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Navigation, Guidance, Control and Dynamics Commons™

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Air Force Institute of Technology

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Articles 1 - 30 of 250

Full-Text Articles in Navigation, Guidance, Control and Dynamics

Spline-Based Factor-Graph Optimization With High-Grade Inertial Sensors, Kyle Leland, Clark N. Taylor, David Woodburn, Randal Beard Jan 2026

Spline-Based Factor-Graph Optimization With High-Grade Inertial Sensors, Kyle Leland, Clark N. Taylor, David Woodburn, Randal Beard

Faculty Publications

Inertial measurement units (IMUs) are central to global navigation satellite system-based and alternative navigation solutions. This paper combines three lines of research to explore a novel methodology for using inertial sensors: factor graphs, spline-based trajectory estimation, and high-grade inertial sensing. Spline-based factor-graph trajectory estimation is increasingly used in the literature, especially for asynchronous or high-rate sensors. However, prior models neglect the impact of the Earth’s rotation, which is significant for high-grade IMUs. We extend spline-based factor graphs to incorporate accelerometer and gyroscope models that account for the Earth’s rotation. We apply this approach to simulated data from high-grade inertial sensors …

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Amp: Single-Shot Ultra-Wide Fisheye-To-Cubemap Pnp Pose Estimation, Ryan M. Raettig, Richard R. Nyquist, Scott L. Nykl, Clark N. Taylor, Christine M. Schubert Kabban Dec 2025

Amp: Single-Shot Ultra-Wide Fisheye-To-Cubemap Pnp Pose Estimation, Ryan M. Raettig, Richard R. Nyquist, Scott L. Nykl, Clark N. Taylor, Christine M. Schubert Kabban

Faculty Publications

Estimating the position and orientation of a rigid object from an image is critical for situational awareness in robotics and autonomous systems. This study explores relative pose estimation using an ultra-wide fisheye camera for unmanned aircraft inspection vehicles. Ultra-wide fisheye lenses introduce radial distortion and capture features beyond the rectilinear image plane, rendering rectilinear Perspective-n-Point (PnP) algorithms inadequate. Designing a bespoke ultra-wide fisheye localization algorithm requires consideration of both the feature detection method and the pose estimator itself. This study proposes a novel method that combines (1) a fisheye-to-cubemap reprojection, (2) a You Only Look Once (YOLO) convolutional neural network …

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Identification Of Authentic Gnss Signals In Time-Differenced Carrier-Phase Measurements With A Software-Defined Radio Receiver, Zhen Zhu, Sanjeev Gunawardena, Eric Vinande, Jason Pontious Jul 2025

Identification Of Authentic Gnss Signals In Time-Differenced Carrier-Phase Measurements With A Software-Defined Radio Receiver, Zhen Zhu, Sanjeev Gunawardena, Eric Vinande, Jason Pontious

Faculty Publications

The time-differenced carrier phase can be computed from measurements recorded by a multi-global navigation satellite system software-defined radio receiver such as PyChips, from which the user displacement and receiver clock drift can be solved. PyChips is able to simultaneously track authentic and inauthentic signals in separate channels, which makes it possible to observe both types of measurements with corresponding navigation data. A random sample consensus algorithm has been introduced to assess the consistency between the measurements and data. This algorithm successfully separated authentic channels from inauthentic channels when they are broadcast simultaneously.

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Investigation Of Stability And Control Shortcomings Of The North American X-15, William Lorenzo, Ramana Grandhi, Timothy T. Takahashi Jun 2025

Investigation Of Stability And Control Shortcomings Of The North American X-15, William Lorenzo, Ramana Grandhi, Timothy T. Takahashi

Faculty Publications

There is growing interest in the design of maneuvering high-speed aircraft to fly within or at the edge of the atmosphere. We identify and develop novel quasi-static vehicle screening methodologies, suitable for use during preliminary design, to better predict an incipient loss of control due to the dynamic effects of feedback. We validate these metrics by reverse-engineering Neil Armstrong’s 1962 loss of control and inadvertent atmospheric skip while piloting the X-15. In 1962, then-extant flight dynamics screening methods did not forecast likely troubles. We assemble and refine a collection of predictive metrics which operate upon basic quasi-static aerodynamic data and …

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Leveraging Large Language Models (Llms) For Automated Generation Of Sysml V2 State Machines In Guidance, Navigation, And Control (Gnc) Systems, Andrea Louise Ames Jun 2025

Leveraging Large Language Models (Llms) For Automated Generation Of Sysml V2 State Machines In Guidance, Navigation, And Control (Gnc) Systems, Andrea Louise Ames

Theses and Dissertations

Modern defense systems continue to grow in complexity, placing increasing pressure on engineering workflows to be faster and more adaptable. While Model-Based Systems Engineering (MBSE) with the emerging SysML v2 standard provides a framework for capturing system behavior, its practical use is often limited by the expertise and time required for manual modeling. This research investigates whether large language models (LLMs) can help overcome that barrier by automatically generating SysML v2 state machines from Guidance, Navigation, and Control (GNC) textual inputs. Three LLM Flowise-based models were developed and evaluated: the Structured Transformation Model (STM), which uses a structured extraction and …

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Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments, Gal Tsfaty Mar 2025

Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments, Gal Tsfaty

Theses and Dissertations

This thesis addresses the challenge of generating optimized UAV waypoints for complete coverage of complex 3D environments, utilizing graph-based computational techniques. The proposed framework replaces computationally intensive steps—triangulation and three-coloring—within the Vantage Waypoint Set Generation Algorithm (VWSGA) pipeline with Graph Neural Networks (GNNs). By learning structural patterns, the GNN achieves scalable and robust triangulation and node classification, enabling enhanced coverage planning in irregular geometries. A novel penalty mechanism ensures alignment with graph structure during adjacency prediction. Experimental results demonstrate the effectiveness of GNNs in balancing accuracy, computational efficiency, and adaptability, advancing UAV coverage optimization.

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Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan Mar 2025

Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan

Theses and Dissertations

Autonomous vehicles are increasingly being deployed for use in high-stakes and uncertain environments where safe and efficient navigation is critical. In these scenarios, traditional path planning approaches, which rely primarily on deterministic models and fixed assumptions, fall short due to the inherent uncertainty of dynamic threats, sensor inaccuracies, and incomplete information. This research addresses these challenges by developing a novel path-planning methodology that combines the Chance-Constrained Rapidly Exploring Random Tree* (CC-RRT*) algorithm with a probabilistic risk assessment heuristic. This method models uncertainty in sensor detection zones, obstacles in the environment, and the Autonomous Vehicle itself, which allows for uncertainty during …

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Visual Segmentation For Autonomous Aircraft Landing On Austere Runways, Alissa M. Owens Mar 2025

Visual Segmentation For Autonomous Aircraft Landing On Austere Runways, Alissa M. Owens

Theses and Dissertations

Autonomous aircraft must land without human intervention, but existing methods rely on GPS or marked runways, which may be unavailable in austere environments. This paper presents a vision-based approach using semantic segmentation to detect runways and estimate aircraft pose by comparing camera and satellite imagery. We detail the model’s training and demonstrate its effectiveness with simulated and real UAV data.

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Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones Mar 2025

Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones

Theses and Dissertations

The advancement of Global Navigation Satellite System (GNSS) technology in modern smartphones has made these devices pervasive in both civilian and military applications. Although smartphone GNSS chipsets are more susceptible to jamming and spoofing than military grade hardware, smartphone networks offer an underutilized opportunity to detect and mitigate threats to position, navigation, and timing (PNT) services essential to the Department of Defense (DoD) and civilian first responders. Traditional methods for geolocating ground-based jamming sources using smartphone GNSS often fail in environments with dense vegetation or significant occlusions, resulting in substantial localization errors.

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An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow Mar 2025

An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow

Theses and Dissertations

This paper is concerned with a co-planar pursuit-evasion scenario where two Pursuers (P) are after an Evader (E). The players are holonomic/can turn on a dime and their speeds, VP and VE, are constant, but the evader is faster than the pursuers, that is, the speed ratio parameter μ =  VE/VP > 1. The Pursuers are endowed with a circular capture disc whose radius l > 0. A differential game (DG) with three states and one parameter is addressed through geometric and analytical methods where a partial solution is outlined and visualized. The game is split …

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Navigating Together: The Conav Testbed And Framework For Benchmarking Cooperative Localization, Rohith Boyinine, Jayanth Ammapalli, Anusna Chakraborty, Rajnikant Sharma, Kevin Brink, Clark N. Taylor Jan 2025

Navigating Together: The Conav Testbed And Framework For Benchmarking Cooperative Localization, Rohith Boyinine, Jayanth Ammapalli, Anusna Chakraborty, Rajnikant Sharma, Kevin Brink, Clark N. Taylor

Faculty Publications

This paper presents CoNaV, a comprehensive framework for creating a multi-vehicle cooperative localization (CL) testbed designed to support the benchmarking, development, and deployment of cooperative navigation algorithms. Given the essential role of CL in improving localization accuracy for both defense and civilian applications, CoNaV provides a robust environment for rigorously validating algorithms under real-world conditions. By establishing a benchmark for CL algorithms, CoNaV lays a foundation for advancing research into more sophisticated and distributed CL solutions. This framework highlights the potential of cooperative navigation to enhance multi-vehicle operations and offers a scalable, practical approach for future developments in CL technology.

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Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor Dec 2024

Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor

Faculty Publications

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …

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Stereo Vision Relative Navigation Of Airborne Vehicles, Scott L. Nykl, Brian Woolley, John Pecarina Oct 2024

Stereo Vision Relative Navigation Of Airborne Vehicles, Scott L. Nykl, Brian Woolley, John Pecarina

AFIT Patents

An automated aerial formation (AAF) system includes an imaging device mounted on an imaging first aircraft that receives reflected energy from an imaged second aircraft. A controller is communicatively coupled to the imaging device and a flight control system of one of the first and the second aircraft. The controller generates a three-dimensional (3D) point cloud based on the reflected energy and identifies a target 3D model in the 3D point cloud. The controller rotates and scales one of a pre-defined 3D model and the target 3D model to find a 3D point registration between the target 3D model and …

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Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen Aug 2024

Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen

Faculty Publications

Recently, there has been significant interest in the ability to navigate without GPS using the magnetic anomaly field of the Earth (magnav). One of the key technical bottlenecks to achieving magnav is obtaining an accurate magnetic sensor calibration, taking into account own-ship and sensor effects. The Tolles-Lawson magnetic calibration method continues to be the industry standard and was developed when airborne magnetic survey aircraft were first employed over 70 years ago. In this paper, we present a magnetic calibration algorithm based on a factor graph optimization using inertial measurements as well as inputs from both a vector and scalar magnetometer. …

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Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor Mar 2024

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …

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Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen Mar 2024

Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen

Faculty Publications

It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …

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Aerospace Vehicle Navigation And Control System Comprising Terrestrial Illumination Matching Module For Determining Aerospace Vehicle Position And Attitude, Liberty M. Shockley, Robert A. Bettinger Jan 2024

Aerospace Vehicle Navigation And Control System Comprising Terrestrial Illumination Matching Module For Determining Aerospace Vehicle Position And Attitude, Liberty M. Shockley, Robert A. Bettinger

AFIT Patents

The present invention relates to an aerospace vehicle navigation and control system comprising a terrestrial illumination matching module for determining spacecraft position and attitude. The method permits aerospace vehicle position and attitude determinations using terrestrial lights using an Earth-pointing camera without the need of a dedicated sensor to track stars, the sun, or the horizon. Thus, a module for making such determinations can easily and inexpensively be made onboard an aerospace vehicle if an Earth-pointing sensor, such as a camera, is present.

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Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won Jan 2024

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …

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Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding Dec 2023

Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding

Theses and Dissertations

Multi-agent systems and swarms in spacecraft formation flying are of ever-increasing importance in a contested space environment—use of multiple spacecraft to contribute to a cooperative mission potentially increases positive outcomes on orbit, while autonomy becomes an ever more important requirement to reduce reaction time in dynamic situations and lower the burden on space operators. This research explores difficult swarm Guidance Navigation and Control (GNC) scenarios using Deep Reinforcement Learning (DRL). DRL polices are trained to provide guidance inputs to agents in multi-agent swarm environments for completing complex, teamwork focused objectives in geosynchronous orbit. An example scenario is explored for a …

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Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl Jul 2023

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl

Faculty Publications

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …

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Belief Space Planning For Alternative Navigation In Gnss-Denied Environments, Timothy I. Machin Mar 2023

Belief Space Planning For Alternative Navigation In Gnss-Denied Environments, Timothy I. Machin

Theses and Dissertations

Robust alternative navigation for autonomous agents becomes critical without reliable GNSS. Autonomous agents utilize measurement updates to constrain uncertainty. Belief space planning builds graph structures of beliefs within environments based on probable paths, agent and measurement models, and information of the environment. The Rapidly-exploring Random Alt-Nav Belief Graph (RRBANG) algorithm leverages stochastic filtering to implement a range of alt-nav measurement capabilities for robust navigation in GNSS-denied environments.

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Robust Feature Matching For Visual-Based Aerial Navigation Using Registered Imagery, Luis Montenegro Mar 2023

Robust Feature Matching For Visual-Based Aerial Navigation Using Registered Imagery, Luis Montenegro

Theses and Dissertations

This work leverages the SIFT detector along with known robust feature matching techniques for vision-aided sUAS navigation solutions. The proposed algorithm focuses on a sufficient number of features extracted, their quality and their distribution.

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Magnetic Anomaly Mapping For Navigation, Luke T. Bergeron Mar 2023

Magnetic Anomaly Mapping For Navigation, Luke T. Bergeron

Theses and Dissertations

Magnetic navigation (MagNav) has the potential to provide a global form of navigation that uses magnetic measurements of the Earth’s anomaly magnetic field and compares those measurements to a magnetic anomaly map in order to determine the user’s position. Widespread use of MagNav will require a database of fully-sampled, low-altitude magnetic anomaly maps. Existing magnetic anomaly map databases usually come from under- or poorly-sampled surveys. In this work, we provide an easy to follow MagNav anomaly map generation framework and set of survey collection metrics/requirements in an effort to help facilitate and standardize the creation of such a database. We …

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Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler Mar 2023

Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler

Theses and Dissertations

Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.

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To The Moon: Strategic Competition In The Cislunar Region, Shawn M. Willis Jan 2023

To The Moon: Strategic Competition In The Cislunar Region, Shawn M. Willis

Faculty Publications

China’s advancing space capabilities, particularly in the cislunar region, call for increased cislunar space domain awareness on the part of the United States. US military and civilian decisionmakers must take into account the full scope of China’s cislunar plans and capabilities as the military builds space strategies and future force designs. The United States must also increase near-term investments that support more robust cislunar space domain awareness.

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Resilience Monitoring For Multi-Filter All-Source Navigation Framework With Assurance, Jonathon S. Gipson, Robert C. Leishman Dec 2022

Resilience Monitoring For Multi-Filter All-Source Navigation Framework With Assurance, Jonathon S. Gipson, Robert C. Leishman

Faculty Publications

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.), do not intrinsically meet this requirement. This paper presents a novel method to monitor real-time overlapping position state observability and introduces an observability bank within the ARMAS framework, known as stable observability monitoring (SOM). SOM …

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Magnetic Anomaly Absolute Positioning For Hypersonic Aircraft, Alexander J. Mcneil Mar 2022

Magnetic Anomaly Absolute Positioning For Hypersonic Aircraft, Alexander J. Mcneil

Theses and Dissertations

GPS has proven to be an extremely valuable asset for navigation, and timing. GPS has become the standard navigation system for all applications, but GPS has limitations. GPS is susceptible to jamming, spoofing, and in the case of hypersonic aircraft, is likely unavailable. When an aircraft is traveling at hypersonic speeds, there is a plasma sheath that surrounds the aircraft. This plasma sheath blocks electromagnetic waves, and is therefore responsible for a GPS blackout. GPS unavailability for hypersonic aircraft has prompted the research into the viability of alternate navigation systems for these aircraft. This paper seeks to explore the viability …

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Covariance Analysis For Multi-Source Navigation Architecture, Tristan T. Williams Mar 2022

Covariance Analysis For Multi-Source Navigation Architecture, Tristan T. Williams

Theses and Dissertations

Currently, analysis on navigation systems can be slow and computationally expensive using Monte Carlo approaches. Covariance analysis is a tool that can return trade space analysis results promptly and can be computationally reasonable. This research aims to create a covariance analysis tool in a new navigation framework architecture, PntOS. The creation of this covariance tool is explained in coordination with the tool being used in a few different navigation scenarios with the results. These scenarios include a Doppler LiDAR velocity sensor and magnetic anomaly navigation.

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Uav Positioning Data Determined Via Aruco Tags For Aircraft Surface Inspection, Caleb B. Schmidt Mar 2022

Uav Positioning Data Determined Via Aruco Tags For Aircraft Surface Inspection, Caleb B. Schmidt

Theses and Dissertations

Aircraft are frequently inspected to ensure that military and civilian safety standards are adhered to. These inspections are performed pre- and post-flight and are currently performed by trained maintenance personnel. This work furthers the automation of aircraft surface inspection by using ArUco tags to determine the position of the UAV during aerial inspections. The ArUco tag based position data was then compared to a highly accurate infrared motion capture system to determine the viability of this for accurate positioning of the vehicle. This work includes flight experiments with two different UAVs to perform a system viability comparison.

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Magnetic Navigation Using Online Calibration Filter Analysis, Jonnathan D. Bonifaz Mar 2022

Magnetic Navigation Using Online Calibration Filter Analysis, Jonnathan D. Bonifaz

Theses and Dissertations

Magnetic navigation using the Earth’s magnetic anomaly field has proven to be a promising alternative that can provide coverage for a navigation system. This research demonstrates a magnetic navigation system using an extended Kalman filter (EKF) to aid an aircraft’s inertial navigation system (INS). Traditional magnetic anomaly navigation uses a “static calibration method,” which takes post-processed data to calibrate, obtaining the Tolles-Lawson coefficients needed for magnetic anomaly navigation filter compensation. These coefficients are constant and may cause drifts in the navigation filter if not re-calibrated. The online calibration method continuously updates the Tolles-Lawson coefficients as a filter state, reducing the …

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