Weighing strategy for network localization under scarce ranging information
IEEE Transactions on Wireless Communications
Accuracy comparison of LS and squared-range LS for source localization
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Reformulating the least-square source localization problem with contracted distances
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Block LMS-based source localization using range measurement
Digital Signal Processing
On the Solution of the GPS Localization and Circle Fitting Problems
SIAM Journal on Optimization
Proceedings of the Seventh ACM International Conference on Underwater Networks and Systems
Localization with sparse acoustic sensor network using UAVs as information-seeking data mules
ACM Transactions on Sensor Networks (TOSN)
Benefits of averaging lateration estimates obtained using overlapped subgroups of sensor data
Digital Signal Processing
Closed-form estimation of the speed of propagating waves from time measurements
Multidimensional Systems and Signal Processing
TDOA-based acoustic source localization in the space---range reference frame
Multidimensional Systems and Signal Processing
| Hi-index | 35.69 |
We consider least squares (LS) approaches for locating a radiating source from range measurements (which we call R-LS) or from range-difference measurements (RD-LS) collected using an array of passive sensors. We also consider LS approaches based on squared range observations (SR-LS) and based on squared range-difference measurements (SRD-LS). Despite the fact that the resulting optimization problems are nonconvex, we provide exact solution procedures for efficiently computing the SR-LS and SRD-LS estimates. Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR-LS and SRD-LS solutions as well as approximations of the R-LS and RD-LS solutions which are based on a semidefinite relaxation.