Abstract:Next-generation communication and localization systems increasingly rely on extremely large-scale arrays (XL-arrays), which promise unprecedented spatial resolution and new functionalities. These gains arise from their inherent operation in the near field (NF) regime, where the spherical nature of the wavefront can no longer be ignored; consequently, characterizing the ambiguity function -- which amounts to the matched beam pattern -- is considerably more challenging. Implementing very wide apertures with half-wavelength element spacing is costly and complex. This motivates thinning the array (removing elements), which introduces intricate aliasing structures, i.e., grating lobes. Whereas prior work has addressed this challenge using approximations tailored to specific array geometries, this paper develops a general framework that reveals the fundamental origins and geometric behavior of grating lobes in near-field ambiguity functions. Using a local spatial-frequency analysis of steering signals, we derive a systematic methodology to model NF grating lobes as aliasing artifacts, quantifying their structure on the AF, and providing design guidelines for XL-arrays that operate within aliasing-safe regions. We further connect our framework to established far-field principles. Finally, we demonstrate the practical value of the approach by deriving closed-form expressions for aliasing-free regions in canonical uniform linear arrays and uniform circular arrays.
Abstract:This paper presents a chirp-based framework for characterising aliasing in a bistatic Near-Field (NF) imaging system equipped with multidimensional antenna arrays. Extending monostatic formulations, we derive closed-form expressions for the maximum spatial frequency, enabling the analytical derivations of the conditions for aliasing-free image reconstruction. The framework also provides a geometric interpretation of aliasing based on the antenna array geometry, target position, and antenna element spacing. Numerical results corroborate theoretical findings and show that the aliasing-free region enlarges with smaller antenna spacing, greater target range, lower array dimensionality, and smaller arrays. These results enable more effective design of bistatic NF imaging systems.
Abstract:In antenna arrays, wave propagation modeling based on Euclidean principles is typically represented by steering vectors or signals. This paper provides a new, chirp-based, interpretation of steering vectors in the Spherical Wavefront Regime (SWR), establishing a relationship between the spatial spectrum of the received (resp. transmitted) signal and the geometry of the array and the source (resp. target). Leveraging the well-known sampling theorem, we analyze aliasing effects arising from spatial sampling with a finite number of antennas and understand how these effects degrade the Ambiguity Function (AF). Our framework provides geometric insight into these degradations, offering a deeper understanding of the non-space-invariant aliasing mechanisms in the SWR. The proposed approach is formulated for general antenna arrays and then instantiated to Circular Array and to Uniform Linear Array structures operating in Near Field conditions.




Abstract:Traditional radar and integrated sensing and communication (ISAC) systems often approximate targets as point sources, a simplification that fails to capture the essential scattering characteristics for many applications. This paper presents a novel electromagnetic (EM)-based framework to accurately model the near-field (NF) scattering response of extended targets, which is then applied to three canonical shapes : a flat rectangular plate, a sphere and a cylinder. Mathematical expressions for the received signal are provided in each case. Based on this model, the influence of bandwidth, carrier frequency and target distance on localisation accuracy is analysed, showing how higher bandwidths and carrier frequencies improve resolution. Additionally, the impact of target curvature on localisation performance is studied. Results indicate that detection performance is slightly enhanced when considering curved objects. A comparative analysis between the extended and point target models shows significant similarities when targets are small and curved. However, as the target size increases or becomes flatter, the point target model introduces estimation errors owing to model mismatch. The impact of this model mismatch as a function of system parameters is analysed, and the operational zones where the point abstraction remains valid and where it breaks down are identified. These findings provide theoretical support for experimental results based on point-target models in previous studies.