A comparative study of target localization methods for large GDOP

Abstract

In this chapter, we present a comparative study on two algorithms to localize ground targets using Unmanned Aerial Vehicles (UAVs): an angle-of-arrival (AOA) emitter-location algorithm using triangulation techniques and an angle-rate algorithm. In particular, we focus on the performance of the two algorithms locating targets when a sensor platform is under a large Geographic Dilution of Precision (GDOP) condition. The large GDOP condition occurs when a target is seen by a sensor platform within a small included angle; the total included angle between Line-Of-Bearings (LOBs) is less than five degrees. The comparative study is a part of the United States Air Force Academy's Unmanned Aerial Vehicles (UAVs) research project to develop a group of cooperative UAVs to search, detect, and localize moving ground targets. The GDOP conditions limit the accuracy of the AOA triangulationemitter-location algorithm's accuracy due to the resulting highly elliptical probable error. In such cases, angle-rate algorithms should be used for better localization accuracy. Usually, a large GDOP condition is encountered during two important operational applications: (1) tasks that use slow-moving-sensor platforms, such as a small UAV, and (2) tasks involving short-up-time emitters that typically are not transmitting signals long enough for any sensor platform to open more than a small total included angle. We investigate the performance of the two algorithms as we vary the included angle for the sensor platform. The performances of angle-rate and triangulation algorithms are compared via MATLAB simulation to determine the preferred regions of operation. © 2007 Springer-Verlag Berlin Heidelberg.