Finance

Identification (biology)

Aerospace engineering

Non-line-of-sight propagation

Subspace topology

Wireless

Base station

Biology

Operating system

Algorithm

Engineering

Artificial intelligence

Position (finance)

Economics

Set (abstract data type)

Programming language

Range (aeronautics)

Mobile station

Overhead (engineering)

Computer science

Botany

Real-time computing

Telecommunications

IEEE Sensors Journal

Least squares estimation is a widely-used technique for range-based source localization, which obtains the most probable position of mobile station. These methods cannot provide desirable accuracy in the case with a non line of sight (NLOS) path between mobile station and base stations. To circumvent this drawback, many algorithms have been proposed to identify and mitigate this error; however, they have a large run-time overhead. On the other hand, new positioning systems utilize a large set of base stations, and a practical algorithm should be fast enough to deal with them. In this paper, we propose a novel algorithm based on subspace method to identify and eliminate the NLOS error. Simulation studies show that our algorithm is faster and more accurate compared with other conventional methods, especially in the large-scale cases.

NLOS Identification in Range-Based Source Localization: Statistical Approach