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...

We propose a Bayesian method for distributed sequential localization of mobile networks composed both cooperative agents and noncooperative objects. Our provides consistent combination self-localization (CS) tracking (DT). Multiple objects are localized tracked using measurements between agents. For operation low complexity, we combine particle-based belief propagation with consensus or gossip scheme. High accuracy is achieved through probabilistic information transfer the CS DT parts...

In the era of Internet Things (IoT), efficient localization is essential for emerging mass-market services and applications. IoT devices are heterogeneous in signaling, sensing, mobility, their resources computation communication typically limited. Therefore, to enable location awareness large-scale networks, there a need efficient, scalable, distributed multisensor fusion algorithms. This article presents framework designing network navigation (NLN) IoT. Multisensor operation algorithms...

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...

Situational awareness in wireless networks refers to the availability of position information on transmitters and receivers as well their propagation environments aid communications. In millimeter wave massive multiple-input multiple-output communication systems, situational can significantly improve quality robustness this paper, we establish a model that describes statistical dependencies between channel state position, orientation, clock offset user equipment along with locations features...

We present a simultaneous localization and mapping (SLAM) algorithm that is based on radio signals the association of specular multipath components (MPCs) with geometric features. Especially in indoor scenarios, robust from challenging due to diffuse propagation, unknown MPC-feature association, limited visibility In our approach, reflections at flat surfaces are described terms virtual anchors (VAs) mirror images physical (PAs). The positions these VAs possibly also PAs unknown. develop...

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....

Multiobject tracking provides situational awareness that enables new applications for modern convenience, public safety, and homeland security.This paper presents a factor graph formulation particle-based sum-product algorithm (SPA) scalable detection of extended objects.The proposed method dynamically introduces states newly detected objects, efficiently performs probabilistic multiple-measurement to object association, jointly infers the geometric shapes objects.Scalable (EOT) is enabled...

The sigma point (SP) filter, also known as unscented Kalman is an attractive alternative to the extended filter and particle filter. Here, we extend SP nonsequential Bayesian inference corresponding loopy factor graphs. We propose belief propagation (SPBP) a low-complexity approximation of (BP) message passing scheme. SPBP achieves approximate marginalizations posterior distributions (generally) It well suited for decentralized because its low communication requirements. For decentralized,...

Cooperative localization in agent networks based on interagent time-of-flight measurements is closely related to synchronization. To leverage this relation, we propose a Bayesian factor graph framework for cooperative simultaneous and synchronization (CoSLAS). This suited mobile agents time-varying local clock parameters. Building the CoSLAS graph, develop distributed (decentralized) belief propagation algorithm practically important case of an affine model asymmetric time stamping. Our...

We introduce a distributed cooperative framework and method for Bayesian estimation control in decentralized agent networks. Our combines joint of time-varying global local states with information-seeking optimizing the behavior agents. It is suited to nonlinear non-Gaussian problems and, particular, location-aware For estimation, combination belief propagation message passing consensus used. control, negative posterior entropy all maximized via gradient ascent. The layer provides...

The Internet of Things (IoT) will seamlessly integrate a large number densely deployed heterogeneous devices and enable new location-aware services. However, fine-grained localization IoT is challenging as their computation communication resources are typically limited different may have qualities internal clocks mobility patterns. To address these challenges, we propose cooperative, scalable, time-recursive algorithm for network synchronization (NLS). Our based on time measurements supports...

Tracking extended objects based on measurements provided by light detection and ranging (LIDAR) millimeter wave radio (RADAR) sensors is a key task to obtain situational awareness in important applications including autonomous driving indoor robotics. In this paper, we propose probabilistic data association methods for localizing tracking of that originate an unknown number measurements. Our approach factor graphs the sum-product algorithm (SPA). particular, reduce computational complexity...

Passive monitoring of acoustic or radio sources has important applications in modern convenience, public safety, and surveillance. A key task passive is multiobject tracking (MOT). This paper presents a Bayesian method for multisensor MOT challenging problems where the object states are high-dimensional, measurements follow nonlinear model. Our developed framework factor graphs sum-product algorithm (SPA) implemented using random samples "particles". The multimodal probability density...

Protein kinase D3 (PKD3) is an important regulator of triple-negative breast cancer (TNBC) progression by promoting invasion, proliferation, and stem cell maintenance. However, the mechanism underlying these cellular functions has remained unclear. Here, we report that endogenous PKD3 localizes to Rab7/Lamp1-positive vesicles in MDA-MB-231 cells cultured on stiff matrices. Notably, upon depletion size Rab7-positive smaller. This correlates with impaired endosomal acidification, which...

We propose a fast labeled multi-Bernoulli (LMB) filter that uses belief propagation for probabilistic data association. The complexity of our scales only linearly in the numbers Bernoulli components and measurements, while performance is comparable to or better than Gibbs sampler-based LMB filter.

We apply joint probabilistic data association (JPDA) to multipath-assisted indoor navigation and tracking (MINT). In MINT, position-related information in multipath components (MPCs) is exploited increase the accuracy robustness of tracking. Conventional MINT algorithms are based on deterministic perform a global nearest-neighbor "hard" MPC-related delays with room geometry. such setup, incorrect associations may lead severe errors divergence Bayesian filter. Here, we propose JPDA-MINT...

The goal of maritime situational awareness (MSA) is to provide a seamless wide‐area operational picture ship traffic in coastal areas and the oceans real time. Radar central sensing modality for MSA. In particular, oceanographic high‐frequency surface‐wave (HFSW) radars are attractive surveying large sea at over‐the‐horizon distances, due their low environmental footprint power requirements. However, design not optimal challenging conditions prevalent MSA applications, thus calling...

This paper presents methods for the estimation of time-varying directions arrival (DOAs) signals emitted by moving sources. Following sparse Bayesian learning (SBL) framework, prior information unknown source amplitudes is modeled as a multi-variate Gaussian distribution with zero-mean and variance parameters. For sequential variance, we present two SBL-based that propagate statistical across time to improve DOA performance. The first method heuristically calculates parameters an...

Tracking multiple time-varying states based on heterogeneous observations is a key problem in many applications. Here, we develop statistical model and algorithm for tracking an unknown number of targets the probabilistic fusion from two classes data sources. The first class, referred to as target-independent perception systems (TIPSs), consists sensors that periodically produce noisy measurements without requiring target cooperation. second target-dependent reporting (TDRSs), relies...

Localization and tracking of marine animals can reveal key insights into their behaviors underwater that would otherwise remain unexplored. A promising nonintrusive approach to obtaining location information is process bioacoustic signals, which are passively recorded using multiple hydrophones. In this paper, a data processing chain automatically detects tracks odontocetes (toothed whales) in three dimensions (3-D) from echolocation clicks with volumetric hydrophone arrays proposed. First,...

Multipath-based simultaneous localization and mapping (SLAM) is an emerging paradigm for accurate indoor constrained by limited navigation resources. The goal of multipath-based SLAM to support the estimation time-varying positions mobile agents detecting localizing radio-reflective surfaces in environment. In existing Bayesian methods, a propagation surface represented mirror image each physical anchor (PA) across that – known as corresponding "virtual anchor" (VA). Due this Vas...