.98 0.149 6.96 0.062 2.91
(e) 0.262 12.23 0.063 2.93 0.106 4.94
(f) 0.357 16.67 0.031 1.46 0.063 2.93
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