RFI MITIGATION
RFI MITIGATION Applications to Nançay Observatory and LOFAR
, )
Rodolphe WEBER((1,2)
Cedric DUMEZ‐VIOU(2)
Rym FELIACHI(1)
Dalal Ait‐Allal
Ait Allal(2)
(1) Institut
PRISME, Université d’Orléans
de radioastronomie de Nançay
Observatoire de Paris
(2) Station
Example 1 : Decameter band
10 – 100 MHz
N
Nançay decameter array
d
t
L
2
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Example 2 : meter band
150‐450 MHz
Nançay Radioheliographe
ç y
g p
(Solar Interferometer)
3
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Exemple 3 : LOFAR
110 – 240 MHz
30 – 80 MHz
4
With RFI
Wi h
Without RFI
RFI
Courtesy of A.J. Boonstra (Astron)
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Exemple 4 : EMBRACE => AAVP
Multi‐beam
Multi
beam
capability
5
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Example 5 : Square Kilometer Array
70MHz – 10 GHz Australia site
6
South Africa site
Courtesy of M. Kesteven (CSIRO)
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
RFI mitigation approaches
•Prevention of RFI :
•Quiet zones, sitingg
•Regulatory measures
•Self‐generated RFI (Shielding)
Australian core site (RQZ)
3 nano‐human/m2
• RFI Detection
• blanking
• flagging
7
no power grid
• Spatial selectivity
• Adaptive filtering by using reference antenna
• Adaptive Beamforming
Ad i B
f
i
• Subspace approaches
• Estimation and subtraction
Estimation and subtraction
• Parametric
• post‐correlation
• Others…
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Power detection and blanking
8
algorithms
hard
dware
Operational power blanker implementation on a digital receiver (PhD, C.Dumez‐Viou) Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Example : Decimeter band
1.1 – 3.5 GHz Nançay decimeter
p
Radio telescope
9
Measured spectrum
Expected profile
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Others Results
Operational power blanker implementation on a digital receiver (PhD, C.Dumez‐Viou) 10
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Cyclostationary detector
RFI Mitigation for pulsars , Giant pulse detection (PhD, Dalal Ait‐Allal)
RFI
Power Detector
2.5
2
wrong
wrong
wrong
1.5
1
0
1000
2000
3000
4000
5000
6000
7000
8000
Conjugate Cyclostationary detector Cαs with α =2fc
11
1
08
0.8
0.6
0.4
0.2
0
1000
2000
3000
4000
5000
6000
7000
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
8000
Pulsar Hardware
Collaboration with the University of Manchester : JRA Uniboard
(JIVE, Astron, Observatoire de Bordeaux, INAF,KASI)
12
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
RFI mitigation approaches
•Prevention of RFI :
•Quiet zones, sitingg
•Regulatory measures
•Self‐generated RFI (Shielding)
• RFI Detection
• blanking
• flagging
13
• Spatial selectivity
• Adaptive filtering by using reference antenna
• Adaptive Beamforming
Ad i B
f
i
• Subspace approaches
• Estimation and subtraction
Estimation and subtraction
• Parametric
• post‐correlation
• Others…
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Antenna array approach
Contextt
x(n) =[x1(n) x2(n)Lxp(n)]H
[ ]
R = E x.x H
M
Model
R
R
rfi
cosmic
647
48 64447
4448 antenna
With the narrow band } noise
H
H
hypothesis :
R = A rfi B rfi A rfi
+ A cosmic B cosmic A cosmic
+
N
where A rfi , A cosmic ≈ Spatial information,
Allgorithm
14
Spatial filtering:
B rfi , B cosmic ≈ Signal information
H
H
A rfi ) −1 A rfi
1) projector P = I − A rfi ( A rfi
2) cleaning:
R clean = PRP
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Classical spatial filtering
If Rrfi << N and array calibrated (i.e. )
R = R rfi + σ N2 I
1) EVD
EVD : : R = UΛU H
2) Extract the RFI subspace : Urfi
U rfi = span{A rfi }
3) Since , H
H
Projector :
j
P = I − U rfi (U rfi
U rfi ) −1 U rfi
4) R clean = PRP
eigenvalue
1 2 3
U= Urfi
4
5
p
Unoise
LOFAR ITS examples:
Simulation : INR>>0dB
Real data
15
Courtesy of A.J. Boonstra (Astron)
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Cyclic spatial filtering (simulation)
If the previous hypothesis cannot be stated : Cyclic spatial filtering
[
]
R α = E xx H exp( − j 2 πα t ) = R αrfif + R αcosmic + N α
14
42 44
3
cleaned map INR=-10 BPSK
1
15
0.8
Cyclic Rα
approach
Observation
initial map INR=-10 BPSK
10
06
0.6
0.4
5
0.2
y
SVD
=0
R clean = PRP
P
Urfi
0
0
1
-0.2
15
08
0.8
Brouilleur
B
ill
(RFI)
0.6
-5
-0.4
04
10
-0.6
0.4
5
-1
-1
0.2
Source
y
-10
-0.8
-15
-0.5
0
x
0.5
1
0
0
cleaned map classic INR=-10 BPSK
-0.2
0.8
-0.4
-10
6
0.6
4
-0.6
0.4
-0.8
-1
-1
2
-15
15
-0.5
0
x
0.5
INR=‐10dB
0.2
y
16
1
-5
1
Classical R
pp
approach
0
0
-0.2
-2
-0.4
-4
-0.6
-6
-0.8
-8
-1
-1
-0.5
0
x
0.5
1
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Cyclic spatial filtering (LOFAR)
Spectrum of the data before and after Spatial Filtering
31
initial
after cyclic SF
RFI :DAB
RFI :DAB
Power Spectru
um Magnitude (dB)
30
nulling
ll
29
28
27
26
25
24
23
222
Classical approach
4
8
800
7
700
6
225
225.5
226
Collaboration with Albert‐Jan Boonstra,Astron
Eigen Values structure for DAB
x 10
223.5
224
224.5
Frequency (MHz)
Eigenvalue decomposition
normalized power
normalized power
223
Cyclic approach
Eigen Values structure for the DAB
900
17
222.5
600
500
5
4
3
400
2
300
200
1
1
2
3
4
5
eigen values
6
7
8
0
1
2
3
4
5
eigen values
6
7
8
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
RFI mitigation approaches
•Prevention of RFI :
•Quiet zones, sitingg
•Regulatory measures
•Self‐generated RFI (Shielding)
• RFI Detection
• blanking
• flagging
18
• Spatial selectivity
• Adaptive filtering by using reference antenna
• Adaptive Beamforming
Ad i B
f
i
• Subspace approaches
• Estimation and subtraction
Estimation and subtraction
• Parametric
• post‐correlation
• Others…
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Estimation and Subtraction
α
R rfi
For some modulations, a precise description of can be derived :
From , we estimate and subtract it from From
Rαrfi , we estimate R̂rfi and subtract it from R
ˆ =R
R cleaned = R − R
cosmic + N
rfi
cleaned map E&S INR=0 BPSK
1
15
0.8
0.6
10
0.4
0.8
Brouilleur
(RFI)
14
12
0.4
Source
02
0.2
EEstimation
i
i
Subtraction
y
16
0.6
0
-0.4
10
-0.6
8
-0.8
-1
-1
1
0
-5
-10
-0.5
0 INR=0 BPSK
0.5
cleaned map cyclic
x
1
4
-0.2
2
-0.4
0
-0 6
-0.6
-2
-0.8
-4
15
0.8
Spatial
Filteringg
0.6
10
0.4
5
0.2
y
y
0
-0.2
6
19
5
0.2
initial map INR=0 BPSK
1
0
0
-1
-1
-0.5
0
x
0.5
1
-6
-0.2
-0.4
-5
-0.6
-10
10
-0.8
-1
-1
-0.5
0
x
0.5
1
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
LOFAR Hardware
20
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Conclusions
1) Radio telescope sensitivity :
Next generation telescopes = 10‐100 x current telescopes
⇒Very good for observing weaker cosmic signals df
b
k
l
⇒BUT also more sensitive to radio frequency interferences (RFI)
2) Telecommunication context :
Th
The demand for radio spectrum is growing
d
df
di
t
i
i
⇒ amount of RFI may increase
21
It is possible to minimize RFI influence on radio observations by It i
ibl t
i i i RFI i fl
di b
ti
b
using more or less sophisticated signal processing techniques
‐ Algorithm design
Cost impact on the system design ?
Cost
pact o t e syste des g
‐ Hardware design
Hardware design
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Conclusions
It is possible to minimize RFI influence on radio observations by using more or less sophisticated signal processing techniques
BUT :
‐ What is the risk to lose the signal of interest while suppressing the RFI ?
‐ What is impact on data quality ?
‐ What is the impact on calibration ?
AND
‐ What is the cost impact on the system design (Hardware and Software)?
22
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Conclusions
SKA Strategy
23
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Conclusions (Pro’s and Con’s)
24
Courtesy of A.J. Boonstra (Astron)
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)
Conclusions (maturity)
25
Courtesy of A.J. Boonstra (Astron)
Journée des technologies de l’OBSERVATOIRE de PARIS, 25 Mars 2009 (R.Weber, C. Dumez‐Viou)