Novel Range-Spread Target Detectors in Non-Gaussian Clutter

He, You; Jian, Tao; Su, Feng; Qu, Changsheng; Gu, Xuemai

doi:10.1109/taes.2010.5545191

Cited by 73 publications

(41 citation statements)

References 29 publications

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“…By taking into account the non-coherent integration technique, and the target energy profile, the authors derived a new expression of the range spread target energy, and an expression of the binary hypothesis test. The performances of the proposed detectors have been compared to those of OS-GLRT [13], and results indicated that even though both detectors present better detection performance when the target is uniformly distributed on the primary cells, the (M-pulse CA-LT ) still outperforms the OS-GLRT [13].…”

Section: Introductionmentioning

confidence: 99%

Lookup Tables-based mean level detection of spatially distributed targets in non Gaussian clutter

Nouar¹,

Farrouki²

2017

Adv. sci. technol. eng. syst. j.

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Section: Introductionmentioning

confidence: 99%

Lookup Tables-based mean level detection of spatially distributed targets in non Gaussian clutter

Nouar¹,

Farrouki²

2017

Adv. sci. technol. eng. syst. j.

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“…Given that the scattering characteristics of range-spread targets are significantly different, completing the aforementioned method is difficult. When the scattering geometry of range-spread targets is unknown, the adaptive detectors that are based on the improved one-step or two-step generalized likelihood ratio test are proposed under the circumstance of homogeneous or inhomogeneous clutter [6][7][8][9][10][11][12]. However, it is difficult to derive a definite distribution model to represent the practical clutter in concealed threat detection, which may consist of radar echoes of the human body, clothing, the ground, and thermal noise.…”

Section: Introductionmentioning

confidence: 99%

Binary integration nonparametric detection for range-spread targets in distributed terahertz radar network under unknown clutter

Liu

Min

et al. 2016

EURASIP J. Adv. Signal Process.

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In this study, to detect person-borne concealed threats in range profiles under the circumstance of unknown clutter, we propose a binary integration nonparametric detection method based on the generalized sign (GS) detector for range-spread targets in a distributed terahertz radar network (DTRN). In the detection, the length of range-spread targets and the number of dominant scatterers on range-spread targets are considered and adaptively estimated. Furthermore, the GS detection method is applied to maintain a constant false alarm rate (CFAR) under the circumstance of unknown clutter. The detection performance of the proposed method for single terahertz radar and DTRN are both examined with the data synthesized by real range-spread targets data and real clutter data. Experimental results show that the proposed method is effective, and for a given false alarm probability, the DTRN exhibits better detection performance than the single terahertz radar.

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“…Compared with those detectors in white Gaussian noise, detecting range-spread targets in nonstationary clutter environments is more complicated and has recently received much more attentions [6][7][8][9][10][11][12][13][14][15]. Those methods mainly focus upon steady range-spread targets, such as air targets in steady flight or slow ship target in sea clutter.…”

Section: Introductionmentioning

confidence: 99%

“…The GLRT-based detectors developed in [6,7] can effectively detect targets in homogenous clutter environments. In [8,9], the order statistical sum of the generalized likelihood ratios at all the range cells of the detection window was recently developed for steady range-spread target detection in non-Gaussian clutter. The target return model available in [6][7][8][9] is unsuitable for range-spread targets in high-speed manoeuvring flight, whose complex HRRPs exhibit much more complicated change.…”

Section: Introductionmentioning

confidence: 99%

Entropy-based detection of manoeuvring range-spread targets in homogeneous weather clutter

Shui

2013

EURASIP J. Adv. Signal Process.

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This paper proposes a waveform-cross-entropy (WCEN)-based detection scheme to detect manoeuvring range-spread targets in homogeneous weather clutter. The input of the detector is composed of complex-valued high resolution range profiles (HRRPs) from a train of coherent pulses in the observation window. The observation window contains a detection window and a reference window, where the received data in reference window is clutter-only secondary data. The detector consists of temporal approximate whitening filtering for clutter suppression followed by the waveform-cross-entropy-based detection. The former is operated on the received vector at each range cell to whiten the clutter and enhance target returns. Then, the WCEN of each pair of filtered power-HRRPs is calculated to capture their sparsity, similarity and energy. The average of the WCENs of all the pairs is utilized as the test statistic to decide whether a target is present or not. Finally, we assess the proposed detector by the raw radar target data collected by high range resolution radar and simulated weather clutter. The experimental results show that the WCEN-based detector outperforms the existing detectors in detection performance for manoeuvring range-spread targets.

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Novel Range-Spread Target Detectors in Non-Gaussian Clutter

Cited by 73 publications

References 29 publications

Lookup Tables-based mean level detection of spatially distributed targets in non Gaussian clutter

Lookup Tables-based mean level detection of spatially distributed targets in non Gaussian clutter

Binary integration nonparametric detection for range-spread targets in distributed terahertz radar network under unknown clutter

Entropy-based detection of manoeuvring range-spread targets in homogeneous weather clutter

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