An Implementation of DBF and CFAR Models in OTHR Signal Processing

Stojkovic, Nikola; Nikolic, Dejan; Petrović, Pavle; Tošić, Nikola; Gluvacevic, Ivan; Stojiljkovic, Nikola; Lekic, Nikola

doi:10.1109/cspa.2019.8695974

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Details regarding the data processing chain for the network of HFSWR that were used can be found in [16], [17]. However, specific blocks engaged in single HFSWR tracking procedure are shown in Fig.…”

Section: Hfswr Data Processing Overviewmentioning

confidence: 99%

“…The nature of false alarms mostly lies in the inability of CFAR processing block and its associated logic to properly handle various clutter. For example, large areas in RDA cube (which is actually a CFAR input [16]) may be polluted by returns from E and F ionospheric layers. These returns can have such extreme values that they can even create complete blind zones for several hours for HFSWR with a fixed working bandwidth.…”

Section: A Clutter Density Estimatormentioning

confidence: 99%

“…On our experimental PC, using an optimal data assignment procedure for a given time and following the recommendations from previous sections, the total number of joint assignments C max , for an arbitrary cluster size in the worst case scenario must be less than 2 16 (represented with the red dashed line in Fig. 8).…”

Section: B Statistical Analysismentioning

confidence: 99%

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Density Based Clustering Data Association Procedure for Real–Time HFSWRs Tracking at OTH Distances

Stojkovic

Nikolic²,

Puzović³

2020

IEEE Access

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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.

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Section: Hfswr Data Processing Overviewmentioning

confidence: 99%

Section: A Clutter Density Estimatormentioning

confidence: 99%

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Density Based Clustering Data Association Procedure for Real–Time HFSWRs Tracking at OTH Distances

Stojkovic

Nikolic²,

Puzović³

2020

IEEE Access

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“…The paper examines the most important questions that have been encountered in the design of Vlatacom's High Frequency Over The Horizon Radar (vHF -OTHR). Please note that this paper relies on [5] and while in [5] main focus is on signal processing, this paper provides an overview of vHF OTHR. A general overview of HFSWR principles can be found in [4,[6][7][8][9] Our solution relies on FMCW and main reason for that choice are: 1.…”

Section: Introductionmentioning

confidence: 99%

The high frequency surface wave radar solution for vessel tracking beyond the horizon

Nikolic¹,

Stojkovic²,

Petrović³

et al. 2020

FACTA U EE

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With maximum range of about 200 nautical miles (approx. 370 km) High Frequency Surface Wave Radars (HFSWR) provide unique capability for vessel detection far beyond the horizon without utilization of any moving platforms. Such uniqueness requires design principles unlike those usually used in microwave radar. In this paper the key concepts of HFSWR based on Frequency Modulated Continuous (FMCW) principles are presented. The paper further describes operating principles with focus on signal processing techniques used to extract desired data. The signal processing describes range and Doppler processing but focus is given to the Digital Beamforming (DBF) and Constant False Alarm Rate (CFAR) models. In order to better present the design process, data obtained from the HFSWR sites operating in the Gulf of Guinea are used.

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Early Interference Detection in HFSWR Input Channel using Convolutional Neural Network

Stojkovic¹,

Matovic²,

Puzović³

et al. 2022

2022 30th Telecommunications Forum (TELFOR)

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An Implementation of DBF and CFAR Models in OTHR Signal Processing

Cited by 5 publications

References 4 publications

Density Based Clustering Data Association Procedure for Real–Time HFSWRs Tracking at OTH Distances

Density Based Clustering Data Association Procedure for Real–Time HFSWRs Tracking at OTH Distances

The high frequency surface wave radar solution for vessel tracking beyond the horizon

Early Interference Detection in HFSWR Input Channel using Convolutional Neural Network

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