This work was supported in part by National Key RD Program of China (Grant No. 2017YFB0502- 703) and National Natural Science Foundation of China (Grant Nos. 61991422, 61822107).
Tables
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Figure 1
(Color online) (a) GF-3 example scene and (b) the corresponding aerial image.
Figure 2
(Color online) Distribution of ships in the Huangpu River of Shanghai at 20:56 on November 18, 2018 as extracted from AIS dataset.
Figure 3
(Color online) The framework of SAR-AIS matchup and ship annotation.
Figure 4
(Color online) The flowchart of the multi-scale CFAR ship detection algorithm.
Figure 5
(Color online) AIS-SAR co-registration.
Figure 6
(Color online) Result of AIS-SAR co-registration. (a) SAR image and (b) AIS reports co-registered with SAR image.
Figure 7
(Color online) SAR-AIS matchup via Hungarian algorithm. (a) Original SAR image; (b) SAR detected ships matched-up with AIS reports.
Figure 8
(Color online) The flowchart of sea-land segmentation.
Figure 9
(Color online) The experimental results of LGMM. (a) Bimodal-peak vs. (b) single-peak.
Figure 10
(Color online) The results of sea-land segmentation.
Figure 11
(Color online) Ship detection result of multi-scale CFAR algorithm (detailed information is shown in Table
Figure 12
FUSAR-Ship of marine objects. From top to bottom, they are ships, strong scatterers, bridges, coastal lands & islands, sea clutter waves, random sea, and land sample patches, respectively.
Figure 13
The structure of 7-category CNN.
Figure 14
(Color online) The results of one example image (from left to right, top to bottom). (a) GF-3 SAR images, (b) AIS-SAR co-registration, (c) sea-land segmentation, (d) ship detection, (e) false-alarm discrimination, (f) ship target contour extraction, (g) final result of ship detection, (h) local amplification result of (g)-1, (i) local amplification result of (g)-2.
Figure 15
(Color online) The taxonomy of SAR ships.
Figure 16
Different categories of ships in FUSAR-Ship.
Figure 17
(Color online) The distribution of FUSAR-Ship datasets of ships. From top to bottom, they are bulk carriers, general cargos, containers, other cargos, fishing, tankers, other ships, and false alarms, respectively.
GF-3 | Sentinel-1 | RadarSat-2 | |
Frequency (km) | 755 | 693 | 798 |
Peak power (kW) | 1.5 | 4.7 | 1.27 |
Incident angle | $10^{\circ}$–$60^{\circ}$ | $20^{\circ}$–$45^{\circ}$ | $10^{\circ}$–$60^{\circ}$ |
Antenna size | 15 m$\times$1.5 m | 12.3 m$\times$0.84 m | 15 m$\times$1.37 m |
Bandwidth (MHz) | 240 | 100 | 100 |
Polarization mode | Single/double/quad polarization | Single/double polarization | Single/double/quad polarization |
Elevation sweep angle | $\pm20^{\circ}$ | $\pm11^{\circ}$ | $\pm20^{\circ}$ |
No. of imaging mode | Spotlight Mode, Strip Mode, Sweep Mode, Wave Mode, Ultrafine Mode, etc | Strip Mode, TOPS Mode, Wave Mode, Ultra-width Mode, etc | Strip Mode, Sweep Mode, Ultrafine Mode, etc |
Resolution (m) | 0.5–500 | 5–20 | 1–100 |
Imaging swath (km) | 10–650 | 20–400 | 20–500 |
Lifespan (year) | 8 | 7.5 | 7.5 |
Ships | Strong | Bridges & | Coastal lands | Sea clutter | Sea patches | Land | |
scatterers | coastlines | & islands | waves | patches | |||
Training data | 1296 | 229 | 1023 | 707 | 1377 | 1250 | 1137 |
Validation data | 555 | 128 | 438 | 303 | 590 | 535 | 487 |
Dataset | 1851 | 427 | 1461 | 1010 | 1967 | 1785 | 1624 |
Category | Ships | Strong | Bridges & | Coastal lands | Sea clutter | Random sea | Random |
scatterers | coastlines | & islands | waves | land | |||
Ships | 529 | 15 | 0 | 0 | 1 | 0 | 0 |
Strong scatterers | 14 | 103 | 0 | 0 | 0 | 0 | 2 |
Bridges & coastlines | 3 | 1 | 428 | 3 | 1 | 0 | 0 |
Coastal lands & islands | 4 | 3 | 6 | 287 | 4 | 1 | 3 |
Sea clutter waves | 2 | 6 | 0 | 3 | 575 | 2 | 0 |
Random sea | 0 | 0 | 1 | 1 | 4 | 528 | 13 |
Random land | 3 | 0 | 3 | 9 | 5 | 2 | 469 |
Sum | 555 | 128 | 438 | 303 | 590 | 535 | 487 |
Accuracy (%) | 95.32 | 80.47 | 97.72 | 94.72 | 97.48 | 98.69 | 96.30 |
Overall accuracy = 96.15% |
Attribute | CHANGKUN7 | HONGFAN6 | SHUIWU | XINHAIHUA | ZHESHENGYU07817 | HANGONGJIAO4 |
CallSign | BHNR2 | 0 | BINW | 0 | 0 | 0 |
IMO | 0 | 0 | 0 | 413441210 | 0 | 0 |
MMSI | 413363550 | 413784469 | 413370630 | 413441210 | 900307817 | 413824589 |
ShipTypeEN | Tanker | Cargo ship | LawEnforceVessel | Passenger ship | WIG | OtherTypeOfShip |
NavStatusEN | Under way | Under way | Moored | Under way | Unknown | Under way |
using engine | using engine | using engine | using engine | |||
Length | 104 | 78 | 30 | 38 | 50 | 25 |
Width | 15 | 14 | 4 | 7 | 6 | 7 |
Draught | 5.2 | 3.9 | 1.6 | 1.5 | 0 | 0 |
Heading | 511 | 249 | 511 | 298 | 511 | 178.2 |
Course | 241.4 | 249.6 | 293.4 | 80 | 268 | 16.1 |
Speed | 8.9 | 5.4 | 0 | 0 | 1.9 | 0.1 |
Lon | 117.40E | 117.36E | 121.46E | 122.18E | 123.18E | 118.3E |
Lat | 30.47N | 30.46N | 31.27N | 29.56N | 31.20N | 31.11N |
Dest | AN QING | SHANGHAI | SHENJIAM | – | – | – |
UnixTime | 1487200911 | 1487221804 | 1487086914 | 1487047384 | 1487080221 | 1487250424 |
Lon_d | 117.66848 | 117.605323 | 121.771713 | 122.302167 | 123.303615 | 118.06088 |
Lat_d | 30.792795 | 30.772788 | 31.466342 | 29.944667 | 31.339332 | 31.193668 |
pos_y | 1861 | 10527 | 6100 | 6143 | 20705 | 1707 |
pos_x | 13030 | 4070 | 20916 | 20144 | 21913 | 6004 |
ship_y | 1850 | 10530 | 6094 | 6104 | 16636 | 1614 |
ship_x | 13040 | 4084 | 20814 | 20164 | 21440 | 6000 |
Polarization mode | DH | DH | DH | DV | DV | DV |
Incident angle | 27.28 | 27.28 | 27.28 | 40.36 | 40.36 | 40.36 |
Resolution | 1.726$\times$1.124 | 1.726$\times$1.124 | 1.726$\times$1.124 | 1.736$\times$1.124 | 1.736$\times$1.124 | 1.736$\times$1.124 |
Category | Bulk | General | Container | Other | False | Fishing | Other | Tanker |
carrier | cargo | cargo | alarm | ship | ||||
Bulk carrier | 240 | 0 | 0 | 0 | 0 | 0 | 2 | 1 |
General cargo | 0 | 120 | 0 | 5 | 1 | 5 | 25 | 16 |
Container | 0 | 0 | 65 | 4 | 12 | 4 | 9 | 0 |
Other cargo | 10 | 5 | 3 | 166 | 18 | 3 | 37 | 7 |
False alarm | 0 | 1 | 5 | 11 | 2406 | 8 | 21 | 2 |
Fishing | 0 | 1 | 0 | 1 | 1 | 10 | 3 | 0 |
Other ship | 82 | 51 | 1 | 116 | 102 | 76 | 519 | 35 |
Tanker | 0 | 0 | 0 | 1 | 2 | 1 | 0 | 52 |
Accuracy (%) | 72.28 | 67.42 | 87.84 | 54.62 | 4.65 | 9.35 | 84.25 | 46.18 |