Terrestrial Radar Interferometry (TRI) is a measurement technique capable of measuring displacements with high temporal resolution at high accuracy. Current implementations of TRI use large and/or movable antennas for generating two-dimensional displacement maps. Multiple Input Multiple Output Synthetic Aperture Radar (MIMO-SAR) systems are an emerging alternative. As they have no moving parts, they are more easily deployable and cost-effective. These features suggest the potential usage of MIMO-SAR interferometry for structural health monitoring (SHM) supplementing classical geodetic and mechanical measurement systems. The effects impacting the performance of MIMO-SAR systems are, however, not yet sufficiently well understood for practical applications. In this paper, we present an experimental investigation of a MIMO-SAR system originally devised for automotive sensing, and assess its capabilities for deformation monitoring. The acquisitions generated for these investigations feature a 180∘ Field-of-View (FOV), distances of up to 60 m and a temporal sampling rate of up to 400 Hz. Experiments include static and dynamic setups carried out in a lab-environment and under more challenging meteorological conditions featuring sunshine, fog, and cloud-cover. The experiments highlight the capabilities and limitations of the radar, while allowing quantification of the measurement uncertainties, whose sources and impacts we discuss. We demonstrate that, under sufficiently stable meteorological conditions with humidity variations smaller than 1%, displacements as low as 25m can be detected reliably. Detecting displacements occurring over longer time frames is limited by the uncertainty induced by changes in the refractive index.

Deformations affect the structural integrity of wind turbine towers. The health of such structures is thus assessed by monitoring. The majority of sensors used for this purpose are costly and require in situ installations. We investigated whether Multiple-Input Multiple-Output Synthetic Aperture Radar (MIMO-SAR) sensors can be used to monitor wind turbine towers. We used an automotive-grade, low-cost, off-the-shelf MIMO-SAR sensor operating in the W-band with an acquisition frequency of 100 Hz to derive Line-Of-Sight (LOS) deformation measurements in ranges up to about 175 m. Time series of displacement measurements for areas at different heights of the tower were analyzed and compared to reference measurements acquired by processing video camera recordings and total station measurements. The results showed movements in the range of up to 1 m at the top of the tower. We were able to detect the deformations also with the W-band MIMO-SAR sensor; for areas with sufficient radar backscattering, the results suggest a sub-mm noise level of the radar measurements and agreement with the reference measurements at the mm- to sub-mm level. We further applied Fourier transformation to detect the dominant vibration frequencies and identified values ranging from 0.17 to 24 Hz. The outcomes confirmed the potential of MIMO-SAR sensors for highly precise, cost-efficient, and time-efficient structural monitoring of wind turbine towers. The sensors are likely also applicable for monitoring other high-rise structures such as skyscrapers or chimneys.

Sensors capable of measuring surface deformations with areal coverage and high spatial and temporal resolution are beneficial for many monitoring applications. However, such sensors are typically expensive, or their configuration cannot be adapted flexibly by the user like in case of satellite-based systems. Automotive Multiple-Input-Multiple-Output Synthetic Aperture Radar (MIMO-SAR) systems are interesting potential alternatives associated with low cost and high flexibility. In this paper, we present an experimental investigation showing the capabilities of a particular off-the-shelf, automotive radar system for structural monitoring. We analyse the accuracy of the measured line-of-sight displacements, the spatial and temporal resolution, and the impact of simultaneous coverage of the same area by two sensors of the same type. Finally, we demonstrate the MIMO-SAR system in a real-world use case measuring deformations of a railway bridge in response to dynamic load by trains passing over it. We operated two MIMO-SAR sensors simultaneously, analyse and interpret the individual interferograms and combine the data to derive the temporal and spatial distribution of vertical displacements along selected profiles. The results show that off-the-shelf automotive-grade MIMO-SAR systems can be used to quantify sub-millimetre deformations of structures and derive high-resolution time series beneficial for structural health monitoring applications.

We propose an in situ self‐calibration method by detecting and matching intensity features on the local planes in overlapping point clouds based on the Förstner operator. We successfully matched the intensity features from scans at different locations by feature matching on common local planes rather than on the rasterised grids of the horizontal and vertical angles adopted by the affirmed keypoint‐based algorithm. The capability of extracting features from different stations offers the possibility of comprehensive scanner calibration, solving the disadvantage that the existing keypoint‐based methods can only estimate the two‐face‐sensitive model parameters. The proposed algorithm has been tested with a high‐precision panoramic scanner, Leica RTC360, using datasets from a calibration hall and a general working scenario. It has been shown that the proposed approach consistently calibrates the two‐face‐sensitive model parameters with the affirmed keypoint‐based one. For the case of comprehensive calibration with the offset estimated and some angular parameters separated where the previous keypoint‐based one failed, the proposed algorithm achieves an accuracy of 0.16 mm, 2.7″ and 2.1″ in range, azimuth and elevation for the estimated target centres. The proposed algorithm can accurately calibrate two‐face‐sensitive and more comprehensive model parameters without any preparation on‐site, for example, mounting targets.