Determining building interior structures using compressive sensing

Abstract

Abstract. We consider imaging of the building interior structures using compressive sensing (CS) with applications to through-thewall imaging and urban sensing. We consider a monostatic synthetic aperture radar imaging system employing stepped frequency waveform. The proposed approach exploits prior information of building construction practices to form an appropriate sparse representation of the building interior layout. We devise a dictionary of possible wall locations, which is consistent with the fact that interior walls are typically parallel or perpendicular to the front wall. The dictionary accounts for the dominant normal angle reflections from exterior and interior walls for the monostatic imaging system. CS is applied to a reduced set of observations to recover the true positions of the walls. Additional information about interior walls can be obtained using a dictionary of possible corner reflectors, which is the response of the junction of two walls. Supporting results based on simulation and laboratory experiments are provided. It is shown that the proposed sparsifying basis outperforms the conventional through-thewall CS model, the wavelet sparsifying basis, and the block sparse model for building interior layout detection.

Multipath exploitation in sparse scene recovery using sensing-through-wall distributed radar sensor configurations

“…The walls locations rather have to be estimated from the returns using building layout estimation techniques, such as [13][14][15]. These estimates are subject to errors that will certainly be on the order of TWRI system wavelengths.…”

Partially sparse imaging of stationary indoor scenes

“…Note that since the scan direction is parallel to the walls, the delay τ w,l does not depend on the variable n and is a function only of the downrange distance between the lth wall and the antenna baseline. Finally, the reflections from the K corners measured at the nth antenna location corresponding to the mth frequency can be expressed as [33,37] …”

“…It is noted that, due to the specular nature of the wall reflections, a SAR system located parallel to the front wall will only be able to receive backscattered signals from interior walls, which are parallel to the front wall. The contributions of walls perpendicular to the front wall will be captured primarily through the backscattered signals from the corners [33,34]. The component of the received signal corresponding to the mth frequency at the nth antenna position, with phase center at x tn = (x tn , 0), due to the P point targets is given by [35,36] z tgt m; n ð Þ¼…”

Pattern Matching for Building Feature Extraction

“…Corners appear in building structures as a result of the right-angle intersection between two walls. Recently, overcomplete dictionaries for sparse representation of corners from compressed observations have been proposed [13], [14], whose atom coefficients directly indicate the presence of building features at specific positions. Alternatively, image-based complex matched filters were proposed for image feature extraction under full data volume [15].…”

“…The feature-based nature of the proposed detector enables corner separation from other indoor scatterers, such as humans. Numerical electromagnetic (EM) data are employed to show that the use of spatial correlation of complex amplitudes makes the detection performance superior to that of either using raw signal matching [13], [14] or image matching [15].…”