Abstract
In order to efficiently cover maritime areas at over the horizon (OTH) distances and thus increase marine safety in a nation’s exclusive economic zone (EEZ), a network of maritime sensors built around High Frequency Surface Wave Radars (HFSWR) can be an excellent choice. The critical parameter for success of the deployed sensor network is a real time tracking of all detected vessels. During the tracking process, data association (DA) is the first step and it defines the complexity and thus the speed of the whole tracking process. This paper presents a density based clustering DA procedure where the cluster complexity determines the applied DA procedure within the cluster itself. It is demonstrated that the great majority of clusters (over 98 % of all clusters in the worst case) may be processed in a timely manner with an optimal DA procedure, or more precisely, a Joint Probability Data Association (JPDA). However, a small number of unusually large clusters (less than 2 % of all clusters) requires the application of a sub–optimal DA procedure, more accurately, the Roecker’s suboptimal JPDA algorithm, in order to maintain real time performance of the whole tracking process. Moreover, unlike standard JPDA procedure which tends to be inapplicable for real time tracking in heavily cluttered environment, the density based clustering DA procedure presented here provides real time performances in the very same environment. The whole analysis is done on real HFSWR data obtained from two HFSWR, located in the Gulf of Guinea. The data set used for the experiments includes data obtained during a month and a half of constant HFSWR operation.
Highlights
According to the United Nations convention, the Exclusive Economic Zone (EEZ) [1] is a zone of a specific width that is stretched from a country’s territorial sea in the direction of open sea, up to 200 nautical miles (370 km), in which countries have exclusive rights to exploit the biological and mineral resources of the sea
EXPERIMENTAL RESULTS The purpose of the data association analyses is to investigate characteristics of High Frequency Surface Wave Radars (HFSWR) tracking scenario and to support the hypothesis that majority of associations are formed in small clusters, which could be solved by an optimal DA procedure
This assumption is derived from tactical supposition that HFSWRs are used for open sea surveillance at over the horizon distances, where traffic is generally dispersed over a great area making the dense concentration of vessels a seldom case
Summary
According to the United Nations convention, the Exclusive Economic Zone (EEZ) [1] is a zone of a specific width that is stretched from a country’s territorial sea in the direction of open sea, up to 200 nautical miles (370 km), in which countries have exclusive rights to exploit the biological and mineral resources of the sea. Since during each association step there can be hundreds of tracks and individual measurements, it might show that the aforementioned joint procedures are unsuitable for practical use, because execution time can grow beyond integration periods used in HFSWR data acquisition. There are procedures with linear complexity (linear multi-target approach), such as LM IPDA [8] or LM Integrated Track Splitting (ITS) [9] whose execution time is growing much slower Another approach is using heuristics and approximations of the aforementioned joint procedures, like integer programming [10], DFS [11], or Roecker-Phillis suboptimal JPDA [12] and its modifications such as the one described in [13] and others.
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