Tracking and data association
Time difference of arrival estimation of speech source in a noisy and reverberant environment
Signal Processing - Content-based image and video retrieval
Target tracking by time difference of arrival using recursive smoothing
Signal Processing
Automatica (Journal of IFAC)
Optimal angular sensor separation for AOA localization
Signal Processing
Distributed adaptive sampling using bounded-errors
Proceedings of the 1st international conference on Robot communication and coordination
Optimality analysis of sensor-target localization geometries
Automatica (Journal of IFAC)
Optimal sensor placement and motion coordination for target tracking
Automatica (Journal of IFAC)
Performance evaluation of UKF-based nonlinear filtering
Automatica (Journal of IFAC)
| Hi-index | 0.08 |
This paper investigates the adaptive sensing for cooperative target tracking in three-dimensional environments by multiple autonomous vehicles based on measurements from time-difference-of-arrival (TDOA) sensors. An iterated filtering algorithm combined with the Gauss-Newton method is applied to estimate the target location. By minimizing the determinant of the estimation error covariance matrix, an adaptive sensing strategy is developed. A gradient-based control law for each agent is proposed and a set of stationary points for local optimum geometric configurations of the agents is given. The proposed sensing strategy is further compared with other sensing strategies using different optimization criteria such as the Cramer-Rao lower bound. Potential modifications of the proposed sensing strategy is also discussed such as to include the formation control of agents. Finally, the proposed sensing strategy is demonstrated and compared with other sensing strategies by simulation, which shows that our method can provide good performance with even only two agents, i.e., one measurement at each time.