Related papers: Improving Beam Granularity Performance of Reconfig…
We present geometric-phase microscopy allowing a multipurpose quantitative phase imaging in which the ground-truth phase is restored by quantifying the phase retardance. The method uses broadband spatially incoherent light that is…
Reset control is known to be able to outperform PID and the like linear controllers. However, in motion control systems, quantization can cause severe performance degradation. This paper shows the application of time regularization to…
In conventional colocated multiple-input multiple-output (MIMO) radars, practical waveform constraints including peak-to-average power ratio, constant or bounded modulus lead to a significant performance reduction of transmit beampattern,…
Phase retrieval can be expressed as one non-convex constrained optimization problem to identify one phase minimizer in the primal space. Many iterative transform techniques have been proposed to identify the minimizer, e.g., relaxed…
Conventional active array radars often jointly design the transmit and receive beamforming for effectively suppressing interferences. To further promote the interference suppression performance, this paper introduces a reconfigurable…
We study tunable refraction of light in one-dimensional periodic lattices induced optically in a photorefractive crystal. We observe experimentally both positive and negative refraction of beams which selectively excite the first or second…
The technology of reconfigurable intelligent surfaces (RIS) has been showing promising potential in a variety of applications relying on Beyond-5G networks. Reconfigurable intelligent surface (RIS) can indeed provide fine channel…
This paper introduces Dr-BA, a first-of-its-kind radar bundle adjustment (BA) framework that operates directly on 2D spinning radar intensity images. Unlike camera or lidar sensors, radar is largely unaffected by precipitation, making it a…
Although existing Quantization-Aware Training (QAT) methods intensively depend on knowledge distillation to guarantee performance, QAT still suffers from severe performance drop. The experiments have shown that vanilla quantization is…
Communication performance and channel estimation accuracy in MIMO systems are known to be limited by hardware impairments. Specifically, the presence of phase impairments, such as phase noise, makes real-time coherent transmission a…
X-ray ptychography is one of the versatile techniques for nanometer resolution imaging. The magnitude of the diffraction patterns is recorded on a detector and the phase of the diffraction patterns is estimated using phase retrieval…
Array synthetic aperture radar (Array-SAR), also known as tomographic SAR (TomoSAR), has demonstrated significant potential for high-quality 3D mapping, particularly in urban areas.While deep learning (DL) methods have recently shown…
A common problem that arises in radar imaging systems, especially those mounted on mobile platforms, is antenna position ambiguity. Approaches to resolve this ambiguity and correct position errors are generally known as radar autofocus.…
The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform. Mathematically, it is obtained by correlating the waveform with its…
Synthetic aperture radar (SAR) is a day or night any-weather imaging modality that is an important tool in remote sensing. Most existing SAR image formation methods result in a maximum a posteriori image which approximates the reflectivity…
Post-training Quantization (PTQ) has become a widely used technique for improving inference efficiency of large language models (LLMs). However, existing PTQ methods generally suffer from crucial limitations such as heavy calibration data…
Conventional radar feature extraction faces limitations due to low spatial resolution, noise, multipath reflection, the presence of ghost targets, and motion blur. Such limitations can be exacerbated by nonlinear object motion, particularly…
Recent studies have shown that regularization techniques using soft labels, e.g., label smoothing, Mixup, and CutMix, not only enhance image classification accuracy but also mitigate miscalibration due to overconfident predictions, and…
A multistatic radar set-up is considered in which distributed receive antennas are connected to a Fusion Center (FC) via limited-capacity backhaul links. Similar to cloud radio access networks in communications, the receive antennas…
Quantization is the key method for reducing inference latency, power and memory footprint of generative AI models. However, accuracy often degrades sharply when activations are quantized below eight bits. Recent work suggests that…