Target Discrimination and Classification in Through-the-Wall Radar Imaging

Debes, Christian; Hahn, Jürgen T.; Zoubir, Abdelhak M.; Amin, Moeness G.

doi:10.1109/tsp.2011.2157914

Cited by 39 publications

(25 citation statements)

References 33 publications

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“…Despite the noteworthy advances achieved in the field of through-wall radar (TWR) technology, most systems currently available are complex, expensive, and bulky owing to the necessity to achieve adequate performance in terms of imaging resolution [1][2][3][4][5][6][7][8]. For these reasons, apart from the military sector, such systems have limited applicability and are not suitable for civilian applications where large scale and long-term investigations with cost-effective sensing devices are usually demanded.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

2016

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This paper deals with the development of a short-range radar suitable for the detection of humans behind visually opaque structures such as building walls. The system consists in a continuous wave Doppler radar operating in the S-band of the electromagnetic spectrum in order to ensure an adequate signal penetration through the walls. Based on the interaction of the electromagnetic waves with human targets, a phase modulation of the radar signal arises due to their movements and tiny periodic chest displacements associated with the respiratory activity. A simple and effective radar data processing algorithm is proposed to detect, in real-time, the presence of one or several human subjects in the through-wall scene. Such an algorithm automatically provides also an indication on whether the subjects are static or moving in the environment. As shown by experimental tests carried out in an indoor scenario, the proposed sensing device and related signal processing yields prompt and reliable information about the scene thus confirming its practical value.

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Section: Introductionmentioning

confidence: 99%

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

2016

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“…Beside the hardware improvements [5][6][7], many image enhancement schemes (including background subtraction [8], spatial filtering [9], wall parameter estimation/modeling [10,11], doppler domain filtering [12] and image fusion [13]) are in literature. These schemes have their own drawbacks and limitations (some of them are discussed in [14]).…”

Section: Introductionmentioning

confidence: 99%

Spectral and Textural Weighting Using Takagi-Sugeno Fuzzy System for Through Wall Image Enhancement

Riaz¹,

Ghafoor

2013

PIER B

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Abstract-A through wall image enhancement scheme based on Takagi-Sugeno fuzzy system and principal component analysis is proposed. The scheme incorporates spectral properties of image and textural properties of eigen components of image to assign weights. The scheme overcomes the empirical setting of inference engine and output membership functions. Simulation demonstrates the effectiveness of proposed scheme in terms of accuracy.

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“…Image enhancement in TWI, has enjoyed an increasing interest over last few years [14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Clutter and noise (due to antenna attenuation, cross talk, false targets and wall reflections) result in degradation of image quality, ambiguity in localization of targets and appearance of false targets.…”

Section: Introductionmentioning

confidence: 99%

“…Clutter and noise (due to antenna attenuation, cross talk, false targets and wall reflections) result in degradation of image quality, ambiguity in localization of targets and appearance of false targets. Techniques for image enhancement in TWI include, background subtraction [14], spatial filtering [15], wall parameter estimation/modeling based [17,18], doppler domain filtering [21], image fusion [22,23] and statical methods.…”

Section: Introductionmentioning

confidence: 99%

“…Doppler domain filtering assumes that background is stationary and targets are moving so a doppler shift occurs which can be used to discriminate target and clutter signals [21]. Image fusion methods require multiple images of same scene from different locations (which is not possible especially in case of moving targets) [22,23]. Some statistical method for TWI enhancement include Singular Value Decomposition (SVD), Factor Analysis (FA), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) [27].…”

Section: Introductionmentioning

confidence: 99%

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Principle Component Analysis and Fuzzy Logic Based Through Wall Image Enhancement

Riaz¹,

Ghafoor

2012

PIER

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Abstract-Principle component analysis based through wall image enhancement is proposed which is capable of discriminating target, noise and clutter signals. The overlapping boundaries of clutter, noise and target signals are separated using fuzzy logic. Fuzzy inference engine is used to assign weights to principle components. The proposed scheme works well significantly for extracting multiple targets having different range profiles in heavy cluttered through wall images. Simulation results are compared on the basis of mean square error, peak signal to noise ratio and visual inspection.

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Target Discrimination and Classification in Through-the-Wall Radar Imaging

Cited by 39 publications

References 33 publications

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

Spectral and Textural Weighting Using Takagi-Sugeno Fuzzy System for Through Wall Image Enhancement

Principle Component Analysis and Fuzzy Logic Based Through Wall Image Enhancement

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