Design and implementation of near-field, wideband synthetic aperture beamformers

Ahmad, Fauzia; Frazer, G.J.; Kassam, S.A.; Amin, Moeness G.

doi:10.1109/taes.2004.1292154

Cited by 89 publications

(54 citation statements)

References 16 publications

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“…Doppler-radar was first demonstrated for remotely monitoring human activity in [1,2]. SAR imaging and range detection [3][4][5][6] do not work well to distinguish human targets from cluttered background. In general, humans seldom stay still and their activities involve considerable movement of their limbs.…”

Section: Introductionmentioning

confidence: 99%

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Through-the-Wall Detection of Stationary Human Targets Using Doppler Radar

Narayanan¹,

Shastry²,

Chen³

et al. 2010

PIER B

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Abstract-In homeland security and law enforcement situations, it is often required to remotely detect human targets obscured by walls and barriers. In particular, we are specifically interested in scenarios that involve a human whose torso is stationary. We propose a technique to detect and characterize activity associated with a stationary human in through-the-wall scenarios using a Doppler radar system. The presence of stationary humans is identified by detecting Doppler signatures resulting from breathing, and movement of the human arm and wrist. The irregular, transient, non-uniform, and non-stationary nature of human activity presents a number of challenges in extracting and classifying Doppler signatures from the signal. These are addressed using bio-mechanical human arm movement models and the empirical mode decomposition (EMD) algorithm for Doppler feature extraction. Experimental results demonstrate the effectiveness of our approach to extract Doppler signatures corresponding to human activity through walls using a 750-MHz Doppler radar system.

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Section: Introductionmentioning

confidence: 99%

“…Such functions permit the application of the Hilbert transform and the corresponding definition of instantaneous frequency in [13]. The Hilbert transform yields the analytic version of the signal, from which, the instantaneous frequency is extracted as shown in Equations (1)- (3).…”

Section: Introduction To Emd-hsmentioning

confidence: 99%

Through-the-Wall Detection of Stationary Human Targets Using Doppler Radar

Narayanan¹,

Shastry²,

Chen³

et al. 2010

PIER B

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“…A 57 × 57 element array is synthesized using a single horn antenna. The horn is moved to each element position in the array in turn and, if the scene being imaged remains constant, the array can be synthesized in post processing [18]. The spacing between elements was 0.0215 m in both cross-range and height.…”

Section: Alignment Results and Analysis A The Twri Datasetmentioning

confidence: 99%

A target alignment algorithm for through-the-wall radar imagery classification

Mobasseri

Smith

Estephan

2010

2010 IEEE Radar Conference

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Abstract-Sensing through the wall using radar is a valuable capability. There is considerable work in generating radar images of the interior of a room by beamforming of the radar backscatter generated in a Synthetic Aperture Radar (SAR) configuration. However, high level interpretation of the scene is a more difficult task. In previous work a minimum distance classifier was successfully used to recognize various targets placed in the scene. The approach suffered from the dependency of target features on target location. This work presents a solution to this problem by bringing the target intensity profiles into alignment with the training data prior to classification. The alignment is performed by moving the intensity profiles between locations using an Autoregressive Moving Average (ARMA) model. The classification results before and after alignment show a marked improvement.

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“…, N z − 1. The complex composite signal, corresponding to the (k, l)th pixel, is obtained by applying a set of focusing delays τ (k, l), n to align all signal returns from the (k, l)th pixel, and then summing the following results: [17] …”

Section: Twr Signal Modelmentioning

confidence: 99%

Pattern Matching for Building Feature Extraction

Lagunas

Amin

Ahmad

et al. 2014

IEEE Geosci. Remote Sensing Lett.

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Abstract-We address the problem of detecting building dominant scatterers using a reduced number of measurements with applications to through-the-wall radar (TWR) and urban sensing. We consider oblique illumination, which specially enhances the radar returns from the corners formed by the orthogonal intersection of two walls. This letter uses a novel type of image descriptor, named correlogram, which encodes information about spatial correlation of complex amplitudes of each TWR image pixel. The proposed technique compares the known correlogram of the scattering response of an isolated canonical corner reflector with the correlogram of the received radar signal. The feature-based nature of the proposed detector enables corner separation from other indoor scatterers, such as humans.Index Terms-Building dominant scatterers, pattern matching, through-the-wall radar imaging (TWRI).

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Design and implementation of near-field, wideband synthetic aperture beamformers

Cited by 89 publications

References 16 publications

Through-the-Wall Detection of Stationary Human Targets Using Doppler Radar

Through-the-Wall Detection of Stationary Human Targets Using Doppler Radar

A target alignment algorithm for through-the-wall radar imagery classification

Pattern Matching for Building Feature Extraction

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