Adaptive acoustic localization algorithm for sensor networks

Sensor networks have proved their usefulness in various acoustic localization applications. Recently a consistency function-based algorithm was proposed, which can provide accurate solution even if a large number of independent outliers are present in the measurement set. In certain practical cases, however, sensors may have cooperative and consistent errors, resulting in bad estimations. In this paper an adaptive consistency function-based solution is proposed, which can compensate for co-operative and systematic measurement errors and thus provides accurate results even if the original consistency function-based algorithm fails.