Pre-Requisite: Senior standing. Prior exposure to rotation matrices and coordinate transformations, MATLAB/Simulink programming experience, and probability. Knowledge of state-space representations of systems would be desirable, however, not required.

Spring 2015 Schedule: M/W/F 3:00 p.m. – 4:00 p.m. in King Eng. Rm 132

Instructor Dr. Stephen Bruder
  Office: KEC 108
  Office hrs: MWF 10:30 - 11:30am, 1 - 2pm, and Thur 7:30-9:30am
TAs Patrick Reber:

Textbook: Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems 2E by Paul Groves

Course Description:

This course will cover the basics of terrestrial location and navigation with an emphasis on practical exposure to the technology. In particular, the class will collaborate on the design and implementation of a GPS aided Inertial Navigation System (aided-INS) for use on a small UAV.

Key components of the course include: GPS fundamentals; an overview of inertial navigation technology; principles of strapdown inertial navigation systems including coordinate frames, attitude representation, and position, velocity, and attitude (PVA) determination in various coordinate frames; navigation sensor technology including a wide range of accelerometers and gyroscopes; sensor specifications and characterization; testing and calibration approaches; effects of inertial sensor error and compensation methods; analysis of real sensor data; and simulation and modeling using MATLAB/Simulink.

ACQNOWLEDGEMENT: This course has been developed in collaboration with Dr. Aly El-Osery, EE Dept., New Mexico Tech.

Topics Covered:

  1. Navigation Mathematics
    • Introduction to Navigation
    • Relevant Coordinate Frames
    • Kinematics
    • Earth Surface and Gravity
    • Frame Transformations
  2. Navigation Sensors and INS Mechanization
    • Accelerometers
    • Gyroscopes
    • Error Characteristics
    • Inertial Navigation Equations
  3. INS/GPS Integration
    • GPS
    • Kalman Filtering
    • Integration Architectures
    • System Model
    • Measurement Model
  4. System Example

Grading Structure:

Homework Assignments 30%
Two Mini-Projects (15% each) 30%
Final Project: Presentation and Report 35%
Class Participation 5%

MATLAB Code Repository (Link):

Class Schedule:

Week # Dates Topic Assignments / Code Reading
Wed, Jan 7 Introduction (ppt, pdf) dead_reckoning.m Ch 1
Fri, Jan 9 The Four Coord Frames (ppt, pdf)   Sec 2.1
2 Mon, Jan 12 Rotation Matrices I (ppt, pdf)   Sec 2.2
Wed, Jan 14 Rotation Matrices II (ppt, pdf)

hwk 1, soln_1 (& files)

Sec 2.2
Fri, Jan 16 Rotation Matrices III (ppt, pdf)  

Sec 2.2

3 Mon, January 19 MLK Holiday    
Wed, January 21 Rotation Summary   Sec 2.2
Fri, January 23 3D Translation (ppt, pdf)

hwk 2, soln_2 (& files)
in-class example

Sec 2.2
4 Mon, January 26 Angular Velocity (ppt, pdf)   Sec 2.2
Wed, January 28 Angular Velocity (ppt, pdf) VN200 IMU example (code) Sec 2.3
Fri, January 30 Linear Velocity (ppt, pdf)

hwk 3, soln_3 (& files)

Sec 2.3
5 Mon, February 02 Linear Velocity (ppt, pdf)   Sec 2.3
Wed, February 04 Earth Surface and Gravity (ppt, pdf)   Sec 2.4
Fri, February 06 Coordinate Frames Transformations (ppt, pdf)

hwk 4, soln_4 (& files)

Sec 2.5
6 Mon, February 9 Inertial Sensors (ppt, pdf) Ch 4
Wed, February 11 Inertial Sensors & Errors (ppt, pdf)   Ch 4
Fri, February 13 IMU Comparison (data sheets)

hwk 5, soln_5 (files)

7 Mon, February 16 Presidents Day Holiday    
Wed, February 18 Inertial Nav in the ECI Frame (ppt, pdf)   Sec 5.2
Fri, February 20 Inertial Nav in the ECEF Frame (ppt, pdf)   Sec 5.3
8 Mon, February 23 Inertial Nav in the Nav Frame (ppt, pdf)

Project 1 - Solution

Sec 5.4
Wed, February 25 Inertial Nav in the Nav Frame / Discuss Project 1   Sec 5.2
Fri, February 27 Coarse self-alignment (ppt, pdf) Mathematica Code Sect. 5.6
9 Mon, March 02 Noise & Random Processes (ppt, pdf)  
Wed, March 04 Sensor Noise Characteristics (ppt, pdf) BI_example.m & ARW_example.m Sect 4.4 & 5.7
Fri, March 06 Final Project Assignments


10 Mon, March 9 -- Spring Break --    
Wed, March 11 -- Spring Break --    
Fri, March 13 -- Spring Break --    
11 Mon, March 16

Project 2 Intro (ppt, pdf)

Project 2 - Solution  
Wed, March 18

INS Error Mech (ppt, pdf)

Fri, March 20 ECI Error Mech. (ppt, pdf)   Sec. 14.2.2
12 Mon, March 23 ECEF Error Mech. (ppt, pdf)   Sec. 14.2.3
Wed, March 25 Error Modeling and State Aug (ppt, pdf)  
Fri, March 27 Kalman Filtering Part 1 (ppt, pdf) MATLAB code Ch 3
13 Mon, March 30 Kalman Filtering Part II (ppt, pdf) MATLAB code Ch 3
Wed, April 01 Kalman Filtering Part II.5 (ppt, pdf)   Ch 3
Fri, April 03 The Global Positioning System (ppt, pdf)   Ch 3
14 Mon, April 06 GPS Part II (ppt, pdf)   Ch 8
Wed, April 08 Aided INS (ppt, pdf)
Discussion of final projects.
  Ch 14.1
Fri, April 10 INS/GPS Integration Architectures (ppt, pdf)   Ch 14.3
15 Mon, April 13

INS/GPS System Integration Example(ppt, pdf)

Ch 14
Wed, April 15

Final Project Presentations:

  1. Sidney Jones " Inertial Sensor Noise Analysis"
  2. Adan Magana "GPS Only Navigation"
  3. Nicholas Sullivan "GPS Based Positioning"
Fri, April 17

Final Project Presentations

  1. Blake Colson "An Attitude and Heading Reference System (AHRS)"
  2. Jeff Ferguson "High Performance MEMS Sensors"
  3. Kurt Andrada "IMU with Altimeter and Compass"
16 Mon, April 20

Final Project Presentations:

  1. Trent Gardner "Mobile Robot INS-GPS Fusion"
  2. Brigette Cochran "Fusion of INS and Odometry for Navigation"
  3. Trent Wargo "GPS, IMU, & Odometry based Nav For a Mobile Robot"
Wed, April 22

Final Project Presentations:

  1. Jafert Hernandez "INS-Only Based Self Alignment"
  2. Naru Muraleedharan "Indoor Navigation using LiDAR and INS"
  3. A. J. Marin "GPS and Star Tracker integration with Kalman Filtering"
Fri, April 24

Study day

Final project report due 6am Monday 27th April