Overview

1. Simultaneous Estimations of Ground Target Location and Aircraft Direction Heading via Image Sequence and GPS Carrier-Phase Data Luke K.Wang, Shan-Chih Hsieh, Fei-Bin Hsaio2, Kou-Yuan Huang3, Guo-Shing Huang4, and Fan-Jen Tsai Dept. of Electrical Engineering National Kaohsiung Univ. of Applied Sciences,Kaohsiung,Taiwan,R.O.C. 2Institute of Aeronautics and Astronautics National Cheng Kung Univ.,Tainan,Taiwan,R.O.C. 3Dept. of Computer and Information Science National Chiao-Tung Univ.,Hsinchu,Taiwan,R.O.C 4Dept. of Electrical Engineering National Chin-Yi Institute of Technology,Taichung,Taiwan,R.O.C.

2. Overview • Introduction • Fundamental Concepts • Simulation Results • Conclusion

3. Introduction {b} {c} {e}

4. POSITION AND ORIENTATION CAMERA GPS CARD IMAGE FEATURE EXTRACTION Measurement & Process Error Initial State & Error Covariance EKF ESTIMATED POSITION

5. Fundamental Concepts • GPS • Coordinate Transformation • Perspective Projection • EKF

6. Three Segments of GPS Space Segment User Segment Control Segment

7. Sources of Signal Interference Ionosphere Troposphere

10. The Carrier-Phase Measurements actual distance between receiver and satellite satellite‘s clock error GPS satellite speed of light Integer ambiguity wave length receiver‘s clock error GPS receiver accounts for ionospheric, tropospheric delays

11. Single Difference Solution Two stations observe the same SV at the same epoch

12. Double Difference Solution Two stations observe the same two SVs at the same epoch

13. Fundamental Concepts • GPS • Coordinate Transformation • Perspective Projection • EKF

14. The Homogeneous Transformation Note • (1)Earth-Centered-Earth-Fixed (ECEF), i.e., {e} • (2)Camera coordinate ,i.e., {c} • (3)Body frame ,i.e., {b} • (4) [XCYCZC]T : The target location expressed in {C} • (5) bTC : Transformation between body and camera • (6) eTb : Transformation between earth and body

15. Coordinate Frames ECEF and ENU frames (Earth Centered Earth Fixed Cartesian Coordinates) (East North Up) Body frame

16. Azimuth Angle Note: d is a baseline length between two antennas.

17. Fundamental Concepts • GPS • Coordinate Transformation • Perspective Projection • EKF

18. 3-D to 2-D Perspective Projection

19. Fundamental Concepts • GPS • Coordinate Transformation • Perspective Projection • EKF

20. Extended Kalman Filter (EKF) State equation & Measurement equation xk+1 = f(xk,k) + wK, wK ~ N(0,QK) zk = hk(xk,,k) + vk, vK ~ N(0,RK) Time Update (Predict) Measurement Update (Correct)

21. State Assignment Define the state: [2]

22. Outline • Introduction • Fundamental Concepts • Simulation Results • Conclusion • Reference

23. Simulation Steps • Step1: Obtaining carrier phase data from two GPS receivers. There are eight satellites being observed. Thus, according to double difference method, seven double differences are recorded. • Step2: Given a known trajectory of the target, the image point sequences [u, v] are obtained. • Step3: Given a sequence of noisy image point [u, v], we use Kalman filter technique to estimate the ground target position and azimuth angle. • Step4: Compare the errors between true and estimated target positions.

24. Simulation Results

25. Simulation Results Root-mean-square mismatch of the target using EKF

26. Simulation Results The estimation errors for ground target in x-, y-, and z-direction.

27. Simulation Results Estimation of azimuth angle using EKF

28. Simulation Results Integer ambiguity numbers of N12ab~ N14abusing EKF.

29. Simulation Results Integer ambiguity numbers of N15ab~ N18abusing EKF.

30. Outline • Introduction • Fundamental Concepts • Simulation Results • Conclusion

31. Conclusion • The proposed filter is verified by utilizing actual GPS carrier-phase measurement data. The root-mean-square error of ground target coordinate is substantially reduced to less than 1 meter and 0.2 deg. for position and azimuth angle, respectively. • The worst case in position estimation is in z direction(elevation) according to simulation. • The benefits of using the proposed scheme are due to its low cost and simplicity to implement on wing tips.

32. Thank you！

33. Reference [2]J.C. Juang and G. S. Huang," Development of GPS-Based Attitude Determination Algorithm," IEEE Trans. on Aerospace and Electronic Systems, Vol.33, No.3, 1997, pp.968-976. Back