Navigation Systems Course

Lesson 1 • Core Navigation Concepts and Terminology

Establishes the vocabulary and conceptual models underpinning all navigation disciplines. Precise terminology enables accurate interpretation of system outputs throughout the course.

Lesson 2 • Navigation System Architectures

Surveys standalone, aided, and integrated navigation architectures. Recognizing architectural trade-offs prepares students to select appropriate solutions for given applications.

Lesson 3 • Earth Geometry and Motion Effects

Examines Earth's shape, rotation, and gravitational field as they affect navigation accuracy. These effects must be compensated in all high-precision systems.

Lesson 1 • Inertial Measurement Unit Design

Covers IMU configurations, calibration procedures, and performance grades. Proper calibration directly determines achievable navigation accuracy.

Lesson 2 • INS Error Propagation and Analysis

Analyzes how sensor errors accumulate over time into navigation errors. Understanding error growth guides aiding strategy and system design decisions.

Lesson 3 • INS Initialization and Alignment

Covers static and in-motion alignment techniques that establish initial attitude before navigation begins. Alignment quality sets the error floor for the entire mission.

Lesson 4 • Inertial Sensing Principles

Explains how accelerometers and gyroscopes measure specific force and angular rate. These measurements form the raw inputs for all inertial navigation computations.

Lesson 1 • GNSS Architecture and Signal Structure

Describes satellite constellations, orbital mechanics, and signal modulation schemes. Signal structure knowledge is prerequisite to understanding receiver processing.

Lesson 2 • Receiver Tracking and Measurement

Explains code and carrier tracking loops that extract pseudorange and Doppler measurements. Tracking loop performance determines measurement quality under dynamic conditions.

Lesson 3 • GNSS Error Sources and Mitigation

Identifies atmospheric, multipath, and satellite-related error contributors and their mitigation strategies. Error awareness is essential for achieving required accuracy levels.

Lesson 4 • GNSS Positioning Algorithms

Covers least-squares and weighted positioning solutions using pseudorange observations. Mastery of these algorithms enables evaluation of receiver output quality.

Lesson 1 • Extended and Unscented Kalman Filters

Extends linear filtering to nonlinear navigation systems using linearization and sigma-point methods. Nonlinear filters are required for attitude and tightly coupled integration.

Lesson 2 • Filter Tuning and Validation

Addresses process noise, measurement noise selection, and consistency testing methods. Proper tuning prevents filter divergence and ensures reliable navigation output.

Lesson 3 • Probability and Statistics for Navigation

Reviews probability distributions, covariance, and stochastic processes relevant to sensor modeling. Statistical fluency is required for all subsequent filter design work.

Lesson 4 • Linear Kalman Filter Theory

Derives the discrete Kalman filter equations and explains each processing step. The linear filter is the foundation for all advanced navigation estimators.

Lesson 1 • GNSS Outage and Bridging Strategies

Addresses INS coasting performance and techniques to extend accuracy during GNSS denial. Bridging capability is critical for operations in contested or obstructed environments.

Lesson 2 • Integration Architecture Overview

Compares loose, tight, and deep coupling strategies across accuracy, complexity, and robustness dimensions. Architecture selection drives all subsequent design decisions.

Lesson 3 • Integrity Monitoring for Integrated Systems

Covers fault detection, exclusion, and protection level computation for integrated navigation. Integrity assurance is mandatory for safety-critical navigation applications.

Lesson 4 • Loosely Coupled INS/GNSS Filter Design

Implements an error-state Kalman filter using GNSS position and velocity as measurements. This architecture is the most common starting point for integrated navigation.

Lesson 1 • Vision-Based Navigation Aiding

Introduces optical flow, visual odometry, and feature-based position aiding techniques. Vision sensors provide navigation updates in GNSS-denied indoor and urban environments.

Lesson 2 • Magnetic Sensors and Heading Aiding

Covers magnetometer operating principles, calibration, and heading extraction in the presence of interference. Magnetic heading provides low-cost attitude aiding for slow-moving platforms.

Lesson 3 • Barometric and Altimetry Aiding

Explains pressure-altitude measurement, error sources, and integration with INS vertical channel. Barometric aiding bounds the vertical error growth inherent in inertial systems.

Lesson 4 • Doppler Velocity Sensors

Presents Doppler radar and sonar velocity measurement principles and their integration with INS. Doppler velocity aiding significantly reduces position drift during GNSS outages.

Lesson 1 • Performance Metrics and Specifications

Defines accuracy, availability, continuity, and integrity as quantitative navigation performance measures. Precise metric definitions enable objective comparison of competing system designs.

Lesson 2 • Performance Verification and Validation

Applies formal verification and validation processes to confirm system meets specifications. V&V evidence is required for certification in safety-critical navigation applications.

Lesson 3 • Simulation and Modeling Methods

Applies Monte Carlo simulation and hardware-in-the-loop testing to predict navigation performance. Simulation reduces costly field testing and reveals edge-case failure modes.

Lesson 4 • Error Budget Development

Constructs systematic error budgets by allocating sensor, algorithm, and environmental error contributions. Error budgets guide design trade-offs and identify dominant error sources.

Lesson 1 • Federated and Centralized Filter Architectures

Compares federated and centralized multi-sensor fusion architectures for scalability and fault tolerance. Architecture choice affects computational load, fault isolation, and accuracy.

Lesson 2 • System Requirements and Trade-Off Analysis

Translates operational needs into quantitative navigation requirements and evaluates design alternatives. Requirements engineering prevents costly redesign during later development phases.

Lesson 3 • Real-Time Implementation Considerations

Covers computational platforms, latency budgets, and software architecture for real-time navigation. Implementation constraints often drive algorithm selection and filter complexity.

Lesson 4 • Navigation in Challenging Environments

Addresses navigation under jamming, spoofing, urban canyon, and underwater conditions. Robust design for challenging environments is a key differentiator in advanced systems.