Abstract: A Kalman-based hypothesis testing (KHT) algorithm is proposed for mobile location estimation in non-line of sight (NLOS) environments. Hypothesis testing is employed to detect whether the environment is NLOS or LOS along with time of arrival (TOA) and received signal strength (RSS) measurements. And then an extended Kalman filter is used to nonlinear estimation. Simulation results show that the Kalman-based hypothesis testing algorithm has higher estimate accuracy in comparison with extended Kalman filter. Keywords: wireless sensor networks, non-line of sight, indoor localization, Kalman filter, hypothesis testing Classification: Wireless circuits and devices [1] Y. Kong, Y. Kwon, and G. Park, "Robust localization over obstructed interferences for inbuilding wireless applications," IEEE Trans. Consum.
A Kalman base hypothesis testing algorithm is proposed for NLOS localization REF .
Mobile location estimation scheme in NLOS environment
IEICE Electronic Express
IEICE Electronic Express
Computer Science