Vibration parameter estimation using FMCW radar

Ding, Lei; Ali, Muhammad Yasir; Patole, Sujeet; Dabak, A.G.

doi:10.1109/icassp.2016.7472072

Cited by 43 publications

(20 citation statements)

References 6 publications

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“…Here, the conjugate of the actual FMCW waveform [46] is used as the backscattered data model for the sake of simplicity in the image reconstruction algorithms. The last term of (4) is known as the residual video phase (RVP), which is usually negligible [47], [48]. Therefore, the received beat signal can be expressed in the wavenumber domain as…”

Section: A Fmcw Chirp Signalmentioning

confidence: 99%

“…where ω b (x , y ) = 2πf b (x , y ) is the angular beat frequency. Because the beat signal is assumed to be uniformly sampled over time, the sampled version of (10) can be obtained by performing a fast Fourier transform (FFT) operation, which is usually referred to as the range FFT [48]. In Fig.…”

Section: Mimo Array Calibrationmentioning

confidence: 99%

“…If we selectω = ω b (x , y )T s in (10) for all measurement points, i.e., the beat frequency corresponding the peak index of the FFT output, the complex values at that index will only have the phase terms e jφ(x ,y ) . The residual phase error caused by the limited FFT resolution is assumed to be negligible [48]. Using the range FFT output in Fig.…”

Section: Mimo Array Calibrationmentioning

confidence: 99%

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Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

2020

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Multiple-input multiple-output (MIMO) radars and synthetic aperture radar (SAR) techniques are well researched and have been effectively combined for many imaging applications ranging from remote sensing to security. Despite numerous studies that apply MIMO concepts to SAR imaging, the design process of a MIMO-SAR system is non-trivial, especially for millimeter-wave (mmWave) imaging systems. Many issues have to be carefully addressed. Besides, compared with conventional monostatic sampling schemes or MIMO-only solutions, efficient image reconstruction methods for MIMO-SAR topologies are more complicated in short-range applications. To address these issues, we present highly-integrated and reconfigurable MIMO-SAR testbeds, along with examples of three-dimensional (3-D) image reconstruction algorithms optimized for MIMO-SAR configurations. The presented testbeds utilize commercially available wideband mmWave sensors and motorized rail platforms. Several aspects of the MIMO-SAR testbed design process, including MIMO array calibration, electrical/mechanical synchronization, system-level verification, and performance evaluation, are described. We present three versions of MIMO-SAR testbeds with different implementation costs and accuracies to provide alternatives for other researchers who want to implement their testbed framework. Several representative examples in various real-world imaging applications are presented to demonstrate the capabilities of the proposed testbeds and algorithms. INDEX TERMS Millimeter-wave (mmWave) radar, multiple-input multiple-output (MIMO) radar, synthetic aperture radar (SAR), frequency-modulated continuous-wave (FMCW), back projection algorithm (BPA), range migration algorithm (RMA), three-dimensional (3-D) imaging, testbed design, calibration.

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Section: A Fmcw Chirp Signalmentioning

confidence: 99%

Section: Mimo Array Calibrationmentioning

confidence: 99%

Section: Mimo Array Calibrationmentioning

confidence: 99%

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Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

2020

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“…In Table 1 the main details of Radar are reported. 3 VIBRATION ANALYSIS ALGORITHM AND CONFIGURATION OF THE RADAR The vibration analysis was based on the work described in [6]. The vibration of the target cannot be identified from the measure of the distance due to the limited spatial resolution R def of the radar, defined by the equation .…”

Section: The Fmcw Radarmentioning

confidence: 99%

“…The beat signal however does not only contain a component ω b (t) of a single target, but also of all echoes detected. In fact, in [6] it is shown that the FFT of s b (t), fixed ω b (t) related to the chosen target, becomes:…”

Section: The Fmcw Radarmentioning

confidence: 99%

Automotive Radar Application for Structural Health Monitoring

Gambi

Ciattaglia

Santis

2019

WIT Transactions on the Built Environment

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Monitoring of communication and residential infrastructures, such as buildings, bridges and tunnels, has always been important to ensure the safety of citizens. In particular, it is of interest to verify the level of mechanical stress to which bridges and buildings are subjected during earthquakes, measuring the oscillations that the structure undergoes during the seismic event, in order to verify the overcoming of safety thresholds, in which stability may be impaired. In this paper the mmWave radars designed for the automotive world is taken into account, since it allows high precision measurements at a relatively low cost. mmWave radars are able to detect vibrations of the order of tens of microns and, therefore, are very useful for monitoring buildings. Furthermore, using MIMO (Multiple Input Multiple Output) mmWave radars, it is possible to implement the Beamforming technology for the spatial shaping of the radio beam, in order to detect more targets simultaneously. In this way it is possible to monitor multiple buildings or structures simultaneously, or different parts of the same structure with a single sensor. The objective of the present work is to show the applicability of automotive radar to the measurement of oscillations suffered by buildings and bridges, in order to be used as a monitoring tool in the event of earthquakes. Results of software simulations, laboratory test and real measurements on infrastructures are provided.

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