António Barros | Searcharxiv

arXiv2025

Interference and Multipath Resilient ToA Estimation

We present a computationally-efficient algorithm for time-of-arrival (ToA) estimation that is robust under multipath propagation and strong interference. Our algorithm leverages multiple receive antennas to combine adaptive spatial filtering with autodifferentiation in order to super-resolve the tap of the first-arriving path at low computational complexity and without requiring model-order estimation. We use simulations with ray-traced indoor propagation channels to demonstrate significant performance improvements over conventional correlation-based ToA estimation methods and subspace techniques such as JADE.

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arXiv2025

Adaptive Extended Kalman Filtering for Battery State of Charge Estimation on STM32

Accurate and computationally light algorithms for estimating the State of Charge (SoC) of a battery's cells are crucial for effective battery management on embedded systems. In this letter, we propose an Adaptive Extended Kalman Filter (AEKF) for SoC estimation using a covariance adaptation technique based on maximum likelihood estimation - a novelty in this domain. Furthermore, we tune a key design parameter - the window size - to obtain an optimal memory-performance trade-off, and experimentally demonstrate our solution achieves superior estimation accuracy with respect to existing alternative methods. Finally, we present a fully custom implementation of the AEKF for a general-purpose low-cost STM32 microcontroller, showing it can be deployed with minimal computational requirements adequate for real-world usage.

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