This letter is devoted to the layout reconstruction via the ultra-wideband (UWB) through-wall imaging radar under one single observation and simultaneously takes account of the real-time human indication. In the proposed framework, layout reconstruction is taken as the preprocessing, where a coherent processing interval consisting of several successive received echoes in the initial stage is first employed to construct a range-Doppler (RD) spectrum. Then, in the RD spectrum, a series of selected discrete Doppler frequency signals is used to form Doppler back projection (BP) images. Finally, in the Doppler BP image stack, we design a 3-D constant false alarm rate detector to extract the building layout. Once completed, the achieved layout as auxiliary information is fused with the simultaneous human indication. Through-wall experiments show that the proposed method can effectively extract the covered layout of multiple walls under one single view and accordingly provide strong support for the concealed human sensing.

Building Layout Reconstruction in Concealed Human Target Sensing via UWB MIMO Through-Wall Imaging Radar

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls.

/pdf/detection-of-multiple-stationary-humans-using-uwb-mimo-radar-3ejl101n71.pdf

Detection of Multiple Stationary Humans Using UWB MIMO Radar.

The detection and tracking of human targets behind the wall is of great importance in urban sensing. The random and high maneuvering behaviors of moving human targets and the clutter diversity lead to high missed detection and false-alarm probability. In this paper, we consider two-dimensional human-target tracking problem, and a multi-algorithm fusion (MAF) framework exploiting the mean-shift algorithm and the Kalman filter is proposed. Compared with the mean-shift algorithm, the proposed MAF framework has robust tracking performance, especially in the presence of multiple targets. Finally, the proposed MAF framework is evaluated by simulations and real data.

Robust Human Targets Tracking for MIMO Through-Wall Radar via Multi-Algorithm Fusion

In this letter, we derive the distribution characteristics of first-order multipath ghosts in a nested multiple-input–multiple-output (MIMO) through-wall radar and evaluate the efficacy of the phase coherence factor (PCF) in ghost suppression. Different from a synthetic aperture radar, the first-order multipath echoes of a nested MIMO through-wall radar generate several ghosts. For example, for a nested MIMO array composed of a compact receiving subarray and $M$ spatially dispersed transmitters, there are $M$ ghosts at the same side of the wall as the array. The $m$ th ghost is supposed to occur near the intersection of the line, connecting the target and the center of the receiving subarray, and the ellipse whose foci are the positions of the target and the $m$ th transmitter. Under the assumption of phase uniform distribution clutter, the PCF can suppress the ghosts up to $-20 \lg(1-\sqrt {(M^{2}-1)/M^{2}})$ dB, which is about 17.46 dB when $M = 2$ .

First-Order Multipath Ghosts' Characteristics and Suppression in MIMO Through-Wall Imaging

The use of a UWB system for sensing breathing activity of astronauts must account for many critical issues specific to the space environment. The aim of this paper is twofold. The first concerns the definition of design constraints about the pulse amplitude and waveform to transmit, as well as the immunity requirements of the receiver. The second issue concerns the assessment of the procedures and the characteristics of the algorithms to use for signal processing to retrieve the breathing frequency and respiration waveform. The algorithm has to work correctly in the presence of surrounding electromagnetic noise due to other sources in the environment. The highly reflecting walls increase the difficulty of the problem and the hostile scenario has to be accurately characterized. Examples of signal processing techniques able to recover breathing frequency in significant and realistic situations are shown and discussed.

Non-Invasive UWB Sensing of Astronauts' Breathing Activity

The phase coherence factor (PCF) is revised according to stepped frequency signal imaging radar, adding additional phase diversity in frequency domain. Then, it is applied to through-the-wall moving target indication processing for side and grating lobe artifacts mitigation. Experimental results show that PCF weighting approach can suppress both side and grating lobe artifacts effectively for through-the-wall images.

Phase coherence factor for mitigation of sidelobe artifacts in through-the-wall radar imaging

Human is one kind of the most interesting targets in through-the-wall imaging. In high-resolution imaging applications, human is no longer a point target. Therefore, the previous signal models constructed by point target assumption cannot accurately describe real characteristics of EM propagation. We construct the signal models based on extended target theory in this paper. Compared with previous works, the main contributions are as follows. Firstly, human is considered as an extended target. The expressions of target scattering and wall reflections are derived. Secondly, target scattering is no longer isotropic in new model. A new kind of ghost problem which is caused by target obscuring in EM propagation is discovered and exploited. Thirdly, to improve image quality in moving target imaging, an efficient approach which adopts CFAR, clustering method, and spatial geometry relationship is proposed to remove the ghosts. The derived models are shown to agree with synthetic and experimental results. And the efficiency of proposed method is also validated, which illuminates that the ghosts are efficiently mitigated and the image quality is significantly improved.

/pdf/moving-target-imaging-and-ghost-mitigation-in-through-the-3a3d4f5ijd.pdf

Moving Target Imaging and Ghost Mitigation in Through-the-Wall Sensing Application

Through-wall imaging method based on image domain wall influence compensation

In through-the-wall imaging, the three-dimensional (3D)imaging results are much more efficient in detecting and identifying targets than two-dimensional imaging results. To getting the high-quality imaging results, the 3-D BP imaging method is adapted and the crucial problem about the signal propagation delay is rigorously derived. Based on the derivation results, a compensation method is proposed for refocusing the targets in 3D imaging application. By using this method, the effects of the wall can be compensated and more accurate information of the targets can be obtained. Experimental data processing results validate the conclusion of this paper.

Three-dimensional imaging for UWB though-the-wall radar

To keep the system complexity at a reasonable level and conform to the propagation demands, MIMO arrays are usually sparse in through-the-wall applications, which results in corrupted and gapped data. The corresponding imaging results are seriously affected by the high-level sidelobes. To solve this problem, a new imaging model for ultra-wideband (UWB) MIMO arrays is constructed via spatial spectrum theory in this paper. Based on the model, the characteristics of the spatial spectrum for the MIMO array and its effects on imaging are discussed. To improve the imaging quality, a through-the-wall imaging enhancement method is proposed via spatial spectrum estimation. Synthetic and experimental results show that, unlike the conventional amplitude weighting methods and nonlinear techniques, the proposed method can efficiently suppress sidelobes in the imagery, especially for the sparse MIMO array, and consequently improve the target image quality without degrading the mainlobe resolution. The proposed method has been successfully used in our real through-the-wall radar system.

https://downloads.hindawi.com/journals/ijap/2014/825403.pdf

Xin Sun

Papers

Phase coherence factor for mitigation of sidelobe artifacts in through-the-wall radar imaging

Moving Target Imaging and Ghost Mitigation in Through-the-Wall Sensing Application

Through-wall imaging method based on image domain wall influence compensation

Three-dimensional imaging for UWB though-the-wall radar

Spatial Spectrum-Based Imaging for UWB Through-the-Wall MIMO Arrays