Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals.

Eftychios Protopapadakis,Dimitrios Dres,Matthaios Bimpas,Nikolaos Doulamis,Athanasios Voulodimos,Anastasios Doulamis

doi:10.1155/2017/5891417

Abstract

Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlier detection at over-the-horizon (OTH) distances. However, a number of disadvantages, such as their low spatial resolution and presence of clutter, have a negative impact on their accuracy. In this paper, we explore the applicability of deep learning techniques for detecting deviations from the norm in behavioral patterns of vessels (outliers) as they are tracked from an OTH radar. The proposed methodology exploits the nonlinear mapping capabilities of deep stacked autoencoders in combination with density-based clustering. A comparative experimental evaluation of the approach shows promising results in terms of the proposed methodology's performance.

Highlights

Detection of targets and outliers in radar signals is a research issue that has gained significant attention in the academic and industrial research community, mainly because of the important associated impact of relevant applications in surveying of large areas
High-Frequency Surface-Wave (HFSW) radars are a category of radars that operate at the frequency band 3–30 MHz and, in contrast with other radars, use ground wave or sky wave propagation and ionospheric reflections of the electromagnetic waves for target detection, which allows for achieving longer ranges, where microwave radars cannot perform [1], but to the detriment of the attained accuracy
The goal of this paper is to present a framework for detecting deviations from the norm in behavioral patterns of vessels, as they are tracked from an OTH radar

Summary

Introduction

Detection of targets and outliers in radar signals is a research issue that has gained significant attention in the academic and industrial research community, mainly because of the important associated impact of relevant applications in surveying of large areas. HFSW radars, or over-the-horizon (OTH) radars, as they are commonly known, have been used to remotely measure oceanographic parameters, providing information about surface currents, wave spectra, wind direction and intensity, and so on [2]. Their extraordinary range (up to 200 nautical miles) combined with their continuous mode of operation make for an ideal candidate tool for longrange oceanic surveillance. Related research issues continue to present significant challenges, which can be attributed to few reasons, briefly described below:

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