Mine Location Algorithm Based on Multiple Linear Regression

Autor: Ying Ge Chen, Xiao Ying Wang
Rok vydání: 2011
Předmět:
Zdroj: Applied Mechanics and Materials. :1830-1835
ISSN: 1662-7482
DOI: 10.4028/www.scientific.net/amm.58-60.1830
Popis: This paper put forward a mine location algorithm based on multiple linear regression, which using only simple RSSI value to get a higher location accuracy under long narrow and sensitive mine environment. General RSSI measurement method and its drawbacks are discussed in the paper. In order to acquire smaller location error, we filtered some abnormal RSSI data through Gaussian filter method. And we deduced regression equation according to multiple linear regression principle. Combined with training sample, we got their regression parameter. We did relevant location experiment again in the same environment---40m long and narrow bomb shelter which may imitate mine tunnel to a great extent, which shows that the total errors are limited in 3m and 75% errors are less than 2m. What’s more, it can be extended to infinite measuring range with the same set regression coefficient in similar environment.
Databáze: OpenAIRE