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Automatic real-time collection of RCS of airplanes in a real bistatic configuration

using a passive SDR based on illuminators of opportunity

Jonathan PISANE, Sylvain AZARIAN,

Marc LESTURGIE, Jacques VERLY

SONDRA Lab, SUPELEC, France EECS, University of Liège, Belgium

Rungis Sept. 24th 2012

OUTLINE

l  Motivation for collecting RCS

l  Computation of RCS l  System requirements

l  System architecture

l  Signal processing l  Classification of air targets based on collected data

l  Conclusions

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Goal: Identify ?’s (+ check response from ADS-B)

SN533, A320 transponder ON

? Unknown airplane transponder OFF

?

SN533, A320

Radar

MOTIVATION : CLASSIFICATION OF AIR TARGETS

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PPI

MOTIVATION: ENVISIONED SYSTEM

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Receiver 2 Illuminators of opportunity

Receiver 3

Receiver 1

GSM

DVB-T

•  Bistatic configuration •  Operate at low frequency (<1GHz) •  Data = RCS of airplanes •  No image reconstruction

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COMPUTATION OF RCS

Direct-path signal: Echo signal:

PRD =PTGTGR

LPRE =

PTGTGR!2"

(4# )3R2TR2R

! =PREPRD

(4" )3RR2RT

2

# 2L

Receiver Transmitter

RT σ

L

RR

PTGT PRE

GR PRDGR

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l  Detection of airplane

l  Geometry of configuration to be known: => Distances RR and RT

l  Selection of transmitter

l  Acquisition of received signals => Powers PRE

and PRD => Quasi constant loss L

l  Signal processing to compute « true » RCS σ

SYSTEM REQUIREMENTS

! =PREPRD

(4" )3RR2RT

2

# 2L

USB or remote

Network (direct or Internet)

Network (direct or Internet)

Donor(VOR, FM station, …)

Donor(VOR, FM station, …)

Geo databaseDonors & Receivers

Software Defined Receiver

Software Defined Receiver

SDR controller

ADSB-B decoderKinetic SBS-1

ADSB Receiver

Apache Tomcatsupervision

MySQL

remote

Central systemData collection / storage / analysis

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SYSTEM ARCHITECTURE

Detection of plane

Illuminator of opportunity

Reception of signals

Digital signal processing

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PRACTICAL IMPLEMENTED SYSTEM

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RECEIVED POSITIONS OF AIRPLANES

Positions given by ADS-B receiver

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!

Doppler  

AIRPLANE DATA RECONSTRUTED FROM DECODED ADS-B FRAMES Airplane  trajectory    

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SELECTED VOR TRANSMITTER

Software Defined Receiver

Receiver tuned on a “quiet” area of the spectrum to have good SNR

Needs: - Constant frequency - Constant power - Few modulation

s(t) = Ae j! (t )e2" ft

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SDR RECEIVER: PRINCIPLE

CPUADCDAC

Digital world Analog world

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SDR FRONT-END ARCHITECTURE

!

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DIGITAL SIGNAL PROCESSING

l  I(t), Q(t) => I[n], Q[n]: digitizing by computer sound card

l  Doppler processing + PR = I n[ ]+ jQ n[ ]2

Frequency

Tim

e

Direct-path signal

Echo signal on airplane

Estimated from ADS-B data

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COMPUTED RCS

No ADS-B data No Doppler

l  Objects to be classified:

l  Experiments run for 10 days => 1329 airplanes of 41 different types detected => 54154 sample RCS’s computed

l  Large-size: 47 airplanes, 2672 sample RCS’s l  Mid-size: 549 airplanes, 25741 sample RCS’s (+small-size)

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CLASSIFICATION: DATA & CLASSES

z(i) =! (",# )," ! "min,"max[ ]! ! !min,!max[ ]

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Orientation angle

RCS(β,θ) FOR LARGE-SIZE AIRPLANES B

ista

tic a

ngle

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Bis

tatic

ang

le

Orientation angle

RCS(β,θ) FOR MID-SIZE AIRPLANES

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Orientation angle

RCS(β,θ) FOR SMALL-SIZE AIRPLANES B

ista

tic a

ngle

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CLASSIFICATION: PARAMETER SPACE

Tr1

!

"#0!#

#

Tr2

1

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CLASSIFICATION

l  Each target class j characterized by a vector space U(j)

of K singular vectors

l  Classification criteria (Projection):

ρ = weight of sing. vectors

l  Class(z) attributed corresponds to higher E(j)

l  Aggregation according to majority vote

E!( j ) =

!i!1

!

"#

$

%&

"zHui

( j )ui( j )H z

zH zi=1

K

' ,! = 0,0.05,{ 1}

θ = [0°; 360°]

β =

[0°;

180

°] -­‐0.25   0.70   0.76   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   0.99   -­‐0.25   -­‐0.25  

0.88   0.78   0.91   0.85   0.93   0.79   0.98   0.91   0.96   0.88   0.99   0.96  -­‐0.25   0.81   0.74   -­‐0.25   0.80   0.50   0.93   0.87   0.79   0.74   -­‐0.25   -­‐0.25  -­‐0.25   0.93   -­‐0.25   -­‐0.25   0.73   0.49   0.91   -­‐0.25   0.88   0.72   -­‐0.25   -­‐0.25  -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   0.77   0.99   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25  -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   0.83   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25   -­‐0.25  

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CLASSIFICATION OF AIR TARGETS BASED ON THEIR RCS : RESULTS

•  3 classes: large-size (A343), mid-size (A319), small (simulated) airplanes

Angular step = 30°

Overall classif: 83%

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CONCLUSIONS

l  Motivation: classify air targets according to their RCS, acquired in bistatic mode, at low-frequency

l  RCS computed based on received direct-path and echo signals

l  Needed components: - Existing transmitter of opportunity - ADS-B receiver & decoder - SDR receiver + digital signal processor

l  Real RCS computed at low cost l  Entirely automated system l  Classification based on vector spaces l  Achieved classification rate = 83% l  Interesting and non-interesting configurations

Thank you for listening

Any question?

This work has been funded by Belgian FRIA scholarship

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