An Evolutionary Algorithm With Constraint Relaxation Strategy for Highly Constrained Multiobjective Optimization

A Procedural Method to Predictively Assess Power-Quality Trade-Offs of Circuit-Level Adaptivity in IoT Systems

The constant miniaturization of IoT sensor nodes requires a continuous reduction in battery sizes, leading to more stringent needs in terms of low-power operation. Over the past decades, an extremely large variety of techniques have been introduced to enable such reductions in power consumption. Many involve some form of offline reconfigurability (OfC), i.e., the ability to configure the node before deployment, or online adaptivity (OnA), i.e., the ability to also reconfigure the node during run time. Yet, the inherent design trade-offs usually lead to ad hoc OnA and OfC, which prevent assessing the varying benefits and costs each approach implies before investing in implementation on a specific node. To solve this issue, in this work, we propose a generic predictive assessment methodology that enables us to evaluate OfC and OnA globally, prior to any design. Practically, the methodology is based on optimization mathematics, to quickly and efficiently evaluate the potential benefits and costs from OnA relative to OfC. This generic methodology can, thus, determine which type of solution will consume the least amount of power, given a specific application scenario, before implementation. We applied the methodology to three adaptive IoT system studies, to demonstrate the ability of the introduced methodology, bring insights into the adaptivity mechanics, and quickly optimize the OfC–OnA adaptivity, even under scenarios with many adaptivity variables.

An Efficient Backprojection Algorithm Based on Wavenumber-Domain Spectral Splicing for Monostatic and Bistatic SAR Configurations

This paper introduces a fast backprojection synthetic aperture radar (SAR) imaging algorithm based on wavenumber-domain spectral splicing. The traditional fast backprojection (FBP) algorithm establishes the polar coordinate system with the center of the sub-aperture as the origin. Therefore, the coordinates of the image obtained from each sub-aperture are different. Sub-aperture images must be projected to a uniform coordinate system before they can be coherently superimposed to form the final image, which requires a large amount of calculation. In order to deal with this problem, this paper proposes a novel imaging method, which uses the same polar coordinate system for each sub-aperture. The sub-aperture images are then spliced in the wavenumber-domain, and directly added after upsampling. This method avoids the projection from each sub-aperture to the uniform coordinate system, thus improving the imaging accuracy and efficiency. At the same time, the algorithm is suitable for various configurations, and can achieve good imaging results for bistatic forward-looking SAR and high-speed mobile platform. Finally, simulations are presented to demonstrate the effectiveness of the algorithm.