1 university of pretoria & csir small vessel detection in coastal radar data m.d. strempel under...

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1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

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Page 1: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

1

UNIVERSITY OF PRETORIA

& CSIR

Small Vessel Detection In Coastal Radar Data

M.D. StrempelUnder supervision of

Dr. P. de Villiers

Page 2: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

2

Summary

• Detect small vessels and other low observables from dense clutter data

Time [s]

Ran

ge [

m]

TFC15_023 No Threshold filtering Time bins 10:13

0 5 10 15 20 253000

3200

3400

3600

3800

4000

4200

4400

-60

-50

-40

-30

-20

-10

0

10

Time [s]

Ran

ge [

m]

TFC15_023 No Threshold filtering Time bins 10:13

0 5 10 15 20 253000

3200

3400

3600

3800

4000

4200

4400

-60

-50

-40

-30

-20

-10

0

10

Page 3: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

3

Summary

• Detect small vessels and other low observables from dense clutter data

Time [s]

Ran

ge [

m]

TFC15_023 No Threshold filtering Time bins 10:13

85 90 95 100 1053000

3200

3400

3600

3800

4000

4200

4400

-60

-50

-40

-30

-20

-10

0

10

Time [s]

Ran

ge [

m]

TFC15_023 No Threshold filtering Time bins 10:13

85 90 95 100 1053000

3200

3400

3600

3800

4000

4200

4400

-60

-50

-40

-30

-20

-10

0

10

Page 4: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

Current Methodology

4

• Approach 1: Image processing technique• Approach 2: Time-based technique• Approach 3: Clustering technique (currently being pursued)

Page 5: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

Proposed Methodology

5

• Approach 1: Image processing technique– Use common image processing algorithms to simplify datasets.– detect and then track wave crests– Can then combine crests into groups– This can improve track quality and reduce computational

complexity

Page 6: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

3000 3500 4000 4500-10

-5

0

5

10

15

20

25Range bin time series analysis

Range [

m]

Time [s]

Proposed Methodology

6

• Approach 2: Time-based technique

– Specific range bin analysis (Bin: 3010)– Do estimation in the time series domain

– When sinusoidal structure collapses (estimation covariance high), there is a chance of a target – indicated by flat spot in this graph

target

Time [s]

Range [

m]

TFC15_023 No Threshold filtering range bin 10

1 2 3 4 5 6

x 104

34353435.23435.43435.63435.8

-40

-20

0

Page 7: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

Proposed Methodology

7

• Approach 3: Clustering technique

– Specific Time bins– Bins: 10s to 13s– Track peaks above

threshold– Association on peaks– Cluster on tracks

Page 8: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

Proposed Methodology

8

• Approach 3: Velocity clustering technique

track1

track2

track3 Wav

e tr

ack

Page 9: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

Proposed Methodology

9

• Approach 3: Velocity clustering technique

• Association techniques:• Associate on velocity • Associate based on Doppler

track1

track2

track3 Wav

e tr

ack

Page 10: 1 UNIVERSITY OF PRETORIA & CSIR Small Vessel Detection In Coastal Radar Data M.D. Strempel Under supervision of Dr. P. de Villiers

Proposed Methodology

10

• Approach 3: Velocity clustering technique• Moving data illustration