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].