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Course 537 Details

 

 

Course 537: Advanced Integration of GPS and Inertial Navigation Systems (1.5 CEUs) (Public and On-Site)
Instructors: Dr. Alan Pue, John Hopkins Applied Physics Lab and Dr. James Sennott, Tracking and Imaging Systems, Inc. (Friday Afternoon Session)

Description

This 2.5-day course (with the optional Friday afternoon session added upon request for on-site courses) concentrates on the software algorithms and practical implemenations for aiding an inertial navigation system with a GPS receiver.

Objectives

  • You will learn the essential basics of Kalman filter theory and inertial navigation. A central topic is how the understanding and modeling of inertial navigation errors are used to develop the navigation Kalman filter for loosely, tightly and deeply coupled integration architectures. This course will focus on critical details such as timing synchronization, accounting for data latency, computation of measurement residuals, and adjustment of filter parameters to optimize navigation performance. The available inertial instrument technologies and operating principles for accelerometers, ring laser gyros, fiber optic gyros, and MEMS devices will be described.
  • This course will highlight the nature of the inertial instrument error sources, strapdown computations, the meaning of manufacturer specifications, and show how they are applied to the filter design. Case studies are used to illustrate various implementation techniques such as inertial aiding of the GPS receiver to mitigate the effects of signal interference, integration with other aiding sources, carrier phase differential integration, and INS/GPS interferometer integration. The course concludes with a discussion of trends in IMU and receiver technologies.

Prerequisites

  • Familiarity with principles of engineering analysis, including matrix algebra.
  • An understanding of GPS operational principles; Course 111, Course 122, Course 356, or equivalent experience is recommended.
  • Some familiarity with inertial navigation systems is recommended.

Who Should Attend?

Engineers, scientists, system analysts, program specialists and others concerned with the integration of inertial sensors and systems.

Materials You Will Keep

  • A color electronic copy of all course notes will be provided on a USB Drive or CD-ROM. Bringing a laptop to this class is highly recommended; power access will be provided. 
  • A black and white hard copy of the course notes will also be provided.

What Attendees Have Said

 "Dr. Pue is one of the best instructors I have had for a short course. Well prepared. Well presented. ‘Expert’ is an inadequate term for how knowledgeable he is."
— Stephen Pearcy, Picatinny Arsenal 
 
"Dr. Pue’s expertise is evident. Good intuitive insight into key effects. Good relating concepts to real developments. Good lists of references."
— Paul Lakomy, JHU/APL 
 
"Good to have instructors who know the material so well... as practitioners."
— Name withheld upon request
 
"I work with GPS/INS systems, and this will help me with both development and analysis. The most useful session for me was INS initialization technologies because it relates directly to my work and will have many practical applications."  
— Name withheld upon request
 
"I do work with the analysis of the accuracy of submarine INS using GPS data. The most useful session for me was ‘Introduction to INS/GPS Integration’ because I am still fairly new in the field and needed the general information to give me an overall understanding."
— Name withheld upon request.

Course Outline            PDF Course Outline            To Register

Day 1, Morning

Introduction to INS/GPS Integration
● Advantages of integration
● Integration architectures
● Example applications
 
Filter Fundamentals
● Filtering principles and applications
● Vectors and matrices
● State-space modeling
 
Kalman Filter Derivation
● Least squares estimation
● Random process descriptions
● Kalman filter derivation

Day 1, Afternoon

Filter Implementation
● Filter processing example 
● Filter tuning
● Non-linear estimation
 
Inertial Navigation Fundamentals
● Vector kinematics
● Navigation coordinate systems
● Earth relative kinematics
 
Inertial Navigation Mechanization
● Gravity models
● Implementation options
● Mechanization example

Day 2, Morning

Strapdown Inertial Sensor Technologies
● Accelerometer technologies
● Ring laser gyro & fiber optic gyro 
● MEMS inertial instruments
 
Strapdown Systems
● Coning and sculling compensation
● Strapdown processing
● INS Survey
 
Navigation System Error Models
● Tilt angle definitions
● Navigation error dynamics
● Simplified error characteristics

Day 2, Afternoon

System Initialization
● INS alignment concepts 
● Alignment Kalman filter
● Air-launched weapon example
 
Loosely-Coupled INS/GPS Design
● Measurement processing 
● Filter design and tuning
● Navigation system update
 
INS Aiding of Receiver Signal Tracking
● Code and carrier tracking
● Track loop design trades and examples 
● Interference suppression

Day 3, Morning

Tightly-Coupled INS/GPS Design
● Measurement processing
● Filter design
● Performance analysis techniques
 
Case Studies: Multisensor Integration
● Terrain aiding and use of relative GPS
● GPS interferometer/INS integration
● Carrier phase differential GPS integration
 
Future Trends
● Deeply coupled integration
● GPS system improvements
● Technology/cost expectations

Day 3, Afternoon

Ultra-Tight, Deep Integration of GPS/INS
(Option Session Taught By Dr. James Sennott)
 
Non-Linear Estimation Perspective 
● Nonlinear waveform estimation and the MAP estimator
● Estimation bounds
● GPS waveform mapping and correlator observation model
● GPS line-of-sight dynamics innovations model 
 
Extended Kalman Filter Mechanizations 
● Integration hierarchy
● Sub-components and interfaces
● Filter formulations
● Latency and clock effects
● Jamming adaptation 
 
Case Studies 
● Modeling and simulation techniques
● Stand-alone high accuracy applications
● High accuracy tactical applications, including landing guidance
● Anti-jamming applications
 
 
 
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