OFDM Based UWB Synthetic Aperture Through-wall Imaging Radar

Slimane, Zohra; Abdelmalek, Abdelhafid; Feham, Mohammed

doi:10.1109/broadcom.2008.34

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…Furthermore, wideband detection can perform in dust-filled environments, where infrared and optical systems fail [17]- [19]. Hyperspectral sensors and infrared system provides good resolution through exterior layers of an object [20]- [23].…”

Section: Wideband Technologymentioning

confidence: 99%

Modeling techniques for target detection

2014

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To better study hyperspectral imaging sensors and remote sensing system performance, different parts of the remote sensing system can be modeled.Here, a scientific overview of recent modeling techniques is presented to come up with an appropriate approach for modeling of a target detection system. In particular, this study focuses on the development in modeling of scene, sensors, and processing algorithms. Moreover, the parallelization of the detection methods is emphasized for which the process of target detection accelerates. In conclusion, an appropriate model to evaluate a target detection system can be a hybrid model in which hyperspectral sensors, radars, and local sensors have been modeled.

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Section: Wideband Technologymentioning

confidence: 99%

Modeling techniques for target detection

2014

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“…UWB signal employs a very large electromagnetic spectrum bandwidth and has advantages of good penetration capacity of building walls and high imaging resolution [6][7]. Chirp signal is a well-known signal type in radar systems for low SNR signal detection and high resolution range estimation.…”

Section: Introductionmentioning

confidence: 99%

Through-the-wall tomographic imaging using chirp signals

Huang

2011

2011 IEEE International Symposium on Antennas and Propagation (APSURSI)

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This paper presents a feasibility study of using chirp signal for through-the-wall radar imaging and indoor positioning applications. Chirp signal enables frequency diversity while multistatic geometry of tomographic imaging enables space diversity. Pulse compression of chirp aims for range compression of received signals. Beamforming reconstruction algorithm is then applied on compressed signals to produce the final image. In the computer simulation experiments, we have considered using chirp signal and pulsed sine signal as transmitting signals for point targets imaging with building walls in different situations. This study draws a conclusion that using chirp signals, highquality imaging and positioning results can be obtained.

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“…To date, waveforms used for through-the-wall detection and imaging include both classical (such as short pulse or impulse, and linear or stepped frequency-modulated) and sophisticated (such as noise or noise-like, chaotic, and M-sequence phase coded) approaches [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Each of these waveforms has its own advantages and limitations.…”

Section: Introductionmentioning

confidence: 99%

Through-Wall Single and Multiple Target Imaging Using MIMO Radar

2017

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Abstract:The ability to perform target detection through walls and barriers is important for law enforcement, homeland security, and search and rescue teams. Multiple-input-multiple-output (MIMO) radar provides an improvement over traditional phased array radars for through-wall imaging. By transmitting independent waveforms from a transmit array to a receive array, an effective virtual array is created. This array has improved degrees of freedom over phased arrays and mono-static MIMO systems. This virtual array allows us to achieve the same effective aperture length as a phased array with a lower number of elements because the virtual array can be described as the convolution of transmit and receive array positions. In addition, data from multiple walls of the same room can be used to collect target information. If two walls are perpendicular to each other and the geometry of transmit and receive arrays is known, then data can be processed independently of each other. Since the geometry of the arrays is known, a target scene can be created where the two data sets overlap. The overlapped scene can then be processed so that image artifacts that do not correlate between the data sets can be excised. The result gives improved target detection, reduction in false alarms, robustness to noise, and robustness against errors such as improperly aligned antennas. This paper explores MIMO radar techniques for target detection and localization behind building walls and addresses different mitigation techniques, such as a singular value decomposition of wavelet transform method to improve localization and detection of targets. Together, these techniques demonstrate methods that show a reduction in size and complexity of traditional through-wall radar systems while still providing accurate detection and localization. The use of the range migration algorithm in single and multi-target scenarios is shown to provide adequate imaging of through the wall targets in near and far field. Also, a multi-view algorithm is used to provide improved target detection and localization by fusing together multiple wall views.

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OFDM Based UWB Synthetic Aperture Through-wall Imaging Radar

Cited by 8 publications

References 3 publications

Modeling techniques for target detection

Modeling techniques for target detection

Through-the-wall tomographic imaging using chirp signals

Through-Wall Single and Multiple Target Imaging Using MIMO Radar

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