performances prediction of optronic sensors in maritime environment itbms 2011 – 27-30 june

Performances prediction

of optronic sensors inmaritime environment

ITBMS 2011 – 27-30 JuneL. Gardenal (CS, France)D. Dion (RDDC-Valcartier,

Canada)F. Lapierre (ERM, Belgium)

E. Mandine (CS, France)

CS Communication & Systèmes – ITBMS 20112

Outline

Frame

Overview on the LIBPIR library

First results

Future work

Perspectives


Frame

Since more than 10 years, CS works on optronic projects in different context (MWPS [maritime security], Basirn [IR images data base], Sypir, …)

3 years ago, CS has decided to invest on the development of a calculation library for predicting performances of optronic sensor

LIBPIR is the pedestal of a future PREDIR

First version of LIBPIR has just been completed by CS with the help of DRDC Valcartier and ERM

SMARTI : computational module developped by DRDC (Defence R&D Canada) including MODTRAN

OSMOSIS : opensource library developped by ERM (Royal Military Academy of Belgium)

It is currently integrated in the French Navy TDA « PSAD » by DCNS group

PSAD will provide the future french frigate FREMM with AC/EM/IR sensor performance assessment


Overview on the LIBPIR library (2/2)

TARGET- CAD

- Emissivity...

OSMOSISFacet surface temperature

Radiance target

calculation

Intrinsic target radiance

Meteorological and

environmental description

Reader

PROPAGATION MEDIUM

- Meteorological profiles

- Marine surface layer

- Sky+land+sea- ...

MODTRAN

SMARTI

Ray paths

Transmittances

Path radiances

Background radiances

SENSOR- Height

- Spectral band- Resolution

- ...

Target IR signature

calculationTarget radiance

2D optronic scene

Optical horizon, Maximum

InterVision Range

2D optronic scene

generator

3D intrinsic target radiance

image generator

Sensor performances

calculation

3D intrinsic target radiance image

Contrast, Detection

probability, DRI ranges


LIBPIR Calculation components

SMARTI (DRDC-Valcartier) Spectral and wideband CK transmittance & radiance

MODTRAN molecular extinctions (CK)

Marine surface layer model

MODTRAN and DRDC aerosol models

DRDC accurate refracted path calculation

Lambert and Sea surface (DRDC analytical model) BRDF

Reference: DENIS DION

Osmosis (ERM) Open-source target surface temperature Modeling Software

Fast and robust software

Validation : CUBI project

Reference: FABIAN LAPIERRE or www.osmosis-project.org


LIBPIR: Some intermediary results

1E-43

1E-41

1E-39

1E-37

1E-35

1E-33

1E-31

1E-29

1E-27

1E-25

1E-23

1E-21

1E-19

1E-17

1E-15

1E-13

1E-11

0.000000001

0.0000001

0.00001

0.001

0.1

0 5000 10000 15000 20000 25000

Distance (m)

Tra

nsm

itta

nce

LIBPIR IR3 LIBPIR ADVECTIVE FOG LIBPIR // RADIATIVE FOG

0

20

40

60

80

100

120

140

160

180

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0 5000 10000 15000 20000 25000 30000 35000 40000

RANGE

HE

IGH

T


First resultsInfluence of environment on performances of optronic

sensorsSensor: 3 FOV:

• 40°x30° (for short ranges)• 5°x3.75°(for medium ranges)• 2°x1.5° (for long ranges)

Height: 10 m

MidWave

Environment: 3 RH: 50, 80 and 95%

3 WSPD: 5, 10 and 15 m/s

3 ASTD: -10, 0 and 10 °C

Advective and radiative fogs

12h00 // MAY 2010

Place: Mediterranean sea (South of France)

Target: Destroyer


First results First task: Definition of optical properties on the target

VISIBLE / 12h00

50°C

Albedo = 0.9

Albedo = 0.5

Albedo = 0.1


First results IR signature: influence of the optronic band

VISIBLE SWIR

LWIRMWIR


First results Influence of ASTD on an optronic scene

ASTD = 0°C ASTD = -10°C ASTD = +10°C

10 km

20 km 5*3.75°


First results Influence of ASTD on an optronic scene

ASTD = 0°C ASTD = -10°C ASTD = +10°C

Apparition of mirage (ASTD < 0°C)

Compression of target image (ASTD growing)

Variation of optical horizon

Limitation of the target detected form (ASTD < 0°C)

20 km

2*1.5°


Range = 4.5 km

ASTD = +10°C

ASTD = -10°C


Range = 5.6 km

ASTD = +10°C

ASTD = -10°C


Range = 6.7 km

ASTD = +10°C

ASTD = -10°C


Range = 7.8 km

ASTD = +10°C

ASTD = -10°C


Range = 8.9 km

ASTD = +10°C

ASTD = -10°C


Range = 10.0 km

ASTD = +10°C

ASTD = -10°C


Range = 11.1 km

ASTD = +10°C

ASTD = -10°C


Range = 12.2 km

ASTD = +10°C

ASTD = -10°C


Range = 13.3 km

ASTD = +10°C

ASTD = -10°C


Range = 14.4 km

ASTD = +10°C

ASTD = -10°C


Range = 15.5 km

ASTD = +10°C

ASTD = -10°C


Range = 16.6 km

ASTD = +10°C

ASTD = -10°C


Range = 17.7 km

ASTD = +10°C

ASTD = -10°C


Range = 18.8 km

ASTD = +10°C

ASTD = -10°C


Range = 19.9 km

ASTD = +10°C

ASTD = -10°C


Range = 18 km

ASTD = +10°C

ASTD = -10°C


Range = 16.6 km

ASTD = +10°C

ASTD = -10°C


Range = 15.5 km

ASTD = +10°C

ASTD = -10°C


Range = 14.4 km

ASTD = +10°C

ASTD = -10°C


Range = 13.3 km

ASTD = +10°C

ASTD = -10°C


Range = 12.2 km

ASTD = +10°C

ASTD = -10°C


Range = 11.1 km

ASTD = +10°C

ASTD = -10°C


Range = 10.0 km

ASTD = +10°C

ASTD = -10°C


Range = 8.9 km

ASTD = +10°C

ASTD = -10°C


Range = 7.8 km

ASTD = +10°C

ASTD = -10°C


Range = 6.7 km

ASTD = +10°C

ASTD = -10°C


Range = 5.6 km

ASTD = +10°C

ASTD = -10°C


Range = 4.5 km

ASTD = +10°C

ASTD = -10°C


First results Fog examples

LWC = 0.01 g/m3Range = 1 km

LWC = 0.01 g/m3Range = 0.5 km

LWC = 0.01 g/m3Range = 1 km

LWC = 0.01 g/m3Range = 0.5 km

ADVECTIVE RADIATIVE


Some first performance results

Contraste max

Detection probability (PoD) Max value

Using « noise equivalent irradiance » (5e-9 W/m2) for calculating signal to noise ratio

Using Detection probability curves

Pfa = 10-5

DRI ranges Based on Jonhson Critera (NvTherm approach)

Acquistion probability = 0.99


First results Influence of relative humidity on contrast

0

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5000 7000 9000 11000 13000 15000 17000 19000

RANGE (m)

CO

NT

RA

ST

(%

)

RH = 50 p.c. RH = 80 p.c. RH = 95 p.c.


First results Influence of wind speed on contrast

0

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90

100

5000 7000 9000 11000 13000 15000 17000 19000

RANGE (m)

CO

NT

RA

ST

(%

)

WSPD = 5 m/s WSPD = 10 m/s WSPD = 15 m/s


First results Influence of relative humidity on PoD

0

10

20

30

40

50

60

70

80

90

100

5000 7000 9000 11000 13000 15000 17000 19000

RANGE (m)

Pd

(%

)

RH = 50 p.c. C RH = 80 p.c. RH = 95 p.c.


First results Influence of wind speed on PoD

0

10

20

30

40

50

60

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80

90

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5000 7000 9000 11000 13000 15000 17000 19000

RANGE (m)

Pd

(%

)



First results Influence of relative humidity on DRI ranges

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

Identification Recognition Detection

Range (m)

RH = 50 p.c. RH = 80 p.c. RH = 95 p.c.


First results Influence of wind speed on DRI ranges

0

5000

10000

15000

20000

25000

30000

35000

Identification Recognition Detection

Range (m)



First conclusions

LibPir results coherent with what is expected: Contrast is better with

• Low relative humidity (small differences)

• Low wind speed

System PoD is better with:

• Low relative humidity (small differences)

• Low wind speed

Estimation of DRI sensor performances: Better with low relative humidity and low wind speed

LibPir calculation time: 1 to few minutes

Calculation coherent along the atmospheric column

Marine surface layer characteristics are taken into account refraction

presence of sea aerosol particles

humidity gradient


Future works and perspectives

Future works : Take into account Inhomogeneous environnement by coupling LIBPIR with a NWP

model (like Arome from Meteo France)

Add Turbulence effects (scintillation, diffusion and centroïd move)

Use Sea, land and sky texture (for IR scene purpose)

Improve

• sensor model (MRTD, PoD)

• Air target model (plume, gaz, …)

• Surface target model (e.g. adding wake)

Work with Matisse

… integration in a stand-alone software (PREDIR)

Short-term perspective: Measurement campaign for Aerosol model improvement

Validation of the coupling of Meteo France NWP Arome with a 3D aerosol extinction


Performances prediction of optronic sensors in maritime environment

Thank you for your attention

Any questions ?

Mail: [email protected]

performances prediction of optronic sensors in maritime environment itbms 2011 – 27-30 june

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