DSI Suppression with Adaptive Beamforming in DVB-T Passive Radar Measurements

Strom, Kyrre; Lie-Svendsen, Øystein; Norheim-Nass, Idar; Johnsen, Terje; Finden, Erlend; Olsen, Karl Erik

doi:10.23919/irs.2018.8448023

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…In [ 27 ], the estimate of the spatial covariance matrix combining deterministic sidelobe reduction and adaptive pattern shaping that preserves the low sidelobe level is discussed. An intermediate solution between the angular domain and the range–Doppler domain can be found in [ 33 ], where adaptive beamforming is applied after the range–Doppler processing has been processed, whereas the sample matrix inversion method has been previously used in the angular domain to estimate the noise plus interference spatial covariance matrix.…”

Section: Introductionmentioning

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: Introductionmentioning

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

“…On the other hand, CAF contributions of echoes generated by non-desired stationary targets (surface clutter, for example) present maximum values along the zero Doppler line and increase the pedestal throughout the CAF domain. Different techniques for DPI and zero Doppler interferences cancellation have been studied in the literature, such as Extensive CancellationAlgorithm (ECA) [11] and block Normalised Mean Least Squares (NMLS) [11][12][13][14]. DPI can also be reduced through the antenna system by designing an antenna with low gain in the direction where IoO is located, or introducing a null via beamforming techniques if an array is being employed [14].…”

Section: Introductionmentioning

confidence: 99%

“…Different techniques for DPI and zero Doppler interferences cancellation have been studied in the literature, such as Extensive CancellationAlgorithm (ECA) [11] and block Normalised Mean Least Squares (NMLS) [11][12][13][14]. DPI can also be reduced through the antenna system by designing an antenna with low gain in the direction where IoO is located, or introducing a null via beamforming techniques if an array is being employed [14].…”

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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