Related papers: Amateur Drones Detection: A machine learning appro…
Safe navigation of drones in the presence of adversarial physical attacks from multiple pursuers is a challenging task. This paper proposes a novel approach, asynchronous multi-stage deep reinforcement learning (AMS-DRL), to train…
In the incoming years, the low-aerial space will be crowded by unmanned aerial vehicles (UAVs), which will be providing different services. In this expected context, an emerging problem is to detect and track unauthorized or malicious…
In the past decade, the number of amateur drones is increasing, and this trend is expected to continue in the future. The security issues brought by abuse and misconduct of drones become more and more severe and may incur a negative impact…
This paper presents a new Metacognitive Decision Making (MDM) framework inspired by human-like metacognitive principles. The MDM framework is incorporated in unmanned aerial vehicles (UAVs) deployed for decentralized stochastic search…
Accurate Direction of Arrival (DoA) estimation is critical for applications in robotics and communication, but high costs and complexity of coherent multi-channel receivers hinder accessibility. This work proposes a cost-effective DoA…
There is a growing need for anomaly detection methods that can broaden the search for new particles in a model-agnostic manner. Most proposals for new methods focus exclusively on signal sensitivity. However, it is not enough to select…
Accurate motion capture of aerial robots in 3-D is a key enabler for autonomous operation in indoor environments such as warehouses or factories, as well as driving forward research in these areas. The most commonly used solutions at…
Autonomous drone technology holds significant promise for enhancing search and rescue operations during evacuations by guiding humans toward safety and supporting broader emergency response efforts. However, their application in dynamic,…
Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count birds, marine mammals and large herbivores in different…
In this paper, we propose an anomaly detection algorithm for machine sounds with a deep complex network trained by self-supervision. Using the fact that phase continuity information is crucial for detecting abnormalities in time-series…
Integration of Unmanned Aerial Vehicles (UAVs) or "drones" into the civil aviation airspace is a problem of increasing interest in the aviation community, as testified by many initiatives developed worldwide. Many traditional surveillance…
Unmanned aerial vehicles (UAVs) are widely used due to their low cost and versatility, but they also pose security and privacy threats. Therefore, reliable detection for low-altitude UAVs is an important issue. The strong ground clutter…
Unmanned aerial vehicle (UAV) operations are steadily expanding into many important applications. A key technology for better enabling their commercial use is an onboard sense and avoid (SAA) technology which can detect potential mid-air…
The applications of the unmanned aerial vehicles (UAVs) increase rapidly in everyday life, thus detecting the UAVs and/or its pilot is a crucial task. Many UAVs adopt frequency hopping spread spectrum (FHSS) technology to efficiently and…
Data centers host a variety of essential services such as cloud computing and artificial intelligence. Electric grid operators, however, have limited knowledge of the reliability risks of data center interconnection due to their unique…
Utilizing autonomous drones or unmanned aerial vehicles (UAVs) has shown great advantages over preceding methods in support of urgent scenarios such as search and rescue (SAR) and wildfire detection. In these operations, search efficiency…
This paper introduces a scheme for drone surveillance coordinated with the fifth generation (5G) synchronization signal block (SSB) cell-search procedure to simultaneously detect low-altitude drones within a volumetric surveillance grid.…
This paper proposes an intelligent technique for maximizing the network connectivity and provisioning desired quality of service (QoS) of integration of internet of things (IoT) and unmanned aerial vehicle (UAV). Prediction of the signal…
Precise Time-of-Arrival (TOA) estimations of aircraft and drone signals are important for a wide set of applications including aircraft/drone tracking, air traffic data verification, or self-localization. Our focus in this work is on TOA…
For drones, as safety-critical systems, there is an increasing need for onboard detect & avoid (DAA) technology i) to see, sense or detect conflicting traffic or imminent non-cooperative threats due to their high mobility with multiple…