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Found 35 papers, 3 papers with code
A New Statistical Model for Waveguide Invariant-Based Range Estimation in Shallow Water
In the undersea environment, positioning is often challenging, and thus, ranging based on passive acoustic data can provide valuable information for subsurface navigation and source localization.
A New Architecture for Neural Enhanced Multiobject Tracking
In particular, in problems where plenty of labeled data for the training of neural networks is available, data-driven MOT tends to have advantages compared to traditional methods.
Direct Multipath-Based SLAM
The factor graph is the starting point for the development of an efficient belief propagation (BP) method for multipath-based SLAM that avoids data preprocessing by a channel estimator.
Particle Flows for Source Localization in 3-D Using TDOA Measurements
Our numerical results demonstrate that the proposed method can correctly determine the number of sources and provide accurate location estimates.
ISR: Invertible Symbolic Regression
The proposed ISR method naturally combines the principles of Invertible Neural Networks (INNs) and Equation Learner (EQL), a neural network-based symbolic architecture for function learning.
Multiobject Tracking for Thresholded Cell Measurements
Our numerical results demonstrate the advantages of the proposed method that relies on thresholded cell measurements compared to the conventional multiobject tracking based on point measurements with and without AM.
A Probabilistic Focalization Approach for Single Receiver Underwater Localization
We introduce a Bayesian estimation approach for the passive localization of an acoustic source in shallow water using a single mobile receiver.
Learning Dynamics from Multicellular Graphs with Deep Neural Networks
Multicellular self-assembly into functional structures is a dynamic process that is critical in the development and diseases, including embryo development, organ formation, tumor invasion, and others.
A Belief Propagation Approach for Direct Multipath-Based SLAM
This factor graph is the starting point for the development of an efficient belief propagation (BP) method for multipath-based SLAM that directly uses received radio signals as measurements.
Graph-based Simultaneous Localization and Bias Tracking
We demonstrate that the position-related information enables the algorithm to provide high-accuracy position estimates even in fully obstructed line-of-sight (OLOS) situations.
Track Coalescence and Repulsion in Multitarget Tracking: An Analysis of MHT, JPDA, and Belief Propagation Methods
Joint probabilistic data association (JPDA) filter methods and multiple hypothesis tracking (MHT) methods are widely used for multitarget tracking (MTT).
A BP Method for Track-Before-Detect
Our proposed method is based on a new statistical model that introduces a new object hypothesis for each data cell of the raw sensor measurements.
Navigation in shallow water using passive acoustic ranging
The ability to compute the range rate and range measurements from the pressure field measured using a single hydrophone is demonstrated on real data from the SWellEx-96 experiment.
Message Passing-Based 9-D Cooperative Localization and Navigation with Embedded Particle Flow
However, particle-based BP algorithms are known to suffer from particle degeneracy in large and dense networks of mobile agents with high-dimensional states.
Multisensor Multiobject Tracking with Improved Sampling Efficiency
We perform a numerical evaluation in a passive acoustic monitoring scenario where multiple sources are tracked in 3-D from 1-D time-difference-of-arrival (TDOA) measurements provided by pairs of hydrophones.
Active Planning for Cooperative Localization: A Fisher Information Approach
A numerical case study demonstrates the intelligent behavior of a single controlled anchor in a 3-D scenario and the resulting significantly improved localization accuracy.
Neural Enhanced Belief Propagation for Multiobject Tracking
State-of-the-art MOT methods fully rely on a statistical model and typically use preprocessed sensor data as measurements.
Data Fusion for Multipath-Based SLAM: Combining Information from Multiple Propagation Paths
A key aspect of the proposed estimation method based on MVAs is to check the availability of singlebounce and double-bounce propagation paths at a specific agent position by means of ray-launching.
Indoor Localization
Simultaneous Localization and Mapping
+1
Bayesian Detection and Tracking of Odontocetes in 3-D from Their Echolocation Clicks
Time-difference-of-arrival (TDOA) measurements of echolocation clicks emitted by odontocetes can be extracted and used for detection, localization, and tracking in 3-D. We propose a data processing chain that automatically detects and tracks multiple odontocetes in 3-D from their echolocation clicks.
Graph-based sequential beamforming
At each time step, belief propagation predicts the number of DOAs and their DOAs using posterior probability density functions (pdfs) from the previous time and a different Bernoulli-von Mises state transition model.
Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
First, we present a PMBM conjugate prior on the posterior of sets of trajectories for a generalized measurement model, in which each object generates an independent set of measurements.
Data Fusion for Radio Frequency SLAM with Robust Sampling
A promising approach to address this problem is to exchange radio signals between mobile agents and static physical anchors (PAs) that bounce off flat surfaces in the indoor environment.
Neural Enhanced Belief Propagation for Data Association in Multiobject Tracking
Situation-aware technologies enabled by multiobject tracking (MOT) methods will create new services and applications in fields such as autonomous navigation and applied ocean sciences.
Fusion of Sensor Measurements and Target-Provided Information in Multitarget Tracking
Here, we develop a statistical model and algorithm for tracking an unknown number of targets based on the probabilistic fusion of observations from two classes of data sources.
Acoustic Source Localization in Shallow Water: A Probabilistic Focalization Approach
This paper presents a Bayesian estimation method for the passive localization of an acoustic source in shallow water.
An Efficient Labeled/Unlabeled Random Finite Set Algorithm for Multiobject Tracking
Only if a quantity characterizing the plausibility of object existence is above a threshold, a new labeled Bernoulli component is created and the object is tracked by the more accurate but more computationally demanding LMB part of the algorithm.
A Scalable Track-Before-Detect Method With Poisson/Multi-Bernoulli Model
We propose a scalable track-before-detect (TBD) tracking method based on a Poisson/multi-Bernoulli model.
Track Coalescence and Repulsion: MHT, JPDA, and BP
In particular, JPDA suffers from the track coalescence effect, i. e., estimated tracks of targets in close proximity tend to merge and can become indistinguishable.
Probabilistic Scan Matching: Bayesian Pose Estimation from Point Clouds
We formulate a holistic Bayesian estimation problem for both data association and pose estimation and present the corresponding joint factor graph.
Neural Enhanced Belief Propagation for Cooperative Localization
Location-aware networks will introduce innovative services and applications for modern convenience, applied ocean sciences, and public safety.
Scalable Detection and Tracking of Geometric Extended Objects
The proposed method dynamically introduces states of newly detected objects, efficiently performs probabilistic multiple-measurement to object association, and jointly infers the geometric shapes of objects.
Graph-Based Multiobject Tracking with Embedded Particle Flow
Seamless situational awareness provided by modern radar systems relies on effective methods for multiobject tracking (MOT).
QMA: A Resource-efficient, Q-Learning-based Multiple Access Scheme for the IIoT
Results show that QMA considerably increases reliability and throughput in comparison to CSMA/CA, especially in networks with a high load.
Q-Learning
Networking and Internet Architecture
C.2.2
Classification-Aided Multitarget Tracking Using the Sum-Product Algorithm
Multitarget tracking (MTT) is a challenging task that aims at estimating the number of targets and their states from measurements of the target states provided by one or multiple sensors.
Sigma Point Belief Propagation
Here, we extend the SP filter to nonsequential Bayesian inference corresponding to loopy factor graphs.
