Conference Agenda

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Introduction to the workshop

Maria Michela Corvino and Thibault Taillade

European Space Agency

Spaceborne SAR micro-Doppler is an emerging and potentially disruptive technology that can significantly enhance the use of SAR for both civilian and security applications. In SAR imagery, many targets exhibit micro-motions, and the ability to detect, measure, and characterise these motions, thereby generating additional insight, requires advanced modelling, signal processing, and technological developments. Only in recent years the SAR community has begun to investigate this topic in depth.

The unique characteristics of new SAR missions, including long dwell times and fine spatial resolution, now make the extraction of micro-Doppler information from a wide variety of targets feasible. This opens the door to several new downstream applications. For example, extracting additional target features, such as the vibrational modes of a vehicle or vessel induced by its engine, can enhance automatic target recognition. Similarly, quantifying the natural harmonics of critical infrastructure with SAR may provide early warning or continuous monitoring capabilities, enabling novel commercial services, cost-effective wide-area surveying, and rapid damage assessment after natural disasters.

This talk will provide an overview of recent advances, existing challenges, and application areas for spaceborne SAR micro-Doppler. Developments in processing and acquisition paradigms aimed at improving micro-Doppler extraction will be reviewed.

Emerging applications, such as infrastructure monitoring, advanced maritime domain awareness, and the use of micro-motion signatures for underwater radiated noise prediction, will also be discussed.

In civilian contexts, micro-Doppler measurements can support the monitoring of critical infrastructure such as bridges, buildings, and pipelines. By characterising structural vibrational modes, micro-Doppler analysis can detect early signs of wear or damage through changes in vibration patterns, enabling continuous health monitoring. In security contexts, similar techniques could enhance automatic target recognition and assist in classifying vehicles or identifying concealed strategic assets (e.g., generators under canopies). By detecting and characterising dynamic movements, such as the oscillations of engine components, it becomes possible to distinguish between different vehicle types or operational states (e.g., a fishing vessel operating at high RPM). These and other applications will be presented, followed by a discussion of current challenges and future research directions.

Recent advances in spaceborne Synthetic Aperture Radar (SAR) technology are enabling a new generation of high-performance Earth observation systems. The emergence of commercial constellations operated by companies such as Capella Space, Umbra and ICEYE has significantly increased the availability of very-high-resolution (VHR) SAR data with improved spatial and temporal resolution. These agile small-satellite platforms, capable of wide bandwidth operation and advanced acquisition modes, complement established missions such as COSMO-SkyMed and TerraSAR-X. In particular, their high antenna steering agility enables long dwell acquisitions (up to ~25 s), opening new opportunities for surveillance applications beyond traditional remote sensing.

Maritime situational awareness (MSA) represents a key application domain. Monitoring vessel activity across open seas and inland waterways is essential for security, environmental protection, and economic management. Compared with terrestrial sensors, spaceborne SAR provides high-resolution imaging independent of weather conditions and illumination. However, the imaging of moving targets violates the stationary-scene assumption of conventional SAR processing, leading to defocusing and target mislocation—effects that are particularly critical in constrained inland navigation scenarios.

This work investigates the integration of Inverse SAR (ISAR) techniques within the SAR processing framework to enhance ship imaging and characterization. The proposed approach enables target refocusing, estimation of vessel kinematics (translational and rotational motion), cross-range scaling for size estimation, and relocation of the target to its true geographic position. The complete processing chain operates on level-1A single-channel SAR data, addressing the limitations imposed by the absence of multi-channel systems.

Experimental results are presented using real datasets acquired by different satellite classes and vessel types, with validation supported by Automatic Identification System (AIS) data. Finally, future research directions are discussed, with particular focus on the exploitation of long-dwell SAR acquisitions for advanced maritime surveillance applications

In the context of Synthetic Aperture Radar (SAR) processing, it is well known that the coherent integration of backscattered signals, one of its key steps, relies heavily on stationary scene models. When targets exhibit uncompensated complex motions or height deviations, this assumption breaks down, inducing residual phase errors and severe defocusing. This phenomenon is detrimental in Very High Resolution (VHR) imagery acquired with long integration times, complicating critical downstream applications.

Advanced SAR processing techniques exist, such as Inverse SAR (ISAR) and sub-aperture Micro-Doppler analysis to characterize roto-translational dynamics and vibrations, they entail significant trade-offs. They frequently demand high Signal-to-Noise Ratios, require complex phase unwrapping, or sacrifice maximum spatial resolution by relying on subapertures. To overcome these limitations, we have recently proposed a novel approach, named Doppler Phase Coherence (DPC), which bring a significant advancement. The DPC method retrieves 3D shapes and complex motion parameters directly from single-pass VHR SAR acquisitions by maximizing the coherence of the Doppler history against a unified phase model, fully exploiting the available spectral bandwidth without the need for sub-apertures.

Moreover, we have been further developing the method by moving from a point-wise analysis to a novel object-based constraint model. By treating extended targets coherent rigid or semi-rigid bodies, we enforce kinematic and geometric consistency across the entire structure. This flexible framework supports both global parameters (e.g., uniform vibration frequencies across an asset) and soft constraints (e.g., spatial continuity of heights or modal amplitudes). Crucially, this joint estimation approach successfully decouples the superimposed phase effects of structural height and motion signatures, resolving physical ambiguities that severely limit traditional single-scatterer analyses.

The methodology is validated using VHR SAR data across diverse operational scenarios:

• As regards the height estimation, ICEYE Dwell Mode imagery proves the framework's capability for precise 3D urban reconstruction and vessel cargo load inference [Fig. 1].
• Regarding the velocity estimation, experimental results on a TerraSAR-X spotlight acquisition demonstrate accurate ship azimuth velocity estimation (4.63 m/s), closely aligning with AIS ground truth (4.82 m/s) [Fig. 2].
• Concerning the vibrational components estimation, structural health monitoring is validated using an UMBRA SAR image of a suspension bridge; the DPC-derived vibration frequencies (~1.6 Hz) and the mapping of nodal spatial patterns show a remarkable agreement with in-situ accelerometer data [Fig. 3-4].

These results confirm the validity of the object-based DPC method as a powerful tool for

We present the results of the MIDAS (MIcro-Doppler InfrAstructure Stability Assessment using SAR) project, funded by the European Space Agency. Micro-Doppler (mD) processing of spaceborne SAR (SB-SAR) data is applied to generate vibration maps. A sub-aperture decomposition is performed, followed by the estimation of the Doppler centroid (DC) for each sub-look. Several azimuth sub-aperture images with partially overlapping Doppler spectra are generated from a SAR image. The sampling rate that characterizes the micro-Doppler behavior depends on the number of sub-apertures and the percentage of overlap between two consecutive Doppler sub-bands.

A fast correlation-based Doppler estimator (CDE) is applied using a two-dimensional sliding window on each sub-aperture image, which leads to a series of Doppler centroid (DC) images. Therefore, a DC data cube is obtained. Therein, the first two dimensions denote the radar coordinates, i.e., range and azimuth, whereas the third coordinate represents the DC axis. The DC values along the sub-aperture dimension are proportional to the linear movement of vibrating targets located in the SAR image if the sub-aperture dwell time is much shorter than the vibration mode repetition interval.

Finally, a Fourier transform applied along the sub-aperture dimension provides an estimate of the vibration spectrum for each pixel. The vibration spectra contain a limited number of discrete vibration frequencies. Therefore, to identify pixels containing vibrating targets, we compute a sparsity measure (e.g., entropy or spectral concentration) of the spectrum, where a sparse spectrum indicates possible vibration.

StripMap SAR images acquired by the X-band COSMO-SkyMed mission and Spotlight images from the ICEYE spaceborne mission are processed, and the estimated vibrations are compared with in-situ Ku-band ground-based radar (GBR) measurements. GBR data are interferometrically processed to generate displacement time series and corresponding spectra of targets. The azimuth and elevation angles of the GBR acquisition are set to be aligned with the line-of-sight (LoS) of the SB-SAR acquisitions. GBR data are acquired using antennas with different radiation patterns to obtain different spatial resolutions on the infrastructure surface and different spatial coverage of the target.

The identified vibration frequencies suggest reasonable agreement between GBR and SB-SAR measurements, validated also using a vibrating corner reflector. Case studies of the Chialandreia viaduct (Basilicata region, Italy) and three water towers (Capitanata irrigation district, Apulia region, Italy) are presented. The potential use of the SAR micro-Doppler methodology for the non-destructive, fully remote monitoring of critical infrastructures is discussed.