How to Select the Best Sensors for TDOA and TDOA/AOA Localization?

摘要

This paper focuses on the sensor subset optimization problem in time difference of arrival (TDOA) passive localization scenar-io. We seek for the best sensor combination by formulating a non-convex optimization problem, which is to minimize the trace of covariance matrix of localization error under the condition that the number of selected sen-sors is given. The accuracy metric is described by the localization error covariance matrix of classical closed-form solution, which is introduced to convert the TDOA nonlinear equations into pseudo linear equations. The non-convex optimization problem is relaxed to a standard semi-definite program (SDP) and efficiently solved in a short time. In addition, we extend the sensor selection method to a mixed TDOA and angle of arrival (AOA) lo-calization scenario with the presence of sensor position errors. Simulation results validate that the performance of the proposed sensor se-lection method is very close to the exhaustive search method.