Design of Robust Radar Detectors Through Random Perturbation of the Target Signature

Coluccia, Angelo; Ricci, Giuseppe; Besson, Olivier

doi:10.1109/tsp.2019.2935915

Cited by 14 publications

(11 citation statements)

References 29 publications

(83 reference statements)

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“…In particular, Kelly's horizontal boundary best separates the H 0 cluster from any H 1 cluster under matched conditions; conversely, detectors with marked robust or selective behaviors exhibit an oblique linear or non-linear boundary, with increasing trend for robust behavior and decreasing trend for selective behavior, as visible in Fig. 1, respectively, for AMF and the robustified GLRT (ROB) [18] and for ACE and WABORT.…”

Section: B Detection In the Cfar Feature Planementioning

confidence: 96%

Design of Customized Adaptive Radar Detectors in the CFAR Feature Plane

Coluccia¹,

Fascista²,

Ricci³

2022

Preprint

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The paper addresses the design of adaptive radar detectors having desired behavior, in Gaussian disturbance with unknown statistics. Specifically, given detection probability specifications for chosen signal-to-noise ratios and steering vector mismatch levels, a methodology for the optimal design of customized CFAR detectors is devised in a suitable feature plane based on maximal invariant statistics. To overcome the analytical and numerical intractability of the resulting optimization problem, a novel general reduced-complexity algorithm is developed, which is shown to be effective in providing a close approximation of the desired detector. The proposed approach solves the open problem of ensuring a prefixed false alarm probability while controlling the behavior under both matched and mismatched conditions, so enabling the design of fully customized adaptive CFAR detectors.

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Section: B Detection In the Cfar Feature Planementioning

confidence: 96%

Design of Customized Adaptive Radar Detectors in the CFAR Feature Plane

Coluccia¹,

Fascista²,

Ricci³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…A robust detector is then designed using second-order cone (SOC) programming [113][114][115][116][117]. A fourth method involves adding a random component in the test data under the signal-presence hypothesis, which makes the hypothesis more plausible when signal mismatch occurs [118].…”

Section: Adaptive Detection In the Presence Of Signal Mismatchmentioning

confidence: 99%

Multichannel adaptive signal detection: basic theory and literature review

Liu

Chen

et al. 2022

Sci. China Inf. Sci.

137

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Multichannel adaptive signal detection uses test and training data jointly to form an adaptive detector to determine whether a target exists. The resulting adaptive detectors typically possess constant false alarm rate (CFAR) properties; thus, no additional CFAR processing is required. In addition, a filtering process is also not required because the filtering function is embedded in the adaptive detector. Adaptive detection typically exhibits better detection performance than the filtering-then-CFAR detection technique. It has been approximately 35 years since the first multichannel adaptive detector was proposed by Kelly in 1986. However, there are few overview articles on this topic. Thus, in this study, we present a tutorial overview of multichannel adaptive signal detection with an emphasis on the Gaussian background. We discuss the main design criteria for adaptive detectors, investigate the relationship between adaptive detection and filtering-then-CFAR detection techniques, investigate the relationship between adaptive detectors and adaptive filters, summarize typical adaptive detectors, present numerical examples, provide a comprehensive literature review, and discuss potential future research tracks.

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“…We now consider the Wald test for the detection problem described in (10). According to [48], we can express the Wald test as…”

Section: Ps-wald-i Detector Designmentioning

confidence: 99%

Subspace Detection for Range-Spread Target to Suppress Interference: Exploiting Persymmetry in Non-Homogeneous Scenario

Gao

Mao

Zhu

et al. 2022

J. of Syst. Eng. Electron.

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This paper deals with subspace detection for rangespread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data. Through exploiting the persymmetry of the clutter covariance matrix, we propose two adaptive target detectors, which are referred to as persymmetric subspace Rao to suppress interference and persymmetric subspace Wald to suppress interference ( "PS-Rao-I " and "PS-Wald-I "), respectively. The persymmetry-based design brings in the advantage of easy implementation for small training sample support. The signal flow analysis of the two detectors shows that the PS-Rao-I rejects interference and integrates signals successively through separated matrix projection, while the PS-Wald-I jointly achieves interference elimination and signal combination via oblique projection. In addition, both detectors are shown to be constant false alarm rate detectors, significantly improving the detection performance with other competing detectors under the condition of limited training.

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Design of Robust Radar Detectors Through Random Perturbation of the Target Signature

Cited by 14 publications

References 29 publications

Design of Customized Adaptive Radar Detectors in the CFAR Feature Plane

Design of Customized Adaptive Radar Detectors in the CFAR Feature Plane

Multichannel adaptive signal detection: basic theory and literature review

Subspace Detection for Range-Spread Target to Suppress Interference: Exploiting Persymmetry in Non-Homogeneous Scenario

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