Beamforming and Tracking Assessment with Passive Radar Experimental Data

Cao, Tri-Tan Van; Vu, Tuyet; Byrne, Marion; Dahal, Nabaraj; Berry, Paul E.; Iji, Ayobami B.; Gustainis, Daniel; Ummenhofer, Martin; Köhler, Michael

doi:10.1109/radar42522.2020.9114715

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…However, most of the work focuses on scenarios where the detection capabilities of the system focus on searching for a single target. A more challenging scenario arises when multiple targets are present, especially when the number of targets is not available [ 63 , 64 ]. Smart employment of the scenario information and target attributes is the key to obtaining reasonable performance detection even without reference signals [ 65 , 66 ].…”

Section: Open Issues and Future Research Directionsmentioning

confidence: 99%

Beamforming Techniques for Passive Radar: An Overview

Núñez-Ortuño¹,

González-Coma²,

López³

et al. 2023

Sensors

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Passive radar is an interesting approach in the context of non-cooperative target detection. Because the signal source takes advantage of the so-called illuminator of opportunity (IoO), the deployed system is silent, allowing the operator cheap, portable, and practically undetectable deployments. These systems match perfectly with the use of antenna arrays to take advantage of the additional gains provided by the coherent combination of the signals received at each element. To obtain these benefits, linear processing methods are required to enhance the system’s performance. In this work, we summarize the main beamforming methods in the literature to provide a clear picture of the current state of the art. Next, we perform an analysis of the benefits and drawbacks and explore the chance of increasing the number of antenna elements. Finally, we identify the major challenges to be addressed by researchers in the future.

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Section: Open Issues and Future Research Directionsmentioning

confidence: 99%

Beamforming Techniques for Passive Radar: An Overview

Núñez-Ortuño¹,

González-Coma²,

López³

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…This algorithm is referred to as the Fast Sparse Functional Iteration Algorithm (FSFIA) and has been found to be robust for various radar applications [52][53][54]. If it succeeds in finding a solution to the convex optimisation problem stated in Equation ( 5), by making the residual error sufficiently small for a sufficiently large number of iterations, this can reasonably be assumed to be the correct physical solution, as the convex optimisation problem stated in Equation ( 5) is known to have a unique solution.…”

Section: Sparse Solution Algorithmmentioning

confidence: 99%

On the design of an optimal coherent multistatic radar network configuration

Berry

Dahal

Venkataraman

2022

IET Radar Sonar & Navi

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The purpose of operating a radar system multistatically is to acquire information about targets of interest more quickly and reliably than would be possible using disparate radars, which fuse data and track post‐detection. This paper identifies and addresses the critical issues for designing a coherent multistatic radar system using conventional coherent radars and proposes a set of design principles for configuring a coherent multistatic radar network with the aim of maximising the utility of information while constraining system cost and complexity. The issues discussed are as follows: the localisation of targets in three dimensions; eliminating the inevitable spatial ambiguities arising from sparse spatial sampling while exploiting the large aperture for high resolution; the achievement of spatial coherent processing gain for target detection; the effect of phase centre localisation, phase and frequency errors on synchronisation; the incorporation of three‐dimensional Doppler estimation for slow‐time coherent integration. The arguments presented are physically‐based and complemented by mathematical analysis and numerical experimentation using non‐linear sparse estimation, the sparse algorithm being critically important for resolving spatial ambiguities. An optimal configuration is identified, which has sufficiently many nodes to overcome spatial ambiguities and achieves significant spatial coherent processing gain, while simultaneously constraining the overheads of inter‐node synchronisation and communication.

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“…Adaptive Beamforming (ABF) is commonly employed in active radars to suppress jamming signals enabling target detection [16]. Deterministic and adaptive beamformers have also been designed to improve target detection and localisation performances [4,5,17,18]. ABF techniques are examples of optimisation problems that can take advantage of methods proposed for a wide variety of applications [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Beamforming Approaches to Improve Passive Radar Performance in Sea and Wind Farms’ Clutter

Rosado-Sanz

Jarabo-Amores

Mata-Moya

et al. 2022

Sensors

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This article presents the problem of passive radar vessel detection in a real coastal scenario in the presence of sea and wind farms’ clutter, which are characterised by high spatial and time variability due to the influence of weather conditions. Deterministic and adaptive beamforming techniques are proposed and evaluated using real data. Key points such as interference localisation and characterisation are tackled in the passive bistatic scenario with omnidirectional illuminators that critically increase the area of potential clutter sources to areas far from the surveillance area. Adaptive beamforming approaches provide significant Signal-to-Interference improvements and important radar coverage improvements. In the presented case study, an aerial target is detected 28 km far from the passive radar receiver, fulfilling highly demanding performance requirements.

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Beamforming and Tracking Assessment with Passive Radar Experimental Data

Cited by 3 publications

References 9 publications

Beamforming Techniques for Passive Radar: An Overview

Beamforming Techniques for Passive Radar: An Overview

On the design of an optimal coherent multistatic radar network configuration

Adaptive Beamforming Approaches to Improve Passive Radar Performance in Sea and Wind Farms’ Clutter

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