A weighted detector for mismatched subspace signals

Li, Jun; Li, Kai; Zhang, Xichuan; Liu, Ming; Liu, Weijian

doi:10.1016/j.sigpro.2017.05.011

Cited by 15 publications

(4 citation statements)

References 36 publications

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“…A robust two-stage detector obtained by cascading a GLRT-based subspace detector and the Rao test has been proposed in [16]. Robust and selective detectors have also been considered in the context of subspace detection [17], [18], [19]. Multidimensional/multichannel signal detection in homogeneous or partially homogeneous Gaussian disturbance (with unknown covariance matrix and unknown structured deterministic interference) is considered in [20], [21].…”

Section: B Existing Results and Motivationmentioning

confidence: 99%

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

Coluccia

Ricci

Besson

2019

IEEE Trans. Signal Process.

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The paper addresses the problem of designing radar detectors more robust than Kelly's detector to possible mismatches of the assumed target signature, but with no performance degradation under matched conditions. The idea is to model the received signal under the signal-plus-noise hypothesis by adding a random component, parameterized via a design covariance matrix, that makes the hypothesis more plausible in presence of mismatches. Moreover, an unknown power of such component, to be estimated from the observables, can lead to no performance loss. Derivation of the (one-step) GLRT is provided for two choices of the design matrix, obtaining detectors with different complexity and behavior. A third parametric detector is also obtained by an ad-hoc generalization of one of such GLRTs. The analysis shows that the proposed approach can cover a range of different robustness levels that is not achievable by state-ofthe-art with the same performance of Kelly's detector under matched conditions.

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Section: B Existing Results and Motivationmentioning

confidence: 99%

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

Coluccia

Ricci

Besson

2019

IEEE Trans. Signal Process.

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“…Here, the directivity can be changed smoothly by adjusting the weight. A weighted detector called SAMF-ASD was proposed in [144].…”

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.

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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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“…Moreover, FTMF and AMF are known to have different benefits. FTMF is known to be more selective than AMF [31,32] . Then in a complicated scenario, where possible target-like background components may exist, using the FTMF will be better than AMF.…”

Section: Subspace Fitting Matched Filtermentioning

confidence: 99%