Abstract
In this article, a multifeature detector based on isolation forest (iForest) algorithm is developed to detect floating small targets in sea clutter. The conventional multifeature detector can only process three features or less. The proposed detector aims to break the limitation of feature dimensions’ number of the existed feature-based detectors and to improve the detection performance. It transforms the detection of floating small target into an anomaly detection problem in a high-dimensional feature space, breaking the limitation of the number of features. First, a modified isolation forest is constructed from multiple features extracted from sea clutter. Meanwhile, the relative Doppler coefficient of variation is proposed and added into the feature library. Then, taking the average path length as detection statistic, the detection threshold is obtained by Monte-Carlo technique at the given false alarm probability. Finally, the final decision is made by comparing the path length calculated from the cell under test of radar returns with the detection threshold. Detection performances are evaluated based on twenty measured IPIX radar datasets. The experiment results show that the multifeature detector based on isolation forest can obtain a significant performance improvement and has lower computation cost compared with the existed detectors.
Highlights
T HE detection of sea-surface floating small targets, such as floating ice, victims of aircraft crashes at sea, vent pipes, periscopes of the submarine, etc., has always been a difficult problem in the field of radar target detection
The proposed relative Doppler coefficient of variation detection feature and the multifeature detector based on modified isolation forest algorithm are used to expand the number of detection features and realize joint detection of multiple features, respectively
Via modifying the original isolation forest (iForest) algorithm, the average path length is used as the detection statistic that could control the false alarm probability
Summary
T HE detection of sea-surface floating small targets, such as floating ice, victims of aircraft crashes at sea, vent pipes, periscopes of the submarine, etc., has always been a difficult problem in the field of radar target detection. In order to accumulate more energy in different frequency subbands, the modified adaptive coherent detectors [8], [9] have been applied to solve this problem These detectors require that potential targets must keep a constant radial velocity during the integration time and the relatively high signal-to-clutter ratio (SCR). For floating small target detection in sea-surface, anomaly detection algorithms only need -obtained sea clutter samples for training detection models, which is more suitable for the problem. It overcomes the shortcomings that convexhull cannot make full use of multiple features and the defects of local effective detection algorithm guided by target samples This detector can arbitrarily utilize a variety of detection features and effectively detect small targets in high-dimensional space.
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