Airborne Attitude Determination and Ground Target Location Using GPS Information and Vision Technique Shan-Chih Hsieh, Luke K.Wang, Yean-Nong Yang †,Fei-Bin Hsaio*, Fan-Jen Tsai Dept. of Electrical Engineering,National Kaohsiung University of Applied Sciences † Dept. of Electronic Engineering, National I-Lan Institute of Technology *Institute of Aeronautics and Astronautics, National Cheng Kung University

OVERVIEW 1.INTRODUCTION 2.THE GPS SYSTEM 3.THE GPS-VISION SYSTEM 4.SIMULATION 5.SUMMARY

1.INTRODUCTION Sensor fusion method(vision+GPS+INS,or gyros) Vision-based navigation Focus of expansion(FOE) Attitude determination GPS Wabba problem Least-squares Rotation representation

2.1The Homogeneous Transformation {b}:body coordinate {e}:ECEF {C}:camera coordinate {C} -----> {e} (2.1-1)

For our case, (2.1-2) b R e : attitude of aircraft with respect to {e} [X 0 Y 0 Z 0 ] T :origin of the body frame.

2.2The Kinematic Equation Quaternion: q = [q 0 q 1 q 2 q 3 ] T Kinematics: (2.2-1) q R(q)

{b} GPS antenna {C} Earth Target {e} Figure 1.The illustration of the imaging geometry and target location

3.THE GPS-VISION SYSTEM System: (1)a GPS pseudorange receiver (2)a CCD camera 3.1The Monocular Vision System Perspective projection: 3.2The Kalman Filter Formulation

where State: Linearization: where

3.3The Problem Formulation for Identification of Target Location Q:Given (1)a sequence of noisy measurement of ground target (2)a sequence of time-tagged GPS measurement of aircraft body coordinate Solve:(1)WGS-84 coordinate of ground target (2)aircraft’s attitude

4.SIMULATION Aircraft maneuver: pitch rate=0.001 grad. Translate with constant velocity measurement noise covariance: diag[10 m pixel 2 ] Ground target:stationary with an unknown WGS-84 coordinate

Target loci in image plane The estimated attitude

The estimated target location The estimated errors of ground target location

5.SUMMARY Key features: Using only a single GPS pseudorange receiver to compute attitude Simultaneous determination of both ground target location and aircraft’s attitude Using EKF Future Work Using Unscented Kalman Filter Using Particle Filter Using sophisticated camera model instead of pinhole model

Comments and Suggestions: