2 citations · 3 across the 17 of their papers we have counts for
20 papers
Can An Array of Magnetometers Replace a DVL - A Cramér-Rao Bound Analysis
Ludvig Lindström, Isaac Skog, Magnus Lundberg Nordenvaad +1
Underwater vehicles rely on noisy dead-reckoning systems, such as Doppler velocity log (DVL)-aided inertial navigation systems, for positioning. However, DVLs rely on active acoust…
A Computationally Efficient Likelihood Approximation for Target Tracking in Time-Varying Multipath Channels
Ashwani Koul, Gustaf Hendeby, Isaac Skog
Active sonar target tracking in shallow-water environments is challenging when weak target echoes are embedded in a time-varying background containing structured multipath componen…
Pilot-Free Predictive Multi-User Beamforming via Sensing Management in Cell-Free Networks
Eren Berk Kama, Murat Babek Salman, Isaac Skog +1
This paper presents a sensing management frame- work for integrated sensing and communications (ISAC) within cell-free massive multiple-input multiple-output (MIMO) systems to redu…
Path Planning for Sound Speed Profile Estimation
Ludvig Lindström, Tadas Paskevicius, Andreas Jakobsson +1
Accurate estimation of the sound speed profile (SSP) is essential for underwater acoustic communication, sonar performance, and navigation, as the acoustic wave propagation depends…
Tracking Time-Varying Multipath Channels forActive Sonar Applications
Ashwani Koul, Gustaf Hendeby, Isaac Skog
Reliable detection and tracking in active sonar require accurate and efficient learning of the acoustic multipath background environment. Conventionally, background learning is per…
Magnetic-Field-Based Localization Using Spatial Field Variations: Signal Processing Principles, Models, and Challenges
Isaac Skog, Manon Kok, Christophe Prieur +1
Signal processing has played, and continues to play, a fundamental role in the evolution of modern localization technologies. Localization using spatial variations in the Earth's m…
MI-SLAM: Magnetic Inertial SLAM Systems
Chuan Huang, Gustaf Hendeby, Isaac Skog
Spatially inhomogeneous magnetic fields offer a valuable, non-visual information source for positioning. Among systems leveraging this, magnetic field-based simultaneous localizati…
Sensing Management for Pilot-Free Predictive Beamforming in Cell-Free Massive MIMO Systems
Eren Berk Kama, Murat Babek Salman, Isaac Skog +1
This paper introduces a sensing management method for integrated sensing and communications (ISAC) in cell-free massive multiple-input multiple-output (MIMO) systems. Conventional…
Performance Analysis of Communication Signals for Localization in Underwater Sensor Networks
Ashwani Koul, Gustaf Hendeby, Isaac Skog
Efficient localization in underwater sensor networks faces challenges due to limited bandwidth, energy constraints, and hardware complexity. Traditional systems separate sensing an…
Joint Magnetometer-IMU Calibration via Maximum A Posteriori Estimation
Chuan Huang, Gustaf Hendeby, Isaac Skog
This paper presents a new method for jointly calibrating a magnetometer and inertial measurement unit (IMU), focusing on balancing calibration accuracy and computational efficiency…
On the Connection Between Magnetic-Field Odometry Aided Inertial Navigation and Magnetic-Field SLAM
Isaac Skog, Manon Kok, Gustaf Hendeby +2
Magnetic-field simultaneous localization and mapping (SLAM) using consumer-grade inertial and magnetometer sensors offers a scalable, cost-effective solution for indoor localizatio…
Broadband Passive Sonar Track-Before-Detect Using Raw Acoustic Data
Daniel Bossér, Magnus Lundberg Nordenvaad, Gustaf Hendeby +1
This article concerns the challenge of reliable broadband passive sonar target detection and tracking in complex acoustic environments. Addressing this challenge is becoming increa…
Adaptive Basis Function Selection for Computationally Efficient Predictions
Anton Kullberg, Frida Viset, Isaac Skog +1
Basis Function (BF) expansions are a cornerstone of any engineer's toolbox for computational function approximation which shares connections with both neural networks and Gaussian…
An Observability-Constrained Magnetic Field-Aided Inertial Navigation System -- Extended Version
Chuan Huang, Gustaf Hendeby, Isaac Skog
Maintaining consistent uncertainty estimates in localization systems is crucial as the perceived uncertainty commonly affects high-level system components, such as control or decis…
Dynamically Iterated Filters: A unified framework for improved iterated filtering and smoothing
Anton Kullberg, Martin A. Skoglund, Isaac Skog +1
Typical iterated filters, such as the iterated extended Kalman filter (IEKF), iterated unscented Kalman filter (IUKF), and iterated posterior linearization filter (IPLF), have been…
MAINS: A Magnetic Field Aided Inertial Navigation System for Indoor Positioning
Chuan Huang, Gustaf Hendeby, Hassen Fourati +2
A Magnetic field Aided Inertial Navigation System (MAINS) for indoor navigation is proposed in this paper. MAINS leverages an array of magnetometers to measure spatial variations i…
Extended target tracking utilizing machine-learning software -- with applications to animal classification
Magnus Malmström, Anton Kullberg, Isaac Skog +2
This paper considers the problem of detecting and tracking objects in a sequence of images. The problem is formulated in a filtering framework, using the output of object-detection…
Fusion framework and multimodality for the Laplacian approximation of Bayesian neural networks
Magnus Malmström, Isaac Skog, Daniel Axehill +1
This paper considers the problem of sequential fusion of predictions from neural networks (NN) and fusion of predictions from multiple NN. This fusion strategy increases the robust…
Unified Linearization-based Nonlinear Filtering
Anton Kullberg, Isaac Skog, Gustaf Hendeby
This letter shows that the following three classes of recursive state estimation filters: standard filters, such as the extended Kalman filter; iterated filters, such as the iterat…
On the Relationship Between Iterated Statistical Linearization and Quasi-Newton Methods
Anton Kullberg, Martin A. Skoglund, Isaac Skog +1
This letter investigates relationships between iterated filtering algorithms based on statistical linearization, such as the iterated unscented Kalman filter (IUKF), and filtering…