In indoor localization using sensor networks, performance improvements are required for non-line-of-sight (NLOS) environments in which the estimation error is high. NLOS mitigation schemes involve the detection and elimination of the NLOS measurements. The iterative minimum residual (IMR) scheme, which is often applied to the localization scheme using the time of arrival (TOA), is commonly employed for this purpose. The IMR scheme is a low-complexity scheme and its NLOS detection performance is relatively high. However, when there are many NLOS nodes in a sensor field, the NLOS detection error of the IMR scheme increases and the estimation accuracy deteriorates. Therefore, we propose a new scheme that exploits coarse NLOS detection based on stochastic characteristics prior to the application of the IMR scheme to improve the localization accuracy. Improved performances were confirmed in two NLOS channel models by performing numerical simulations.

Sensor networks, in which many small terminals are wirelessly connected, have recently received considerable interest according to the development of wireless technology and electronic circuit. To provide advanced applications and services by the sensor networks, data collection including node location is essential. Hence the location estimation is important and many localization schemes have been proposed. Time of arrival (TOA) localization is one of the popular schemes because of its high estimation accuracy in ultra wide-band (UWB) sensor networks. However, a non-line-of-sight (NLOS) environment between the target and the anchor nodes causes a serious estimation error because the time is delayed more than its true one. Thus, the NLOS nodes should be detected and eliminated for estimation. As a well-known NLOS detection scheme, an iterative minimum residual (IMR) scheme which has low calculation complexity is used for detection. However, the detection error exists in IMR scheme due to the measurement error. Therefore, in this paper, we propose a new IMR-based NLOS detection scheme and show its performance improvement by computer simulations.