Optimal Sensor Placement for Target Localization Using Hybrid RSS, AOA and TOA Measurements

This letter investigates the optimal sensor placement strategy for single static target localization using the hybrid received-signal-strength (RSS), angle-of-arrival (AOA) and time-of-arrival (TOA) measurements on the 2-dimensional (2D) plane. Firstly, the problem formulation is introduced. Secondly, the theoretical smallest trace of the Cramér-Rao lower bound (CRLB), which is equivalent to the smallest estimation mean-squared-error (MSE), is derived using the A-optimality criterion. Besides, we propose that the reachable smallest trace of the CRLB (tr(CRLB)) will be determined, once the number and characters of the sensors are selected. Thirdly, the corresponding optimal sensor placement strategies are proposed and concluded in two observations. Finally, the findings are demonstrated by simulation examples.

I. Introduction

In recent years, target localization has been widely required in both military and civilian applications, such as radar detection, node positioning in wireless communication systems, and rescue missions. In the target localization problem, different types of sensors are utilized to collect the signals from a target. Then, some estimation algorithms, such as extended Kalman filter (EKF), particle filter (PF), least-squares estimator and maximum-likelihood estimator (MLE), are required to calculate the target states from the noisy sensor measurements [1]–[3]. These different methods can acquire different estimation performance. In addition, different measurements, e.g., time-difference-of-arrival (TDOA), time-of-arrival (TOA), angle-of-arrival (AOA), received signal strength (RSS), frequency difference of arrival (FDOA) and scan period of the received signals, can be employed to estimate the target states. Furthermore, multiple sensors are required for accurate target localization and the sensor geometrical placement impacts the target localization accuracy significantly [4].