For commercial ship traffic the automatic identification system (AIS) is obligatory for all vessels above a certain size and thus warrants their cooperative classification and even identification. However, for smaller craft and especially for non-cooperative objects with hostile intent, the classification has to rely on classical approaches of automatic target recognition (ATR), which mostly are based on radar due to its day/night and all-weather capabilities. This leads to applications such as coastal surveillance for border control, the protection of harbour installations, ship self-defence or the suppression of drug trafficking, where the classification of ships by means of ATR schemes becomes more and more important. This is especially true in times of asymmetric (terrorist) threat and piracy. With a modern high resolution radar one has the choice of two different ways of target imaging. The first is 2D imaging, either from an airborne (SAR) or from a ground-based platform (ISAR). The latter depends on the relative motion of the target itself and therefore may be difficult in the case of non-cooperative targets. The desired axis of rotation should be vertical, which may not be the case when high sea states cause strong roll and pitch motion for smaller ships. Moreover, when the hostile ship is approaching or receding on a straight course, there is no relative rotation that lends itself to ISAR exploitation.
Chapter Contents:
- 4.1 Introduction
- 4.2 The use of high range resolution (HRR) profiles for ATR
- 4.3 The derivation of ATR features from HRR profiles
- 4.3.1 Length estimate
- 4.3.2 Position specific matrices (PSMs)
- 4.3.2.1 Determination of length
- 4.3.2.2 Alignment
- 4.3.2.3 Quantisation
- 4.3.2.4 Creation of reference PSMs
- 4.3.2.5 Compare the quantised test profile to the reference PSMs
- 4.3.2.6 Determine a figure of merit
- 4.3.2.7 Classification
- 4.3.3 Other examples of ATR features
- 4.3.4 Choosing sets of uncorrelated features
- 4.4 Ship ATR under the influence of multipath
- 4.4.1 What is multipath?
- 4.4.2 The problem of defining testing and training vectors
- 4.5 Results
- 4.5.1 Length estimate
- 4.5.1.1 Results for L
a and L
b based on measurements of ship HRR profiles
- 4.5.1.2 Simulation of ship HRR profiles
- 4.5.2 PSM results
- 4.5.3 Results based on geometrical, statistical and structural features
- 4.5.3.1 Measurements
- 4.5.3.2 Classification based on simulated ships
- 4.6 The mitigation of multipath effects on ship ATR
- 4.6.1 Using several antennas
- 4.6.2 Using several frequencies
- 4.6.3 Combining two antennas and two frequencies
- 4.6.4 Classification improvement via multi-frequency and/or multi-antenna approach
- 4.7 Summary
- References
Inspec keywords:
object detection;
synthetic aperture radar;
radar tracking;
radar resolution;
airborne radar;
target tracking;
ships;
radar imaging;
marine radar
Other keywords:
ship self-defence;
AIS;
hostile ship;
terrorist threat;
border control;
automatic identification system;
ISAR;
maritime target;
ground-based platform;
piracy;
coastal surveillance;
2D imaging;
commercial ship traffic;
vessel;
automatic target recognition;
high resolution radar;
asymmetric threat;
radar ATR;
target imaging;
drug trafficking suppression;
airborne radar;
harbour installation protection;
cooperative classification
Subjects:
Optical, image and video signal processing;
Radar equipment, systems and applications