Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, implementation flexibility. Most importantly, it...

We propose a method for tracking an unknown number of targets based on measurements provided by multiple sensors. Our achieves low computational complexity and excellent scalability running belief propagation suitably devised factor graph. A redundant formulation data association uncertainty the use "augmented target states" including binary indicators make it possible to exploit statistical independencies drastic reduction complexity. An increase in targets, sensors, or leads additional...

Data-driven methods open up unprecedented possibilities for maritime surveillance using Automatic Identification System (AIS) data. In this work, we explore deep learning strategies historical AIS observations to address the problem of predicting future vessel trajectories with a prediction horizon several hours. We propose novel sequence-to-sequence trajectory models based on encoder-decoder recurrent neural networks (RNNs) that are trained data predict samples given previous observations....

Abstract To prevent the outbreak of Coronavirus disease (COVID-19), many countries around world went into lockdown and imposed unprecedented containment measures. These restrictions progressively produced changes to social behavior global mobility patterns, evidently disrupting economic activities. Here, using maritime traffic data collected via a network Automatic Identification System (AIS) receivers, we analyze effects that COVID-19 pandemic measures had on shipping industry, which...

In many environmental monitoring applications of Wireless Sensor Networks (WSNs), safe information retrieval from any subset sensors, at an arbitrary instant time, should be guaranteed. Accordingly, we study the behavior a WSN that continuously senses surrounding environment, while consensus among its nodes is simultaneously enforced. For this running scheme, analytical bounds in terms degree and comparison with ideal centralized system are provided, example presented.

X-band marine radar systems represent a flexible and low-cost tool for the tracking of multiple targets in given region interest. Although suffering several sources interference, e.g., sea clutter, these can provide high-resolution measurements, both space time. Such features offer opportunity to get accurate information not only about target position/motion but also size. Accordingly, this paper, we exploit emergent extended (ETT) methodologies which state, typically...

In the last decades, great interest has been directed toward low-power high-frequency (HF) surface-wave radars as long-range early warning tools in maritime-situational-awareness applications. These sensors, developed for ocean remote sensing, provide an additional source of information ship detection and tracking, by virtue their over-the-horizon coverage capability continuous-time mode operation. Unfortunately, they exhibit many shortcomings that need to be taken into account, such poor...

Underwater surveillance has traditionally been carried out by means of surface and undersea manned vessels equipped with advanced sensor systems. This approach is often costly manpower intensive. Marine robotics an emerging technological area that enables the development networks for underwater applications. In contrast use standard assets, these are typically composed small, low‐power, possibly mobile robots, which have limited endurance, processing wireless communication capabilities. When...

Surveillance in antisubmarine warfare has traditionally been carried out by means of submarines or frigates with towed arrays. These techniques are manpower intensive. Alternative approaches have recently suggested using distributed stationary and mobile sensors, such as autonomous underwater vehicles (AUVs). In contrast the use standard assets, these small, low-power, devices limited processing wireless communication capabilities. However, when deployed a spatially separated network,...

We present a novel method for predicting long-term target states based on mean-reverting stochastic processes. use the Ornstein-Uhlenbeck (OU) process, leading to revised state equation and time scaling law related uncertainty that in long term is shown be orders of magnitude lower than under nearly constant velocity (NCV) assumption. In support proposed model, an analysis significant portion real-world maritime traffic provided.

Situation-aware technologies enabled by multitarget tracking algorithms will create new services and applications in emerging fields such as autonomous navigation maritime surveillance. The system models underlying often involve unknown parameters that are potentially time-varying. A manual tuning of model the user is prone to errors can, thus, dramatically reduce target detection performance. We address this challenge proposing a framework "self-tuning" multisensor-multitarget algorithms....

Consensus in sensor networks is a procedure to corroborate the local measurements of sensors with those surrounding nodes, and leads final agreement about common value that, detection applications, represents decision statistic. As amount collected data increases, convergence toward statistic ruled by suitable scaling laws, question arises if asymptotic (large sample) properties are retained when this approximated via consensus algorithms. We investigate running detectors both under...

Maritime anomaly detection requires an efficient representation and consistent knowledge of vessel behaviour. Automatic Identification System (AIS) data provides ships state vector identity information that is here used to automatically derive maritime traffic in unsupervised way. The proposed approach only utilises AIS data, historical or real-time, aimed at incrementally learning motion patterns without any specific a priori contextual description. This can be applied single terrestrial...

These last decades spawned a great interest toward low-power high-frequency (HF) surface-wave (SW) radars for ocean remote sensing. By virtue of their over-the-horizon coverage capability and continuous-time mode operation, these sensors are also effective long-range early warning tools in maritime situational awareness applications providing an additional source information target detection tracking. Unfortunately, they exhibit many shortcomings that need to be taken into account, proper...

Port-starboard ambiguity is an important issue in underwater tracking systems with anti-submarine warfare applications, especially for wireless sensor networks based upon autonomous vehicles. In monostatic this leads to a ghost track of the target symmetrically displaced respect sensor. Removal such artifacts usually made by rough and heuristic approaches. context Bayesian filtering approximated means particle techniques, we show that optimal disambiguation can be pursued deriving full...

X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. Although they may suffer from several sources of interference, e.g., sea clutter, can provide high-resolution measurements both space time. Such features offer the opportunity to get accurate information not only about target kinematics, i.e., positions velocities, as other conventional radars, but also targets' extents. This research area is named extended tracking (ETT). In...

Tracking moving targets hidden behind visually opaque structures as building walls is a crucial issue in many surveillance, rescue, and security applications. The electromagnetic waves at the low microwave frequency range penetrate into common materials thereby enable radar to expose wall scene. However, due complexity of scattering scenario, signal undergoes multipath propagation phenomena. These typically manifest themselves environmental clutter which may impair detection tracking true...

We propose an unsupervised procedure to automatically extract a graph-based model of commercial maritime traffic routes from historical Automatic Identification System (AIS) data. In the proposed representation, main elements patterns, such as maneuvering regions and sea-lanes, are represented, respectively, with graph vertices edges. Vessel motion dynamics defined by multiple Ornstein-Uhlenbeck processes different long-run mean parameters, which in our approach can be estimated change...

In this paper, we address the problem of predicting vessel trajectories based on Automatic Identification System (AIS) data. The goal is to learn predictive distribution maritime traffic patterns using historical data during training phase, in order be able forecast future target trajectory samples online basis both extracted knowledge and available observation sequence. We explore neural sequence-to-sequence models Long Short-Term Memory (LSTM) encoder-decoder architecture effectively...

Maritime surveillance (MS) is crucial for search and rescue operations, fishery monitoring, pollution control, law enforcement, migration national security policies. Since the early days of seafaring, MS has been a critical task providing in human coexistence. Several generations sensors detailed maritime information have become available large offshore areas real time: radar 1950s automatic identification system (AIS) 1990s among them. However, ground-based radars AIS data do not always...

Tracking an unknown number of objects is challenging, and often requires looking beyond classical statistical tools. When many sensors are available the estimation accuracy can reasonably be expected to improve, but there a concomitant rise in complexity inference task. Nowadays, several practical algorithms for multitarget/multisensor tracking. In terms current research activity one most popular probability hypothesis density, commonly referred as PHD, which goal object locations (unlabeled...

Maritime surveillance (MS) is an important domain for many national and international institutions, agencies, bodies. In this context, the MS initiatives are aimed to enhance search rescue operations, provide effective response accidents disasters, monitor fisheries, prevent pollution support law enforcement defence. This means that it of vital importance generate real-time wide-area maritime operational pictures. However, issues at stake. For instance, deriving mission planning tools with...

A novel anomaly detection procedure based on the Ornstein–Uhlenbeck (OU) mean-reverting stochastic process is presented. The considered a vessel that deviates from planned route, changing its nominal velocity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{v}_0$</tex-math></inline-formula> . In order to hide this behavior, switches off automatic identification system (AIS) device for time...

Since the beginning of 2020, outbreak a new strain Coronavirus has caused hundreds thousands deaths and put under heavy pressure world's most advanced healthcare systems. In order to slow down spread disease, known as COVID-19, reduce stress on structures intensive care units, many governments have taken drastic unprecedented measures, such closure schools, shops entire industries, enforced social distancing regulations, including local national lockdowns. To effectively address pandemics in...