Geolocation with Natural Signals and Constraints

Fei Yang, Purdue University

Abstract

Geolocation using natural signals has become an interesting research area. Natural signals are those signals available from the environment and the nature of the system itself, e.g. the angle of the sun in the sky and inertial measurements. In the research presented herein, we developed an algorithm using all natural signals and the data from inertial measurement unit (IMU) to acquire geolocation information with satisfactory precision. We first introduced a sun sensor, which measures the azimuth and zenith angle of the sun, and then introduced an algorithm using the azimuth and zenith angle of the sun to calculate the Area of Position (AoP) in longitude and latitude, which contains the actual position. After we got the AoP from one location, we developed an algorithm to fuse this information with the IMU sensor data in order to improve the precision of the sun sensor. Generally, the algorithm includes a distance estimation from IMU data, linear interpolation to convert distance to the change of latitude and longitude and interval intersection to narrow the AoP. With these algorithms and the Area of Position we calculated from the sun sensor data at each test point, we use the interval analysis method to reduce the AoP and improve the precision of the sun sensor. Finally, the algorithm is able to reduce the AoP by a factor of 84.17. Finally, a prediction is made that if we can increase the precision of Azimuth/Zenith measurement to 0.001°, the possible area is reduced to 0.0024km2. Usingthe area intersection method, we can usually reduce the area by at least a factor of 10 and that will give us the final possible area less than 200m2.

Degree

Ph.D.

Advisors

Meckl, Purdue University.

Subject Area

Geographic information science|Mechanical engineering

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