Design and experimental validation of knowledge-based constant false alarm rate detectors

Maio, Antonio De; Farina, A.; Foglia, Goffredo

doi:10.1049/iet-rsn:20060113

Cited by 32 publications

(29 citation statements)

References 11 publications

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“…However, in the test results, we also find that all of the detectors are unable to rigorously maintain the theoretical false alarm, and the selection of T of PDLT does not match the values used in the simulation. The reason is that the IID Gaussian random processes is not always valid in the real data [14]. In order to obtain better detection performance of experimental data, possible research tracks might extend the PDLT to the non-Gaussian clutter distributed assumption.…”

Section: Resultsmentioning

confidence: 99%

“…In the real application scene, the detection performance of CA-CFAR will be greatly degraded if the clutter environment is multiple target situations, which results in extreme target masking [10][11][12][13][14][15][16][17][18][19]. The multiple target situations of low-flying helicopters consist of some large spiky and discrete clutters in the reference cell, such as steep mountains terrain, towers, pylons, aerial cableways and power lines [20,21].…”

Section: Introductionmentioning

confidence: 99%

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Positive Definite Matrix Space Based Detector With Limited Training Samples for Multiple Target Situations

Wen¹,

Huang²,

Cui³

et al. 2017

PIER M

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Abstract-Multiple target situation is a typical situation of nonhomogeneous clutter environment, which can cause excessive target masking in radar signal detection system. In order to reduce target masking caused by multiple target situations, this paper proposes a new detection structure based on positive-definite matrix space and limited training samples. The proposed detection structure uses a positive-definite matrix to estimate the background power level. In addition, with limited training samples, the detection structure is used to resist the multiple target situations. The simulation results show that the proposed detection structure exhibits a better detection performance than that of the well-known CA-CFAR in homogeneous environment. The detector also performs robustly in multiple target situations, even though 10 interfering targets exist in a length of 24 samples of reference window. Furthermore, the measured results validate the performance of the proposed method.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Positive Definite Matrix Space Based Detector With Limited Training Samples for Multiple Target Situations

Wen¹,

Huang²,

Cui³

et al. 2017

PIER M

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“…Let us turn now on the derivation of the detector for known . In this case it is possible to solve the GLRT (38) The first step is again optimization over . Following the lead of [2], we have that (39) Observe that (39) and (14) are similar but not identical.…”

Section: B Randommentioning

confidence: 99%

Adaptive Detection of Distributed Targets in Compound-Gaussian Noise Without Secondary Data: A Bayesian Approach

Bandiera

Besson

Ricci

2011

IEEE Trans. Signal Process.

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In this paper, we deal with the problem of adaptive detection of distributed targets embedded in colored noise modeled in terms of a compound-Gaussian process and without assuming that a set of secondary data is available. The covariance matrices of the data under test share a common structure while having different power levels. A Bayesian approach is proposed here, where the structure and possibly the power levels are assumed to be random, with appropriate distributions. Within this framework we propose GLRT-based and ad-hoc detectors. Some simulation studies are presented to illustrate the performances of the proposed algorithms. The analysis indicates that the Bayesian framework could be a viable means to alleviate the need for secondary data, a critical issue in heterogeneous scenarios.

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“…Strategies conceived to cope with such situations exhibit a common denominator that consists in incorporating the available a priori information into the detector design (knowledgeaided paradigm). For instance, in [9], the authors show that significant performance improvements can be achieved exploiting the available information about the surrounding environment. In particular, they propose algorithms which use the information provided by a geographic information system in order to properly select secondary data.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Detection of Point-Like Targets in Spectrally Symmetric Interference

Maio

Orlando

Chen

et al. 2016

IEEE Trans. Signal Process.

102

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Abstract-We address adaptive radar detection of targets embedded in ground clutter dominated environments characterized by a symmetrically structured power spectral density. At the design stage, we leverage on the spectrum symmetry for the interference to come up with decision schemes capable of capitalizing the a-priori information on the covariance structure. To this end, we prove that the detection problem at hand can be formulated in terms of real variables and, then, we apply design procedures relying on the GLRT, the Rao test, and the Wald test. Specifically, the estimates of the unknown parameters under the target presence hypothesis are obtained through an iterative optimization algorithm whose convergence and quality guarantee is thoroughly proved. The performance analysis, both on simulated and on real radar data, confirms the superiority of the considered architectures over their conventional counterparts which do not take advantage of the clutter spectral symmetry.

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Design and experimental validation of knowledge-based constant false alarm rate detectors

Cited by 32 publications

References 11 publications

Positive Definite Matrix Space Based Detector With Limited Training Samples for Multiple Target Situations

Positive Definite Matrix Space Based Detector With Limited Training Samples for Multiple Target Situations

Adaptive Detection of Distributed Targets in Compound-Gaussian Noise Without Secondary Data: A Bayesian Approach

Adaptive Detection of Point-Like Targets in Spectrally Symmetric Interference

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